Since there is no vaccine or regulatory approved therapy available for treatment of SARS-CoV-2 infection, the medical need to prevent the transition of a mild into the severe COVID-19 stage of infection is of outmost importance. Among several drug candidates, Chloroquine (CQN) and Hydroxy-Chloroquine (H-CQN) have been tested most intensively. However, the therapeutic effect of H-CQN and CQN has been discussed controversially in the light of severe side effects. Originally, H-CQN descended from the natural substance Quinine, a medicinal product used since the Middle Ages and is now regulatory approved for various indications. We hypothesized that Quinine also exerts anti-SARS-CoV-2 activity. First, virus production in Vero B4 cells was analyzed by Western blot, showing that Quinine exerts antiviral activity against SARS-CoV-2 that at 10 µM was even stronger than that of H-CQN or CQN. Second, fluorescence end-point and time lapse analysis of SARS-CoV-2-mNeonGreen-infected Caco-2 cells could confirm a similar antiviral effect of Quinine in a human-derived cell line. Thereby, our in vitro studies revealed, that the antiviral effect appears to be specific, since in Vero cells Quinine impacted cell viability at approximately 50-fold higher concentration, while the therapeutic window of H-CQN and CQN was approximately 10-fold lower. In Caco-2 cells no toxic effect was observed while complete block of infection occurred between 50 and 100 µM at high MOIs. In conclusion, our data indicate that Quinine would have the potential of a well tolerable and widely used treatment option for SARS-CoV-2 infections, with a predictable and significantly better toxicological profile when compared to H-CQN or CQN.

The rapidly increasing adoption of high-resolution accurate-mass methods in analytical laboratories has fueled demand for instruments that combine high performance and reliability with small size and greater ease-of-use. This paper presents the major design principles that are driving the evolution of the hybrid quadrupole-Orbitrap instrument architecture to enable a greater range of applications and users. These principles may be summarized as follows: better usage of physical space and better access for service by means of size reduction of pumping and ion optics; expanded use of technologies from electronics in ion-optical design; flexibility in performance via modularity of design of the hardware and software components; and, harmonization of interfaces with other instruments to facilitate sharing and transferability of analytical workflows. The design of a novel family of hybrid mass spectrometers is described in detail, and performance evaluation is carried out on a wide variety of samples for its three representatives: the Orbitrap Exploris 120, Orbitrap Exploris 240 and Orbitrap Exploris 480 mass spectrometers.The new instrument family is shown to offer compelling potential not only for high-end proteomics and biopharmaceutical applications, but also for screening, trace, targeted and clinical analysis by liquid chromatography/mass spectrometry methods.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

In this report, we demonstrate that it is possible to design epitope-based peptide vaccine candidates to counteract the novel China coronavirus (2019-nCoV) by using an approach similar to the one used in cancer neoantigen vaccination therapy. We identified multiepitope peptide vaccine candidates against 2019-nCov that can potentially trigger both CD4⁺ and CD8⁺ T cell immune response with increased efficiency due to the presence of CD4⁺ and CD8⁺ T cell epitopes and a cathepsin-sensitive linker. Furthermore, we suggest that the peptide design strategy should incorporate population-specific HLA alleles in order to optimize binding specificity of the peptides. We refer to this as populationalized vaccinomics.

The production of lithium-ion battery cells is characterized by a high degree of complexit due to numerous cause-effect relationships between process characteristics. Knowledge about the multi-stage production is spread among several experts, rendering tasks such as failure analysis challenging. In this paper, a method is presented, which includes expert knowledge acquisition in production ramp-up by combining Failure Mode and Effects Analysis (FMEA) with a Bayesian Network. We show the effectiveness of this holistic method by building up a large scale, cross-process Bayesian Failure Network in lithium-ion battery production. Using this model, we are able to conduct root cause analyses as well as analyses of failure propagation. The former support operators in identifying root causes once a cell possesses a specific failure by calculating most-probable explanations matched to the individual battery cell data. The latter enable us to analyze propagation of failures and deviations in the production chain and thus provide support for placement of quality gates, leading to a significant reduction in scrap rate. Moreover, it gives an insight into which process steps are key drivers for which final product characteristics.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a global threat to human health and disease risk increases with advancing age. The regulation of the ACE2 gene that codes for COVID-19 host receptor ACE2 has been shown to be under epigenetic regulation. Here, we examined whether intensive DNA methylation profiling of the ACE2 gene differed by human host tissue and cell type, gender, and age. Results: Accessing four public datasets, we observed unique human cell-type-specific ACE2 DNA methylation patterns. In human lung tissues, gender differences in DNA methylation at 2 sites related to the ACE2 gene were identified. Further, in freshly isolated airway epithelial cells, DNA methylation near the transcription start site of the ACE2 gene associated with biological age. Conclusion: Epigenetic profiling of host tissue may permit discovery of age and gender-related potential risk factors for COVID-19. How perturbations in ACE2 methylation relate to clinical severity across the ages and gender needs to be determined to guide screening tools and potential epigenetic modification targeting to alleviate COVID-19 morbidity in the elderly.

This study used eco-friendly materials known as Periwinkle Shell Powder (PSP) in stabilizing the engineering properties of lateritic soil. Preliminary test was performed on the un-stabilized lateritic soil for the purposes of identification and classification (natural moisture content, liquid limits, plastic limits, and plasticity index). The engineering tests were conducted on the lateritic soil stabilized with additions of (2, 4, 6, 8 and 10 %) PSP and OPC respectively. The result showed that cement gave a progressive increase in the Maximum Dry Density (MDD) of the lateritic soil from 1875 kg/m3 (2 %) to 2294 kg/m3 (10 %) respectively. This represents 22 % increase in the MDD from the un-stabilized state. For PSP, the Maximum MDD was attained at 6 % (1974 kg/m3), representing 5.3 % increase in MDD of the soil from the un-stabilized state. For both stabilizing agent, the Optimum Moisture Content (OMC) increases from 13.65 % to 13.83 % and from 11.72 % to 14.41 % for Cement and Periwinkle Shell Powder respectively. PSP recorded an increase of 5.6 % of CBR value compared with OPC that recorded an increase of 34 % CBR value. The study therefore concluded that Periwinkle Shell Powder (PSP) could be considered as good stabilizer for clayey or lateritic, and its uses as a stabilizer could also provide a big relief to the environmental pollution caused by its indiscriminate dumping.

The spillover of the terrorist activities of Boko Haram, a Nigerian jihadi group, into Cameroon’s northern region has resulted in security challenges and humanitarian activity opportunities for Christian churches. The insurgents have attacked and destroyed churches, abducted Christians, worsened Muslim-Christian relations, and caused a humanitarian crisis. Aggregately, these ensuing phenomena have adversely affected Christian churches in this region, triggering an aura of responses: coping strategies, humanitarian work among refugees, and inter-faith dialogue. These responses are predicated on Christianity’s potential as a resource for peace, compassion, and love. In this study we emphasize the role of Christian churches in dealing with the Boko Haram insurgency. It opens up with a contextualization of Boko Haram in Cameroon’s north. This is followed by an examination of the brutality meted out on Christians and church property. The final section is an examination of the spiritual, humanitarian and relief services provided by Christian churches. The paper argues that although Christian churches have suffered at the hands of Boko Haram insurgents, they have engaged in various beneficial responses underpinned by the Christian values of peace and love.

Polylactic Acid (PLA) is an organic polymer commonly used in fused deposition (FDM) printing and biomedical scaffolding that is biocompatible and immunologically inert. However, variations in source material quality and chemistry make it necessary to characterize the filament and determine potential changes in chemistry occurring as a result of the FDM process. We used several spectroscopic techniques, including laser confocal microscopy, Fourier-Transform Infrared (FTIR) spectroscopy and photoacousitc FTIR spectroscopy, Raman spectroscopy, and X-ray photoelectron Spectroscopy (XPS) in order to characterize both the bulk and surface chemistry of the source material and printed samples. Scanning Electron Microscopy (SEM) and Differential Scanning Calorimetry (DSC) were used to characterize morphology, crystallinity, and the glass transition temperature following printing. Analysis revealed calcium carbonate-based additives which were reacted with organic ligands and potentially trace metal impurities, both before and following printing. These additives became concentrated in voids in the printed structure. This finding is important for biomedical applications as carbonate will impact subsequent cell growth on printed tissue scaffolds. Results of chemical analysis also provided evidence of the hygroscopic nature of the source material and oxidation of the printed surface, and SEM imaging revealed micro and sub-micron scale roughness that will also impact potential applications.

As a result of the spread of SARS-CoV-2, a global pandemic was declared. Indiscriminate COVID-19 vaccination has been extended to include age groups and naturally immune people with minimal danger of suffering serious complications due to COVID-19. Solid immuno-histopathological evidence demonstrates that the COVID-19 genetic vaccines can display an off-target distribution in tissues that are terminally differentiated, triggering autoimmune reactions. These include the heart and brain, which may incur in situ production of spike protein eliciting a strong autoimmunological inflammatory response. Due to the fact that every human cell which synthesizes non-self antigens becomes inevitably the target of the immune system, and since the human body is not a strictly compartmentalized system, accurate pharmacokinetic and pharmacodynamic studies are needed in order to determine precisely which tissues can be harmed. Therefore, our article aims to draw the attention of the scientific and regulatory communities on the critical need of bio-distribution studies for the genetic vaccines against COVID-19, as well as of rational harm-benefit assessments by age group.

Crop-type mapping is an important intermediate step for cost-effective crop management at the field level, as an overview of all fields with a particular crop type can be used for monitoring or yield forecasting, for instance. Our study used a data set with 2400 fields and corresponding satellite observations from the federal state of Bavaria, Germany. The study classified corn, winter wheat, winter barley, sugar beet, potato, and winter rapeseed as the main crops grown in Upper Bavaria. We additionally experimented with a rejection class "Other", which summarised further crop types. Corresponding Sentinel-2 data included the normalised difference vegetation index (NDVI) and raw bands from 2016 to 2018 for each selected field. The influence of raw bands compared to NDVI was analysed and the classification algorithms, i.e. support vector machine (SVM) and random forest (RF), were compared. The study showed that the use of an index should be critically questioned and that raw bands provided a wider spectral bandwidth, which significantly improved the mapping of crop types. The results underline the use of RF with raw bands and achieved overall accuracies (OA) of up to 92%. We also predicted crop types in an unknown year with significantly different weather conditions and several months before the end of the growing season. Thus, the influence of climate anomalies and the accuracy depending on the time of prediction were assessed. The crop types of a test site and year without labels could be determined with an OA of up to 86%. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.

This research article reports the results of a qualitative case study that correlates academic literature with five Industry 4.0 cyber trends, seven cyber risk frameworks and two cyber risk models. While there is a strong interest in industry and academia to standardise existing cyber risk frameworks, models and methodologies, an attempt to combine these approaches has not been done until present. We apply the grounded theory approach to derive with integration criteria for the reviewed frameworks, models and methodologies. Then, we propose a new architecture for the integration of the reviewed frameworks, models and methodologies. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of a holistic economic impact assessment model for IoT cyber risk.

The concept of a Social License to Operate (SLO) has become increasingly important in the sustainability literature in recent years. Having its origins in the business discourse of the mining industry with respect to limiting opposition to mining projects, the notion of a social contract above and beyond legal requirements has since become applied across a number of different industries. Despite the concepts adoption confusion exists over the practices and outcomes of SLO, and particularly the nature of engagement. Given this situation it is surprising that not more attention to the role of marketing, and social marketing in particular, in operationalizing the concept. The paper discusses the potential of social marketing to contribute to SLO. Economic, political and social relations are complex in SLO and exchange is intricate in such relational environments. A community-based social marketing orientation is proposed as a means to improve exchange relations and enhance engagement. Seven models of SLO related social marketing models are discussed with community-based social marketing and adaptive co-marketing models being regarded as the most positive for the achievement of an SLO. Potential barriers to adoption of these approaches are noted.

Diesel, gas oil, whole crudes, and bitumen samples were subjected to sulfoxidation, and then subjected to hydroxide attack in the presence of ethylene or propylene glycol. The resultant oils were analyzed by XRF for total sulfur and XANES spectroscopy for sulfur speciation at each stage. The combination of these analyses gave the total amount of sulfur as organic sulfide, sulfoxide, and sulfone at each stage of treatment so as to determine the effectiveness of the desulfonylation for sulfur compounds of different oxidation states.

