Acute leukemias constitute some of the most common malignant disorders. Despite significant progress made in the treatment of these disorders, their etiology remains unknown. A large and diverse group of genetic and environmental variables have been proposed. The role of a variety of factors, including pre-existing and acquired genetic mutations, exposure to radiation and various chemicals during pre-conception, pregnancy and throughout life have been explored. The effects of inherited genetic variations and disorders, pre-existing diseases, infectious agents, hobbies, occupations, prior treatments and a host of other factors have been proposed, but none is universally applicable to all cases. Variation in the incidence and prognosis based on the age, sex, race, type of the disease, geographic area of residence and other factors are intriguing, but remains unexplained. Advances in genomic profiling, including genome‐wide gene expression, DNA copy number, and single nucleotide polymorphism [SNP] genotype may shed some light on the role of genetics in these disparities. Separate two-hit hypothesis for the development of acute myeloblastic and lymphoblastic leukemia have been proposed. The latter combines genetics and infection factors resulting in leukemogenesis. A number of pre- and post-natal environmental conditions and exposure to infections, including a mycovirus infected Aspergillus flavus, have been suggested. The exact nature, timing, sequence of the events and mechanisms resulting in occurrence of leukemia requires further investigations. This review summarizes some of the above factors and the direction for future research on the etiology of acute leukemias.

Liquid biopsy, based on the circulating tumor cells (CTCs) and cell-free nucleic acids has potential applications at multiple points throughout the natural course of cancer, from diagnosis to follow-up. The advantages of doing ctDNA assessment vs. tissue-based genomic profile are the minimal procedural risk, the possibility to serial testing in order to monitor disease-relapse and response to therapy over time and to reduce hospitalization costs during the entire process. However some critical issues related to ctDNA assays should be taken in consideration. The sensitivity of ctDNA assays depends on the assessment technique and genetic platforms used, on tumor-organ, stage, tumor heterogeneity, tumor clonality. The specificity is usually very high, whereas the concordance with tumor-based biopsy is generally low. In patients with renal cell carcinoma (RCC) qualitative analyses of ctDNA have been performed with interesting results regarding selective pressure from therapy, therapeutic resistance, exceptional treatment response to everolimus and mutations associated with aggressive behavior. Quantitative analyses showed variations of cfDNA levels at different tumor stage. Compared to CTC assay, ctDNA is more stable than cells and easier to isolate. Splice variants, information at single-cell level and functional assays along with proteomics, transcriptomics and metabolomics studies can be performed only in CTCs.

The article shows materials to the question about algebraic features of the genetic code and about the dictatorial influence of the DNA and RNA molecules on the whole organism. Presented results testify in favor that the genetic code is an algebraic code related with a wide class of algebraic codes, which are a basis of noise-immune coding of information in communication technologies. Structural features of the genetic systems are associated with hypercomplex double (or hyperbolic) numbers and with bisymmetric doubly stochastic matrices. The received results confirm that represented matrix approaches are effective for modeling genetic phenomena and revealing the interconnections of structures of biological bodies at various levels of their organization. This allows one to think that living organisms are algebraically encoded entities where structures of genetic molecules have the dictatorial influence on inherited structures of the whole organism. New described algebraic approaches and results are discussed.

Crimean Congo hemorrhagic fever virus (CCHFV) is the causative agent of a globally-spread tick-borne zoonotic infection with an eminent risk of fatal human disease. Imminent public health threat posed by disseminated virus activity and lack of an approved therapeutic make CCHFV an urgent target for vaccine development. We described the construction of a DNA vector expressing nucleocapsid protein (N) of CCHFV (pV-N13) and investigated its potential to stimulate cytokine and total/specific antibody responses in BALB/c and challenge experiment in IFNAR-/- mice. Due to lack of sufficient antibody stimulation towards N protein, we have selected CD24 protein as a potential adjuvant which has proliferative effect on B and T cells. Overall, our N expressing construct when administered solely or in combination with pCD24 vector elicited significant cellular and humoral responses in BALB/c, despite variations in particular cytokines and total antibodies. However, the stimulated antibodies produced due to expression of N protein have shown no neutralizing ability in VNA. Furthermore, challenge experiments were revealed protection potential of N expressing construct in IFNAR -/- mice model. In conclusion, we have shown that CD24 has prominent effect as a genetic adjuvant when co-delivers with a synergic foreign gene expressing vector. Besides, targeting of S segment of CCHFV can be considered as a practical way in developing vaccine against this virus due to its ability to induce immune response which leads to protection in challenge assays in IFN-gamma defective mice models.

