Analysis of liquid biopsy samples can reveal a wealth of molecular as well as cellular entities circulating in various body fluids. These entities include circulating tumor cells, circulating cell-free and tumor DNA, RNA, and proteins. Detection and characterization of this genetic and proteomic material can provide crucial information on tumor characteristics, including its heterogeneity, biology, tumor progression, staging, associated gene mutations and the course of therapy. The increased use of liquid biopsy in clinical oncology offers in non-invasive manner easier tumor sampling and continuous monitoring of the disease evolution through repetitive sampling from cancer patients. The continuous monitoring offered by this method is highly relevant to the assessment of a given therapeutic regime and early detection of markers associated with possible drug resistance, which may develop in the course of the therapy. The use of proteomic approaches, including mass spectrometry-based proteomics for the analysis of biofluids extends for over three decades, yet only in the last few years such methods have found their way to clinical oncology. The non-invasive nature of liquid biopsy and the simple procedures for sample collection made this approach far more attractive than the traditional and well-established tissue biopsy. Such preference becomes more practical in the analysis of solid tumors, particularly in pediatric population. In this review we discuss some works on the emerging role of liquid biopsy analyses in clinical oncology, and how such use allows a better understanding of diagnosis, prognosis, disease evolution and response to therapy of various forms of cancer. We also discuss the role of MS-based methods in the characterization of post-translational modifications of proteins circulating in liquid biopsies.

The literature was scoped to help place mass spectrometric (MS) platforms in the spotlight of the life sciences, as a tool of OMICS and OMICS 2.0 technologies. Moreover, today’s appliances are so handy, that they literally place a whole lab on a single chip. Methods of OMICS (and the most recently developed term OMICS 2.0) are tackled, having in mind their aptness for educational purposes, as well as their feasibility. This same topic was highlighted in many reviews that have been periodically published. The author’s initial interest was the forensic application of MS, but since these interests changed, terms such as “biosensors” were also examined, so the review included means of discovery of efficient biomarkers and clinical therapeutic targets. Aside from simply reviewing the research status and the future perspectives, this article tackles terms such as Society 5.0 and OMICS 2.0. However, within the framework of this review, physical chemistry, bioinformatics, or specific software solutions were not specifically studied. Since the topic of generating permanent collections of digital content for retrospective analysis was also reviewed, the need for loads of data – cloud storage was discussed in the context of MS. These large quantities of data are easier to operate with if generated by MS, rather than by any other commercially available assay. In this manner, the review has strengthened an in-depth understanding of the applications of MS.

Exposure to malachite green (MG) may pose great health risks to humans, thus it is of prime importance to develop fast and robust methods to quantitatively screen the presence malachite green in environment. Herein application of extractive electrospray ionization mass spectrometry (EESI-MS) has been extended to the trace detection of MG within lake water and aquiculture water, due to the intensive use of MG as biocide in fisheries. This method has the advantage of obviating offline liquid-liquid extraction or tedious matrix separation prior to the measurement of malachite green in native aqueous medium. The experimental results indicate that the extrapolated detection limit for MG was ~3.8 ug L-1 (S/N=3) in lake water samples and ~ 0.5 ug L-1 in ultrapure water under optimized experimental conditions. The signal intensity of MG showed good linearity over the concentration range of 10–5000 ug L-1. Measurement of practical water samples fortified with MG at 0.01 and 0.1 mg L-1 gave a good validation of the established calibration curve. The average recoveries of malachite green in lake water and Carassius carassius fish farm effluent water were 114.9% (6.6% RSD) and 85.4% (9.2% RSD), respectively. Overall, the established EESI-MS/MS method has been demonstrated suitable for sensitive and rapid (<2 min per sample) quantitative detection of malachite green in various aqueous media, indicating its potential for online real-time monitoring of real life samples.

Many challenges in proteomics result from the high-throughput nature of the experiments. The paper first presents pre-analytical problems, which still occur, although the call for standardisation in omics has been ongoing for many years. This article also discusses aspects, which affect bioinformatic analysis, based on three sets of reference data measured with different orbitrap instruments. Despite continuous advances in mass spectrometer technology as well as analysis software, data set-wise quality control is still necessary and decoy-based estimation, although challenged by modern instruments, should be utilized. We draw attention to the fact that numerous young researchers perceive proteomics as a mature, readily applicable technology. However, it is important to emphasize that the maximum potential of the technology can only be realized by an educated handling of its limitations.

Seafood is considered one of the main food allergen sources by the European Food Safety Authority (EFSA). It comprises several distinct groups of edible aquatic animals including fish and shellfish such as crustacean and mollusks. Recently the EFSA recognized the high risk of food allergy over the world and established the necessity of developing new methodologies for its control. Consequently, accurate, sensitive and fast detection methods for seafood allergy control and detection in food products are highly recommendable. In this work, we present a comprehensive review of the applications of the proteomics methodologies for the detection and quantification of seafood allergens. For that, two consecutive proteomics strategies (Discovery and Targeted Proteomics) applied for the study and control of seafood allergy are reviewed in detail. In addition, future directions and new perspectives were also provided.

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Direct mass spectrometry-based metabolomics has been widely employed in the last years to characterize metabolic alterations underlying to Alzheimer’s disease development and progression. This high-throughput approach presents a great potential for fast and simultaneous fingerprinting of a vast number of metabolites, which can be applied to multiple biological samples such as serum/plasma, urine, cerebrospinal fluid and tissues. In this review article we present the main advantages and drawbacks of metabolomics based on direct mass spectrometry compared with conventional analytical techniques, and provide a comprehensive revision of the literature on the application of these tools in Alzheimer’s disease research.

Two-dimensional mass spectrometry (2D MS) is a method for tandem mass spectrometry that relies on manipulating ion motions to correlate precursor and fragment ion signals. 2D mass spectra are obtained by performing a Fourier transform in both the precursor ion mass-to-charge ratio (m/z) dimension and the fragment ion m/z dimension. The phase of the ion signals evolves linearly in the precursor m/z dimension and quadratically in the fragment m/z dimension. This study demonstrates that phase-corrected absorption mode 2D mass spectrometry improves signal-to-noise ratios by a factor of 2 and resolving power by a factor of 2 in each dimension compared to magnitude mode. Furthermore, phase correction leads to an easier differentiation between ion signals and artefacts, and therefore easier data interpretation.

The spread of SARS-CoV-2 variants of concern (VOCs), is of great importance to the whole community, since their genetic changes may increase transmissibility, disease severity and reduce effectiveness of vaccines. Moreover, these changes may lead to failure of diagnostic measures, thus variant-specific diagnostic methods are essential. To date, genetic sequencing is the gold standard method to discriminate between variants, however it is time consuming (several days) and expensive. Therefore, the development of rapid diagnostic methods for SARS-CoV-2 in accordance with its genetic modification is of great importance. In this study, we introduce a Mass-Spectrometry (MS)-based methodology for the diagnosis of SARS-CoV-2 in clinical specimens, a methodology which enables universal identification, alongside with variant-specific discrimination. The universal identification of SARS-CoV-2 is based on conserved markers shared by all variants, while the identification of the specific variant relies on variant-specific markers. Determining a specific set of peptides for a given variant consists of a multistep procedure, starting with in-silico search for variant-specific tryptic peptides, followed by tryptic digest of a cell-cultured SARS-CoV-2 variant and identification of these markers by HR-LC-MS/MS analysis. As a proof of concept, this approach was demonstrated for four representative VOCs, in comparison with the wild-type Wuhan reference strain. For each variant, at least two unique markers, derived mainly from the spike (S) and nucleocapsid (N) viral proteins, were identified. This methodology is specific, rapid, easy to perform and inexpensive, therefore can be applied as a general diagnostic tool of pathogenic variants.

Microsamples (collections usually less than 50 µL) have been introduced in pre-clinical, clinical, and research settings to overcome obstacles in sampling via traditional venipuncture. However, venipuncture remains the sampling gold standard for metabolic phenotyping of blood. This pre-sents several challenges in metabolic phenotyping workflows: accessibility for individuals in ru-ral and remote underserved areas (due to the need for trained personnel), the unamenable nature to frequent sampling protocols in longitudinal research (for its invasive nature), and sample col-lection difficulty in the young and elderly. Furthermore, venous sample stability may be compro-mised when temperate conditions necessary for cold-chain transport are beyond control. Alter-natively, research utilising microsamples extends phenotyping possibilities to inborn errors of metabolism, therapeutic drug monitoring, nutrition, as well as sport and anti-doping. Although the application of microsamples in metabolic phenotyping exists, it is still in its infancy, with whole blood being overwhelmingly the primary biofluid collected through the collection method of dried blood spots. Research into metabolic phenotyping of microsamples is limited; however, with advances in commercially available microsampling devices, common barriers such as volumetric inaccuracies and the ‘haematocrit effect’ in dried blood spot microsampling can be overcome. In this review, we provide an overview of the common uses and workflows for mi-crosampling in metabolic phenotyping research. We discuss the advancements in technologies, highlighting key considerations and remaining knowledge gaps for employment of microsamples in metabolic phenotyping research. Supporting the translation of research from the ‘bench to the community’.

Despite the increasing number of individuals affected by Alzheimer’s disease (AD) every year, no effective therapy has been developed to treat this neurodegenerative disease yet. The current methods for AD diagnosis are effective for clinical confirmation of the disease only when symptoms become apparent, years after molecular damage started within the patients’ brains. As higher expression of a conformationally altered p53 has been correlated with AD, we developed a mass spectrometry-based method for highly sensitive, specific, and reproducible quantification of a p53 conformational variant in plasma samples of patients with known clinical outcome. In particular, we tested the prognostic performance of an AD-specific 2D3A8-immunoselected p53 peptide (AZ 284™) in different sets of individuals progressing from both cognitively unimpaired (CU) and mild cognitive impairment (MCI) patients progressing to AD dementia. Our data showed that quantitative analysis of AZ 284™ is a reliable tool for predicting AD progression up to 6 years prior to dementia onset with AUC >90%. Taken together, these results support the implementation of p53 conformational variant quantification as an affordable and powerful diagnostic tool for early, non-invasive AD diagnosis.

Proteomics in respiratory allergic diseases has such a battery of techniques and programs that one would almost think that there is nothing impossible to find, invent or mold. All these resources that we document here, are involved in solving problems in allergic diseases, both diagnostic, prognostic, treatment and immunotherapy development. The main perspectives, according to this version, are in three strands and / or lockout immunological system: 1) In blocking the diapedesis of cells involved, 2) modifications and blocking of paratopes and epitopes being understood by modifications to antibodies, antagonism or blocking them and 3) blocking FcεR1 receptors to prevent specific IgEs from sticking to mast cells and basophils. These tools and targets in the allergic landscape are, in our view, the prospects in the field.

Gangliosides are highly abundant in the human brain where they are involved in major biological events. In brain cancers, alterations of ganglioside pattern occur, some of which being correlated with the neoplastic transformation, while others with the tumor proliferation. Of all the techniques, mass spectrometry (MS) has proven to be one of the most effective in gangliosidomics, due to its ability to characterize heterogeneous mixtures and discover species with biomarker value. This review highlights the most significant achievements of MS in the analysis of gangliosides in human brain cancers. The first part presents the state-of-the-art in the MS development for discovery of ganglioside markers in primary brain tumors, with a particular emphasis on the ion mobility separation (IMS) MS and its contribution to the elucidation of the gangliosidome associated with aggressive tumors. The second part is focused on the MS of gangliosides in brain metastases, highlighting the ability of matrix-assisted laser desorption/ionization (MALDI)-MS, microfluidics-MS and tandem MS to decipher and structurally characterize species involved in the metastatic process. In the end, several conclusions and perspectives are presented, among which the need for development of a reliable software and a user-friendly structural database as a search platform in brain tumor diagnostics.

Rapid analysis and characterization of compounds by mass spectrometry may overlook trace compounds, although targeted analysis methods can significantly improve detection sensitivity, it is difficult to discover novel scaffold compounds. This study developed a strategy for discovering trace compounds in the aging process of traditional Chinese medicine based on MS fragmentation and known metabolic pathway. Specifically, we found that the characteristic component of C. reticulata 'Chachi', methyl N-methylanthranilate (MMA), fragmented in ESI-CID to produce rearrangement ion 3-hydroxyindole, which has been proven to exist in trace amounts in C. reticulata 'Chachi' comparing with the reference substance by LC-MS/MS. By combining the known metabolic pathways of 3-hydroxyindole and the possible methylation reactions that may occur during aging, 10 possible indole derivatives were untargeted predicted. These compounds were confirmed to originate from MMA by purchasing or synthesizing reference substances and all of them were detected in C. reticulata 'Chachi' through LC-MS/MS analysis, achieving trace compound analysis from untargeted to targeted. It may contribute to explain the aging mechanism of C. reticulata 'Chachi' and the strategy of CID-induced special rearrangement ion binding metabolic pathway has potential application value in discovering trace compounds.