Oligo- and polyesters of polyglycerol and polyricinoleic acid are widely used as emulsifiers in various industries. Based on the condensation of glycerol and its oligomers with epoxidized derivatives of vegetable oils, new promising emulsifiers for oil-water systems were obtained. Complex structural and functional spectral analysis of synthesized substances showed that the main reactions leading to the formation of the desired products were the opening of epoxide cycles, the transesterification of esters and the condensation of fatty acid derivatives. The new combination of renewable raw materials is of undoubted interest for deeper vegetable oils chemical processing.

Sensory Processing Sensitivity (SPS) is a trait describing inter-individual differences in sensitivity to environments, both positive and negative ones. SPS has attracted growing societal interest. However, (neuro)scientific evidence is lagging behind. We critically discuss how to measure SPS, how it relates to other theories of Environmental Sensitivity and other temperament and personality traits, how SPS interacts with environments to influence (a)typical development, what the underlying aetiologies and mechanisms are, and its relation to mental disorders involving sensory sensitivities. Drawing on the diverse expertise of the authors, we set an agenda for future research to stimulate the field. We conclude that SPS is a heritable, evolutionarily conserved trait, linked to increased risk for psychopathology and stress-related problems in response to negative environments, as well as to greater benefits (e.g., intervention responsivity, positive mood) in positive environments. We need advances in objective assessment of SPS, understanding mechanisms, differentiating it from (seemingly) related mental disorders, to exploit the potential of SPS to improve mental health, preserve human capital, and prevent adverse effects.

Solanesol is a noncyclic terpene alcohol composed of nine isoprene units and it mainly accumulates in solanaceous plants, especially tobacco (Nicotiana tabacum L.). Here, RNA-seq analyses of tobacco leaves, stems, and roots were used to identify solanesol biosynthesis genes. Six 1-deoxy-d-xylulose 5-phosphate synthase, two 1-deoxy-d-xylulose 5-phosphate reductoisomerase, two 2-C-methyl-d-erythritol 4-phosphate cytidylyltransferase, four 4-diphosphocytidyl-2-C-methyl-d-erythritol kinase, two 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase, four 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, two 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase, six isopentenyl diphosphate isomerase, and two solanesyl diphosphate synthase (SPS) genes were identified to be involved in solanesol biosynthesis. Furthermore, the two N. tabacum SPS (NtSPS1 and NtSPS2), which had two conserved aspartate-rich DDxxD domains, were highly homologous with SPS enzymes from other solanaceous plant species. In addition, the solanesol contents of three organs, and leaves from four growing stages, corresponded with the distribution of chlorophyll. Our findings provide a comprehensive evaluation of the correlation between the expression of different biosynthetic genes and the accumulation of solanesol in tobacco.

Problem solving is one of the most important components of the human cognition that affects for ages the progress of the human society. Mathematical modelling is a special type of problem solving concerning problems related to science or everyday life situations. The present study is a review of the author’s earlier works on problem solving and mathematical modelling from the scope of Education. Its real goal is that it presents in a systematic way and in a few pages only the results of many years research on the subject. This helps the reader to get a comprehensive idea about a very important topic belonging to the core of Mathematics Education, which is very useful to those wanting to study deeper the subject and get directions for further research in the area.

The aim of this article is to summarize recent bioinformatic and statistical developments applicable to NMR-based metabolomics. Extracting relevant information from large multivariate datasets by statistical data analysis strategies may be of considerable complexity. Typical tasks comprise for example classification of specimens, identification of differentially produced metabolites, and estimation of fold changes. In this context it is of prime importance to minimize contributions from unwanted biases and experimental variance prior to these analyses. This is the goal of data normalization. Therefore, special emphasize is given to different data normalization strategies. In the first part, we will discuss the requirements and the pros and cons for a variety of commonly applied strategies. In the second part, we will concentrate on possible solutions in case that the requirements for the standard strategies are not fulfilled. In the last part, very recent developments will be discussed that allow reliable estimation of metabolic signatures for sample classification without prior data normalization. In this contribution special emphasis will be given to techniques that have worked well in our hands.

Nutrigenetics concerns individual differences in the reaction to food based on the genetic factors. Nutrigenomics analyses direct influences of nutrients on gene expression. Both terms are explained in our review article. Nutrigenetics and nutrigenomics require a deep understanding of nutrition, genetics and biochemistry and of new ‘omic’ technologies. It is often difficult to appreciate their relevance in the practice of preventive approaches for optimizing health, delaying onset of disease and diminishing its severity. This paper represents a review about the current research on Nutrigenomics and Nutrigenetics, and provide scientific data for a new integrated clinical approach.

The research field of two dimensional (2D) materials strongly relies on optical microscopy characterization tools to identify atomically thin materials and to determine their number of layers. Moreover, optical microscopy-based techniques also opened the door to study the optical properties of these nanomaterials. We present a comprehensive study of the differential reflectance spectra of 2D semiconducting transition metal dichalcogenides (TMDCs), MoS₂, MoSe₂, WS₂ and WSe₂, with thickness ranging from one layer up to six layers. We analyze the thickness-dependent energy of the different excitonic features, indicating the change in the band structure of the different TMDC materials with the number of layers. Our work provides a route to employ differential reflectance spectroscopy for determining the number of layers of MoS₂, MoSe₂, WS₂ and WSe₂.

In this paper, the technical aspects of a multi-lidar instrument, the long-range WindScanner system, will be presented accompanied by an overview of the results from several field campaigns. The long-range WindScanner system consists of three spatially separated coherent Doppler scanning lidars and a remote master computer that coordinates them. The lidars were carefully engineered to perform arbitrary and time controlled scanning trajectories. Their wireless coordination via the master computer allows achieving and maintaining lidars’ synchronization within ten milliseconds. As a whole, the long-range WindScanner system can measure an entire wind field by emitting and directing three laser beams to intersect, and then by moving the beam intersection over the points of interest. The long-range WindScanner system was developed to tackle the need for high-quality observations of wind fields from scales of modern wind turbine and wind farms. It has been in operation since 2013.

Anxiety disorders manifest in women more than in men by almost twofold. This narrative review aims to summarize the sex-related biological factors, which underpin anxiety, focusing on the interactions of sex and tryptophan/serotonin with anxiety.A literature search was conducted using Google Scholar, PubMed/MEDLINE, Scopus, and EMBASE databases from inception until December 31, 2017. This review shows that sex may interact with many serotonin functions thereby modulating anxiety, including 5-HT1A and 5-HT2C receptors, 5-HT transporter and central 5-HT concentrations and metabolism. Sex-steroids modulate the expression of serotonin transporter genes, creating a difference in serotonin availability. Sex and estrous cycle phases lead to varying anxiety responses to tryptophan depletion. Testosterone, progesterone and estrogen are important factors in mediating sex differences in serotonin responses to anxiety-generating behavioral tests. At prenatal levels, there are sex-related differences in the reciprocal relationships between serotonin and the HPA-axis, which modulate anxiety-like behaviors. Activated immune-inflammatory pathways induce indoleamine-2,3-dioxynease (IDO) and the tryptophan catabolite (TRYCAT) pathway thereby increasing tryptophan degradation and increasing the production of TRYCATs including kynurenine and quinolinic acid, which may create an overall anxiogenic effect. The effects of immune activation on IDO are significantly more pronounced in women than men and therefore females may show increased levels of anxiogenic TRYCAT following immune challenge. Aberrations in the IDO-activated TRYCAT pathway are found in pregnant females and parturients and are associated with increased anxiety levels in the postnatal period. The results of this review underscore the necessity of studying the associations between serotonin and anxiety in both sexes taking into account the effects of immune activation on IDO and production of anxiogenic TRYCATs. Future anxiety research should focus on the interactions between serotonin/tryptophan and sex, sex hormones, the menstrual cycle, pregnancy, the HPA axis and the immune system through production of anxiogenic TRYCATs.

The current report represents a case of a 77-year-old man with Parkinson’s disease who died three weeks after receiving his third COVID-19 vaccination in January 2022. The patient was first vaccinated in May 2021 with the ChAdOx1 nCov- 19 vector vaccine, followed by two more doses with the BNT162b2 mRNA vaccine in July and December 2021. The family of the deceased requested an autopsy due to the ambivalent clinical features noted before death. The underlying illness (Parkinson’s disease) was confirmed by autopsy. However, no sign of a florid COVID-19 was discovered. Meanwhile, the immunohistochemical staining of the brain and heart revealed previously undiagnosed conditions. The brain, in distinctive, revealed multifocal necrotizing encephalitis with massive inflammatory lymphocyte infiltrates. In addition, the heart showed signs of serious myocarditis. Finally, immunohistochemical staining revealed that the SARS-CoV-2 spike protein was evident in the tissues investigated. Based on these immunohistochemical findings, it appears that the inflammatory changes in the patient's brain tissues are most likely the result of immunological processes. Concurrently, the absence of SARS-CoV-2 nucleocapsid-protein was evidenced, indicating that the detected spike-protein is unrelated to a SARS-CoV-2 infection. If such an infection was the cause of the spike protein, the SARS-CoV-2 nucleocapsid protein would also be detectable. As a consequence, the confirmed presence of the spike protein had to be attributed to the previous vaccination with the BNT162b2 mRNA vaccine that the deceased patient had received.

Background: Pittosporum tobira (Thunb.) Aiton is an aromatic medicinal plant widely cultivated in the world. However, the essential oils (EOs) from P. tobira flowers for anti-cancer potential is still not systematically studied. The present aim to elucidate the phytochemical composition of the EOs and to explore mechanism of anticancer action. Methods: The EOs were extracted and analyzed by headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry (GC-MS). Volatile components were identified according to Kovats retention index (KI) and NIST database. The anti-neoplasm mechanisms of the EOs was comprehensively investigated in lung carcinoma A549 and H460 cells. Results: A total of 47 secondary metabolites representing 94.18% of the EOs were successfully identified: monoterpenes and sesquiterpenes were the dominant terpenoids. The EOs exhibited antiproliferative activity on A549 and H460 lung carcinoma cells. Hoechst 33324 fluorescent staining indicated the typical characteristics of apoptosis and induced cycle phase arrest. AnnexinV/PI staining revealed that the number of apoptotic cells was increased. Furthermore, the EOs also induced the caspase-mediated mitochondrial apoptosis pathway. Conclusions: Findings suggest that the full-scale chemical composition and first characterization of anticancer activities of the EOs, it could be used for integrative natural anti-cancer agents in health care should be pay more attention.

The microtubule-associated protein TAU is sorted into the axon in healthy brain neurons. Somatodendritic missorting of TAU is a pathological hallmark of many neurodegenerative diseases called tauopathies, including Alzheimer’s Disease (AD). Cause, consequence, and (patho)physiological mechanisms of TAU sorting and missorting are understudied, in part also due to the lack of readily available human neuronal model systems. The human neuroblastoma cell line SH-SY5Y is widely used for studying TAU physiology and TAU-related pathology in AD and related tauopathies. SH-SY5Y cells can be differentiated into neuron-like cells (SH-SY5Y-derived neurons) using various substances. This review evaluates whether SH-SY5Y-derived neurons are a suitable model for i) investigating intracellular TAU sorting in general, and ii) with respect to neuron subtype-specific TAU vulnerability. I) SH-SY5Y-derived neurons show pronounced axodendritic polarity, high levels of axonally localized TAU protein, expression of all six major human brain isoforms, and TAU phosphorylation similar to the human brain. As proliferative cells, SH-SY5Y cells are readily accessible for genetic engineering, stable transgene integration and leading-edge genome editing are valuable and promising tools for TAU-related studies. II) Depending on the used differentiation procedure, SH-SY5Y-derived neurons resemble cells of distinct subcortical nuclei, i.e. the Locus coeruleus (LC), Nucleus basalis (NB) and Substantia nigra (SN), all of which early affected in many tauopathies. This allows to analyse neuron-specific TAU isoform expression and intracellular localization, also in the context of vulnerability to TAU pathology. Limitations are e.g. the lack of mimicking age-related tauopathy risk factors and the difficulty to define the exact neuronal subtype of SH-SY5Y-derived neurons. In brief, this review discusses the suitability of SH-SY5Y-derived neurons for investigating TAU (mis)sorting mechanisms and neuron-specific TAU vulnerability in disease paradigms.