Dendritic cells (DCs) are the professional antigen-presenting cells that recognize and present antigens to naïve T cells to induce antigen-specific adaptive immunity. Among the T-cell subsets, T helper type 2 (Th2) cells produce the humoral immune responses required for protection against helminthic disease by activating B cells. DCs induce a Th2 immune response at a certain immune environment. Basophil, eosinophil, mast cells, and type 2 innate lymphoid cells also induce Th2 immunity. However, in the case of DCs, controversy remains regarding which subsets of DCs induce Th2 immunity, which genes in DCs are directly or indirectly involved in inducing Th2 immunity, and the detailed mechanisms underlying induction, regulation, or maintenance of the DC-mediated Th2 immunity against allergic environments and parasite infection. A recent study has shown that a genetic defect in DCs causes an enhanced Th2 immunity leading to a severe atopic dermatitis. We summarize the Th2 immune-inducing DC subsets, the genetic and environmental factors which involved in DC-mediated Th2 immunity, and current therapeutic approaches for Th2-mediated immune disorders. This review is to provide an improved understanding of DC-mediated Th2 immunity and Th1/Th2 immune balancing, leading to control over their adverse consequences.

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to detect novel threats since it has a strong generalization ability. The deep neural network’s architecture has a significant impact on the model’s results. We propose a genetic algorithm based model to find the optimal number of hidden layers and the number of neurons in each layer of the deep neural network (DNN) architecture for the network intrusion detection binary classification problem. Experimental results demonstrate that the proposed DNN architecture shows better performance than classical machine learning algorithms at a lower computational cost.

There are many theories of carcinogenesis arguing against the orthodox mutation theory, debating on such as “epigenetic alteration” that is inheritable and yet, theoretically, reversible. Our integrated theory describes that any extracellular, intracellular, or intranuclear stressors, mutagenic or not, can initiate a lengthy tumorigenesis to engender a benign or malignant tumor, but the aberrations directly establishing cellular immortality and autonomy may be epigenetic or genetic alterations in the genomic DNA. A neoplasm is considered a semi-new organism with autonomy; it therefore should have genetic mutations to be “new”. We may be able to direct cancer cells towards differentiation as a remedy, because the extracellular milieu may control the phenotype of a cell and the tissue or organ made of the cell’s progenies, and the cytoplasm of a cell may override the nucleus in the phenotypic control. However, the nucleus retains the capacity to manifest itself if allowed by the microenvironment, which then allows the already reversed cells to revert back to tumor cells again. Neoplasms are malignant if they bear epigenetic or genetic anomalies in mutator genes defined as those whose alterations allow or accelerate alterations to occur in other genes, whereas neoplasms are benign if they bear epigenetic or genetic aberrations only in non-mutator genes. It is imperative to identify the immediate tumor-causing cellular alterations defined as those directly responsible for immortality and autonomy, and for treatment purposes to identify the extracellular and intracellular factors that control the phenotype of cancer cells.

This paper presents an alternative constraint handling approach within a specialized genetic algorithm (SGA) for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a nonlinear single-objective optimization problem aiming to minimize power losses while keeping network constraints. The proposed constraint handling approach is based on a product of sub-functions that represents permissible limits on system variables and that includes a specific goal on power loss reduction. The main advantage of this approach is the fact that it allows a straightforward verification of both feasibility and optimality. The SGA is examined and tested with the proposed constraint handling approach and the traditional penalization of deviations from feasible solutions. Several tests are run in the IEEE 30, 57, 118 and 300 bus test power systems. The results obtained with the proposed approach are compared to those offered by other metaheuristic techniques reported in the specialized literature. Simulation results indicate that the proposed genetic algorithm with the alternative constraint handling approach yields superior solutions when compared to other recently reported techniques.

Abstract: A large number of collecting expeditions were launched in regions of ‘centers of diversity’ and hundreds of thousands of sample have been collected and stored in gene banks as ‘genetic resources’. So far, only a small number of the samples have been evaluated for their biotic and abiotic stress tolerance. Now, their time to become useful has come. A new global phenomenon has arisen – climate change. The crop genetic resources and their wild progenitors that have survived countless years of changing environment during the last 11,000 years could harbor genes that may be useful under the new growing conditions and environmental factors thrown up by climate change and global warming. With the deployment of modern bio-engineering techniques selected genes or gene fragments can be transferred from genetic resources to modern varieties of crop plants to make them well-prepared to mitigate the effects of global warming and climate change. The latter is the most serious issue facing plant breeders today. New pests and diseases could affect crop production. These review paper discusses various impacts and issues as a result of this phenomenon and suggest ways to safeguard our most important crops through better management of crop plant genetic resources in the near future.