Stable-isotope dimethyl labeling is a highly reactive and cost-effective derivatization procedure that could be utilized in proteomics analysis. In this study, a liquid chromatography-tandem mass spectrometry in multiple reaction monitoring mode (LC-MS-MRM) platform for the quantification of kiwi allergens was first developed using this strategy. Three signature peptides for target allergens Act d 1, Act d 5, and Act d 11 were determined and were derivatized with normal and deuterated formaldehyde as external calibrants and internal standards, respectively. The results showed that sample preparation with the phenol method provided comprehensive protein populations. Recoveries at four different levels ranging from 72.5–109.3% were achieved for the H-labeled signature peptides of Act d 1 (SPA1-H) and Act d 5 (SPA5-H) with precision ranging from 1.86–9.92%. The limit of quantification (LOQ) was set at 8 pg mL–1 for SPA1-H and at 4 ng mL–1 for SPA5-H. The developed procedure was utilized to analyze seven kinds of hand-made kiwi foods containing 0.0175–0.0515 mg g–1 of Act d 1 and 0.0252–0.0556 mg g–1 of Act d 5. This study extended the applicability of stable-isotope dimethyl labeling to the economical and precise determination of food allergens and peptides.

Isobaric ions having the same mass-to-charge ratio cannot be separately identified by mass spectrometry (MS) alone, but this limitation can be overcome using hydrogen-deuterium exchange (HDX) in microdroplets. Because isobaric ions may contain a varied number of exchangeable sites and different types of functional groups, each one produces a unique MS spectral pattern after droplet spray HDX without the need for MS/MS experiments or introduction of ion mobility measurements. As an example of the power of this approach, isobaric ions in urinary metabolic profiles are identified and used to distinguish between healthy individuals and those having bladder cancer.

Octyl methoxycinnamate (OMC) is a common UVA and UVB filter molecule that is widely used is commercial sunscreens. Here, we use gas-phase laser photodissociation spectroscopy to characterize the intrinsic photostability and photodegration products of OMC, by studying the system as its protonated form, i.e. [OMC·H]+. The major photofragments observed have, m/z 179, 161, and 133, corresponding to fragmentation on either side of the of the ether oxygen of the ester group (m/z 179, and 161) or the C-C bond adjacent to the ester carbonyl group. Additional measurements were obtained using higher-energy collisional dissociation mass spectrometry (HCD-MS), to identify fragments which result from breakdown of the vibrationally hot electronic ground state. We found that the m/z 179 and 161 ions are the main fragments produced by this route. Notably, the m/z 133 ion was not observed through HCD-MS, revealing that this product ion is only produced through a photochemical route. Our results demonstrate that UV photoexcitation of OMC is able to access a dissociative excited state surface that uniquely leads to rupture of the C-C bond adjacent to the key ester carbonyl group.

Plasma and serum are the most widely used blood-derived biofluids for metabolomics and lipidomics assays, but the isolation of these products from blood may introduce additional bias as indicated by the fact that many analytes that are present at high concentrations in blood cells cannot be measured and evaluated in those samples. Of particular concern, variable hemolysis during the pre-processing of blood products could compromise accurate and reproducible quantification. Compared with plasma or serum, whole blood may be a better alternative due to simplicity of processing. In this study, we provide a comprehensive method for quantification of the whole blood sphingolipidome and the concentrations were compared with those from plasma. Combining a single-phase extraction method with liquid-chromatography high resolution mass spectrometry (R=120, 000), assisted by alkaline hydrolysis, we were able to identify and simultaneously quantify more than 150 sphingolipids. Furthermore, most of sphingolipids remained stable after a freeze/thaw cycle. Whole blood contained a higher concentration of most sphingolipids than corresponding plasma. Moreover, individual variations in the levels of sphingolipids were lower for whole blood than plasma. These findings demonstrate that whole blood could be a better alternative to plasma, and potentially guide the evaluation of sphinglipidome for biomarker discovery.

“Gray zone” category tumors in thyroid follicular tumors are difficult to diagnose, especially to distinguish between follicular thyroid adenoma (FTA) and follicular thyroid carcinoma (FTC). This study aimed to assess the diagnostic performance of metabolite enzymes using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to develop a classification model for the characteristics of thyroid follicular tumors among 24 samples. We analyzed the expression of metabolic enzyme markers in an independent validation set of 133 cases and evaluated the potential biological behavior of 19 borderline thyroid lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than in FTC (P<0.001). The metabolic enzyme panel—including FA synthase and Ca²⁺-independent PLA2, which are closely associated with altered metabolic pathways—was further identified in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the receiver operating characteristic curve, sensitivity, and specificity: 73.6%, 82.1%, 60.6%, respectively). The diagnostic strategy suggested considering a putative role of AFAIDESI-MSI in routine clinical triage for strict follow-up, with low metabolic enzyme expression combined with diagnostic in patients with a thyroid follicular borderline tumor diagnosis.

The classic Body Mass Index, (BMI), developed in the 19^th century by the Belgian mathematician Adolphe Quetelet [1] is an important indicator of the risk of death, of obesity, of negative health consequences, body fat percentage and of the shape of the body. While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers [2][3][4][5][9][25] that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. The BMI was developed as a law of natural sciences and “social physics” [1], as it was called then, before the middle of the 19^th century, and it had been used from the 70s for medical purposes, to detect obesity and the risk of mortality [6][7]. The BMI has a huge importance for modern society, affected by an obesity epidemic [8]. BMI has applications in medicine, sport medicine, sport, fitness, bodybuilding, insurance, nutrition, pharmacology. The main limitation of the BMI is that it does not account for body composition including non fat body mass such as muscles, joints, body frame and makes no difference between fat and non fat components of the body weight. The body composition and the proportion of fat and muscles make a difference in health outcomes [12][13][14][25][26][27][35][36][37] [38][39][40][41][42][43][44]…[100]. Body composition makes a difference also in the level of sport performance for athletes of every level. In nearly two centuries since the Body Mass Index was developed, no formula had been successfully developed to account for body composition and make the difference between muscle and fat in a consistent way. This can be considered a longstanding open problem of major importance for society. The objective of this analysis is to develop new formulae taking into account the health implication of body composition measured through indirect, simple indicators and making the difference between muscles and fat, healthy and non healthy metabolism. The formulae developed in this article are the only formula to successfully generalize BMI and make this difference. I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. No other formula generalized the BMI to make the difference between fat and a large frame and muscles has ever been published in nearly two centuries since the BMI formula had been developed. The formulae I developed explain and generalize the conclusions of a large number of highly cited empirical experiments cited in the reference section. [35][36][37][38][38][39] [40][42][43][44]..[100] Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

The prevalence of food allergy has increased over the last decades and consequently the food labeling policies have improved over the time in different countries to regulate allergen presence in foods. In particular, Reg 1169 in EU mandates the labelling of 14 allergens whenever intentionally added to foods, but the inadvertent contamination by allergens still remains uncovered topic. In order to warn consumers on the risk of cross-contamination occurring in certain categories of foods, a precautionary allergen labelling system has been put in place by food industries on voluntary basis. In order to reduce the overuse of PAL, reference doses and action limits have been proposed by the VITAL project representing a guide in this jeopardize scenario. Development of sensitive and reliable mass spectrometry methods are therefore of paramount importance in this regard to check the contamination levels in foods. In this paper we describe the development of a managed time MRM method based on a triple quadrupole platform for milk and egg quantification in processed food. The method was in house validated and allowed to achieve levels of proteins lower than 0.2mg of total milk and egg proteins respectively in cookies, challenging the doses recommended by VITAL. The method was finally applied to cookies labeled as milk and egg-free. This method could represent in perspective a promising tool to be implemented along the food chain to detect even tiny amounts of allergens contaminating food commodities.

The Body Mass Index (BMI) formula has been developed by Belgian mathematician Adolphe Quetelet and published in 1840 [1] as a law of nature and society, based on statistics about the weight and height of the population of that time, the first part of the 19^th century. He called it “social physics”. From then, for nearly two centuries, the BMI had been the most important formula describing the normal relations and ratio of weight to the square of the height for humans. The problem arises if the BMI formula, developed in the first part of the 19^th century is still good today when the type of work people perform is very different? In modern times, most people are less muscular than at the time when the BMI was developed because they do not work physically as heavy as at that time. In many cases, the Body Mass index can predict mortality, morbidity and illness but not always, for example cases such as (a) the obesity paradox for some cardiovascular problems and (b) the U shape mortality paradox as well as (c) false positive obesity diagnostic in regard to people who are strong and muscular, have low body fat percentage but are classified as obese by the BMI and (d) cases where BMI is normal but people have an “obese metabolism” (e) BMI normal but high fat percentage. The objective is to develop a formula good for all body types, a formula that makes the difference between fat and non-fat body weight such as muscle and body frame and quantifies the effect of strength and fitness, which BMI does not. Another objective is to develop a formula to predict the health risks and fitness status of people, better than BMI. The first generalizations of BMI using anthropometric metrics could be found in [2], where I discuss and analyze many formulae, developed, tested, and simulated by me, using similar new methods, accounting for body shape, physical shape and body function, making the difference between muscle mass and fat, fat and non fat body weight. Nearly all formulae and methods developed and proposed in this new model are new, never published before. Many experiments published before, in highly cited papers show that grip strength and muscle strength is a predictor of health, mortality, morbidity, endocrine and metabolic disease outside the BMI and anthropometric measures. The purpose of my formula is to explain the outcome of those experiments and create a formula which predicts these experiments [21-41].

The incidence of obesity which leads to insulin resistance (IR) and metabolic disorder increases in developing countries including Indonesia. Male adult has higher risk to have abdominal obesity than female which is associated with cardiometabolic disorders. Several anthropometric measurements have been proposed to predict IR. The aim of this study was to investigate whether body mass, body mass index (BMI), waist circumference (WC), body fat percentage (BF) or visceral fat percentage (VF) could become a better predictor of IR in healthy young male adult. Total of 140 healthy young male adults ranging from 18-25 years were recruited in the study. Insulin resistance was measured by calculating Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Subjects with HOMA-IR value >75th percentile with cut off 3.75 were defined as IR. Anthropometric measurements included body weight, BMI, WC were performed whereas BF and VC were measured by bioelectrical impedance analysis (BIA). IR had significant strong correlation with body weight, BMI, WC, BF and VF. The area under curve of body mass, BF, VF were greater than WC and BMI. Anthropometric measurements correlated strongly with IR but body weight, BF, VF have stronger correlation than WC and BMI in healthy young male adult.

Proteomic technology has improved at a staggering pace in recent years, with even practitioners challenged to keep up with new methods and hardware. The most common metric used for method performance is the number of peptides and proteins identified. While this metric may be helpful for proteomics researchers shopping for new hardware, this is often not the most biologically relevant metric. Biologists often utilize proteomics in the search for protein regulators that are of lower relative copy number in the cell. In this review, I re-evaluate untargeted proteomics data using a simple graphical representation of the absolute copy number of proteins present in a single cancer cell as a metric. By comparing single shot proteomics data to the coverage of the most in-depth proteomic analysis of that cell line acquired to-date we can obtain a rapid metric of method performance. Using a simple copy number metric allows visualization of how proteomics has developed in both sensitivity and overall dynamic range when using both relatively long and short acquisition times. To enable reanalysis beyond what is presented here, two available web applications have been developed for single and multi-experiment comparisons with reference protein copy number data for multiple cell lines and organisms.

Verteporfin, a free base benzoporphyrin derivative monoacid ring A, is a photosensitizing drug for photodynamic therapy (PDT) used in the treatment of the wet form of macular degeneration and activated by red light of 689 nm. Here, we present the first direct study of its photofragmentation channels in the gas-phase, conducted using a laser interfaced mass spectrometer across a broad photoexcitation range from 250-790 nm. The photofragmentation channels are compared with the collision-induced dissociation (CID) products revealing similar dissociation pathways characterized by the loss of the carboxyl and ester groups. Complementary solution-phase photolysis experiments indicate that photobleaching occurs in verteporfin in acetonitrile; a notable conclusion, as photoinduced activity in Verteporfin was not thought to occur in homogenous solvent conditions. These results provide unique new information on the thermal break-down products and photoproducts of this light-triggered drug.

Psychological wellbeing can be impacted substantially by changes in body image during youth, which can be a predictive factor for positive or negative attitudes, such as for self-esteem and satisfaction. In this study, adherence to the thinness model and to healthy behaviours were analysed in terms of the emotional patterns and body management of the young female Italian population (N = 2287). Skinny girls fitting better with the thinness model tended to develop higher positive emotional patterns, but their body management was low. Findings suggest the urgent need for preventive programmes to enhance awareness of healthy behaviours against appearance models.