The philosophy of testing statistical hypothesis is a natural consequence and functional extension of mathematical analysis of Probability. Along with the concept of recurrence when applied to random sequences and functions, it leads to the analysis of a priori and posterior which implies testing statistical hypothesis. Testing statistical hypothesis also involves algebraic, functional and dimensional considerations, which are found in the works of Laplace. Aspects of mathematical analysis such as universality of solutions, Laws of Large Numbers, Entropy, Information, and various functional dependencies are the main factors explained in the five properties that lead to implication of testing statistical hypothesis. Various interesting examples with modern scientific significance from genetics, astrophysics, and other areas give methodological access to answers of different problems and phenomena which are involved in the logic of testing statistical hypothesis.

The world is currently experiencing the fourth industrial revolution driven by the newest wave of digitisation in the manufacturing sector. The term Industry 4.0 (I4.0) represents at the same time: a paradigm shift in industrial production, a generic designation for sets of strategic initiatives to boost national industries, a technical term to relate to new emerging business assets, processes and services, and a brand to mark a very particular historical and social period. I4.0 is also referred to as Industrie 4.0 the New Industrial France, the Industrial Internet, the Fourth Industrial Revolution and the digital economy. These terms are used interchangeably in this text. The aim of this article is to discuss major developments in this space in relation to the integration of new developments of IoT and cyber physical systems in the digital economy, to better understand cyber risks and economic value and risk impact. The objective of the paper is to map the current evolution and its associated cyber risks for the digital economy sector and to discuss the future developments in the Industrial Internet of Things and Industry 4.0.

It is widely recommended to group house male laboratory mice because they are ‘social animals’, but male mice do not naturally share territories and aggression can be a serious welfare problem. Even without aggression, not all animals within a group will be in a state of positive welfare. Rather, many male mice may be negatively affected by the stress of repeated social defeat and subordination, raising concerns about welfare and also research validity. However, individual housing may not be an appropriate solution, given the welfare implications associated with no social contact. An essential question is whether it is in the best welfare interests of male mice to be group- or singly-housed. This review explores the likely impacts, positive and negative, of both housing conditions, presents results of a survey of current practice and awareness of mouse behaviour, and includes recommendations for good practice and future research. We conclude that whether group- or single-housing is better (or less worse) in any situation is highly context-dependent according to several factors including strain, age, social position, life experiences, and housing and husbandry protocols. It is important to recognise this and evaluate what is preferable from animal welfare and ethical perspectives in each case.

Despite their limited spatial extent, freshwater ecosystems host remarkable biodiversity, including one third of all vertebrate species. This biodiversity is declining dramatically: globally, wetlands are vanishing three times faster than forests and freshwater vertebrate populations have fallen more than twice as steeply as terrestrial or marine populations. Threats to freshwater biodiversity are well- documented but co-ordinated action to reverse this decline is lacking. We present an Emergency Recovery Plan to “bend the curve” of freshwater biodiversity loss. Priorities for action include: 1) accelerating implementation of environmental flows, 2) improving water quality, 3) protecting and restoring critical habitats, 4) managing exploitation of freshwater species and riverine aggregates, 5) preventing and controlling non-native species invasions, and 6) safeguarding and restoring river connectivity. We recommend revised targets and indicators for the Convention on Biological Diversity and the Sustainable Development Goals, and investment in enabling conditions at national, river basin and local scales.

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

This is a case study of a 55-year-old patient who died four months after receiving the mRNA-vaccine BNT162b2 (Pfizer-BioNTech) against COVID-19 as a second dose, following an initial vaccination with the ChAdOx1 nCov-19 vector vaccine (AstraZeneca) two months earlier. The autopsy diagnosis revealed general atherosclerosis. The histopathologic analyses of cardiac tissue demonstrated the presence of a thrombus occluding the right coronary artery (RCA) without evidence of plaque rupture. As a substitute trigger of clotting, the RCA presented with characteristics of acute lymphocytic vasculitis that extended to vasa vasorum in the adventitia and vessels in adjacent adipose tissue. Microthrombi were occasionally detected in these small vessels. It was obvious that lymphocytic myocarditis had been a chronic ongoing process temporally distinct from acute myocardial infarction. The myocardium contained patchworks of fibrotic areas alongside foci of displaying acute inflammation and fresh myocyte damage. SARS-CoV-2 Spike protein, but not nucleocapsid protein was sporadically detected in vessel walls by immunohistochemical assay. The cause of death was determined to be acute myocardial infarction and lymphocytic myocarditis. These findings indicate that myocarditis, as well as thrombo-embolic events following injection of spike-inducing gene-based vaccines, are causally associated with a injurious immunological response to the encoded agent. Because of the fact that the immune response to a first gene-based vaccination is very low in comparison with the immune response to the second vaccination, the found adverse events has rather to be attributed to the mRNA-based second vaccination as to the initial vector-based one.

Originally developed to image the shadow region of the central black hole in Sagittarius A* and in the nearby galaxy M87, the Event Horizon Telescope (EHT) provides deep, very high angular resolution data on other AGN sources too. The challenges of working with EHT data have spurred the development of new image reconstruction algorithms. This work briefly reviews the status of the EHT and its utility for observing AGN sources, with emphasis on novel imaging techniques that offer the promise of better reconstructions at 1.3 mm and other wavelengths.

The choice associated with words is a fundamental property of natural languages. It lies at the heart of quantitative linguistics, computational linguistics, and language sciences more generally. Information-theory gives us tools at hand to measure precisely the average amount of choice associated with words—the word entropy. Here we use three parallel corpora—encompassing ca. 450 million words in 1916 texts and 1259 languages—to tackle some of the major conceptual and practical problems of word entropy estimation: dependence on text size, register, style and estimation method, as well as non-independence of words in co-text. We present three main results: 1) a text size of 50K tokens is sufficient for word entropies to stabilize throughout the text, 2) across languages of the world, word entropies display a unimodal distribution that is skewed to the right. This suggests that there is a trade-off between the learnability and expressivity of words across languages of the world. 3) There is a strong linear relationship between unigram entropies and entropy rates, suggesting that they are inherently linked. We discuss the implications of these results for studying the diversity and evolution of languages from an information-theoretic point of view.

Background: CCL11 (eotaxin) is a chemokine with an important role in allergic conditions. Recent evidence indicates that CCL11 plays a role in brain disorders as well. Aims: This paper reviews the associations between CCL11 and aging, neurodegenerative, neuroinflammatory and neuropsychiatric disorders.Methods: Electronic databases were searched for original articles examining CCL11 in neuropsychiatric disorders.Results: CCL11 is rapidly transported from the blood to the brain through the brain-blood barrier. Age-related increases in CCL11 are associated with cognitive impairments in executive functions, episodic and semantic memory and, therefore, this chemokine was described as an “endogenous cognition deteriorating chemokine” (ECDC) or “accelerated brain-aging chemokine” (ABAC). In schizophrenia, increased CCL11 is not only associated with impairments in cognitive functions, but also with key symptoms including formal thought disorders. Some patients with mood disorders and premenstrual syndrome show increased plasma CCL11 levels. In diseases of old age, CCL11 is associated with lowered neurogenesis and neurodegenerative processes and, as a consequence, increased CCL11 increases risk towards Alzheimer's Disease. Polymorphisms in the CCL11 gene are associated with stroke. Increased CCL11 also plays a role in neuroinflammatory disease including multiple sclerosis. In animal models, neutralization of CCL11 may protect against nigrostriatal neurodegeneration. Increased production of CCL11 may be attenuated by glucocorticoids, minocycline, resveratrol and anti-CCL11 antibodies.Conclusion: Increased CCL11 production during inflammatory conditions may play a role in human disease including age-related cognitive decline, schizophrenia, mood disorders and neurodegenerative disorders. Increased CCL11 production is a new drug target in the treatment and prevention of those disorders.

In humankind’s endeavor to explore beyond our planet and travel further into space, we are now at the threshold of an era in which it is possible to move to and from low Earth orbit (LEO) with increasing ease and reduced cost. Through the International Space Station (ISS) U.S. National Laboratory, investigators from industry, academia, and government can easily access the unique LEO environment on the ISS to conduct research and development (R&D) activities in ways not possible on Earth. A key advantage of the LEO environment for life sciences research is the ability to conduct experiments in sustained microgravity conditions. The ability to conduct long-term research in microgravity enables opportunities for novel, fundamental studies in tissue engineering and regenerative medicine, including research on stem cell proliferation and differentiation, biofabrication, and disease modeling using microphysiological systems (MPS) that build on prior research using simulated microgravity conditions (Grimm, D., et al. 2018). Over the last decade, space-based research has demonstrated that microgravity informs our knowledge of fundamental biology and accelerates advancements in health care and medical technologies (International Space Station 2019). The benefits provided by conducting biomedical research in LEO may lead to breakthroughs not achievable on Earth. We are now at a transition point, in which nations are changing their approach to space-based R&D. The focus is shifting from government-funded fundamental science toward the expansion of privately funded R&D with terrestrial application and economic value that will drive a robust marketplace for innovation and manufacturing in LEO. Making this long-term transition requires public-private participation and near-term funding to support critical R&D to leverage the benefits of the LEO environment and de-risk space-based research. Studies conducted on the ISS over the past several years have indicated that one area with potential significant economic value and benefit to life on Earth is space-based biomanufacturing, or the use of biological and nonbiological materials to produce commercially relevant biomolecules and biomaterials for use in preclinical, clinical, and therapeutic applications. We must take advantage of the remaining lifetime of the ISS as a valuable LEO platform to demonstrate this economic value and Earth benefit. By facilitating access to the space station, the ISS National Lab is uniquely positioned to enable the R&D necessary to bridge the gap between the initial discovery phase of space-based biomedical research and the development of a sustainable, investment-worthy biomanufacturing market in LEO supported by future commercial platforms. Through a joint effort, the Center for the Advancement of Science in Space (CASIS), which manages the ISS National Lab, and the University of Pittsburgh’s McGowan Institute for Regenerative Medicine brought together thought leaders from around the U.S. for a Biomanufacturing in Space Symposium that consisted of a series of working sessions to review data from past space-based tissue engineering and regenerative medicine research, discuss relevant current space-based R&D in this area, and consider potential future markets to address the questions: What are the most promising opportunities to leverage the ISS to advance space-based biomanufacturing moving forward? What are the current gaps or barriers that, if overcome, could clear pathways toward private investment in LEO as a valued site for research, development, and production activity? And, most importantly: For which opportunities do the most compelling value propositions exist? The goal of the Biomanufacturing in Space Symposium was to help identify the specific areas in which government and industry investment would be most likely to stimulate advancements that overcome barriers. This would lead to a more investment-ready landscape for private interests to enter the market and fuel exponential growth. The symposium was meant to serve as the first step in developing a roadmap to a sustainable market for biomanufacturing in space. The symposium identified and prioritized multiple key R&D opportunities to advance space-based biomanufacturing. These opportunities fall in the areas of disease modeling, stem cells and stem-cell-derived products, and biofabrication. Additionally, symposium participants highlighted the critical need for additional data to help validate and de-risk these opportunities and concluded that approaches such as automation, artificial intelligence (AI), and machine learning will be needed to produce and capture the required data. Symposium participants also came to a consensus that public-private partnerships and funding will be needed to advance the opportunities toward a biomanufacturing marketplace in LEO. This paper will summarize the current state of the science and technology on the ISS and in the fields of tissue engineering and regenerative medicine; provide an overview of biomanufacturing R&D in space to date; review the goals of the Biomanufacturing in Space Symposium; highlight the key commercial opportunities and gaps identified during the symposium; provide information on potential market sizes; and briefly discuss the next steps in developing a roadmap to biomanufacturing in space.