This research aimed to figure out the applications of HbA1c protein and HbA1 gene as the prognostic biomarkers for assessing the risks of different cancers among male T2D patients in Bangladesh considering their serological and oncoinformatic parameters. Depending on the concentrations of HbA1c (%) of the T2D patients (n=300), their individual FBS (mmol/L); THABF (mmol/L); creatinine (mg/dl); SC (mg/dl); STGs (mg/dl); HDLC (mg/dl); and LDLC (mg/dl) were estimated. The values of the patients were compared with the control (n=60) group as the serological analysis. Besides, HbA1 gene (encoding hBA1c protein) overexpression and promotor methylation responsible for BLCA, BRCA, CHOL, COAD, LUAD, LUSC, PAAD, and PRAD cancers in the male T2D patients were profiled as the oncoinformatic parameters based on the sample types; caner stages; racial footprints; gender; age; nodal metastasis; p53 methylations; pancreatitis; diabetes status; smoking behaviors; and overall/disease-free survivability. Finally, the ‘HbA1 gene strings’ responsible for genetic coexpression; endophytic vesicle regulation; antioxidant regulation; oxygen species metabolic regulation; and gene-mediated response to the reactive oxygen molecules were studied comprehensively. A strong correlation between BMI and FBS was observed in both the patients and the control (P<0.0001). Similarly, the values of FBS, THABF, and creatinine resulted in equal significance (P<0.0001) as compared to the HbA1c concentrations of all the T2D and control individuals. The SC, STGs, HDLC, and LDLC concentrations regulated ardently in both the control (P<0.0001), and patients group (P<0.0001), while HbA1c ranged from 3.8-5.8%, and 5.11-15.8% respectively. HbA1 gene is found downregulating with cancer progressed in most of the oncoinformatic parameters. According to the DA, CS, EI, CE, PC, NC, GF, H, and AT profiles; the HbA1 gene interacts with 8 other genes responsible for creating a protein cluster comprising- AHSP, HBA1, HBA2, HBB, HBD, HBE1, HBG2, RPS12, and RPS19 proteins for cancer formation. To recapitulate, HbA1c protein and HbA1 gene can be used as the prognostic serological and molecular biomarkers respectively for determining the risks of cancers among male chronic T2D patients.

In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms, based on the imitation of a flock of birds foraging behavior through learning and grouping the best experience. In previous work, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. In simulation results, with less population size of M = 10, the SPSO can perform quickly convergence to sub-optimal solution in the 100^th generation and obtained sub-optimum performance with more 2 UEs than the Rand method. Genetic algorithm (GA) is one of the evolutionary algorithms, based on Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations, in 200 generations can converge to suboptimal solutions. Therefore, with comparing with the SPSO algorithm the proposed GA and RPSO can improve system capacity performance with 1.8 and 0.4 UEs, respectively.

Background: Colorectal cancer is considered the third most fetal among all type of cancer. Spleen tyrosine kinase (SYK) is a non-receptor type tyrosine-protein that plays crucial role in signaling mediated via immune receptor. We adopted an onco-informatics analysis to evaluate the SYK expression and prognostic value of SYK in colorectal cancer, and identification of potential phytochemicals which may inhibit overexpression of SYK protein as well as minimized colorectal cancer. Materials & Methods: Differential expression of SYK gene was analyzed using the several transcriptomic databases including Oncomine, UALCAN, GENT2 and GEPIA2. The server, cBioPortal was used to analyze mutation and copy number alterations whereas GENT2, GEPIA, OncoLnc and PrognoScan were employed to examine the survival rate. A protein-protein interaction network of SYK and co-expressed genes of SYK was conducted via GeneMANIA. Considering SYK gene encoding protein as drug target, selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. YASARA molecular dynamics simulators were applied for the post validation of the molecular docking data. Results: We have observed significant overexpression of mRNA expression levels of SYK gene colorectal adenocarcinoma (COAD) samples compared with normal tissues. Significant methylation level and various genetic alterations are assembled in SYK gene which can lead to the development of colorectal cancer. As a result, lower level of SYK expression was related to the more chances of patients’ survival by which all the outcomes from the multiple bioinformatics platforms and web resources have demonstrated the significant evidences that the SYK kinsase can possess as a potential biomarker for the treatment of colorectal cancer. Here, aromatic phytochemicals namely, Kaempferol and Glabridin targeting SYK showed more stability compared to controls and may be useful for the treatment of colorectal cancer. Conclusion: Our study showed dysregulated expression of SYK in colorectal cancer and potentiality to act as a biomarker for the prognosis of CRC. Moreover, we have shown phytochemicals (Kaempferol and Glabridin) target SYK as potential treatment strategies and drug repositioning potentiality in colorectal cancer.