Tandem mass spectrometry (MS/MS) for diagnosing inborn errors of metabolism (IEM) is recognized as an ethical, safe, simple, and reliable screening test. Presented bibliometric analysis aims to describe the network structure of the scientific community in the study area at the level of countries, institutions, authors, papers, keywords, and sources; scientific productivity, directions, and collaboration efforts in a considered period (1991–2023.) Using the PRISMA method, we conducted a systematic search for articles reporting using MS/MS to screen for inherited metabolic disorders and inborn errors of metabolism collected from the Web of Science Core Collection (WOSCC.) A total of 451 articles out of 546, by 2,682 authors, published in 190 journals, with 15,440 citations in 8,181 citing articles, with an average citation of 34.24 per article, and an H-index of 64 were retrieved from the WOSCC. The research status of MS/MS in IEM screening was identified. The most relevant current research directions and future areas of interest were revealed: "selective screening for IEM," "new treatments for IEM," "new disorders considered for MS/MS testing," "ethical issues associated with newborn screening," "new technologies that may be used for newborn screening," "use of a combination of MS/MS and gene sequencing," etc.

One of the research priorities in atmospheric chemistry is to advance our understanding of heterogeneous reactions and their effect on the composition of the troposphere. Chemistry on aqueous surfaces is particularly important in this regard because of their ubiquity and expanse. They range from the surfaces of oceans (360 million km²), cloud and aerosol drops (~10 trillion km²) to the fluids lining the human lung (~200 m²). Typically, ambient air contains reactive gases that may affect human health, influence climate and participate in biogeochemical cycles. Despite their importance, reactions between gases and solutes at air-aqueous interfaces are not well understood. New, surface-specific techniques are required that detect and identify the intermediates and products of such reactions as they happen on liquids. This is a tall order because genuine interfacial reactions are faster than mass diffusion into bulk liquids, and may produce novel species at low concentrations. Herein, we review evidence that validates online pneumatic ionization mass spectrometry of liquid microjets dosed by reactive gases as a technique meeting such requirements. Next, we call attention to results obtained by this approach on reactions of ozone, nitrogen dioxide and hydroxyl radicals with various solutes on aqueous surfaces. The overarching conclusion is that the outermost layers of aqueous solutions are unique media, where equilibria shift and reactions proceed faster than, in some cases along different pathways from the bulk liquids. The fact that the rates and mechanisms of reactions at air-aqueous interfaces may not be deduced from experiments in bulk liquids opens new conceptual frameworks and lines of research, and adds an overlooked dimension to atmospheric chemistry.

The photosystem I (PSI) of the green alga Chlamydomonas reinhardtii associates with 10 light-harvesting proteins (LHCI) to form the PSI-LHCI complex. Binding of LHCII to PSI may also occur and is controlled by a process called state transitions. Hereby, two LHCII trimers bind to the PSAL, PSAH and PSAO side of PSI to produce the PSI-LHCI-LHCII complex. In this work, we took advantage of chemical crosslinking of proteins in conjunction with mass spectrometry to identify protein-protein interactions between the light-harvesting proteins of PSI and PSII. We detected binding of LHCBM proteins to the LHCA1-PSAG side of PSI and identified protein-protein interactions of LHCSR3 with LHCA5 and LHCA3. Our data indicate that the binding of LHCII to PSI is more versatile as anticipated and reveal that LHCSR3 likely regulates excitation energy transfer to the PSI core via LHCA5/LHCA3.

Breath volatile organic compound analysis is a non-invasive tool for assessing health status; the compositional profile of these compounds in the breath of patients with chronic kidney disease is believed to change with decreasing renal function. We aimed to identify breath volatile organic compounds for recognizing patients with chronic kidney disease. Using thermal desorption-gas chromatography-mass spectrometry, untargeted analysis of breath markers was performed using breath samples of healthy controls (n=18) versus non-dialysis (n=21) and hemodialysis (n=12) patients with chronic kidney disease in this cross-sectional study. A total of 303 volatile organic compounds alongside 12 clinical variables were used to determine the breath volatile organic compound profile. Metabolomic analysis revealed that age, systolic blood pressure, and fifty-eight breath volatile organic compounds differed significantly between the chronic kidney disease group (non-dialysis + hemodialysis) and healthy controls. Thirty-six volatile organic compounds and two clinical variables that showed significant associations with chronic kidney disease in the univariate analysis were further analyzed. Different spectras of breath volatile organic compounds between the control and chronic kidney disease groups were obtained. Multivariate model incorporating age, 2-methyl-pentane, and cyclohexanone showed high performance (accuracy, 86%) in identifying patients with chronic kidney disease, with odds ratios (95% confidence interval) P-values of 0.18 (0.07-2.49) 0.013; 2.10 (0.94-2.24) 0.025; and 2.31 (0.88–2.64) 0.008, respectively. Hence, renal dysfunction-associated characteristic profiles of breath volatile organic substances can be used as non-invasive markers to screen for chronic kidney disease.

Background - Technological developments induced lifestyle changes and increase population physical inactivity. This change in lifestyle can affect the male-female morphological and physical fitness differences. The aim of this study is to determine and to compare the effect of sex differences in percentage of body fat on speed and endurance running performance. Methods - 72 male and 64 female students aged 20 to 23 years participated in this study. After assessing their morphological characteristics, running performances during 30 m and 400 m, and maximum aerobic velocity (MAV) and maximal oxygen consumption (VO2max) during a 20 m shuttle running test have been estimated for each subject. Male students were re-tested after being overweighed down with a weight equivalent to the mean differences in body fat recorded between the two sexes in the form of a loaded worn vest. Results – Male presented a percentage of fat mass (17.2 ±2%) significantly (p <0.001) lower than that of women subject (25.0 ±2.5%). Running performances during 30 m and 400 m, MAV and VO2max were significantly (p<0.001) better in males. During the weighted condition, male performances during 30 m and 400 m, MAV and VO2max were attenuated by 6.89%, 14.16%, 6.48% and 10.07%, respectively but remain significantly better than those of female students. Conclusion - The persistence of sex differences after overweighting male students indicates that body fat could be responsible for ≈ 50 to 70% of the observed differences between sexes performances during short and long sprints, and 20 m shuttle running test.

Engine oil degradation and tribological properties are strongly interrelated. Hence, understanding the chemical processes resulting in additive depletion and degradation products is necessary. In this study, in-service engine oils from petrol and diesel vehicles were analyzed with conventional and advanced methods (mass spectrometry). Additionally, the effect of the utilization profile (short- vs. long-range) was studied. Petrol engine oils generally showed accelerated antioxidant and antiwear degradation and higher oxidation, especially in case of a short-range utilization profile, which can be attributed to the higher air-to-fuel ratio (more rich combustion) compared to diesel engines. A detailed overview of oxidation and nitration products, as well as degradation products resulting from zinc dialkyl dithiophosphate and boron ester antiwear additives, diphenylamine antioxidants and salicylate detergents is given. A side-reaction between oxidation products (aromatic carboxylic acids) and the boron ester antiwear is highlighted. This reaction was only detected in the petrol engine oils, where the oxidation products were measured in a high abundance. However, no side reaction was found in the samples from the diesel vehicle, since there the aromatic carboxylic acids were largely absent due to lower oxidation.

Tributyltin (TBT) is one of the most toxic anthropogenic compounds introduced into the marine environment. Despite its global ban in 2008, TBT is still a problem of great concern due to its high affinity for particulate matter, providing a direct and potentially persistent route of entry into benthic sediments. Bioremediation strategies may constitute an alternative approach to conventional physicochemical methods, benefiting from the microorganism’s potential to metabolize anthropogenic compounds. In this work, a simple, precise and accurate static headspace gas chromatography method was developed to investigate the ability of TBT degrading microbes in sedimentary microcosms over a period of 120 days. The proposed method was validated for linearity, repeatability, accuracy, specificity, limit of detection and limit of quantification. The method was subsequently successfully applied for the detection and quantification of TBT and degrading compounds in sediment samples on day 0, 30, 60, 90 and 120 of the experiment employing the principles of green chemistry. On day 120 the concentration of TBT remaining in the microcosms ranged between 91.91 ng/g wet wt for the least effective microbial inoculant to 52.73 ng/g wet wt for the most effective microbial inoculant from a stating concentration of 100 ng/g wet wt.

Studies on the gait's parameters have been identified on the patients population. Most researchers confirm that the patients walk differently than normal people and they may have a risk for falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects. A cross-sectional study with forty-five young adult (F = 20, M = 25) was conducted. Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyser 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Females are found with higher total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. These findings may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important informations should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and riks to falling.

Glycosphingolipids (GSL) represent a highly heterogeneous class of lipids with many cellular functions, implicated in a wide spectrum of human diseases. Their isolation, detection, and comprehensive structural analysis is a challenging task due to the structural diversity of GSL molecules. In this work, GSL subclasses are isolated from human plasma using an optimized monophasic ethanol–water solvent system capable to recover a broad range of GSL species. Obtained deproteinized plasma is subsequently purified and concentrated by C18-based solid-phase extraction (SPE). The hydrophilic interaction liquid chromatography (HILIC) coupled to electrospray ionization linear ion trap tandem mass spectrometry (ESI-LIT-MS/MS) is used for GSL analysis in the human plasma extract. Our results provide an in-depth profiling and structural characterization of glycosphingolipid and some phospholipid subclasses identified in the human plasma based on their retention times and the interpretation of tandem mass spectra. The structural composition of particular lipid species is readily characterized based on the detailed interpretation of MS and MS/MS spectra and further confirmed by specific fragmentation behavior following predictable patterns, which yields to the unambiguous identification of 154 GSL species within 7 lipid subclasses and 77 phospholipids representing the highest number of GSL species ever reported in the human plasma. The developed HILIC-ESI-MS/MS method can be used for further clinical and biological research of GSL in the human blood or other biological samples.

The present work describes the optimization and validation of a highly selective and sensitive analytical method using solid phase extraction and liquid chromatography tandem mass spectrometry (SPE LC-MS/MS) for the determination of some frequently prescribed pharmaceuticals in urban wastewater received and treated by Sharjah sewage treatment plant (STP). The extraction efficiency of different SPE cartridges was tested and the simultaneous extraction of pharmaceuticals was successfully accomplished using hydrophilic-lipophilic-balanced reversed phase Waters^® Oasis HLB cartridge (200 mg/ 6 mL) at pH 3. The analytes were separated on an Aquity BEH C₁₈ column (1.7 µm, 2.1 mm x 150 mm) using gradient elution and the mass spectrometric analysis were performed in multiple reactions monitoring (MRM) selecting two precursor ions to produce ion transition for each pharmaceutical using positive electrospray ionization (+ESI) mode. The correlation coefficient values in the linear calibration plot for each target compound exceeded 0.99 and the recovery percentages of the investigated pharmaceuticals were more than 84%. Limit of detection (LOD) varied between 0.1-1.5 ng/L and limit of quantification (LOQ) was 0.3-5 ng/L for all analytes. The precision of the method was calculated as the relative standard deviation (RSD%) of replicate measurements and was found to be in the ranges of 2.2% to 7.7% and 2.2% to 8.6% for inter and intra-day analysis, respectively. All of the obtained validation parameters satisfied the requirements and guidelines of analytical method validation.

Bioactive lipids are involved in cellular signalling events with links to human disease. Many of these are involved in inflammation under normal and pathological conditions. Despite being attractive molecules from a pharmacological point of view, detection and quantification of lipids has been a major challenge. Here, we have optimised a liquid chromatography dynamic multiple reaction monitoring targeted mass spectrometry (LC-dMRM-MS) approach to profile eicosanoids and fatty acids in biological samples. In particular, by applying this analytic workflow to study a cellular model of Chronic Myeloid Leukaemia (CML), we found that intra- and extra-cellular 2-Arachidonoylglycerol (2-AG), intracellular Arachidonic Acid (AA), and extracellular Prostaglandin F_2α (PGF_2α), 5-Hydroxyeicosatetraenoic acid (5-HETE), Palmitic acid (PA, C16:0) and Stearic acid (SA, C18:0) were altered in response to immunomodulation by type I Interferon (IFN-I), a currently approved treatment for CML. Our observations indicate changes in eicosanoid and fatty acid metabolism with potential relevance in the context of cancer inflammation and CML.

SPME analysis of the scent Ophrys orchids gave the following results: O. apifera: benzyl benzoate, -copaene, caryophyllene, and cyclosativene. O. crabronifera subsp. biscutella: pentadecene, pentadecane, heptadecane, nonadecane, and heinecosane. O. bertolonii subsp. bertolonii: pentadecane, heptadecane and nonadecane. O. passionis subsp. garganica: i-propyl palmitate, caryophyllene, pentadecane, and heptadecane. O. holosericea subsp. apulica: -copaene, pentadecane, caryophyllene, and heptadecane. O. lacaitae: -copaene, pentadecane, heptadecane, and caryophyllene. O. bombyliflora: cyclosativene, pentadecane, and ethyl dodecanoate. O. insectifera: 8-heptadecene, pentadecane, and heptadecane. O. lutea: heptadecane, 8-heptadecene, nonadecane, and docosane. O. tenthredinifera subsp. neglecta: -copaene, caryophyllene, and i-propyl palmitate.