The ongoing outbreak of the novel coronavirus pneumonia (also known as COVID-19) has triggered a series of stringent control measures in China, such as city closure, traffic restrictions, contact tracing and household quarantine. These containment efforts often lead to changes in the contact pattern among individuals of the population. Many existing compartmental epidemic models fail to account for the effects of contact structure. In this paper, we devised a pairwise epidemic model to analyze the COVID-19 outbreak in China based on confirmed cases reported during the period February 3rd--17th, 2020. By explicitly incorporating the effects of family clusters and contact tracing followed by household quarantine and isolation, our model provides a good fit to the trajectory of COVID-19 infections and is useful to predict the epidemic trend. We obtained the average of the reproduction number $R=1.494$ ($95\%$ CI: $1.483-1.507$) for Hubei province and $R=1.178$ ($95\%$ CI: $1.145-1.158$) for China (except Hubei), suggesting that some existing studies may have overestimated the reproduction number by neglecting the dynamical correlations and clustering effects. We forecasted that the COVID-19 epidemic would peak on February 13th ($95\%$ CI: February $9-17$th) in Hubei and 6 days eariler in the regions outside Hubei. Moreover the epidemic was expected to last until the middle of March in China (except Hubei) and late April in Hubei. The sensitivity analysis shows that ongoing exposure for the susceptible and population clustering play an important role in the disease propagation. With the enforcement of household quarantine measures, the reproduction number $R$ effectively reduces and epidemic quantities decrease accordingly. Furthermore, we gave an answer to the public concern on how long the stringent containment strategies should maintain. Through numerical analysis, we suggested that the time for the resumption of work and production in China (except Hubei) and Hubei would be the middle of March and the end of April, 2020, respectively. These constructive suggestions may bring some immeasurable social-economic benefits in the long run.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

Saccharomyces cerevisiae cells are killed by zymocin, a tRNase ribotoxin complex from Kluyveromyces lactis, which cleaves anticodons and inhibits protein synthesis. Zymocin’s action requires specific chemical modification of uridine bases in the anticodon wobble position (U34) by the Elongator complex (Elp1-Elp6). Hence, loss of anticodon modification in mutants lacking Elongator or related KTI (K. lactis Toxin Insensitive) genes protects against tRNA cleavage and confers resistance to the toxin. Here, we show that zymocin can be used as a tool to genetically analyse KTI12, a gene previously shown to code for an Elongator partner protein. From a kti12 mutant pool of zymocin survivors, we identify motifs in Kti12 that are functionally directly coupled to Elongator activity. In addition, shared requirement of U34 modifications for nonsense and missense tRNA suppression (SUP4; SOE1) strongly suggests that Kti12 and Elongator cooperate to assure proper tRNA functioning. We show that the Kti12 motifs are conserved in plant ortholog DRL1/ELO4 from Arabidopsis thaliana and seem to be involved in binding of cofactors (e.g. nucleotides, calmodulin). Elongator interaction defects triggered by mutations in these motifs correlate with phenotypes typical for loss of U34 modification. Thus, tRNA modification by Elongator appears to require physical contact with Kti12, and our preliminary data suggest that metabolic signals may affect proper communication between them.

To better understand farmers’ refusal and corresponding negative emotions to pay agricultural water fee under current policy in rural China, this paper applies mental accounting, a behavioral economics framework, to explore how the governmental policies of reform of rural taxes and fees, direct agricultural subsidy programs and agricultural water fee individually influence farmers’ decisions in paying agricultural water fee. Using fieldwork data from 577 farmers and 20 water managers in Sichuan, we explore farmers’ information processing regarding paying agricultural water fee via three sequential mental accounting processes, with the associated underlying principles and measures behind each process. We find that the information processing in three mental accounting scenarios related to the agricultural water fee elucidates farmers’ observed behaviors in rural China. Generally, in the three mental accounting scenarios, two conditional intuitive expectations and nine conditional intuitive preferences are formed, however, the conditions of those expectations or preferences cannot be matched with the facts due to the reform of rural taxes and fees, the direct agricultural subsidy programs and the internal attributes of agricultural water fee, which interpret those negative behaviors in rural China. Additionally, this paper offers a view into how previous policies create negative psychological externalities (such as farmers’ psychological dependence on the government) through mental accounting to negatively influence agents’ subsequent decision making; it highlights the significance of underlying mental factors and information processing of negative behaviors in policymaking for managing or conserving common pool resources.

Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

This work investigated the isothermal holding time dependence of the densification, microstructure, weight loss and tensile properties of Fe-Mn-Si powder compacts. Elemental Fe, Mn and Si powder mixtures with a nominal composition of Fe-28Mn-3Si (in weight percent) were ball milled for 5h and subsequently pressed under a uniaxial pressure of 400 MPa. The compacted Fe-Mn-Si powder mixtures were sintered at 1200 ℃ for 0, 1, 2 and 3 h, respectively. In general, the density, weight loss and tensile properties increased with the increase of isothermal holding time. A significant increase in density, weight loss and tensile properties occurred in the compacts isothermally holding for 1 h, as compared to those with no isothermal holding. However, further extension of isothermal holding time (2 and 3 h) only played a limited role in promoting the density and tensile properties. The weight loss of the sintered compacts was mianly caused by the sublimation of Mn in Mn depletion region on the surface layer of the sintered Fe-Mn-Si compacts. The length of the Mn depletion region increased as isothermal holding time increased. A single α-Fe phase was detected on the surface of all the sintered compacts, and the locations beyond the Mn depletion region were comprised of a dual dominant γ-austenite and minor ε-martensite.

The challenge posed by multi-drug resistance (MDR) of pathogenic organisms, spectacularly manifested in the 6 “ESKAPE” bacterium (two Gram-positive, four Gram-negative) species, should invoke new comprehensive strategies, and needs cooperation of scientists with medical, veterinary and natural science background. This review is aimed at informing newcomers, coming from the field of biology and genetics, about problems related to rapidly emerging, new multi-drug resistant, pathogenic, bacteria. Unlike persistence, the antibiotic resistance is inherited. A functioning “resistance gene” makes a susceptible organism resistant to a given antibiotic, encoding for polypeptides capable of acting either as decomposing enzymes, or acting as trans-membrane pumps, or membrane structure components capable of modifying the permeability implementing a «by pass» mechanism enabling the antibiotic molecule to reach its cellular target(s). A functioning “sensitivity gene” encode for a polypeptide, capable (directly or indirectly) of transferring toxic molecules into target cells, or of metabolizing non-transferable to transferable, or non-toxic molecules to toxic derivatives. A gene of a normal function could act as a “sensitivity” gene in the presence of antibiotics of chemical structures similar to the natural substrate of the gene product, (enzyme or binding/ trans-membrane protein). The Agrocin 84 story is a good example. Multi-drug resistance is a phenotypic consequence of the sequential accumulation of mutations, and/or up-take of plasmids or genomic islands carrying resistance genes from the environment via horizontal gene transfer, mediated by conjugative plasmid or bacteriophage carrying mobile genetic elements. Both multi-drug resistance and collateral sensitivity are evolutionary products. Some revealed evolutionary process and their Lamarckian and Darwinian interpretations are discussed. Toolkits of comparative full-genome sequencing, genomics, experimental evolution and population genetics may provide perspectives for overcoming the invincibility of multi-drug panresistance. The status of some recently emerging pathogenic bacterium species with zoonic features and of veterinary background is also discussed.

With Internet of Things (IoT) gaining presence throughout different industries a lot of new technologies have been introduced to support this undertaking. Implications on one such technology, wireless systems allowed for the use of different communication methods to achieve the goal of transferring data reliably, with more cost efficiency and over longer distances. Anywhere from a single house with only a few IoT devices such as a smart light bulb or a smart thermostat connected to the network, all the way to a complex system that can control power grids throughout countries, IoT has been becoming a necessity in everyday lives. This paper presents an overview of the devices, systems and wireless technologies used in different IoT architectures (Healthcare, Vehicular Networks, Mining, Learning, Energy, Smart Cities, Behaviors and Decision Making), their upbringings and challenges to this date and some foreseen in the future.

The development of low-cost, open-source Remotely Operated Vehicle (ROV) systems has provided almost unrestricted access for researchers looking to monitor the marine environment in ever greater resolution. Sampling microbial communities from the marine environment, however, still usually relies on Niskin-bottle sampling (ROV or CTD based), a method which introduces an inaccuracy and variability that is incompatible with metatranscriptomic analysis. Here, we describe a versatile, easily-replicated platform which achieves in situ mRNA preservation, via the addition of RNAlater to filtered microbial cells, to enhance ROV or CTD functionality.

The increasing popularity of porphyrins and hydroporphyrins for application in a variety of biomedical (photodynamic therapy, fluorescence tagging and imaging, photoacoustic imaging) and technical (chemosensing, catalysis, light harvesting) applications is also associated with the growing number of methodologies that enable their solubilization in aqueous media. Natively, the vast majority of synthetic porphyrinic compounds are not water-soluble. Moreover, any water-solubility imposes several restrictions on the synthetic chemist on when to install solubilizing groups in the synthetic sequence, and how to isolate and purify these compounds. This review summarizes the chemical modifications to render synthetic porphyrins water-soluble, with a focus on the work since 2000. Where available, practical data such as solubility, indicators for the degree of aggregation, and special notes for the practicioner are listed. We hope that this review will guide synthetic chemists through the many strategies known to make porphyrins and hydroporphyrins water soluble.

Cancer is often characterised by the presence of hypoxia and inflammation. Paramount to the mechanisms controlling cellular responses under such stress stimuli, are the transcription factor families of Hypoxia Inducible Factor (HIF) and Nuclear Factor of kappa-light-chain-enhancer of activated B cells (NF-кB). Although, a detailed understating of how these transcription factors respond to their cognate stimulus is well established, it is now appreciated that HIF and NF-кB undergo extensive crosstalk, in particular in pathological situations such as cancer. Here, we focus on the current knowledge on how HIF is activated by inflammation and how NF-кB is modulated by hypoxia. We summarise the evidence for the possible mechanism behind this activation and how HIF and NF-кB function impacts cancer, focusing on colorectal, breast and lung cancer. We discuss possible new points of therapeutic intervention aiming to harness the current understanding of the HIF-NF-кB crosstalk.

The advent of the genome editing era brings forth the promise of adoptive cell transfer using engineered chimeric antigen receptor (CAR) T-cells for targeted cancer therapy. CAR T-cell immunotherapy is probably one of the most encouraging developments for the treatment of hematological malignancies. In 2017, two CAR T-cell therapies were approved by the U. S Food and Drug Administration; one for the treatment of pediatric Acute Lymphoblastic Leukemia (ALL), the other for adult patients with advanced lymphomas. However, despite significant progress in the area, CAR T-cell therapy is still in its early days and faces significant challenges, including the complexity and costs associated with the technology. B-cell lymphoma is the most common hematopoietic cancer in dogs, with an incidence approaching 0.1% and a total of 20-100 cases per 100,000 individuals. It is a widely accepted naturally occurring model for human non-Hodgkin’s lymphoma. Current treatment is with combination chemotherapy protocols, which prolong life for less than a year in canines and are associated with severe dose-limiting side effects, such as gastrointestinal and bone marrow toxicity. To date, one canine study generated CAR T-cells by transfection of mRNA for CAR domain expression. While this was shown to provide a transient anti-tumor activity, results were modest, indicating that stable, genomic integration of CAR modules is required in order to achieve lasting therapeutic benefit. This Commentary summarizes the current state of knowledge on CAR T-cell immunotherapy in human medicine and its potential applications in animal health, while discussing the potential of the canine model as a translational system for immuno-oncology research.

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtained through a methodology applicable to any type of existing and upcoming nacelle lidar technology. The generic methodology consists in calibrating all the inputs of the wind field reconstruction algorithms of a lidar. These inputs are the line-of-sight velocity and the beam position, provided by the geometry of the scanning trajectory and the lidar inclination. The line-of-sight velocity is calibrated in atmospheric conditions by comparing it to a reference quantity based on classic instrumentation such as cup anemometers and wind vanes. The generic methodology was tested on two commercially developed lidars, one continuous wave and one pulsed systems, and provides consistent calibration results: linear regressions show a difference of ∼ 0.5 % between the lidar-measured and reference line-of-sight velocities. A comprehensive uncertainty procedure propagates the reference uncertainty to the lidar measurements. At a coverage factor of two, the estimated line-of-sight velocity uncertainty ranges from 3.2 % at 3 m s⁻¹ to 1.9 % at 16 m s⁻¹. Most of the line-of-sight velocity uncertainty originates from the reference: the cup anemometer uncertainty accounts for ∼ 90 % of the total uncertainty. The propagation of uncertainties to lidar-reconstructed wind characteristics can use analytical methods in simple cases, which we demonstrate through the example of a two-beam system. The newly developed calibration methodology allows robust evaluation of a nacelle lidar’s performance and uncertainties to be established in order to further be used for various wind turbines’ applications in confidence.