The study presents a comparative approach between response surface methodology (RSM) and hybridized, genetic algorithm artificial neural network (GA-ANN) in predicting the water absorption, compressive strength, flexural strength split tensile strength and slump for steel fiber reinforced concrete. The effect of process variables such as aspect ratio, water cement ratio and cement content were investigated using the central composite design of response surface methodology. This same experimental design was used in training the hybrid-training approach of artificial neural network. The predicting ability of both methodologies were compared using the root mean sqaured error (RMSE), mean absolute error (MAE), model predictive error (MPE) and absolute average deviation (AAD). The RSM model was found more accurate in prediction compared to hybrid GA-ANN.

Lightning discharges in electric power networks generate voltage and current surges that are propagated through the electrical network causing damage and shutdowns in the electrical system. To protect the system against these phenomena, surge arresters are very effective and widely used by electrical utilities in their electric grids. This paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), creating a simulation environment in the software ATP (Alternative Transients Program) to implement the proposed methodology. The optimized allocation procedure is based on a fitness function that minimizes the cost of surge arresters and maximizes the number of protected equipment. To carry out this optimized arrester allocation procedure using ATP may demand too much processing time when running large distribution grids. To overcome this difficulty a procedure is proposed to obtain an overvoltage severity description of the grid and select the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The case study is applied to the IEEE 123-bus electrical feeder to demonstrate the effectiveness of the proposed methodology.

Background: Advancements in the next-generation sequencing (NGS) techniques have allowed for efficient genetic variant detection at reduced costs. Methods: We describe an ad hoc NGS-based custom designed resequencing gene panel to identify genetic variants in 8 patients with dementing disorders. Results: We found variants of TREM2 and APP genes in three patients; these have been previously identified as pathogenic or likely pathogenic and, therefore, considered as “Disease Causing”. In the remaining subjects, the pathogenicity was evaluated on the in silico analysis, according to the guidelines of the American College of Medical Genetics. In one patient, the p.R205W variant was causative of the disease, thus considered as “Possibly Disease Causing”. The variants found from the other four subjects in the CSF1R, SERPINI1, GRN, and APP genes revealed discordant in silico results and, therefore, it was not possible to assign a definitive pathogenicity. Conclusions: Notwithstanding the limitations of a customized panel, we detected some rare genetic variants with a probable disease association. The future application of NGS techniques and the further replication of these experimental data will replace the so-called “gene by gene” approach with a “panel of genes” strategy, that offers promising perspectives in the diagnosis and management of neurodegenerative disorders.

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made on complex multicellular organisms, and then modified to fit a DNA-centric view. In this article, I argue that, based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that: i) natural selection plays a dominant role in evolution, and ii) the probability of mutations is independent of the generated phenotype. I will show that the adaptation of a phenotype to an environment does not correspond to organism fitness but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome, and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype, the phenotype ensuring the stability of the genotype in a cellular and environment physicochemical parameter-depending manner.

Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common variants which differ across populations and hence do not fully account for HbF variation. To investigate rare and common variants influencing HbF levels in SCD, we performed targeted next generation sequencing covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. Results revealed a range of functionally relevant genetic variants. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletion in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. This study provides new insights in selecting essential variants associated with extreme HbF levels in SCD.

Managing the multisystemic symptoms of type I Gaucher Disease (GD) requires a multidisciplinary team approach that includes disease-specific treatments, as well as supportive care. This involves a range of medical specialists, general practitioners, supportive care providers, and patients. Phenotype classification and the setting of treatment goals are important for optimizing the management of type I GD, and providing personalized care. The ability to classify disease severity using validated measurement tools allows the standardization of patient monitoring, and the measurement of disease progression and treatment response. Defining treatment goals is useful to provide a benchmark for assessing treatment response, and managing the expectations of patients and their families. Although treatment goals will vary depending on disease severity, they include the stabilization, improvement or reversal (if possible) of clinical manifestations. Enzyme replacement therapy (ERT) is the standard care for patients with type I GD, but a novel substrate reduction therapy (SRT), Eliglustat has demonstrated safety and efficacy in selected patients. To ensure that treatment goals are being achieved, regular, comprehensive follow up is necessary.