Obesity is treatment-resistant, and is linked with a number of serious, chronic diseases. Adult obesity rates in the United States have tripled since the early 1960s. Recent reviews show that an increased ratio of omega-6 to omega-3 fatty acids contributes to obesity rates by increasing levels of the endocannabinoid signals AEA and 2-AG, overstimulating CB₁R and leading to increased caloric intake, reduced metabolic rates, and weight gain. Cannabis, or THC, also stimulates CB₁R and increases caloric intake during acute exposures. The present meta-analysis reveals significantly reduced body mass index and rates of obesity in Cannabis users, in conjunction with increased caloric intake. We provide for the first time a causative explanation for this paradox, in which rapid and long-lasting downregulation of CB₁R following acute Cannabis consumption reduces energy intake and storage and increases metabolic rates, thus reversing the impact on body mass index of elevated dietary omega-6/omega-3 ratios.

Fabric phase sorptive extraction, an innovative integration of solid phase extraction and solid phase microextraction principles, has been combined with gas chromatography-mass spectrometry for the rapid extraction and determination of nineteen organochlorine pesticides in various fruit juices and water samples. FPSE consolidates the advanced features of sol-gel derived extraction sorbents with the rich surface chemistry of cellulose fabric substrate, which could directly extract target analytes from complex sample matrices and substantially simplifies the sample preparation operation. Important FPSE parameters including sorbent chemistry, extraction time, stirring speed, type and volume of back-extraction solvent and back-extraction time have been optimized. Calibration curves were obtained in the concentration range 0.1-500 ng/mL. Under the optimum conditions, the limits of detection were obtained in the range 0.007-0.032 ng/mL with satisfactory precision (RSD<6%). The relative recoveries obtained by spiking organochlorine pesticides in water and selected juice samples were in the range of 91.56–99.83%. The sorbent sol-gel poly(ethylene glycol)-poly(propylene glycol)-poly(ethylene glycol) was applied for the extraction and preconcentration of organochlorine pesticides in aqueous and fruit juice samples prior to analysis with gas chromatography-mass spectrometry. The results demonstrated that the present method is simple, rapid, and precise for the determination of organochlorine pesticides in aqueous samples.

To investigate whether high body mass index (BMI) increases the risk of recurrence and corre-lates with higher glucose uptake in recurrent lesions in post-menopausal female patients with breast cancer. The hospital database was searched to retrieve breast cancer patients, who had undergone an [18F]FDG PET/CT scan before neoadjuvant chemotherapy and curative-intent sur-gery. BMI was calculated at the baseline [18F]FDG PET/CT scan. There was a median follow-up of 5 years after the baseline PET/CT scan to identify: recurrence in the breast (T_rec); lymph nodes (N_rec); distant locations (M_rec). Furthermore, SUVmax was measured in the sites of recur-rence. A chi-square test was used to investigate any difference in the frequency of any recur-rence, T_rec, N_rec, and M_rec between overweight women (BMI≥25 kg/m2) and women with a BMI<25 kg/m2 (p<0.05). SUVmax, was compared using a t-test (p<0.05) between the two groups. A total of post-menopausal 142 women (BMI: 26.84±5.59; 84 overweight and 58 with normal weight) were retrieved. There were 48 recurrences at the follow-up. The chi-square test demon-strated in overweight women an increased frequency of any recurrence (35 vs. 13; p=0.025) and T_rec (15 vs. 2; p=0.018) and a higher T_rec SUVmax (4.74±2.90 vs. 1.85 ± 0.63; p=0.09) compared to women with a BMI<25 kg/m2. BMI seems to correlate with an increased rate of recurrence, espe-cially in the breast, and a higher glucose uptake in post-menopausal patients with recurrent breast cancer.

The aquaculture industry has become a sustainable provider of food to humans. Remaining challenges include disease issues, as well as ethical concerns for discomfort and stress among farmed fish. There is a need for reliable biomarkers to monitor welfare in fish, and the stress hormone cortisol has been suggested as a good candidate. This study presents a novel method for measurement of cortisol in fish feces based on enzymatic hydrolysis, liquid-liquid extraction, derivatization, and finally instrumental analysis by liquid chromatography coupled with tandem mass spectrometry. Hydrolysis and extraction conditions were optimized. Cortisol appeared to be mostly conjugated to sulfate and less conjugated to glucuronic acid in the studied samples of feces from farmed Atlantic salmon. The method was suitable for quantification of cortisol after enzymatic deconjugation by either combined glucuronidase and sulfatase activity, or by glucuronidase activity alone. The limit of detection was 0.15 ng/g and the limit of quantification was 0.34 ng/g, and the method was linear (R2>0.997) up to 380 ng/g, for measurement of cortisol in wet feces. Method repeatability and intermediate precision were acceptable, both with a CV of 11%. Stress level was high in fish released into seawater, and significantly reduced after eight days.

Fibroblast growth factor 14 (FGF14) is a member of the intracellular FGFs, a group of proteins with roles in neuronal ion channel regulation and synaptic transmission. We have previously demonstrated that a male Fgf14-/- mouse model recapitulates salient endophenotypes of synaptic dysfunction and behaviors associated with schizophrenia (SZ). As the underlying etiology of SZ and its sex-specific onset remain elusive, the Fgf14-/- model provides a valuable tool to interrogate pathways that might be related to the disease mechanism. Here, we performed label free quantitative proteomics and bioinformatics to identify enriched pathways at the proteome level in the male and female hippocampi from Fgf14+/+ and Fgf14-/- mice. We discovered that many differentially expressed proteins in Fgf14-/- animals are associated with SZ. In addition, measured changes in the proteome and signaling pathways were predominantly sex-specific with the male Fgf14-/- being distinctly enriched for pathways associated with neuropsychiatric disorders and addiction and the female exhibiting modest changes. In the male Fgf14-/- mouse the major protein changes that could in part explain the previously described neurotransmission and behavioral phenotype of this model were loss of ALDH1A1 and PRKAR2B. ALDH1A1 has been shown to mediate an alternative pathway for GABA synthesis, while PRKAR2B is essential for dopamine 2 receptor signaling, which is the basis of current antipsychotics. Collectively, our results provide new insights in the role of FGF14 and support the use of the Fgf14-/- mouse as a useful preclinical model of SZ for generating hypothesis on the disease mechanism, sex-specific manifestation and therapy.

BACKGROUND: Body mass index (BMI) is calculated by dividing a person's height in meters by their weight in kilograms and is always expressed in kg/m². BMI is a reliable risk indicator for various diseases that can develop due to a higher percentage of body fat. There is a possibility of developing certain medical conditions including heart disease, high blood pressure, type 2 diabetes, gallstones, breathing problems and some malignancies that increase with BMI. OBJECTIVE: This study seeks to identify the trends in the Body Mass Index (BMI) of women visiting Better Life Primary Health Care Centre in Ondo City, Ondo State, Nigeria for various healthcare services. METHODOLOGY: Seventy (70) women who participated in this study were randomly selected using systematic random sampling. Their necessary information was obtained using a prepared record sheet to collect their data. Results were analysed using SPSS version 21. RESULTS: The results show mean age of the respondents is 30.50 + 6.52921 21 (30%) were between 31 – 35 years, 21 (30%) were traders, 36 (51%) had tertiary education, 39 (55.7%) were between 151 – 160 cm in height. 32 (45.7%) were between 60 – 80 kg in weight and 30 (42.9%) had normal weight, respectively. CONCLUSION: Body Mass Index (BMI) calculation is an essential tool that can help in identifying one of the significant public health issues that leads to obesity; a predisposing factor to various medical conditions like hypertension, musculoskeletal issues, heart diseases, cancers, and lots more. It is therefore important to incorporate BMI calculation into routine checks to prevent or reduce health burdens that may arise from obesity.

The association between obesity and clinical as well as radiological outcomes in patients suffering non-traumatic intracerebral haemorrhage (ICH) remains unclear. The obesity paradox suggests a protective effect regarding in-hospital mortality. This study evaluates the impact of body mass index (BMI) on functional long-term outcome and bleeding volume in patients with non-traumatic ICH. A retrospective cohort study including all consecutive patients with spontaneous ICH treated at a tertiary referral centre between December 2017 and June 2021, aged 80 years or younger (n = 218), were included. Patients were dichotomized into overweight (OW, BMI ≥ 25 kg/m2) and normal weight (NW, BMI < 25 kg/m2). Functional outcomes were assessed by the modified Rankin scale (mRS), extended Glasgow Outcome Scale (GOS-E) and the National Institutes of Health Stroke Scale score (NIHSS) at 1, 3, 6 and 12-months follow-up. Bleeding volumes were calculated as ABC/2. Univariate and multivariate analysis were performed to assess clinical predictors of favourable outcome in the long-term. Of 218 patients (66.04 ± 15.18 years) suffering non-traumatic ICH, 115 (52.75%) were OW (29.72 ± 3.82). Female sex (p = 0.1), NIHSS (p = 0.69), cardiovascular risk factors (p = 0.55), ICH volume (p = 0.19), and presence of anticoagulation (p = 0.67) did not significantly differ between the OW and NW cohort. At discharge, functional outcome did not significantly differ between both cohorts (NW, mRS 3.92 ± 2.54 vs. OW, mRS 3.21 ± 2.43, (p = 0.28)). Multivariate analysis revealed that haemorrhage volume (p = 0.01) was the only robust risk factor to predict functional outcome after 1 year. Our data suggests that in ICH patients, neither obesity nor patient’s age are negative predictors for functional outcome in the long-term. Instead, bleeding volume is a robust risk factor predicting poor functional status after ICH. Therefore, prospective randomized trials analysing this coherence are highly warranted.

The presence of antibiotic residues in honey has recently become a growing public health concern due to the overuse of these products in beekeeping and their transfer to the food industry. The aim of this study was to develop and validate a simple, selective and sensitive method for the simultaneous identification and quantification of residues of twenty-two sulfonamides, trimethoprim and dapsone in honey using a rapid and reliable liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. The developed method showed good linearity, specificity, precision (repeatability and intra-laboratory reproducibility) and recovery. The decision limit (CCalpha) ranged between 2.16-22.12 µg/kg for CCα, while the detection capability (CCbeta) was between 2.16- 2.67-27.36 µg/kg. The method proved to be rapid, reliable and effective for the determination of sulfonamides, trimethoprim and dapsone from honey samples. The average recoveries were estimated to be between 70 and 106%. The relative standard deviations (RSDs) were between 6-18%. In practice, the method is essential to check the honey sold on the market and ensure its safety before it reaches the consumer.

Today, due to recent developments in technology, children devote plenty of time for screen viewing. However, its harmful effects are not yet clear. The purpose of present study was to examine the associations among screen viewing and sleep duration, and body mass index (BMI) in under-five years old children. This cross-sectional study was conducted with 322 under-five healthy children that were selected using multistage stratified cluster sampling method in 2017. The data that were gathered by time-use diary method were analyzed using Kolmogorov-Smirnov test, Spearman correlation tests, multiple linear regression analysis, one-way ANCOVA, two-way ANCOVA. There was a negative correlation between screen time and sleep duration (rs = -0.42, p = 0.00), positive correlation between screen time and BMI (rs = 0.38, p = 0.00) and sleep duration negatively correlated with BMI (rs = -0.22, p = 0.00). screen viewing was a predictive factor for both sleep duration (β = -0.26, p = 0.00) and BMI (β = -0.26, p = 0.00). screen viewing had a significant impact on sleep duration (4, 314) = 5.02, P = 0.001) and BMI (F (4, 314) = 1.16, P=0.298). Results of this study indicated that screen viewing is related to sleep duration and BMI in under-five children. furthermore, screen time has an impact on sleep duration and BMI scores of children. findings of our study suggest that sleep duration negatively is associated with BMI in under-five-year-old children.

Objetives: Adequate donor-recipient matching is necessary to achieve the best renal function after transplantation. The nephron load received from the donor, which can be reflected in variables such as age, sex and body mass index, may influence the evolution of the graft. Our objetive was develop a combined score according to the donor-recipient pairing in age, sex and body mass index, and assess its influence on the evolution of the renal graft. Materials and methods: Transplant patients between 2013 and 2020 who had at least 1 year of post-transplant follow-up. A ranking of 0 to 2 points was awarded according to the match between donor and recipient for sex, age and body mass index individually, with higher rank to greater mismatch. Subsequently, a Score with value of 0 to 6 points was created with the combined ranking of the indivudual variables, analyzing its influence on the evolution of the graft by multivariate linear regression. Results: 280 patients followed for 4.3 years of median. Worse renal function was observed at the end of follow-up as the range of each variable increased separately, and the Score created, with a worsening of renal function as the combined Score increased in the multivariate analysis: Coefficient B= -2.4 ml/min, p=0.018. Conclusions: An adequate match between donor and recipient in age, sex and body mass index using this combined Score can help achieve better kidney function after transplantation.

Astragalus bone is one of the most important fossil records as it can reconstruct the prehistoric life. Respectively, this study aims to model the body mass, habitat preference, and population density of prehistoric bovid Duboisia santeng (Dubois 1891) in eastern Java island in the early Pleistocene. The astragali from 9 specimens were used to estimate the body mass and population density. Likewise regression models are used to analyze the relationship between astragalus lateral length, width, and body mass compared to the astragalus of extant Bovid species. The result revealed the body mass average was 60.3 kg (95%CI: 58.9-61.7) and this indicates the D. santeng belongs to large herbivores. While the population density was estimated at about 5.39 individuals per km2 (95% CI: 3.18-7.6).