Crosslinking of proteins for their irreversible immobilization on surfaces is a proven and popular method. However, many protocols lead to random orientation and the formation of undefined or even inactive by-products. Most concepts to obtain a more targeted conjugation or immobilization requires the recombinant modification of at least one binding partner, which is often impractical or prohibitively expensive. Here a novel method is presented, which is based on the chemical preactivation of Protein A or G with selected conventional crosslinkers. In a second step, the antibody is added, which is subsequently crosslinked in the Fc part. This leads to an oriented and covalent immobilization of the immunoglobulin with a very high yield. Protocols for Protein A and Protein G with murine and human IgG are presented. This method may be useful for the preparation of columns for affinity chromatography, immunoprecipitation, antibodies conjugated to magnetic particles, permanent and oriented immobilization of antibodies in biosensor systems, microarrays, microtitration plates or any other system, where the loss of antibodies needs to be avoided, and maximum binding capacity is desired. This method is directly applicable even to antibodies in crude cell culture supernatants, raw sera or protein-stabilized antibody preparations without any purification nor enrichment of the IgG. This new method delivered much higher signals as a traditional method and, hence, seems to be preferable in many applications.

Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, the rapidly changing of LULC is mainly due to population pressure, resettlement programs, climate change, and other human and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatio-temporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. Seventeen articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview (KII), focal group discussions (FGDs) and collection of ground truth data using ground positioning systems (GPS) for data validation were the major approaches discussed in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed to agricultural land use, waterbody, commercial farmland and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland and bare/ rock out cropland cover class were changed to other LULC class types, mainly as a consequence of increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences. However, most of the study provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the basin scale.

Modularity is arguably one of the most influential theses guiding research on brain and cognitive function since phrenology. This paper considers the following question: is modularity entailed by recent Bayesian models of brain and cognitive function, especially the predictive processing framework? It starts by considering three of the most well-articulated arguments for the view that modularity and predictive processing work well together. It argues that all three kinds of arguments for modularity come up short, albeit for different reasons. The analysis in this paper, although formulated in the context of predictive processing, speaks to broader issues with how to understand the relationship between functional segregation and integration and the reciprocal architecture of the predictive brain. These conclusions have implications for how to study brain and cognitive function. Specifically, when cognitive neuroscience works within an acyclic Markov decision scheme, adopted by most Bayesian models of brain and cognitive function, it may very well be methodologically misguided. This speaks to an increasing tendency within the cognitive neurosciences to emphasise recurrent and reciprocal neuronal processing captured within newly emerging dynamical causal modelling frameworks. The conclusions also suggest that functional integration is an organising principle of brain and cognitive function.

Recent advances in sensor and platform technologies such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data is produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally refers to Common DataBase which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0 which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

Nanopowders are continuously under investigation as they open new perspectives in numerous fields. There are two main challenges to stimulate their development: sufficient low-cost high throughput synthesis methods leading to a production with well-defined and reproducible properties, and for ceramics, conservation of their nanostructure after sintering. In this context, this paper presents the synthesis of a pure nanosized powder of ZnO (dv₅₀ ~ 60 nm, easily redispersable) by using a continuous Segmented Flow Tubular Reactor (SFTR), which has previously shown its versatility and its robustness, ensuring a high powder quality and reproducibility over time. A higher scale of production can be achieved based on a “scale-out” concept by replicating the tubular reactors. The sinterability of ZnO nanopowders synthesized by the SFTR was studied, by natural sintering at 900 °C and 1100 °C, and Spark Plasma Sintering (SPS) at 900 °C. The performances of the synthesized nanopowder were compared to a commercial ZnO nanopowder of high quality. The samples obtained from the synthesized nanopowder could not be densified at low temperature by traditional sintering, whereas SPS led to a fully dense material after only 5 minutes at 900 °C, while limiting the grain growth and thus leading to a nanostructured material.

Bamboo agroforestry is currently being promoted as a viable land use option to reduce dependence on natural forest for wood fuels in Ghana. To align the design and introduction of bamboo agroforestry in conformity with farmers’ needs, perceptions, skills and local cultural practices, information on its acceptability and adoption potential among farmers is necessary. It is therefore the objective of this study to (1) describe bamboo ethnobotany and (2) assess socioeconomic factors that affect the acceptability and adoption of bamboo and its integration into farming practices. Accordingly, information has been collected from 200 farmers in the dry semi-deciduous forest zone of Ghana. The study identified the socioeconomic risks and uncertainties as well as biophysical factors that are likely to influence the potential adoption of bamboo agroforestry in the study region. Gender, age, farmers’ known uses of bamboo, the practice of leaving trees on farmlands, farmers’ networking and access to extension services, land availability and ownership by farmers were identified as suitable predictor variables for the adoption of bamboo agroforestry. It is envisaged that bamboo agroforestry is a good bet in the DSFZ though there is the need to explore domestic energy (fuelwood) provision and substitution potential in order to have a broader picture of the technology.

Software analysis, debugging, and reverse engineering have a crucial impact in today’s software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and implementation restrictions. In this paper, we present HyperDbg, a new hypervisor-assisted debugger for high-performance and stealthy debugging of user and kernel applications. To accomplish this, HyperDbg relies on state-of-the-art hardware features available in today’s CPUs, such as VT-x and extended page tables. In contrast to other widely used existing debuggers, we design HyperDbg using a custom hypervisor, making it independent of OS functionality or API. We propose hardware-based instruction-level emulation and OS-level API hooking via extended page tables to increase the stealthiness. Our results of the dynamic analysis of 10,853 malware samples show that HyperDbg’s stealthiness allows debugging on average 22% and 26% more samples than WinDbg and x64dbg, respectively. Moreover, in contrast to existing debuggers, HyperDbg is not detected by any of the 13 tested packers and protectors. We improve the performance over other debuggers by deploying a VMX-compatible script engine, eliminating unnecessary context switches. Our experiment on three concrete debugging scenarios shows that compared to WinDbg as the only kernel debugger, HyperDbg performs step-in, conditional breaks, and syscall recording, 2.98x, 1319x, and 2018x faster, respectively. We finally show real-world applications, such as a 0-day analysis, structure reconstruction for reverse engineering, software performance analysis, and code-coverage analysis.

COVID-19 represents an unprecedented threat to global public health and economies. Assays are urgently needed for rapid detection and diagnosis of SARS-CoV-2-infected patients in order to inform treatment and quarantine strategies. Establishing globally accepted easy-to-access diagnostic tests is extremely important to understanding the epidemiology of the present pandemic. While nucleic acid-based tests are considered to be more sensitive with respect to serological tests, but the present gold standard RT-PCR-based assays possess limitations such as low sample throughput, requirement for sophisticated reagents and instrumentation. To overcome these shortcomings, recent efforts of incorporating LAMP-based isothermal detection, and minimizing the number of reagents required are on rise. Novel CRISPR- and other nuclease-based techniques, when merge with isothermal and allied technologies, promises to provide sensitive and rapid detection of SARS-CoV-2 nucleic acids. Here we discuss and present compilation of state-of-the-art CRISPR based detection techniques for use in COVID diagnosis and epidemiology.

Population genetic data underpin many studies of behavioral, ecological, and evolutionary processes in wild populations and contribute to effective conservation management. However, collecting genetic samples can be challenging when working with endangered, invasive, or cryptic species. Environmental DNA (eDNA) offers a way to sample genetic material non-invasively without requiring visual observation. While eDNA has been trialed extensively as a biodiversity and biosecurity monitoring tool with a strong taxonomic focus, it has yet to be fully explored as a means for obtaining population genetic information. Here, we review current research that employs eDNA approaches for the study of populations. We outline challenges facing eDNA-based population genetic methodologies, and suggest avenues of research for future developments. We advocate that with further optimizations, this emergent field holds great potential as part of the population genetics toolkit.

The monitoring of sick newborns is a challenging task that health care providers in Neonatal Intensive Care Units (NICU) must contend with each day. Conventionally, newborns are monitored via probes that are affixed to their skin and attached to processing monitors (Fig.1). However, an alternative exists in contactless imaging to record such physiological signals (Physio-Markers), surface changes and internal structures which can be used independently of, or in conjunction with conventional monitors. Advantages of contactless monitoring methods include: i) quick data generation; ii) lack of contact with skin, which reduces skin breakdown and decreases risk of infection; and iii) minimizing the number of probes and monitors affixed to the skin, which allows greater body surface-area for other care. This paper is an attempt to build a foundation for and to provide a vision of the potential neonatal clinical applications of technologies that use non-contact modalities such as Visible Light Imaging (VLI), Near InfraRed Spectrum (NIRS), and Thermal Imaging (TI) using InfraRed Spectrum (IRS).

Automotive manufacturers and suppliers develop new vehicle systems, such as Advanced Driver Assistance Systems (ADAS), to increase traffic safety and driving comfort. ADAS are technologies that provide drivers with essential information or take over demanding driving tasks. More complex and intelligent vehicle systems are being developed toward fully autonomous and cooperative driving. Apart from the technical development challenges, training of drivers with these complex vehicle systems represents an important concern for automotive manufacturers. This paper highlights the new evolving requirements concerning the training of drivers with future complex vehicle systems. In accordance with these requirements, a new training concept is introduced, and a prototype of a training platform is implemented for utilization in future driving schools. The developed training platform has a scalable and modular architecture so that more than one driving simulator can be networked to a common driving instructor unit. The participating driving simulators provide fully immersive visualization to the drivers by utilizing head-mounted displays instead of conventional display screens and projectors. The driving instructor unit consists of a computer with a developed software tool for training session control, monitoring, and evaluation. Moreover, the driving instructor can use a head-mounted display to participate interactively within the same virtual environment of any selected driver. A simulation model of an autonomous driving system was implemented and integrated in the participating driving simulators. Using this simulation model, training sessions were conducted with the help of a group of test drivers and professional driving instructors to prove the validity of the developed concept and show the usability of the implemented training platform.

Iterated games, in which the same economic interaction is repeatedly played between the same agents, are an important framework for understanding the effectiveness of strategic choices over time. To date very little work has applied information theory to the information sets used by agents in order to decide what action to take next in such strategic situations. This article looks at the mutual information between previous game states and an agent's next action by introducing two new classes of games: ’invertible games’ and ‘cyclical games'. By explicitly expanding out the mutual information between past states and the next action we show under what circumstances these expressions can be simplified. These information measures are then applied to the Traveler's Dilemma game and the Prisoner's Dilemma game, the Prisoner's Dilemma being invertible, to illustrate their use. In the Prisoner's Dilemma a novel connection is made between the computational principles of logic gates and both the structure of games and the agents' decision strategies. This approach is applied to the cyclical game Matching Pennies to analyse the foundations of a behavioural ambiguity between two well studied strategies: ‘Tit-for-Tat' and ’Win-Stay, Lose-Switch'.

Injuries to the ligaments of the knee are extremely common among athletes who participate in high-risk sports, or any sport that requires frequent cutting motions, jumping, or contact. In order to determine the best way to heal these injuries, it is important to understand not just the pathology of the injury, but also the biomechanical factors that are affected, including stability and steadiness. While many studies have been done to examine the stability of healthy knees, there is little to no existing literature on stability of knees afflicted by injury. In order to surpass this obstacle, static steadiness and dynamic stability data was collected using the Lockhart Monitor phone application and Xsens accelerometers, respectively, both before and after completion of a course of physical therapy in a patient with a grade 2 medial collateral ligament (MCL) tear. These results were then used to determine the degree to which the prescribed physical therapy protocol was effective in healing the MCL, which can be useful for tweaking the individual protocol for future conservative treatment and management of the injury.