Enteroviruses (EVs) are viruses of the family Picornaviridae that cause mild to severe infections in humans and in several animal species, including nonhuman primates (NHPs). We conducted a survey and characterization of enteroviruses circulating between humans and great apes in the Congo. Fecal samples (N=24) of gorillas and chimpanzees living close to or distant from humans in three Congolese parks were collected, as well as from healthy humans (N=38) living around and within these parks. Enterovirus were detected in 29.4% gorilla and 13.15% human feces, including wild and human-habituated gorillas, local humans and eco-guards. Two identical strains were isolated from two humans come from two remote regions. Their genomes were similar and all genes showed their close similarity to Coxsackieviruses except for 3C, 3D and 5’UTR region where they were most similar to poliovirus 1 and 2, suggesting recombination. Recombination events were found between these strains, poliovirus 1 and 2 and EV-C99. The same EV- C species detected in both humans and apes in different regions suggest a clonal distribution of the virus in Congo.

Studies on evolution have made significant progress in multiple disciplines, but evolutionary theories remain scattered, complicated, elusive, and controversial. To address this issue, a novel evolutionary theory is deduced from thermodynamics in this article. As per the formula of Gibbs free energy, carbon-based entities (CBEs) on Earth tend to absorb more energy. This is the evolutionary driving force leading to organic synthesis of higher-hierarchy CBEs (HHCBEs). The organic synthesis raises the amount of HHCBEs and increases the structural complexity and hierarchy of CBEs. Increased structural complexity and hierarchy spontaneously offer complicated functions to HHCBEs. Genetic mutations, epigenetic changes, and uninheritable variations provide diversified HHCBEs for natural selection which is redefined as survival of the fit and elimination of the unfit, leading to increase of diversity and fitness of HHCBEs. Order in biology resulting from permanent natural selection is largely contrary to order in physics. Natural selection acts on the overall fitness involving all traits through the co-action of positive selection and negative selection. Natural selection can establish biological traits in short geological periods. Different combinations of traits can lead to sympatric speciation targeting the same niche. Altruism, collaboration, and obeying rules with balanced freedom are all important throughout the CBE evolution, which harbors three overlapping phases including chemical evolution (abiogenesis), biological evolution, and group evolution. Altogether, this theory termed the CBE evolutionary theory (CBEET) suggests that evolution which favors fitness and diversity is driven hierarchy-wise by energy. It reveals the driving force of evolution and reestablishes the key role of natural selection. It integrates with advances from multiple disciplines and provides simple and rational answers to some evolutionary conundrums. It removes several elusive or erroneous views including the one regarding negative entropy. It bridges natural sciences and social sciences and sheds novel insights into harmonious development of human society.

Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection such as genomic selection (GS) must be integrated to decrease the time it takes to release new varieties to meet the demand of a growing population. The implementation of GS into breeding programs is still being explored, with many studies showing its potential to change wheat breeding through achieving higher genetic gain. In this review, we explore the integration of GS for a wheat breeding program by redesigning the traditional breeding pipeline to implement GS. We propose implementing a two-part breeding strategy by differentiating between population improvement and product development. The implementation of GS in the product development pipeline can be integrated into most stages and can predict within and across breeding cycles. Additionally, we explore optimizing the population improvement strategy through GS recurrent selection schemes to reduce crossing cycle time and significantly increase genetic gain. The recurrent selection schemes can be optimized for parental selection, maintenance of genetic variation, and optimal cross-prediction. Overall, we outline the ability to increase the genetic gain of a breeding program by implementing GS and a two-part breeding strategy.

Pig genetic resources in Africa originate from different regions. Genetic analysis has shown a strong phylogeographic pattern with the pigs on the eastern parts showing a high frequency of alleles from the Far East while the ones on the western parts show a strong European influence. This highlights the influence of trade routes on the genetic legacy of African pigs. They have, however, since adapted to the local environments to produce unique populations with unique attributes. Most of the pigs are now reared in resource-constrained smallholdings under free-range conditions. They are largely owned by women who spread ownership of the resource through kinship networks. Very little work has been done to characterize, conserve and sustainably utilize pig genetic resources in Southern Africa. The risk status of the breeds together with population numbers, distribution and other attributes are largely unknown. This paper proposes several strategies for the sustainable utilization of the pig genetic resources: a market-driven in situ conservation program and two complementary ex situ strategies. In addition, the possibility of community-based breed improvement programs is discussed.