Background and Objectives: Acculturation is associated with excessive weight gain among immigrants to the U.S. Whether dietary factors mediate this association is unclear. This study aimed to examine whether overall diet quality or specific component(s) of diet quality mediate the association between acculturation and Body Mass Index (BMI) among Mexican American (MA) men and women. Material and Methods: This is a secondary data analysis using dietary intake data from 24-hour dietary recalls, measured height and weight, and self-reported acculturation from the National Health and Nutrition Examination Survey (NHANES) cycles 1999-2000 to 2011-2012. A total of 6848 MA adults (≥20 yrs) with reliable dietary recall status and body measures were included in the study. Path analyses was performed in Mplus with complex survey design effects adjusted. Results: HEI components of whole grains and sodium were found to play meditating roles in the acculturation-BMI association, and their effects on BMI were opposing [indirect effect were -0.01 (SE 0.00) and 0.02 (0.01), respectively]. In gender-specific analysis, sodium [0.01 (0.00)] was a significant mediator only in MA men; whereas, whole grains [-0.01 (0.00)] was a significant mediator only in MA women. Conclusions: HEI components of whole grains and sodium appeared to be significant dietary mediators in the acculturation-BMI association. Understanding the variations of dietary components and their relationship with acculturation as well as BMI is useful for developing dietary interventions and obesity reduction.

To determine promethazine (PMZ) and its metabolites promethazine sulfoxide (PMZSO) and monodesmethyl-promethazine (Nor1PMZ) in swine muscle, fat, kidney, and liver, a sample preparation and high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis method were established and validated. The sample was extracted with 0.1% formic acid-acetonitrile, and the extract was purified with acetonitrile-saturated n-hexane. After concentration by rotary evaporation, the extract was re-dissolved in 0.1% formic acid-water and acetonitrile (80:20, v/v). The HPLC-MS/MS column used was a Waters Symmetry C18 (100 mm × 2.1 mm i.d., 3.5 μm), with 0.1% formic acid-water and acetonitrile as the mobile phase, and the target compounds were determined by positive ion scan and multiple reaction monitoring. PMZ and Nor1PMZ were quantified with deuterated promethazine (PMZ-d6) as the internal standard, while PMZSO was quantified by external standard method. The limits of detection (LOD) and limits of quantification (LOQ) of PMZ and PMZSO in muscle, liver, and kidney spiked samples were 0.05 μg/kg and 0.1 μg/kg, respectively, while those of Nor1PMZ were 0.1 μg/kg and 0.5 μg/kg, respectively. The LOD and LOQ of analytes in fat spiked sample were 0.05 μg/kg and 0.1 μg/kg, respectively. The sensitivity of this method reaches or exceeds its presented in previous reports. The analytes PMZ and PMZSO showed good linearity within the range of 0.1 μg/kg to 50 μg/kg, while Nor1PMZ showed good linearity within the range of 0.5 μg/kg to 50 μg/kg, with correlation coefficients (r) greater than 0.99. The recoveries of the target compounds in the sam-ples were between 81.73% and 107.17%, and the precision ranged from 1.78% to 10.47%. This study developed for the first time an HPLC-MS/MS method for the determination of PMZ and its metabolites PMZSO and Nor1PMZ in four swine edible tissues, comprehensively covered target tissues of monitoring object, which is applicable for monitoring veterinary drug residues in ani-mal-derived foods and ensuring food safety.

The blue sepal color of hydrangea is due to a metal complex anthocyanin composed of 3-O-glucosyldelphinidin (1) and an aluminum ion with the co-pigments 5-O-caffeoylquinic acid (2) and/or 5-O-p-coumaroylquinic acid (3). The three components, namely, anthocyanin, Al³⁺ and 5-O-acylquinic acids, are essential for blue color development, but the complex is unstable and only exists in aqueous solution. Furthermore, the complex did not give analyzable NMR spectra or crystals. Therefore, many trials to determine the detailed chemical structure of the hydrangea-blue complex have failed to date. Instead, via experiments mixing 1, Al³⁺ and 2 or 3 in a buffered solution at pH 4.0, we obtained the same blue solution derived from the sepals. However, the ratio was not stoichiometric but fluctuated. To determine the composition of the complex, we tried direct observation of the molecular ion of the complex using electrospray-ionization mass spectrometry. In a very low-concentration buffer solution (2.0 mM) at pH 4.0, we reproduced the hydrangea-blue color by mixing 1, 2 and Al³⁺ in ratios of 1:1:1, 1:2:1 and 1:3:1. All solution gave the same molecular ion peak at m/z = 843, indicating that the blue solution has a ratio of 1:1:1 for the complex. By using 3, the observed mass number was m/z = 827 and the ratio of 1, 3 and Al³⁺ was also 1:1:1. A mixture of 1, 3-O-caffeoylquinic acid (4) and Al³⁺ did not give any blue color but instead was purple, and the intensity of the molecular ion peak at m/z = 843 was very low. These results strongly indicate that the hydrangea blue-complex is composed of a ratio of 1:1:1 for 1, Al³⁺ and 2 or 3.

Glycated hemoglobin (HbA1c) is used to assess glycemic control in Type 1 diabetes (DM1) patients. Apolipoproteins play an essential role in DM1 pathophysiology and may be associated with complications, as well as HbA1c. This cross-sectional observational study consisting of 81 children and adolescents of both sexes diagnosed with DM1 investigated the relationship between body fat distribution and lean mass with HbA1C and apolipoprotein values analyzing biochemical and body composition measurements. Shapiro-Wilk test with Lilliefors correction, non-parametric Mann-Whitney test, and others were used with a significance level of 5%. The sample had a diagnosis time of 4.32 years and high blood glucose levels (mean 178.19 mg/dL) and HbA1c (mean 8.57%). Subjects also had a moderate level of adiposity, as indicated by arm and thigh fat areas. The study also found significant differences in the distribution of patients concerning levels of apolipoproteins A and B, with a smaller proportion of patients having undesirable levels. Finally, the study found a significant difference in the distribution of patients with estimated cardiovascular risk based on the ApoB/ApoA-1 ratio. Conclusively, visceral fat in children and adolescents with DM1 may increase the risk of DM1 long-term complications owing to its association with elevated HbA1C and apolipoprotein values.

Background: This study explored the effects of a virtual reality exercise program on overweight middle-aged women. Methods: This randomized controlled trial included women 4065 years of age with a body mass index (BMI) of 23 kg/m2 or more living in D city. The virtual reality environment was set up by attaching an IoT sensor to an indoor bicycle and linking it with a smartphone, enabling exercise in an immersive virtual reality through a head-mounted display. Results: In the virtual reality exercise group, the BMI was significantly decreased after the 8-week intervention compared with the baseline value (F=100.806, p<.001). The depression scores were significantly different among the three groups, with the intervention effect being more significant in the virtual reality exercise group than in the indoor bicycle exercise and con-trol groups (F=3.462, p<.001). Furthermore, the levels of exercise fun (F=12.373, p<.001) and exer-cise immersion (F=14.629, p<.001) were significantly higher in the virtual reality exercise group than in the indoor bicycle exercise and control groups. Conclusions: The virtual reality exercise program positively affected the BMI and the levels of depression, exercise fun, and exercise im-mersion in overweight middle-aged women. It is an effective home exercise program for obesity management in this population.

Precise association of serum leptin with body mass index (BMI) and blood pressure (BP; both systolic blood pressure (SBP) and diastolic blood pressure (DBP) is not well known for understanding their involvement in health and disease. Hence, the present study was planned to be conducted for investigating the association of BP, BMI and serum leptin levels in young normal weight (NW) and overweight (OW) male Saudi students. The NW (n: 198) and OW male subjects (n: 192) in the age range of 18-20 years were consulted. Blood pressure (BP) was measured with a mercury sphygmomanometer. Leptin Human ELISA Kits were employed for the determination of the serum leptin levels. The mean ± SD values of BMI (kg/m2), serum leptin (ng/ml), SBP (mmHg), and DBP (mmHg) all showed significant difference for young OW vs. NW male university students as: 27.52± 1.42 vs. 21.49± 2.03; 10.70± 4.67 vs. 4.68± 1.91; 121.37±2.59 vs.118.51±1.54 and 81.44±1.97 vs. 78.79±1.44 respectively. All associations (among BMI, leptin, SBP and DBP) showed positive linear and significant correlation except nonsignificant correlation of BMI and SBP for NW group. The present study in the young Saudi male students, presents significant variations for BP and serum leptin levels and significant positive linear association among serum leptin, BMI and BP.

Protein import into the endoplasmic reticulum (ER) is the first step in the biogenesis of about 10,000 different soluble and membrane proteins in humans. It involves co- or post-translational targeting of precursor polypeptides to the ER and their subsequent membrane insertion or translocation. So far, three pathways for ER targeting of precursor polypeptides plus four pathways for ER targeting of mRNAs were described. Typically, these pathways deliver their substrates to the Sec61 polypeptide-conducting channel in the ER membrane. Next, the precursor polypeptides are inserted into the ER membrane or translocated into the ER lumen, which may involve auxiliary translocation components, such as the TRAP and Sec62/Sec63 complexes, or auxiliary membrane protein insertases, such as EMC and the TMCO1 complex. Recently, the PEX19/PEX3-dependent pathway, which has a well-known function in targeting and inserting various peroxisomal membrane proteins into pre-existent peroxisomal membranes, was also found to act in targeting and, putatively, inserting monotopic hairpin proteins into the ER. These either remain in the ER as resident ER membrane proteins or are pinched off from the ER as components of new lipid droplets. Therefore, the question arose if this pathway may play a more general role in ER protein targeting, i.e. represents a fourth pathway for ER targeting of precursor polypeptides. Thus, we addressed the client spectrum of the PEX19/PEX3-dependent pathway in both PEX3-depleted HeLa cells and PEX3-deficient Zellweger patient fibroblasts by an established approach, which involves label-free quantitative mass spectrometry of the total proteome of depleted or deficient cells and differential protein abundance analysis. The negatively affected proteins included twelve peroxisomal proteins and two hairpin proteins of the ER, thus confirming two previously identified classes of putative PEX19/PEX3-clients in human cells. Interestingly, fourteen collagen-related proteins with signal peptides or N-terminal transmembrane helices and belonging to the secretory pathway were also negatively affected by PEX3-deficiency, which may suggest compromised collagen biogenesis as a hitherto unknown contributor to organ failures in the respective Zellweger patients.

Since the photocatalytic reaction is a surface reaction, enhancing the gas movement around photocatalyst would promote photocatalytic CO₂ reduction performance. A new approach to enhance the gas movement around the photocatalyst by the natural thermosiphon movement of gasses around photocatalyst using black body material was proposed and confirmed experimentally, but the heat transfer mechanism on the phenomena was not clarified yet. The purpose of this study is to clarify the heat transfer mechanism of it. This study calculated the temperature of mixed gases of CO₂ and NH₃ around P₄O₁₀/TiO₂ photocatalyst by the heat transfer formula. It is revealed that there was no difference between the increase temperature (T_g) from the temperature at the beginning of the CO₂ reduction experiment (T_ini) and the temperature of mixed gases of CO₂ and NH₃ measured by thermocouple in the experiment (T_e) under the illumination condition with a visible light (VIS) + an infrared light (IR) and IR only. The heat transfer model proposed by this study has predicted T_g well under the illumination condition with VIS + IR and IR only well. On the other hand, it is revealed that the difference between T_g and T_e was as large as 10 ℃ under the illumination condition with an ultra violet light (UV) + VIS + IR.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) is a commonly used technique for analyzing large biomolecules. However, the utilization of organic matrices limits the small-molecule analysis because of the interferences in the low-mass region and reproducibility issues. To overcome these limitations, a surface-assisted laser desorption/ionization (SALDI), which utilizes nanostructured metallic surfaces, has been developed. Herein, a novel approach for SALDI–MS was proposed using nanoengineered gold shell with nanogaps on the silica core (SiO2@Au NGS), which is an emerging material due to its excellent heat-generating capabilities. The gold shell thickness was controlled by adjusting the concentration of gold precursor for the growth of gold nanoparticles. SALDI-MS measurements were performed on a layer formed by drop-casting a mixture of SiO2@Au NGS and analytes. At the optimized process, the gold shell thickness was observed to be 17.2 nm, which showed the highest absorbance. The ion desorption efficiency was confirmed with a survival yield upon fragmentation. Based on the enhanced SALDI capability, SiO2@Au NGS was utilized to detect various small molecules including amino acids, sugars, and flavonoids. The limits of detection, reproducibility, and salt tolerance of SiO2@Au NGS demonstrate its potential as an effective and reliable SALDI material for small-molecule analyses.