A subset of patients with schizophrenia experience physio-somatic symptoms reminiscent of chronic fatigue and fibromyalgia. In schizophrenia, these symptoms contribute to impaired quality of life, and are strongly related to neuro-cognitive deficits, and increased IgA responses to tryptophan catabolites. Negative and PHEM (psychosis, hostility, excitation, mannerism) symptoms, psychomotor retardation (PMR) and formal thought disorders, appear to be manifestations of a single trait reflecting overall severity of schizophrenia (OSOS). In this study, 120 patients with deficit schizophrenia (DEFSCZ) and 54 healthy subjects were assessed with the FibroFatigue (FF) rating scale, and the above-mentioned symptom domains as well as neuro-cognitive tests and biomarkers were measured. In DEFSCZ, there were robust associations between the FF score and all above-mentioned symptom domains, and impairments in semantic and episodic memory and executive functions. Furthermore, the FF score loaded highly on an OSOS latent vector (LV), which showed adequate convergent validity, internal consistency reliability and predictive relevance and fitted a reflective model. Soft Independent Modelling of Class Analogy (SIMCA) showed that the FF items discriminated DEFSCZ from controls with an overall accuracy of 100%. Interleukin IL-1β, IL-1 receptor antagonist (sIL-1RA), tumour necrosis factor (TNF)-α and CCL-11 (eotaxin) explained 66.8% of the variance in the FF score and 59.4% of the variance in OSOS. In conclusion, these data show that physio-somatic symptoms are a core component of the phenomenology of DEFSCZ and are largely mediated by neurotoxic effects of activated immune pathways, including aberrations in CCL-11, IL-1β and TNF-α signalling.

Wastewater surveillance for pathogens using the reverse transcription-polymerase chain reaction (RT-PCR) is an effective, resource-efficient tool for gathering additional community-level public health information, including the incidence and/or prevalence and trends of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater may provide an early-warning signal of COVID-19 infections in a community. The capacity of the world’s environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is rapidly increasing. However, there are no standardized protocols nor harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors. Recommendations include, stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly during a low incidence of SARS-CoV-2 in wastewater. Corrective and confirmatory actions must be in place for inconclusive and/or potentially significant results (e.g., initial onset or reemergence of COVID-19 in a community). It will also be prudent to perform inter-laboratory comparisons to ensure results are reliable and interpretable for ongoing and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance was demonstrated during this global crisis. In the future, wastewater will play an important role in the surveillance of a range of other communicable diseases.

Autonomous and cooperative vehicle systems represent a key priority in the automotive realm. Networked driving simulation can be utilized as a safe, cost-effective experimental replica of real traffic environments in order to support and accelerate the development of such systems. In networked driving simulation, different independent systems collaborate to achieve a common task: multi-driver traffic scenario simulation. Yet distinct system complexity levels are necessary to fulfill the requirements of various application scenarios, such as development of vehicle systems, analysis of driving behavior, and training of drivers. With myriad alternatives of available systems and components, developers of networked driving simulation are typically confronted with high design complexity. There are no systematic approaches to date for the design of networked driving simulation in accordance with the specific requirements of the concerned application scenarios. This paper presents a novel design method for networked driving simulation. The method consists mainly of a procedure model that is accompanied by a configuration software. The procedure model includes the necessary phases for the systematic design of application-oriented platforms for networked driving simulation. The configuration software embeds supportive decision-making processes that enable developers to apply the design method and easily create different system models. The design method was validated by generating system models and developing platforms of networked driving simulation for three different application scenarios.

Polyethylene glycol (PEG) is an inert, water soluble polymer, used for decades in pharmaceuticals. Although PEG is considered safe, concerns persist about the potential adverse effects of long-term exposure to PEG-containing therapies, specifically in children, following the introduction of PEGylated recombinant factor products used for the treatment of hemophilia. Given the absence of long-term surveillance data, and to evaluate the potential risk, we estimated PEG exposure in the pediatric population receiving US Food and Drug Administration-approved parenteral therapies with pediatric indications. We used a range of pediatric weights and doses based on prescribing information (PI) or treatment guidelines. PIs and reporting websites were searched for information about adverse events (AEs). For a child weighing 50 kg on the highest prophylactic dose of a FVIII product, the range of total PEG exposure was 40–21,840 mg/year; for FIX products, the range was 13–1342 mg/year; and for other products, the range was 383–26,743 mg/year, primarily as a derivative excipient. No AE patterns attributable to PEG were found for any of these products, including potential renal, neurological, or hepatic AEs. Our analyses suggest the pediatric population has had substantial exposure to PEG for several decades, with no evidence of adverse consequences.

This study examines the effect of a hyaluronic acid (HyAc) containing tricalcium phosphate putty scaffold material (TCP-P) and of a particulate tricalcium phosphate (TCP-G) graft on bone formation, volume stability and osteogenic marker expression in biopsies sampled 6 months after bilateral sinus floor augmentation (SFA) in 7 patients applying a split-mouth design. Biopsies were processed for immunohistochemical analysis of resin embedded sections. Sections were stained for collagen type I (Col I), alkaline phosphatase (ALP), osteocalcin (OC) and bone sialoprotein (BSP). Furthermore, the bone area and particle area fraction were determined histomorphometrically. Cone-beam CT data recorded after SFA and 6 month later were used for calculating the graft volume at these two time points. TCP-P displayed more advantageous surgical handling properties and a significantly greater bone area fraction and smaller particle area fraction. This was accompanied by significantly greater expression of Col I and BSP and in osteoblasts and osteoid and a less pronounced reduction in grafting volume with TCP-P. SFA using both types of materials resulted in formation of sufficient bone volume for facilitating stable dental implant placement with all dental implants having been in function without any complications for 6 years. Since TCP-P displayed superior surgical handling properties and greater bone formation than TCP-G, without the Hyac hydrogel matrix having any adverse effect on bone formation or graft volume stability, TCP-P can be regarded as excellent grafting material for SFA in a clinical setting.

Healthy brain functioning depends on balancing stable integration between brain areas for effective coordinated functioning, with bursts of desynchronisation to allow subsystems to reconfigure and express functional specialisation. Metastability, a concept originated in statistical physics and dynamical systems theory, has been proposed as a key signature that characterises this balance. Building on this principle, the neuroscience literature has employed markers of metastability to investigate various aspects of brain function including cognitive performance, healthy ageing, meditation, sleep, responses to pharmacological challenges, and to characterise psychiatric conditions or disorders of consciousness. However, this body of work often uses the notion of metastability heuristically, and sometimes inaccurately, making it hard for the uninitiated to navigate the vast literature, interpret findings, and foster further development of theoretical and experimental methodologies. In this paper we provide a comprehensive review of metastability and its applications in neuroscience, covering its scientific and historical foundations and the practical estimators used to estimate it in empirical data. We also provide a critical analysis of recent theoretical developments, clarifying common misconceptions and paving the road for future developments.

We are calling for a paradigm shift in engineering education. In times of the Fourth Industrial Revolution (“4IR”), a myriad of potential changes is affecting all industrial sectors leading to increased ambiguity that makes it impossible to predict what lies ahead of us. Thus, incremental culture change in education is not an option any more. The vast majority of engineering education and training systems, having remained mostly static and underinvested in for decades, are largely inadequate for the new 4IR labor markets. Some positive developments in changing the direction of the engineering education sector can be observed. Novel approaches of engineering education already deliver distinctive, student centered curricular experiences within an integrated and unified educational approach. We must educate engineering students for a future whose main characteristics are volatility, uncertainty, complexity and ambiguity. Talent and skills gaps across all industries are poised to grow in the years to come. The authors promote an engineering curriculum that combine timeless didactic tradition, such as Socratic inquiry, project-based learning and first-principles thinking with novel elements (e.g. student centered active and e-learning by focusing on the case study and apprenticeship pedagogical methods) as well as a refocused engineering skillset and knowledge. These capabilities reinforce engineering students’ perceptions of the world and the subsequent decisions they make. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent communicators better navigating increasingly complex multistakeholder ecosystems.

Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

Humans may be exposed to microbial pathogens at recreational beaches via environmental sources, such as water, sand, and aerosols. Although infectious disease risk from exposure to waterborne pathogens has been an active area of research for decades, sand is a relatively unexplored reservoir of pathogens and fecal indicator bacteria (FIB). Beach sand and water habitats provide unique advantages and challenges to pathogen introduction, growth, and persistence, as well as continuous exchange between habitats. Models of FIB and pathogen fate and transport in sandy beach habitats can help predict the risk of infectious disease from recreational water use, but filling knowledge gaps such as decay rates and potential for microbial growth in beach habitats is necessary for accurate modeling. Climatic variability, whether natural or anthropogenically-induced, adds complexity to predictive modeling, but may increase human exposure to waterborne pathogens via extreme weather events, warming of water bodies and sea level rise in many regions. The popularity of human recreational beach activities, combined with predicted climate change scenarios, could amplify the risk of human exposure to pathogens and related illnesses. Other global change trends such as increased population growth and urbanization are expected to exacerbate contamination events and the predicted impacts of increasing levels of waterborne pathogens on human health. Such changes will alter microbial population dynamics in beach habitats, and will consequently affect the assumptions and relationships used in population models and quantitative microbial risk assessment (QMRA). Here, we discuss the literature on microbial population and transport dynamics in sand-water continuum habitats at beaches, how these dynamics can be modeled, and how climate change and other anthropogenic influences (e.g., land use, urbanization) should be considered when using and developing more holistic, beachshed-based models.

Within microeukaryotes, genetic and functional variation sometimes accumulate more quickly than morphological differences. To understand the evolutionary history and ecology of such lineages, it is key to examine diversity at multiple levels of organization. In the dinoflagellate family Symbiodiniaceae, which can form endosymbioses with cnidarians (e.g., corals, octocorals, sea anemones, jellies), other marine invertebrates (e.g., sponges, molluscs, flatworms), and protists (e.g., foraminifera), molecular data have been used extensively over the past three decades to describe phenotypes and to make evolutionary and ecological inferences. Despite advances in Symbiodiniaceae genomics, a lack of consensus among researchers with respect to interpreting genetic data has slowed progress in the field and acted as a barrier to reconciling observations. Here, we identify key challenges regarding the assessment and interpretation of Symbiodiniaceae genetic diversity across three levels: species, populations, and communities. We summarize areas of agreement and highlight techniques and approaches that are broadly accepted. In areas where debate remains, we identify unresolved issues and discuss technologies and approaches that can help to fill knowledge gaps related to genetic and phenotypic diversity. We also discuss ways to stimulate progress, in particular by fostering a more inclusive and collaborative research community. We hope that this perspective will inspire and accelerate coral reef science by serving as a resource to those designing experiments, publishing research, and applying for funding related to Symbiodiniaceae and their symbiotic partnerships.

Phosphors based on magnesium titanate activated with Mn⁴⁺ ions are of great interest because, when excited with blue light, they display a strong red-emitting luminescence. They are characterized by a luminescence decay which is strongly temperature dependent in the range from 0 to 80 °C, making these materials very promising for temperature sensing in the biochemical field. In this work the optical and thermal properties of the luminescence of Mg₂TiO₄ are investigated for different Mn⁴⁺ doping concentrations. The potential of this material for temperature sensing is demonstrated by fabricating a fiber optic temperature microsensor and by comparing its performance against a standard resistance thermometer. The response of the fiber optic sensor is exceptionally fast, enabling monitoring of temperature fluctuation in subsecond time domain.

We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here we concentrate in describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 at the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those peforming the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-m wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms.

Online food delivery service (OFDS) has been widely utilized during the new normal of COVID-19 pandemic especially in a developing country such as Indonesia. The purpose of this study was to determine factors influencing customer satisfaction & loyalty in OFDS during the new normal of COVID-19 pandemic in Indonesia by utilizing an extended Theory of Planned Behavior (TPB) approach. 253 respondents voluntarily participated and answered 65 questions. Structural equation modeling (SEM) indicated that Hedonic Motivation (HM) was found to have the highest effect on customer satisfaction, followed by Price (P), Information Quality (IQ), and Promotion (PRO). Interestingly, this study found out that usability factors such as Navigational Design (ND) and Perceived Ease of Use (PEOU) were not significant to customer satisfaction and loyalty in OFDS during the new normal of COVID-19. This study can be the theoretical foundation that could be very beneficial for OFDS investors, IT engineers, and even academicians. Finally, this study can be applied and extended to determine factors influencing customer satisfaction and loyalty in OFDS during the new normal of COVID-19 in other countries.