Repeat-Induced Point mutations (RIP) serves as a genome defence mechanism that impedes the deleterious consequences of repeated motifs such as transposable elements in fungi. Genomic regions with RIP are biased for adenosine and thymine transitions and the cumulative influence of RIP is thought to have a considerable impact on genome composition. We investigated the impact of RIP on localized genomic regions and whole-genome sequences for representatives of the pine pathogen, Fusarium circinatum. We set out to determine the intraspecific variation in acquired RIP and the role of RIP in the development of diverse F. circinatum sub-genomic compartments. The results of the study show that the AT-enriched sub-genomic compartment accounts for ca. 97% of the calculated RIP and was further prominent in both core and accessory genomic regions. However, more extensive RIP was observed in the accessory sub-compartment and more variable regions of the genome. Regions with RIP indicated increased intrinsic curvature of the DNA which may influence DNA-protein interactions and may promote constitutive heterochromatin formation. The results show that RIP is an important source of functional novelty and genome variation. RIP contributes to the evolution of the genetic landscape and differentiation of diverse sub-genomic compartments of this important fungal pathogen.

Bus operators around the world are facing the transformation of their fleets from fossil-fuelled to electric buses. Two technologies prevail: Depot charging and opportunity charging at terminal stops. Total cost of ownership (TCO) is an important metric for the decision between the two technologies, however, most TCO studies for electric bus systems rely on generalised route data and simplifying assumptions that may not reflect local conditions. In particular, the need to re-schedule vehicle operations to satisfy electric buses’ range and charging time constraints is commonly disregarded. We present a simulation tool based on discrete-event simulation to determine the vehicle, charging infrastructure, energy and staff demand required to electrify real-world bus networks. These results are then passed to a TCO model. A greedy scheduling algorithm is developed to plan vehicle schedules suitable for electric buses. Scheduling and simulation are coupled with a genetic algorithm to determine cost-optimised charging locations for opportunity charging. A case study is carried out in which we analyse the electrification of a metropolitan bus network consisting of 39 lines with 4748 passenger trips per day. The results generally favour opportunity charging over depot charging in terms of TCO, however, under some circumstances, the technologies are on par. This emphasises the need for detailed analysis of the local bus network in order to make an informed procurement decision.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the most important of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. Through ubiquitination, this heterodimer has significant effects on individual proteins, enabling, among others, the destruction of damaged DNA fragments. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Clustered regularly interspaced short palindromic repeats or CRISPR, one of the major technological tools from nature's toolbox, has revolutionized the scientific world with its potential use in humans and plants. CRISPR Cas9 was first known as an adaptive immune system of bacteria. It is a system that cleaves foreign DNA. It has been exploited to be used as a genome editing tool for correcting genetic diseases in humans, for plants to create stress-resistant plants, and for a variety of different purposes. This review provides a basic overview of its applications in different areas of biological research. It has immense potential for a variety of researches, but it's still a mystery for science. It feels like scientists just know a tip of an iceberg.

Increasing demand for food production with limited available water resources pose the threat to agricultural activities. The conjunctive allocation of water resources maximizes the net benefit of farmers efficiently. In this study, a novel hybrid optimization model was developed based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of water deficit Sathanur reservoir command. The GA-based opti-mization model considered crop-related physical and economical parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reach obtained from BFO is considered as input to ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average produc-tivity values Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, the developed novel hybrid optimization model (GA-BFO-ACO) is very promising to enhance the farmer's net income as well as for the command area water conservation and can be replicated in other irrigated regions of the globe to overcome chronic land and water problems.

In the present work we present a methodology for teaching the basis of the genetic code through music composition, with the aim to combine science and arts learning. The project was carried out by 155 students, the so-called MARGA Consortium, with ages comprised between 10 and 17 years from different public schools located in the Principality of Asturias, Spain. The different groups generated 8 different music works using a short genetic sequence obtained from the human notch1 gene, receptor of mutations leading to chronic lymphocytic leukemia.

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and brain volumes and white matter integrity (FA and MD) with magnetic resonance imaging in the BrainSCALE cohort, consisting of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years of the twins. Genes influenced externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to –0.20); with sizeable genetic correlations (FA ra up to +0.42; MD ra up to –0.33). Cortical gray matter (CGM; rph up to –0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genotypically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence from the same genetic factor.

Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as non-genetic/non-mutational heterogeneity. Such heterogeneity – a ubiquitous nature of biological systems – has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/ noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systems-level approach integrating mathematical modelling and in vitro/in vivo experiments can map the diverse phenotypic repertoire, and identify therapeutic vulnerabilities of an otherwise clonal cell population.

Every protein consists of a linear sequence over an alphabet of $20$ letters/amino acids. The sequence unfolds in the $3$-dimensional space through secondary (local foldings), tertiary (bonds) and quaternary (disjoint multiple) structures. The mere existence of the genetic code for the $20$ letters of the linear chain could be predicted with the (informationally complete) irreducible characters of the finite group $G_n:=\mathbb{Z}_n \rtimes 2O$ (with $n=5$ or $7$ and $2O$ the binary octahedral group) in our previous two papers. It turns out that some quaternary structures of protein complexes display $n$-fold symmetries. We propose an approach of secondary structures based on free group theory. Our results are compared to other approaches of predicting secondary structures of proteins in terms of $\alpha$ helices, $\beta$ sheets and coils, or more refined techniques. It is shown that the secondary structure of proteins shows similarities to the structure of some hyperbolic $3$-manifolds. The hyperbolic $3$-manifold of smallest volume --Gieseking manifold--, some other $3$ manifolds and the oriented hypercartographic group are singled out as tentative models of such secondary structures. For the quaternary structure, there are links to the Kummer surface.

The angiotensin-converting enzyme (ACE) is a peptidase that is involved in the synthesis of Angiotensin II, the bioactive component of the renin-angiotensin system. A growing body of literature argues for a beneficial impact of ACE inhibitors (ACEi) on age-associated metabolic disorders, mediated by cellular changes in reactive oxygen species (ROS) that improve mitochondrial function. Yet, our understanding of the relationship between ACEi therapy and metabolic parameters is limited. Here, we used three genetically diverse strains of Drosophila melanogaster to show that Lisinopril treatment reduces thoracic ROS levels and mitochondrial respiration in young flies, and increases mitochondrial content in middle-aged flies. Using untargeted metabolomics analysis, we also showed that Lisinopril perturbs the thoracic metabolic network structure by affecting metabolic pathways involved in glycogen degradation, glycolysis, and mevalonate metabolism. The Lisinopril-induced effects on mitochondrial and metabolic parameters, however, are genotype-specific and likely reflect the drug’s impact on nutrient-dependent fitness traits. Accordingly, we found that Lisinopril negatively affects survival under nutrient starvation, an effect that can be blunted by genotype and age in a manner that partially mirrors the drug-induced changes in mitochondrial respiration. In conclusion, our results provide novel and important insights into the role of ACEi in cellular metabolism.

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (Ca_Vs). Calcium entering through Ca_Vs is key for multiple neuronal processes. In this review, we will summarize recent findings that link Ca_Vs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of Ca_Vs structure, classification, function, expression and pharmacology. Next, we will summarize tools and databases to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in Ca_V genes when available. We will review pharmacological evidence of the use of Ca_V modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of Ca_Vs.

Rajasthan is a state located in the north-western part of India and it has been cited as a major route of human migration since ancient times. The present study was conducted to find out the genetic affinity of Rajasthani population with the population living in its east and the west. In particular, we compared them with the population of Pakistan which shares the common geographical boundary with the Rajasthan while also having a look at their inter and intra population affinities with the population belonging to other Indian states. We investigated the genetic structure and population parameters of Rajasthani populations obtained for twenty polymorphic autosomal STR loci from 669 unrelated individuals belonging to its three population groups including Mina, Gujjar and the admixed population of Rajasthan. The studied populations showed a wide range of genetic diversity and besides the genetic structure of the studied populations, it was found that the average heterozygosity value was highest among the populations of Rajasthan, possibly, because of gene flow from different directions. Various statistical analyses suggested that the Rajasthani populations had a higher affinity with the North Indian populations rather than with the Pakistani population.