In this paper, a special recurrent neural network (RNN) called \emph{Long Short-Term Memory (LSTM)} is used to design a virtual load sensor that estimates the mass of heavy vehicles. The estimation algorithm consists of a two-layer LSTM network, with the two layers based on sequence-to-sequence and sequence-to-one logic, respectively. The network estimates the vehicle mass based on the vehicle speed, longitudinal acceleration, engine speed, engine torque, and the accelerator pedal position. The network is trained and tested with a data set collected in a high-fidelity simulation environment called Truckmaker. Training data is generated in acceleration maneuvers in a range of speeds whereas test data is obtained by simulating the vehicle in a Worldwide harmonized light vehicles test cycle (WLTC). Preliminary results show that, with the proposed approach, the heavy-vehicle mass can be estimated as accurately as commercial load sensors in a range of load mass as wide as four tons.

Background: The oral health-related quality of life (OHRQoL) assessment evaluated the impact of individual’s oral health on the patient's physical and psychosocial status. We evaluated the association between subjective OHRQoL, measured with the Oral Health Impact Profile-14 (OHIP-14) questionnaire, and unfavorable body mass index (BMI) (i.e., too high or too low) in a large population-based study on older adults from Southern Italy. Moreover, we assessed which of the seven OHIP-14 domains was most strongly associated with an unfavorable BMI. Methods: We used data on a subpopulation of the Salus in Apulia Study, including 216 older adults. BMI &lt;18.4 kg/m2 and &gt;30 kg/m2 were classified as unfavorable, values between 18.5 and 30 kg/m2 were classified as ideal. Results: Higher OHIP-14 total score increased the risk to have an unfavorable BMI [odds ratio (OR):1.08, 95% confidence interval (CI):1.01-1.15]. In the model adjusted for age, sex, education, hypertension, carbohydrate consumption, and alcohol consumption, this finding was confirmed with higher OHIP-14 total score increasing the risk to have an unfavorable BMI (OR:1.10, 95% CI:1.01-1.22), and higher age linked to a decreased risk to have an unfavorable BMI (OR:0.89, 95% CI:0.82-0.97). In a random forest regression model, the most important predictive domains/sub-scales of OHIP-14 in mean decrease Gini for unfavorable BMI were, in order of decreasing importance, physical pain, functional limitation, psychological discomfort, physical disability, social disability, psychological disability, and handicap. Conclusions: In older age, negative OHRQoL, particularly linked to the physical pain domain, increased the risk of underweight or overweight and obesity.

Adults with obesity experience high rates of disability and rapid functional decline. Identifying movement dysfunction early can direct intervention and disrupt disability development, however subtle changes in movement are difficult to detect with the naked eye. This study evaluated how a portable, inertial measurement unit (IMU)-based motion capture system compares to a laboratory-based optokinetic motion capture (OMC) system for evaluating gait kinematics in adults with obesity. Ten adults with obesity performed overground walking while equipped with the OMC and IMU systems. Fifteen gait cycles for each participant were extracted for 150 total cycles analyzed. Kinematics were compared between OMC and IMU across the gait cycles (coefficient of multiple correlations), at clinically significant time points (interclass correlations), and over clinically relevant ranges (Bland Altman plots). Sagittal plane kinematics were most similar between systems, especially at the knee. Sagittal plane joint angles at clinically meaningful timepoints were poorly associated except for ankle dorsiflexion at heel strike (ρ=0.38) and minimum angle (ρ=0.83). Most motions had more than 5° difference between systems across the range of angles measured. IMU-based motion capture shows promise for detecting subtle gait changes in adults with obesity. However, more work is needed before this method can replace traditional OMC.

Both ricin and R. communis agglutinin (RCA120), belonging to the type II ribosome-inactivating proteins (RIPs-Ⅱ), are derived from the seeds of castor bean plant. They share very similar amino acid sequences, but ricin is much more toxic than RCA120. It is urgently necessary to distinguish ricin and RCA120 in response to public safety. Currently, mass spectrometric assays are well established for unambiguous identification of ricin by accurate analysis of differentiated amino acid residues after trypsin digestion. However, diagnostic peptides are relatively limited for unambiguous identification of trace ricin, especially in complex matrices. Here, we demonstrate a digestion strategy of multiple proteinases to produce novel peptide markers for unambiguous identification of ricin. LC-HRMS was used to verified the resulting peptides, among which only the peptides with uniqueness and good MS response were selected as peptide markers. Seven novel peptide markers were obtained from tandem digestion of trypsin and endoproteinase Glu-C in PBS buffer. From the chymotrypsin digestion under reduction and non-reduction conditions, eight and seven novel peptides were selected respectively. Using pepsin under pH 1~2 and proteinase K digestion, 6 and 5 peptides were selected as novel peptide markers. In conclusion, the obtained novel peptides from the established digestion methods can be recommended for the unambiguous identification of ricin during the investigation of illegal use of the toxin.

The neutrino is perhaps the most elusive member of the particle zoo. The questions about its nature, namely: Dirac or Majorana, the value of its mass and the interactions with other particles, the number of its components including sterile species, are long standing ones and still re- main in large extent without conclusive answers. From the side of the nuclear structure and nuclear reactions, both theories and experiments, the need to elucidate these questions have, and still has, prompt crucial developments in the fields of double beta decay, double charge exchange and neutrino induced reactions. The measurements of neutrino flavor os- cillation parameters contribute largely to restrict models with massless neutrinos. From the particle physics side, the possibilities to extent the standard model of electroweak interactions to incorporate a right handed sector of the electroweak lagrangian are directly linked to the adopted neu- trino model. Here, I would like to address another aspect of the problem by asking the question of the neutrino mass mechanism in the cosmological context, and particularly about dark matter.

The study of mechanical properties of rock mass can be effectively carried out through rock-like material model test. The similarity of mechanical properties between rock-like material and protolith is dependent on the appropriate selection of composition and content of rock-like materials. In this research, X-Ray diffraction test was conducted to analyze the composition of deep rock, which confirmed silica, quartz, and dolomite as the primary components of deep sandstone. An orthogonal design test was used to execute the ratio test of rock-like material. River sand was used as an aggregate, cement as a binder, gypsum powder as a regulator, and polystyrene foam (EPS) as rock damage simulation material. The influencing factors considered in the orthogonal mechanical tests were the proportion of aggregate and binder, ratio of binder and regulator, quantity of damage simulation material, and size of damage simulation material. Three levels were set for each factor, and mechanical parameters such as compressive strength, tensile strength, elastic modulus, axial strain, and Poisson's ratio were tested for each group of samples. The changes of those parameters with the levels of the above four factors were studied. The study revealed that adjusting the size of polystyrene foam (EPS) can adjust the values of elastic modulus, tensile strength, and Poisson's ratio of rock-like material. Similarly, changing the ratio of binder and regulator can adjust the values of axial strain and compressive strength of rock-like material. The rock-like material developed in the study can simulate the mechanical properties of different rock masses such as granite, sandstone, shale, and limestone.

With reference to our recently proposed Planck Scale White Hole Cosmology (PS-WHC) or Flat Space Cosmology (PS-FSC), we make an attempt to quantify galactic dark matter and flat rotation speeds in terms of galactic visible matter and cosmic mass. Considering recently observed dwarf galaxies having very little dark matter and assuming a time dependent reference mass unit of $M_X\cong \left(\mbox{3.0 to 4.0}\right)\times 10^{38}$ kg, we suggest an empirical relation for galactic dark matter $M_d$ via galactic visible mass $M_v$ as,$M_d \cong \frac{M_v^{3/2}}{M_X^{1/2}}$. This relation helps in fitting flat rotation speeds starting from 8 km/sec (for Segue 2) to 500 km/sec (for UGC12591). Modifying MOND's galactic flat rotation speed relation with Hubble mass $M_0\cong \left(\frac{c^3}{2GH_0}\right)$ of the universe, ratio of galactic flat rotation speed $V_G$ to speed of light $c$ can be shown to be approximately $\frac{V_G}{c} \cong 0.5 \left(\frac{M_v}{M_0}\right)^{1/4}$. Considering the sum of galactic dark matter and visible matter, ratio of galactic flat rotation speed to speed of light can be shown to be approximately $\frac{V_G}{c}\cong 0.25 \left(\frac{M_v+M_d}{M_0}\right)^{1/4}$. With further study, dark matter's nature, effect and distribution can be understood in terms of visible matter's extended gravity and extended theories of gravity can be understood with 'distance cosmic mass' rather than the empirical 'minimum acceleration'.

Fatty acids (FAs) represent an important class of metabolites, impacting on membrane building blocks and cellular regulatory networks. In nature, prokaryotes are characterized with the most impressing FA structural diversity and the highest relative contents of free fatty acids (FFAs). Thereby, nitrogen-fixing bacteria (order Rhizobiales), often found in symbiosis with legumes, attract a special interest. Indeed, FAs impact on the structure of rhizobial nodulation factors, required for successful infection of plant root. Although the FA patterns can be addressed by GC- and LC-MS, these methods are time-consuming and suffer from compromised sensitivity, low stability of derivatives and artifacts. In contrast, MALDI-TOF-MS represents an excellent platform for high-efficient metabolite fingerprinting, also applicable to FFAs. Therefore, here we propose a simple and straightforward protocol for high-throughput relative quantification of FFAs in rhizobia by the combination of Langmuir technology and MALDI-TOF-MS, which is featured with high sensitivity, accuracy and precision of quantification. Here we propose a step by step procedure comprising rhizobia culturing, pre-cleaning, extraction, sample preparation, mass spectrometric analysis, data processing and post-processing. To demonstrate the analytical potential of the protocol we illustrate it by a case study – comparison the FFA metabolomes of two rhizobia species - Rhizobium leguminosarum and Sinorhizobium meliloti.

Bioelectrocatalysis provides the intrinsic catalytic-functions of redox enzymes to non-specific electrode reactions and is the most important and basic concept for biosensors. This review starts by describing fundamental characteristics of bioelectrocatalytic reactions in mediated and direct electron transfer types from a theoretical viewpoint and summarizes amperometric biosensors based on multi-enzymatic cascades and for multi-analyte detection. The review also introduces prospective aspects of two new concepts of biosensors: mass-transfer-controlled (pseudo)steady-state amperometry at microelectrodes with enhanced enzymatic activity without calibration curves and potentiometric coulometry at enzyme/mediator-immobilized biosensors for absolute determination.

A simple mathematical interaction function, with the limit value w = e2π/e, derived as a basis for modelling emergent properties of nanoparticles, nanodrops and liquids, has been further developed. A correlation between physical systems of uniform particles and fundamental properties of natural numbers leads to a model, which acts as a bridge between properties of macroscopic systems and fundamental physical constants. The four fundamental coupling constants, and the masses of fundamental elementary particles, including the Higgs and Z bosons, are derived by using this interaction function. A proposal for the mass of the electron neutrino is given. Finally, the nuclear binding interaction is modeled with the interaction function. Only the experimental values of the Planck constant h and the speed of light c are needed for the model.

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.

The most cited evidence for (nonbaryonic) dark matter has been an apparent lack of visible mass to gravitationally support the observed orbital velocity of matters in rotating disk galaxies. Yet measurement of the mass of celestial objects cannot be straightforward, requiring theories derived from the known physical laws along with some empirically established semi-quantitative relationship. The most reliable means for determining the mass distribution in rotating disk galaxies is to solve a force balance equation according to Newton’s laws from measured rotation curves, similar to calculating the Sun’s mass from the Earth’s orbital velocity. Another common method to estimate galactic mass distribution is to convert measured brightness from surface photometry based on empirically established mass-to-light ratio. For convenience, most astronomers commonly assumed a constant mass-to-light ratio for estimation of the so-called “luminous” or “visible” mass, which should not be expected accurate. The mass determined from rotation curve typically exhibit an exponential-like decline with galactrocentric distance, qualitatively consistent with observed surface brightness. This fact scientifically suggests variable mass-to-light ratio of baryonic matter in galaxies without the need for dark matter.

We report the application of a recently proposed approach for modeling biological systems using a maximum entropy production rate principle in lieu of having in vivo rate constants. The method is applied in four steps: (1) a new ODE-based optimization approach based on Marcelin’s 1910 mass action equation is used to obtain the maximum entropy distribution, (2) the predicted metabolite concentrations are compared to those generally expected from experiment using a loss function from which post-translational regulation of enzymes is inferred, (3) the system is re-optimized with the inferred regulation from which rate constants are determined from the metabolite concentrations and reaction fluxes, and finally (4) a full ODE-based, mass action simulation with rate parameters and allosteric regulation is obtained. From the last step, the power characteristics and resistance of each reaction can be determined. The method is applied to the central metabolism of Neurospora crassa and the flow of material through the three competing pathways of upper glycolysis, the non-oxidative pentose phosphate pathway, and the oxidative pentose phosphate pathway are evaluated as a function of the NADP/NADPH ratio. It is predicted that regulation of phosphofructokinase (PFK) and flow through the pentose phosphate pathway are essential for preventing an extreme level of fructose 1, 6-bisphophate accumulation. Such an extreme level of fructose 1,6-bisphophate would otherwise result in a glassy cytoplasm with limited diffusion, dramatically decreasing the entropy and energy production rate and, consequently, biological competitiveness.