Concentrations of six polycyclic aromatic hydrocarbons (benzanthrone, benz[a]anthracene, chrysene, fluoranthene, pyrene, and triphenylene) of soil samples from Diboll, an East Texas city (USA), were analyzed with gas chromatography-mass spectrometry (GC-MS). Samples were collected from five sites; Old Orchard Park, two heavy traffic intersections (Judd Street and Lumberjack Drive), an industrial site (West Borden Drive), and a truck stop. Acetone and dichloromethane extracts in all samples showed the presence of fluoranthene and pyrene. The sum of fluoranthene and pyrene concentrations in sites followed the order West Borden Drive > Judd Street > Lumberjack Drive > Old Orchard Park > truck stop. Concentrations of fluoranthene and pyrene were in the range 12.3 – 396.5 μg kg^-1 (ppb) and 13.6 – 209.8 μg kg^-1 ₍in dry soil₎, respectively. Benzanthrone, benz[a]anthracene, chrysene, and triphenylene concentrations were < 2 ppb levels. The higher concentrations in soils were associated with sites close to heavy traffic and vehicular emissions.

The Doubly-Fed Induction Generator (DFIG) has significant features in comparison with Fixed Speed Wind Turbine (FSWT), which has popularized its application in power system. Due to partial rated back-to-back converters in the DFIG, Fault Ride-Through (FRT) capability improvement is one of the great subjects regarding new grid code requirements. To enhance the FRT capability of the DFIG, many studies have been carried out. Fault current limiting devices as one of the techniques are utilized to limit the current level and protect switches of the back-to-back converter from over-current damage. In this paper, a review is done based on fault current limiting characteristic of the proposed fault current limiting devices Therefore, Fault Current Limiters (FCLs) and Series Dynamic Braking Resistors (SDBRs) are mainly taken into account. Operation of all configurations including their advantages and disadvantages is explained. Impedance type and the fault current limiting devices’ location are two important factors, which significantly affect the DFIG behaviour in the fault condition. These two factors are basically studied by the simulation and their effects on the key parameters of the DFIG are investigated. Finally, future works in respect to the FCL application in the FRT improvement of the DFIG have also been discussed.

Connexins are tetraspan transmembrane proteins that form gap junctions and facilitate direct intercellular communication, a critical feature for the development, function and homeostasis of tissues and organs. In addition, a growing number of gap junction-independent functions are being ascribed to these proteins. The connexin gene family is under extensive regulation at the transcriptional and post-transcriptional level, and undergoes numerous modifications at the protein level, including phosphorylation, which ultimately affects their trafficking, stability and function. Here, we summarize these key regulatory events, with emphasis on how these affect their multi-functionality in health and disease.

There is robust evidence that major depression (MDD) is accompanied by a low-grade activation of the immune-inflammatory response system, which is involved in the pathophysiology of this disorder. It is also becoming apparent that glia cells are in reciprocal communication with neurons and orchestrate various neuromodulatory, homeostatic, metabolic, and immune mechanisms and have a crucial role in neuroinflammatory mechanisms in MDD. Those cells mediate the central nervous system (CNS) response to systemic inflammation and psychological stress, but at the same time, they may be an origin of the inflammatory response in the CNS. The sources of activation of the inflammatory response in MDD are immense, however, in recent years, it is becoming increasingly evident that the gastrointestinal tract with gut-associated lymphoid tissue (GALT) and increased intestinal permeability to bacterial LPS and food-derived antigens contribute to activation of low-grade inflammatory response with subsequent psychiatric manifestations. Furthermore, an excessive permeability to gut-derived antigenic material may lead to subsequent autoimmunities which are also known to be comorbid with MDD. In this chapter, we discuss fascinating interactions between the gastrointestinal tract, increased intestinal permeability, intestinal microbiota, and glia-neuron crosstalk, and their roles in the pathogenesis of the inflammatory hypothesis of MDD. To emphasize those crucial intercommunications for the brain functions, we propose the term of microbiota-gut-immune-glia (MGIG) axis.

Humanity will soon define a new era for nature – one that seeks to correct decades of underwhelming responses to the global biodiversity crisis. Area-based conservation efforts, which include both protected areas and other effective area-based conservation measures, are likely to extend and diversify. But persistent shortfalls in ecological representation, management effectiveness and measurable biodiversity outcomes diminish the potential role of area-based conservation in stemming biodiversity loss. Here we show how protected area expansion by governments since 2010 has had limited success in increasing biodiversity coverage, and identify four emergent issues that –if addressed – will enhance the performance of area-based conservation post-2020. We close with recommendations for a broad biodiversity agenda that maximises the potential of area-based conservation. Parties to the Convention on Biological Diversity must recognise that area-based conservation primarily focuses on local threats to species and ecosystems, and needs enhanced emphasis on biodiversity outcomes to better track and fund its contribution to global conservation efforts.

Bauxite residue (BR) is a well promising resource for critical metals and especially scandium (Sc), a rare and expensive metal with increasing applications in advanced technology. Particularly, Greek BR’s composition indicates a sound possibility for a commercially viable recovery of Sc under the conditions of an optimized leaching process and the subsequent use of advanced separation techniques. Leaching with mineral acids emerges as the dominant selection with comparison to other techniques. This study investigates an optimized leaching condition set on Sc recovery, using sulfuric acid as the most suitable among different acids tested, in the context of process economics and environmental constraints. Several variables were studied individually or combined in order to achieve high Sc concentration in the leachate as well as to ensure selectivity, especially in respect to iron. The most significant parameters proved to be the solid to liquid ratio (S/L), the final pH value as well as the use of recycling of leachate on fresh BR batches. The proposed process, using sulfuric acid at low acid molarities under ambient conditions was integrated rapidly leading to high and selective Sc recovery. A flow diagram of the developed leaching process in industrial scale was proposed based on continuous operation.

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing (http://step.esa.int/main/toolboxes/snap/). In this work we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020nm, we derive important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on the spatial grid of 300m. The algorithm also incorporates cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long – term snow property records essential for climate monitoring and data assimilation studies - especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

Over the last few decades, urban expansion and population shifts have modified the existing landscape throughout the U.S. Protected areas and development are compatible lenses, yet stakeholders’ involvement in decision-making is often missing from environmental governance. We examine how stakeholders living and working in proximity to Everglades National Park (EVER) perceive environmental and social changes to the park and community park relations. EVER was selected as a study site for several reasons: proximity to urban areas, rich biological diversity, largest subtropical wilderness in the U.S., International Biosphere Reserve, World Heritage Site, and prominence as a tourist destination for the region. Forty-one semi-structured interviews were conducted with neighborhood groups, representatives from gateway communities, and conservation organizations. An analysis of the interview data generated six research themes: loss of native species, urban development, a shortage and contamination of water, hurricanes, climate change, and increased recreation use. The results of this study add to the literature by providing a better understanding of the relationships stakeholders have with national parks. The results will provide useable knowledge that may help stakeholders and public land managers design strategies related for sustainable plans for the park and its surrounding communities.

Obesity represents a major public health problem with a prevalence increasing at an alarming rate worldwide. Continuous intensive efforts to elucidate the complex pathophysiology and improve clinical management have led to a better understanding of biomolecules like gut hormones, an-tagonists of orexigenic signals, stimulants of fat utilization, and/or inhibitors of fat absorption. In this article, we will review the pathophysiology and pharmacotherapy of obesity including inter-section points to the new generation of antidiabetic drugs. We provide insight into the effective-ness of currently approved anti-obesity drugs and other therapeutic avenues that can be explored.

There is now evidence that major depression is accompanied by lowered serum zinc, an immune-inflammatory biomarker. However, the effect of anti-inflammatory drugs as adjuvant to antidepressants on serum zinc and copper in relation to pro- and anti-inflammatory cytokines are not studied. The aim of the present work is to examine the effects of treatment with sertraline with and without ketoprofen on serum levels of zinc and copper in association with immune-inflammatory biomarkers in drug-naïve major depressed patients. We measured serum zinc and copper, interleukin (IL)-1β, IL-4, IL-6, IL-18, interferon (IFN)-γ, and transforming growth factor (TGF)-β1 in 40 controls and 133 depressed patients. The clinical efficacy of the treatment was measured using the Beck Depression Inventory-II (BDI-II) at baseline and 8 weeks later. In drug-naïve major depressed patients we found significantly reduced baseline levels of serum zinc and copper in association with upregulation of all cytokines, indicating activation of the immune-inflammatory responses system (IRS) as well as the compensatory immune regulatory system (CIRS). Treatment with sertraline significantly increased zinc and decreased copper levels, while ketoprofen did not have a significant add-on effect on zinc but attenuated the suppressant effects of sertraline on copper levels. During treatment, there was a significant inverse association between serum zinc and activation of the IRS/CIRS. The improvement in the BDI-II during treatment was significantly associated with increments in serum zinc coupled with attenuation of the IRS/CIRS. In conclusion, lower serum zinc is a hallmark of depression, while increments in serum zinc and attenuation of the immune-inflammatory response during treatment appear to play a role in the clinical efficacy of sertraline. Intertwined changes in zinc levels and the immune response play a role in the pathophysiology of major depression and participate in the mechanisms underpinning the clinical efficacy of antidepressants.

Object. Utilization of pedicle screws (PS) for spine stabilization is common in spinal surgery. With reliance on visual inspection of anatomical landmarks prior to screw placement, the free-hand technique requires a high level of surgeon skill and precision. Three-dimensional (3D) computer-assisted virtual neuronavigation improves the precision of PS placement and minimize steps. Methods. Twenty-three patients with degenerative, traumatic, or neoplastic pathologies received treatment via a novel three-step PS technique that utilizes a navigated power driver in combination with virtual screw technology. 1) Following visualization of neuroanatomy using intraoperative CT, a navigated 3-mm match stick drill bit was inserted at anatomical entry point with screen projection showing virtual screw. 2) Navigated Stryker Cordless Driver with appropriate tap was used to access vertebral body through pedicle with screen projection again showing virtual screw. 3) Navigated Stryker Cordless Driver with actual screw was used with screen projection showing the same virtual screw. One hundred and forty-four consecutive screws were inserted using this three-step, navigated driver, virtual screw technique. Results. Only 1 screw needed intraoperative revision after insertion using the three-step, navigated driver, virtual PS technique. This amounts to a 0.69% revision rate. One hundred percent of patients had intraoperative CT reconstructed images to confirm hardware placement. Conclusions. Pedicle screw placement utilizing the Stryker-Ziehm neuronavigation virtual screw technology with a three step, navigated power drill technique is safe and effective.

Peer-to-peer (P2P) energy trading is a new data-driven business model currently being trialed within the energy sector. Introducing P2P transactions to an essential service such as energy could have far-reaching implications for individuals and the grid. This paper raises considerations and questions from social, economic/markets and regulatory points of view, that should be understood and addressed by societies and policymakers. It does this by considering under what circumstances it is reasonable to conceptualize P2P energy trading as part of the sharing economy, and drawing parallels to the sharing economy experience in other sectors. In order to reap the full societal benefits, while avoiding considerable risks to infrastructure and individuals, a policy approach promoting dialogue and innovation is necessary. We suggest the regulatory sandbox is the most appropriate tool to achieve this and would help avoid the breakdown of trust between policymakers and platform companies observed in other sectors.

Hypoxia, or reduced oxygen availability, has been studied extensively for its ability to activate specific genes. Hypoxia induced gene expression is mediated by the HIF transcription factors, although not exclusively so. Despite the great knowledge on the mechanisms by which hypoxia activates genes, much less is known about how hypoxia promotes gene repression. In this review, we discuss the potential mechanisms underlying hypoxia-induced transcriptional repression responses. We highlight HIF-dependent and independent mechanisms, but also the potential roles of dioxygenases with functions at the nucleosome and DNA level. Finally, we discuss recent evidence regarding the involvement of transcriptional repressor complexes in hypoxia.

We present an updated design process for adapting and integrating existing cyber risk assessment approaches for impact assessment for the risk from IoT to the digital economy. The new design process includes a set of changes to the original standards (e.g. NIST) that are adapted for the IoT cyber risk in this paper. This paper also presents a new framework for impact assessment of IoT cyber risk, specific for the digital economy.

Ulcerative colitis has a significant impact on the quality of life for the patients, and can substantially increase the risk of colon cancer in patients suffering long-term. Conventional treatments provide only modest relief paired with a high risk of side effects, while complementary and alternative medicines can offer safe and effective options. Over the past decade, we have shown that American ginseng has anti-oxidant and anti-inflammatory properties that can suppress mouse colitis and prevent colitis associated colon cancer. With the goal of isolating a single active compound, we further fractionated the hexane fraction, and found the most abundant molecule in this fraction was the polyacetylene, Panaxynol. After isolating and characterizing Panaxynol, we tested the efficacy of Panaxynol in the treatment and prevention of colitis in mice and studied the mechanism of action. We demonstrate here that Panaxynol effectively treats colitis in a Dextran Sulfate Sodium mouse model by targeting macrophages for DNA damage and apoptosis. Positive outcomes from this study could take American ginseng one-step further towards becoming a conventional drug for the treatment of colitis, and possibility exploring other autoimmune diseases associated with macrophage dysfunction.

Lattice and code cryptography can replace existing schemes such as Elliptic Curve Cryptography because of their resistance to quantum computers. In support of public key infrastructures, the distribution, validation and storage of the cryptographic keys is then more complex to handle longer keys. This paper describes practical ways to generate keys from physical unclonable functions, for both lattice and code based cryptography. Handshakes between client devices containing the PUFs and a server are used to select sets of addressable positions in the PUFs, from which streams of bits called seeds are generated on demand. The public and private cryptographic key pairs are computed from these seeds together with additional streams of random numbers. The method allows the server to independently validate the public key generated by the PUF, and act as a certificate authority in the network. Technologies such as High performance computing, and graphic processing units can further enhance security by preventing attackers to make this independent validation when only equipped with less powerful computers.

Nutrition support is increasingly recognized as a clinically relevant aspect of the intensive care treatment of cardiac surgery patients. However, evidence from adequate large-scale studies evaluating its clinical significance for patients’ mid- to long-term outcome remains sparse. Considering nutrition support as a key component in the perioperative treatment of these critically ill patients, led us to review and discuss our understanding of the metabolic response to the inflammatory burst induced by cardiac surgery. In addition, we discuss how to identify patients who may benefit from nutrition therapy, when to start nutritional interventions, present evidence about the use of enteral and parenteral nutrition and the potential role of pharmaconutrition in cardiac surgery patients. Although the clinical setting of cardiac surgery provides advantages due to its scheduled insult and predictable inflammatory response, researchers and clinicians face lack of evidence and several limitations in the clinical routine, which are critically considered and discussed in this paper.

The objective of this case report is to introduce a customized CAD/CAM freeze-dried bone allograft (FDBA) block for its use in Guided Bone Regeneration (GBR) procedures for severely deficient maxillary bones. Additionally, a special newly developed remote incision technique is presented to avoid wound dehiscence. The results show an optimal integration behaviour of the FDBA block after six months and the formation of new vital bone. Thus, the results of the present case report confirm the use of the customized CAD/CAM bone block for augmentation of complex defects in the maxillary aesthetic zone as a successful treatment concept.

In regions lacking genomic data, analysis of sequences from the early stages of an outbreak can provide important insights into the diversity of pathogens present. Following the detection of the first imported case of COVID-19 in the Northern sector of Ghana on 13^th March 2020, we have now molecularly characterized and phylogenetically analysed sequences including three (3) complete genomes of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) isolated from nine (9) patients observed in Ghana. Eight (8) of these patients reported with a recent history of foreign travel and one (1) with no history of foreign travel. We performed high throughput sequencing for 9 samples following the determination of high concentration of viral RNA. In addition, we estimated the potential impact that long distance transportation of samples to testing centres may have on sequencing outcomes. Here, two samples that were closest in terms of viral RNA concentration but transported from sites which are over 400km apart were assessed. All sequences were compared to previous sequences from Ghana and representative sequences from regions where our patients had previously travelled. Complete genomes were obtained for three (3) sequences and with another near complete genome with a coverage of 95.6%. Sequences with coverage in excess of 80% were found to belong to three lineages namely A, B.1 and B.2. Our sequences clustered in two different clades with the majority falling within a clade composed of sequences from sub-Saharan Africa. Less RNA fragmentation was seen in sample KATH23 which was collected 9km compared with sample TTH6 which was collected and transported over a distance of 400km to the testing site. The clustering of several sequences from sub-Saharan Africa suggests regional circulation of the viruses in the subregion. Importantly, there may be the need to decentralize testing sites and build more capacity across Africa to boost the sequencing output of the subregion.

INTRODUCTION Recently there has been a significant increase in age in the United States. It is necessary to better understand the physiological and surgical needs of these patients in order to optimize outcomes. The vast majority of procedures performed in adult patients are low-risk operations, such as laparoscopic cholecystectomy. Our aim is to investigate the outcomes, including length of stay, morbidity, mortality, re-admission and discharge disposition of the elderly population (>80) undergoing low-risk operations in our tertiary community hospital. METHODS A retrospective chart review was done at a tertiary community hospital. The time frame utilized was 2011-2015. Patients were excluded only on the basis of their age (< 80) at the time of operation. RESULTS There were a total of 30 patients who underwent laparoscopic cholecystectomy from 2011 to 2015. 21 patients (70%) were female and 9 (30%) were male. No patients were converted to an open procedure. The average age was 86.4 years and average ASA classification prior to surgery was 2.88. Higher ASA class, specifically those that were class III/IV were more likely to have an increased length of stay that was statistically significant. Overall age greater than 80 was an independent risk factor for transfer to a higher level of care upon discharge (SNF, LTAC, etc.), a surrogate marker for physical decompensation following surgery. CONCLUSIONS Routine surgery, such as the laparoscopic cholecystectomy, effects the elderly population in a more substantial way, and early recognition coupled with increased education for physicians regarding geriatric patients can help to reduce length of stay, morbidity, and overall physical and mental deconditioning.

A common motivation for increasing open access to research findings and data is the potential to create economic benefits – but evidence is patchy and diverse. This study systematically reviewed the evidence on what kinds of economic impacts (positive and negative) open science can have, how these comes about, and how benefits could be maximized. Use of open science outputs often leaves no obvious trace, so most evidence of impacts is based on interviews, surveys, inference based on existing costs, and modelling approaches. There is indicative evidence that open access to findings/data can lead to savings in access costs, labour costs and transaction costs. There are examples of open science enabling new products, services, companies, research and collaborations. Modelling studies suggest higher returns to R&D if open access permits greater accessibility and efficiency of use of findings. Barriers include lack of skills capacity in search, interpretation and text mining, and lack of clarity around where benefits accrue. There are also contextual considerations around who benefits most from open science (e.g. sectors, small vs larger companies, types of dataset). Recommendations captured in the review include more research, monitoring and evaluation (including developing metrics), promoting benefits, capacity building and making outputs more audience-friendly.

This review was carried out to identify different beta-lactamase resistance genes reported in published literature from Nigeria and to determine the proportion estimates of the important beta-lactamase resistance genes in Nigeria. Sixty-three (63) articles were included in this review based on the eligibility criteria. All the beta-lactamases reported were detected from the Gram-negative bacteria, most especially from Enterobacteriaceae (n=53). Thirty-six different beta-lactamase genes have been reported from Nigeria. These genes belong to the narrow-spectrum, AmpC, extended-spectrum, and carbapenemase beta-lactamase resistance genes. Eight (8) genes (bla_DHA, bla_CTXM-1, bla_CTXM-14, bla_GES-1, bla_VEB-1, bla_OXA-1, bla_OXA-2, and bla_TEM-1) were shared between animals and humans, 5 genes (bla_SHV-1, bla_SHV-2, bla_SHV-11, bla_SHV-12, and bla_NDM-1) were common to both humans and environment while none of the genes was unique to both animals and environment. Four genes including bla_CMY, bla_TEM-1, bla_AmpC, and internationally pandemic bla_CTXM-15 gene were unique to animals, humans, and the environment. No carbapenemase gene was reported from animals yet. The pooled proportion estimate of ESBL genes in Nigeria was 31% (95% CI: 26-36%, P<0.0001), while the estimate of bla_CTXM-15 gene in Nigeria was 46% (95% CI: 36-57%, P<0.0001). The proportion estimate of AmpC genes was 32% (95% CI: 11-52%, P<0.001), while the estimate for carbapenemases was 8% (95% CI: 5-12%, P<0.001). This study has provided information on the beta-lactamases distribution in Nigeria. This is necessary for a better understanding of molecular epidemiology of clinically important beta-lactamases especially the extended-spectrum beta-lactamases and carbapenemases in Nigeria.

BACKGROUND: Stable-phase schizophrenia may comprise two distinct nosological entities namely Major Neuro-Cognitive Psychosis (MNP, largely overlapping with the deficit syndrome) and simple NP (SNP), which are defined by neuroimmune and neurocognitive abnormalities. Furthermore, cognitive impairments and PHEM (psychotic, hostility, excitation, mannerism) and negative symptoms load on the same dimension.METHODS: The current study aimed to investigate associations of psychomotor retardation (PMR) and clinical as well as biomarker characteristics of schizophrenia. We recruited 40 healthy controls and 79 schizophrenia patients and measured IgA responses to tryptophan catabolites (TRYCATs), IgM to malondialdehyde and nitroso (NO)-cysteinyl, macrophage inflammatory protein-1 (MIP-1), soluble interleukin (IL)-1 receptor antagonist (sIL-1RA), IL-10, CCL-11 as well as PMR items of different rating scales and motor screening task (MOT). RESULTS: PMR differentiated schizophrenia from controls and MNP from SNP. In addition, PMR was strongly associated with executive functions, deficits in episodic and semantic memory, PHEM and negative (PHEMN) symptoms. Around 50% of the variance in PMR was predicted by the cumulative effects of immune activation, CCL-11, TRYCATs and NO-Cysteinyl levels, and lowered natural IgM. PRM may be reliably combined with PHEMN symptoms and memory and executive impairments into one latent vector reflecting overall psychopathology.CONCLUSIONS: Current findings indicate that PMR may be a key psychopathological feature of schizophrenia and mainly MNP. In addition, PMR and associated impairments in memory and executive functions, and PHEMN symptoms may be driven by deficits in the compensatory immune regulatory system (natural IgM) combined with increased production of neurotoxic immune products, namely TRYCATs and IgM to NO-cysteinyl, and an endogenous cognition deteriorating chemokine, namely CCL-11.

Malaria and Pneumonia are leading causes of serious illness in children and adults worldwide with their death rate and prevalence on the rise. Such alarming statistics may retard the milestones so far achieved in meeting the Millennium Development Goals 4 and 6 whose targets are to improve child survival and reverse the high prevalence of diseases such as pneumonia and malaria respectively. Two sub-models of malaria-pneumonia co-infection namely malaria model and pneumonia model were considered first and then followed by the full malaria-pneumonia co-infection model. The malaria model, pneumonia model and co-infection model basic reproduction numbers denoted by R_m, R_p and R_mp respectively was obtained using the Next Generation Matrix method. The model disease free equilibrium’s local and global stability was analysed using Descartes’ Rule of signs and Comparison method. The bifurcation analysis for the malaria, pneumonia and co-infection models was studied using the Centre Manifold Theory. The sensitivity indices of the model basic reproduction numbers R_m, R_p and R_mp to the parameters in the models were calculated. Optimal control theory was applied using the Pontryagins’ Maximum Principle to investigate optimal strategies for controlling the spread of malaria, pneumonia and co-infection models using insecticide treated bed nets (u₁(t)) spraying of mosquitoes insecticides (u₂(t)), sanitation (u₃(t)), vaccination (u₄(t)), anti-malaria drugs (u₅(t)), anti-pneumonia drugs (u₆(t)), both anti-malaria drugs and anti-pneumonia drugs (u₇(t)) as the system time control variables. Numerical simulations using a set of parameter values were provided to validate the analytical results.

At research-intensive universities in the United States, eligible faculty must generally excel in research, teaching and service in order to receive tenure. To meet these high standards, junior faculty should begin planning for a strong tenure case from their first day on the job. Here, we provide practical information, commentary and advice on how biomedical faculty at research-intensive institutions can prepare strategically for a successful tenure review.