Nurses in disaster response require comprehensive understanding, training, and col-laboration among educators, researchers, and practitioners to overcome challenges and improve their capabilities. This study evaluates the impact of simulation-based training on improving nursing students' knowledge and performance in crisis management and triage during mass casualty incidents in Saudi Arabia, aiming to enhance existing pro-tocols in disaster management. This quantitative interventional pre-post study aimed to assess the impact of a training intervention on the disaster nursing skills of nursing students at Taif University in Saudi Arabia. The study involved a random sample of 101 nursing students and utilized a realistic train accident simulation with a response team comprising healthcare professionals and emergency specialists. A detailed questionnaire was used to measure emergency management skills and knowledge, and pre-test and post-test evaluations were conducted. Data analysis was performed using SPSS, and the study was conducted on a voluntary basis with necessary approvals obtained. The findings have the potential to enhance disaster management protocols and improve the preparedness of nursing professionals in Saudi Arabia. The posttest analysis revealed that a significant portion of participants achieved excellent, very good, and good levels of performance, indicating the effectiveness of the training program. In contrast, the pretest grades showed a higher percentage of participants receiving fail level grades, high-lighting the need for improvement prior to the training intervention. This study high-lights the importance of comprehensive training and education in disaster nursing for improving emergency response and patient outcomes

A finite element model of 100m X-BOW polar exploration cruise is established. The entire ship frequency response analysis was carried out, comparing the simulated values with the test values, the maximum error is 22%, but only 0.24mm/s difference, the error can be ignored from the perspective of comfort, therefore, the simulation results meet the requirements of engineering accuracy and verify the effectiveness of the model. According to the solution method for global modal equivalent mass, combing the spatial distribution principle of local modal mass, the method for solving the equivalent mass of a single local mode in mixed mode is proposed, the equivalent mass of the local vibration region of 100m X-BOW polar exploration cruise ship is solved by this method, tuned mass dampers mass ratio parameters are calculated using the equivalent mass. According to the analysis, tuned mass dampers has 31dB vibration absorption effect at 13.4Hz when the mass ratio is 0.05, it also has certain control effect at 10Hz and 18.8Hz, the control effect is 3dB and 2dB respectively, the overall control frequency band is flat and robust.

The ‘inverse problem’ of mass spectrometric molecular identification (‘given a mass spectrum, calculate/predict the 2D structure of the molecule whence it came’) is largely unsolved, and is especially acute in metabolomics where many small molecules remain unidentified. This is largely because the number of experimentally available electrospray mass spectra of small molecules is quite limited. However, the forward problem (‘calculate a small molecule’s likely fragmentation and hence at least some of its mass spectrum from its structure alone’) is much more tractable, because the strengths of different chemical bonds are roughly known. This kind of molecular identification problem may be cast as a language translation problem in which the source language is a list of high-resolution mass spectral peaks and the ‘translation’ a representation (for instance in SMILES) of the molecule. It is thus suitable for attack using the deep neural networks known as transformers. We here present MassGenie, a method that uses a transformer-based deep neural network, trained on ~6 million chemical structures with augmented SMILES encoding and their paired molecular fragments as generated in silico, explicitly including the protonated molecular ion. This architecture (containing some 400 million elements) is used to predict the structure of a molecule from the various fragments that may be expected to be observed when some of its bonds are broken. Despite being given essentially no detailed nor explicit rules about molecular fragmentation methods, isotope patterns, rearrangements, neutral losses, and the like, MassGenie learns the effective properties of the mass spectral fragment and valency space, and can generate candidate molecular structures that are very close or identical to those of the ‘true’ molecules. We also use VAE-Sim, a previously published variational autoencoder, to generate candidate molecules that are ‘similar’ to the top hit. In addition to using the ‘top hits’ directly, we can produce a rank order of these by ‘round-tripping’ candidate molecules and comparing them with the true molecules, where known. As a proof of principle, we confine ourselves to positive electrospray mass spectra from molecules with a molecular mass of 500Da or lower, including those in the last CASMI challenge (for which the results are known), getting 49/93 (53%) precisely correct. The transformer method, applied here for the first time to mass spectral interpretation, works extremely effectively both for mass spectra generated in silico and on experimentally obtained mass spectra from pure compounds. It seems to act as a Las Vegas algorithm, in that it either gives the correct answer or simply states that it cannot find one. The ability to create and to ‘learn’ millions of fragmentation patterns in silico, and therefrom generate candidate structures (that do not have to be in existing libraries) directly, thus opens up entirely the field of de novo small molecule structure prediction from experimental mass spectra.

The characteristics of the eddy mass transport are estimated depending on the values of the parameters of a large-scale flow that forms under the conditions of the shelf seas in the Arctic. For this, the results of numerical simulation of the Kara Sea with a horizontal resolution permitting the development of mesoscale eddies are used. The parameters resulting from numerical experiment are considered as a statistical sample and are analyzed using methods of sensitivity study and clustering of sample elements. Functional dependencies are obtained that are closest to the simulated distributions of quantities. These expressions make it possible, within the framework of large-scale models, to evaluate the characteristics of the cross-isobatic eddy mass transport in the diffusion approximation with a counter-gradient flux. Numerical experiments using the SibCIOM model showed that areas along the Fram branch of the Atlantic waters trajectory in the Arctic as well as the shelf of the East Siberian and Laptev seas with adjacent deep water areas are most sensitive to proposed parameterization of eddy exchanges. Accounting for counter-gradient eddy fluxes turned out to be less important.

Solid spent nuclear fuel from nuclear power plants has 3.4% fission products (80-160amu), contributing to over 99.8% radioactivity. On the other hand, liquid high-level radioactive waste (HLRW) from spent fuel reprocessing has 98.9% bulk elements (0-60amu) with 0.1% radioactivity. A separation mechanism on the mass categories as groups presents unique opportunities in managing HLRW for the long term with a considerable cost reduction. This paper proposes a thermal plasma-based separation system incorporating atmospheric pressure plasma torches for HLRW mass separation into low-resolution mass groups. Several engineering issues, such as waste preparation, waste injection into the plasma and waste collecting after mass separation, need to be addressed. Using COMSOL Multiphysics simulation, the generic system can be studied using noble gas mass separation and further analyze the mass filter capabilities. This paper provides the history of plasma-based mass separation. Functional modelling of a thermal plasma mass separation system is proposed under atmospheric pressure. Finally, aspects of mass separation simulation using noble gas Argon and Helium inside the plasma mass separation system were studied in COMSOL Multiphysics.

A spinning gyroscope precesses about the vertical due to a torque acting upon the wheel. The torque is generated by the shift of moment of force by gravity and it points to the vertical instead of the tangential direction of precession. This intuition offers an alternative and straightforward view of precession dynamics in comparison with the literature. It also presumes a dynamic balance of momentum between circular motions of the wheel spin and precession. Accordingly, the gyroscopic dynamics is then applied to the study of galactic motion of the solar system in space and the Galactic mass is calculated with the inclusion of gyroscopic effect of the solar planets. Results indicate that the gyroscopic effect of Mercury orbiting around the Sun can increase the calculated Galactic mass by 23% in comparison with the result obtained by the classic approach.

The experiments of Project 8 have been excellent, but the expected goals still difficult to achieve. So much so that some of the results at your fingertips were also missing. In view of this, the focus of this article is to clarify several easy confused concepts. Only in this way, we can reasonably explain the experimental data. The main points are as follows: 1. The value c of the light speed in vacuum and a particle with zero static mass, both of which do not exist in the reality. That is to say, the so-called a photon's static mass is equal to zero but has energy, which is a paradox that confuses two different definitional domains. 2. In the reality, photons are high-speed particles generated by electromagnetic radiation. They must have the characteristics of (static) mass, energy and wave, in order to describe the main body to aim at photons from different angles. 3. After any main body comes into being electromagnetic radiation, its static mass will inevitably decrease accordingly. 4. The charge-mass ratio of an electron is a physical constant, which is the ratio of its charge to the amount of matter, and is not affected by relativistic effects and electromagnetic radiation. 5. The uncertainty of moving electrons is caused by random electromagnetic radiations. Finally, it is pointed out that if the cyclotron frequency of a single electron is measured, and at the same time, its de Broglie wavelength or frequency can also be measured, then its static mass can be obtained. Even so, the expected goals are still difficult to achieve, because random electromagnetic radiations are always taking away continually the matter composition of the single electron being measured. However, this was precisely a result of the research obtained by Project 8, and had universality, which should be reflect on.

Five fundamental problems—neutrino mass, baryogenesis, dark matter, inflation, strong CP problem—are solved at one stroke in a model, dubbed as “SM-A-S-H” (Standard Model-Axion-Seesaw-Higgs portal inflation) by Andreas Ringwald et. al. The Standard Model (SM) particle content is extended by three right-handed SM-singlet neutrinos $N_i$, a vector-like color triplet quark $Q$, a complex SM-singlet scalar field $\sigma$ that stabilises the Higgs potential, all of them being charged under Peccei-Quinn (PQ) $U(1)$ symmetry, the vacuum expectation value $v_\sigma\sim10^{11}$ GeV breaks the lepton number and the Peccei-Quinn symmetry simultaneously. We found that numerically SMASH model not only solves five fundamental problems but also the sixth problem “Vacuum Metastability” through the extended scalar sector and can predict approximately correct atmospheric neutrino mass splitting around 0.05 eV and the solar neutrino mass splitting around 0.009 eV.

Gas electron multipliers (GEMs) with wire (WGEMs) or metal electrodes (MGEMs), which don’t use any plastic insulators between electrodes are created. The chambers containing MGEMs (WGEMs) with pin-anodes are proposed as detectors for searching of spin-dependent interactions between Dark Matter (DM) particles and gases with nonzero-spin nuclei (H2, D2, 3He, 21Ne, CF4, CH4, etc.). In this paper, we present a review of such chambers. For investigation of the gas mixtures Ne+10%H2, H2 (D2) +3ppmTMAE, the chamber containing WGEM with pin-anode detection system was constructed. In this paper we present the results of an experimental study of these gaseous mixtures exited by an α - source. Mixture of Ar + 40 ppm C2H4 and mixture 50% Xe + 50%CF4 have been investigated. The spatial distributions of photoelectron clouds produced by primary scintillations on α- and β-particle tracks, as well as the distributions of photoelectron clouds due to photons from avalanches at the pin-anode, have been measured for the first time. In our experiments as another filling of the chambers for search of low-mas WIMP (<10 GeV/c2), solar neutrino and solar axions with spin-dependent interaction we propose to use the mixtures: D2 + 3ppmTMAE, 3He + 3%CH4, 21Ne + 10%H2, at pressure 10-17 bar. And in our experiment with liquid gases is used the mixtures with 19F (LAr + CF4, LXe + CF4) and mixture LCH4 + 40ppm TMAE. The time projection chamber (TPC) with the mixture D2 + 3ppmTMAE filling allow to search of spin-dependent interactions of solar axions and deuterium. As well as we present the detecting systems for search of narrow pp-resonances (quarks) in accelerators experiments.

Lung transplantation offers patients with end stage lung disease an opportunity for a better quality of life, but with limited organ availability it is paramount that selected patients have the best opportunity for successful outcomes. Nutrition plays a central role in post-surgical outcomes and historically, body mass index (BMI) has been used as the de facto method of assessing a lung transplant candidate’s nutritional status. Here we review the historical origins of BMI in lung transplantation, summarize the current BMI literature, and review studies of alternative/complementary body composition assessment tools, including lean psoas area, creatinine-height index, leptin, and dual x-ray absorptometry. These body composition measures quantify lean body mass versus fat mass and may provide a more comprehensive analysis of a patient’s nutritional state than BMI alone.

It is discovered that the gravitational field on the surface of a neutron star is with a relativistic mass density of 2.65*10¹⁶~5.87*10¹⁸kgm^-3 which can be larger than the mass density of the neutron star (~10¹⁷kgm^-3). And, the total relativistic mass of the gravitational field of the Sun is ~10⁷ times the mass of the Sun. For different stars, the relativistic mass of the gravitational field is larger as the mass density of the star is larger. In the Milky Way, the total relativistic mass of the gravitational fields is much larger than the total mass of the stars, planets and gas. And, the relativistic mass density of the observed strongest magnetic field is 2.17*10⁸kgm^-3. This discovery should be a new frame to understand the fundamental problem of physics.

The Greenland ice sheet is a major contributor to sea level rise, adding an estimated 0.47 +/− 0.23 mm/yr to global mean sea level between 1991 and 2015 (van den Broeke et al., 2016). Making sea level rise projections for the future and understanding the processes controlling current observed rates of sea level rise are crucially dependent on understanding the present-day state of the ice sheet. Here, we provide an overview of the current state of the mass budget of Greenland based on satellite gravimetry and remote sensing observations of surface elevation change, ice sheet velocity and calving front positions. We also combine these essential climate variables with a regional climate model (RCM) output from an ice sheet model (ISM) to gain insight into poorly understood ice sheet dynamical and surface mass processes. On average from 1992 to 2017 the ice sheet in some locations has lost up −2.65 m/yr in elevation based on ESA Radar altimetry analysis. Calving fronts have retreated all around Greenland since the 1990s and in only two out of 28 study locations have they remained stable. The locations of grounding lines at 5 key glaciers with floating ice tongues have remained stable over the observation period. However a detailed case study at Petermann glacier with an ice fracture model shows the sensitivity of these floating ice shelves to future climate change. GRACE gravimetric mass balance (GMB) data allows us to tie together disparate lines of evidence showing that Greenland has lost about 265 +/− 25 Gt/yr of ice over the period 2002 to 2015. RCM and ISM simulations show that surface mass processes dominate the overall Greenland ice sheet mass budget except for areas of fast ice sheet flow but marked differences between models and between models and observations indicate that not all processes are captured accurately, indicating areas of greater uncertainty and directions of future research for future sea level rise projections.

Abstract The value of the mass of the particles is one more mystery that current theories cannot predict, so they have to be determined experimentally. In this paper we will see how the quantization of 4D space gives rise to the quantization of mass and, in turn, the quantization of mass implies that space-time is discrete.

The use of the Google Scholar produces about 278 hits on the term ‘‘inertial propulsion.’’ If patents are also included, the number of hits increases to 536. This paper discusses, in a critical way, some characteristic aspects of this controversial topic. The review starts with the halteres of athletes in the Olympic games of ancient times and then continues with some typical devices which were developed or/and patented from the second fourth of the twentieth century till today.

We constrain two dynamical dark energy models that are parametrized by the logarithm form of $w(z)=w_{0}+w_{1}\left(\frac{\ln (2+z)}{1+z}-\ln 2\right)$ and the oscillating form of $w(z)=w_{0}+w_{1}\left(\frac{\sin(1+z)}{1+z}-\sin(1)\right)$. Comparing with the Chevallier-Polarski-Linder (CPL) model, the two parametrizations for dark energy can explore the whole evolution history of the universe properly. Using the current mainstream observational data including the cosmic microwave background data and the baryon acoustic oscillation data as well as the type Ia supernovae data, we perform the $\chi^2$ statistic analysis to global fit these models, finding that the logarithm parametrization and the oscillating parametrization are almost as well as the CPL scenario in fitting these data. We make a comparison for the impacts of the dynamical dark energy on the cosmological constraints on the total mass of active neutrinos. We find that the dark energy properties could significantly change the fitting results of neutrino mass. Looser constraints on $\sum m_{\nu}$ are obtained in the logarithm and oscillating models than those derived in the CPL model. Consideration of the possible mass ordering of neutrinos reveals that the most stringent constraint on $\sum m_{\nu}$ appears in the degenerate hierarchy case.

Recent experimental research has shown that mass is linked to Compton periodicity. We suggest a new way to look at mass: Namely that mass at its most fundamental level can simply be seen as reduced Compton frequency over the Planck time. In this way, surprisingly, neither the Planck constant nor Newton's gravitational constant are needed to observe the Planck length, nor in any type of calculation or gravitational predictions. The Planck constant is only needed when we want to convert back to the more traditional and we would say arbitrary mass measures such as kg. The theory gives the same predictions as Einstein's special relativity theory, with one very important exception: anything with mass must have a maximum velocity that is a function of the Planck length and the reduced Compton wavelength. For all observed subatomic particles, such as the electron, this velocity is considerably above what is achieved in particle accelerators, but always below the speed of light. This removes a series of infinity challenges in physics. The theory also offers a way to look at a new type of quantum probabilities. As we will show, a long series of equations become simplied in this way. Further Newton's gravitational constant G is clearly not needed for gravity calculations or predictions; it is the Planck length and the speed of light (gravity) that are essential for gravity, and both can be measured easily with no knowledge of G.

Data independent acquisition - mass spectrometry (DIA-MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA-MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on Arabidopsis sample with spike-in of known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400-1200 m/z. When combining several DIA-MS analyses with narrow precursor ranges (i.e., 400-650, 650-900 and 900-1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 59.4% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the 6-protein mix spike-in. In cDIA only 5 out of the 6-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.

In this paper, we consider the formation of quantum black holes (QBHs) through a genuine quantum process. We treat particles at the Planck energy as QBHs. The Hawking temperature and entropy of QBHs are estimated. We also show that a QBH has a discrete energy spectrum. By analogy with supersymmetric theory, the mass of the superpartner of a QBH is estimated.

Neck lymphangiomas are rare, benign congenital malformations that predominate in childhood. Most present before the age of two. There are no risk factors related to sex, ethnic origin or predominance on either side, and they can occur in any anatomical location, although the most frequent is in the head and neck. The clinical presentation depends on its location. The most frequent symptom is the existence of a painless mass that grows slowly. Available therapeutic tools include surgery, systemic treatment, and injection of sclerosing agents.

This study investigates the potential of a hybrid nanofluid composed of MoS2 and ZnO nanoparticles dispersed in engine oil, aiming to enhance the properties of lubricant's chemical reaction with the Soret effect on stretching sheet under the influence of applied magnetic field. With the growing demand for efficient lubrication systems in various industrial applications, including automotive engines, the development of novel nanofluid-based lubricants presents a promising avenue for improving engine performance and longevity. However, the synergistic effects of hybrid nanoparticles in engine oil remain relatively unexplored. This research addresses this gap by examining the thermal conductivity, viscosity, and wear resistance of the hybrid nanofluid, shedding light on its potential as an advanced lubrication solution. By analyzing the dispersion stability and interaction mechanisms between nanoparticles and base oil, valuable insights are gained into the fundamental aspects governing the entertainment of hybrid nano lubricants. Overall, the objectives of studying hybrid nano lubricant MoS2+ZnO with engine oil aim to advance the development of more efficient and durable lubrication solutions for automotive engines, contributing to improved reliability, fuel efficiency, and environmental sustainability. Governing non-linear partial differential equations are simplified as ordinary differential equations by utilizing similarity variables. MATLAB Bvp4c technique is used to solve the obtained linear ODE equations. The outputs are presented through graphs and tables for various state variables. The comparative survey in all the graphs is presented for the nanofluid (MoS2/Engine oil) with the hybrid nanofluid (MoS2+ZnO/Engine oil). These graphs show the effect of various parameters M, Q, β, Pr, Ec, Sc, Sr, Kp, Kr and (hybrid nano lubricant parameter). The velocity profile diminished against the values of M, Kp, and β. Temperature profile rising with Ec and Q. reciprocally goes down to Pr. The concentration profile incremented with the value of Sr and decremented with the value of Sc, and Kr. With the increasing value of both f′ (η) and θ(η) increases. But in θ(η) hybrid nanofluid slows down with the higher value of .

The growing adoption of electric propulsion systems in Maritime Autonomous Surface Ships (MASS) necessitates advancements in shipboard electronics for safe, efficient, and reliable operation. These advancements are crucial for tasks like real-time sensor data processing, control algorithms for autonomous navigation, and robust decision-making capabilities. This study investigates research trends in MASS using bibliographic analysis to inform policy and future research directions in this evolving field. We analyze 3,363 MASS-related articles from the Web of Science database, employing co-occurrence word analysis and latent Dirichlet allocation (LDA) topic modeling. Findings reveal a rapidly growing field dominated by image recognition research. Keywords like "datum," "image," and "detection" suggest a focus on collecting and analyzing marine data, particularly with deep learning for synthetic aperture radar imagery. LDA confirms this, with "Image analysis and classification research" as the leading topic. The study also identifies national and organizational leaders in MASS research. However, research on Arctic routes lags behind other areas. This work provides valuable insights for policymakers and researchers, promoting a deeper understanding of MASS and informing future policy and research agendas for the integration of electric propulsion systems in the maritime industry.

During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used thirty-five monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied onto the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 45 minutes and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 °C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0 (https://gets.shinyapps.io/ABID/). This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.

In this paper, we consider particles together with the surrounding space as an indivisible system, and then investigate the maximum symmetry of the system at the quantum level. We introduce a new quantity to describe the evolution of this system before and after measurement. The effective mass of gravity is estimated. We also show that a free quantum particle as the source of energy and momentum do not produce gravity.

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

We analyze the expected arrival time spectrum of supernova neutrinos using simulated luminosity and computing the expected number of events in future detectors such as the DUNE Far Detector and Hyper-Kamiokande. We develop a general method using minimum square statistics that can compute the sensitivity to any variable affecting neutrino time of flight. We apply this method in two different situations: First, we compare the time spectrum changes due to different neutrino mass values to put limits in electron (anti)neutrino effective mass. Second, we constrain Lorentz Invariance Violation through the mass scale, MQG, at which it would occur. We consider two main neutrino detection techniques: 1. DUNE-like liquid argon TPC, for which the main detection channel is νe+40Ar→e−+40K*, related to the supernova neutronization burst, and 2. HyperK-like water Cherenkov detector, for which ν¯e+p→e++n is the main detection channel. We consider a fixed supernova distance of 10 kpc and two different masses of the progenitor star: (i) 15 M⊙ with neutrino emission time up to 0.3 s and (ii) 11.2 M⊙ with neutrino emission time up to 10 s. The best mass limits at 3σ are of O(1) eV. For νe, the best limit comes from a DUNE-like detector if the mass ordering happens to be inverted. For ν¯e, the best limit comes from a HyperK-like detector. The best limit for the Lorentz Invariance Violation mass scale at 3σ level, considering superluminal or subluminal effect, is MQG≳1013 GeV (MQG≳5×105 GeV) for linear (quadratic) energy dependence.

Starting from the SU(2) group of weak interactions in the presence of Electric Charge Swap (ECS) symmetry, we show that ordinary and non-regular (ECS) leptons are related by the ECS rotational group SO(3). We find that many Standard Model (SM) algebras depend on the sin of the angle θs of the ECS rotational group SO (3). We call these ECSM algebras. Furthermore, the break of the gauge symmetry of the SM groupoid gives the massive ECS particle. We find that the ECS particle masses are related with the SM particle masses by sinθs . We also investigate the finite subgroups of the ECS Möbius transformations. We find that sinθs could be derived from the ECS dihedral group DF, which refers to the symmetry of the fermionic polygon (F-gon). The average value of the anchor of the SM algebroid depends on the fermionic Catalan numbers (CF). Finally, we find that the ECS physics at loop level differs the SM physics. The ECSM mass is suppressed by the CF numbers. For 24 fermions, the calculated one-loop radiative correction to the bare Higgs mass µ is 125GeV—a value very close to the experimental one.

We have used Mass Multivariate Method on structural, resting state and task related fMRI data from two groups of patients with schizophrenia and depression, respectively, in order to define several regions of significant relevance to the differential diagnosis between those conditions. The regions included the left Planum polare, Left opercular part of the inferior frontal gyrus (OpIFG), Medial orbital gyrus (MOrG), Posterior Insula (PIns), and Parahippocampal gyrus (PHG). This study delivers evidence that multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnosis. Either structural, or resting state or task related functional MRI modality cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity to combine clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.

New ligand platforms of the type p- or m-Ph{-CR(3,6-tBu2Flu)(Cp)}2 (para-, R = Me (2a), H (2b); meta-, R = Me (2c)) were synthesized via nucleophilic addition of the 3,6-tBu2-fluorenyl-anion onto the parent phenylene-bridged difulvenes (1a‒c). The corresponding discrete homodinuclear zirconium and hafnium bis(dichloro ansa-metallocene) complexes, Ph[{-CR(3,6-tBu2Flu)(Cp)}MCl2]2 (p-, R = Me (3a-Zr2, 3a-Hf2), R = H (3b-Zr2); m-, R = Me (3c-Zr2) were prepared by salt metathesis reactions. An attempt to generate in situ a heterodinuclear complex 3a-Zr-Hf was also undertaken. For the first time, Atmospheric Pressure PhotoIonization (APPI) mass-spectrometric data were obtained for all dinuclear compounds and found to be in excellent agreement with the simulated ones. Preliminary studies on the catalytic performances of these dinuclear complexes, upon activation with MAO, in ethylene homopolymerization and ethylene/1-hexene copolymerization revealed a few differences as compared to those of the monometallic analogues. In particular, slightly lower molecular weights and greater formation of short methyl and ethyl branches were obtained with the dinuclear systems.

The Jiangmen Underground Neutrino Observatory (JUNO) is a 20 kton liquid scintillator multi-purpose underground detector, under construction near the chinese city of Jiangmen, with data taking expected to start in 2021. The main goal of the experiment is the neutrino mass hierarchy determination, with more than three sigma significance, and the high precision neutrino oscillation parameters measurements, detecting electron anti-neutrinos, emitted from two near-by (baseline of about 53 km) nuclear power plants. Besides, the unprecedented liquid scintillator type detector performance in target mass, energy resolution, energy calibration precision and low-energy threshold, features a rich physics program for the detection of low-energy astrophysical neutrinos, such as galactic core-collapse supernova neutrinos, solar neutrinos and geo-neutrinos.