Genetic diversity is inevitable in making any crop improvement program successful. DNA fingerprinting technology to assess the genetic relationship among the selected genotypes for identification and cataloging of different species and cultivars of roses is a promising tool for Rosa genomes. The inter-simple sequence repeats markers (ISSRs) were used to investigate the genetic diversity among twenty-one diverse Rosa genotypes belonging to two different species, Rosa hybrida and R. damascena, and three distinct groups of rose varieties, namely Hybrid Tea, Floribunda, and Damask roses. Twenty-four ISSR primers yielded a total of 280 scorable amplified fragments from 250-1800 bp in length, from which 244 were polymorphic, resulting in an average of 86.4% polymorphism. UPGMA cluster analysis based on Jaccard’s pairwise similarity coefficient values ranged from 0.264 to 0.818, clearly distinguished different species and genotypes, grouping them into three distinct clusters. The results confirmed a high degree of variation in the rose germplasm studied highlighting the potential of improvement in roses for the ornamental and perfume industry.

Due to the fact that to date, the question of the origin of SARS-CoV-2 has not been resolved yet, the author analyzed the main advances in the development of genetic engineering of viruses that took place before the onset of the COVID-19 pandemic. The first artificial genetically modified viruses could appear in nature in the mid-1950s. The technique of nucleic acid hybridization was developed by the end-1960s. In the late 1970s, a method called the "reverse genetics" emerged to synthesize RNA and DNA molecules. In the early 1980-s, it became possible to combine the genes of different viruses and insert the genes of one virus into the genome of another virus. Since that time, the production of vector vaccines began. Currently, by modern technologies one can assemble any virus based on the nucleotide sequence available in the virus database or designed by a computer as a virtual model.Scientists around the world are invited to answer the call of Neil Harrison and Jeffrey Sachs of Columbia University, for a thorough and independent investigation into the origin of SARS-CoV-2. Only a full understanding of the origin of the new virus can minimize the likelihood of a similar pandemic in the future.

Extensive limb lengthening (ELL) was completed in 75 patients: 66 achondroplasia and 9 hypochondroplasia. The average lengthening was 27cm for achondroplasia (12-40cm) and 17cm for hypochondroplasia (range 10-25cm). There were 48 females and 27 males. Lengthening was done either by 2-segment (14 patients; both tibias and/or both femurs) or by serial 4-segment lengthenings (64 patients; both femurs and tibias same time). Most patients also had bilateral humeral lengthening. Lengthenings were either juvenile-onset (31), adolescent-onset (38) or adult-onset (6). The average age at final follow-up was 26 years old (range 17-43 years). There were few permanent sequelae of complications. The most serious was one paraparesis. All patients returned to activities of normal living and only one was made worse by the surgery (paraparesis). This is the first study to show that ELL can lead to increase of height into the normal height range. Previous studies showed mean increases of height of up to 20cm, while this study consistently showed an average increase of 30 cm (range 15-40cm) for juvenile-onset and increase of 26cm (range 15-30cm) for adolescent-onset. This results in lower normal height at skeletal maturity for males and females. The adult-onset had a mean increase of 16.8 (range 12-22cm). This long-term follow-up study shows ELL can be done safely even with large lengthenings and that 4-segment lengthening may offer advantages over 2-segment lengthening. While the majority of cases were performed using external fixation, implantable limb lengthening promises to be an excellent alternative and perhaps an improvement.

Objectives: Multicentric Osteolysis, Nodulosis, and Arthropathy (MONA) syndrome is a rare genetic skeletal dysplasia. Its diagnosis can be deceptively similar to childhood-onset genetic skeletal dysplasias and juvenile idiopathic arthritis. We aimed to report the syndrome’s clinical and radiologic features with emphasis on skeletal manifestations. And establish relevant phenotype-genotype correlations. Methods: We evaluated two boys, 4-and-7-years-old with MONA syndrome. Both patients had consanguineous parents. We verified the diagnosis by correlating the outcomes of clinical, radiologic and molecular analysis. We specifically evaluated the craniofacial morphology and clinical and radiographic skeletal abnormalities. We contextualized the resultant phenotype-genotype correlations to publications on MONA and its differential diagnosis. Results: Skeletal manifestations were the presenting symptoms and mostly restricted to hands and feet in terms of fixed extension deformity of the metacarpophalangeal and flexion deformity of the interphalangeal joints with extension deformity of big toes. There were arthritic symptoms in the older patient especially of the wrists and minute pathologic fractures. The skeletal radiographs showed osteopenia/dysplastic changes of hands and feet. Both patients had variants in the matrix metalloproteinase2 gene which conformed to phenotype of previously reported literature in one patient while the other had a novel variant which conformed to MONA phenotype. Craniofacial abnormalities were present. However, minimal extra-skeletal manifestations. Conclusion: Overall, there is an emerging distinctive skeletal pattern of involvement in terms of both clinical and radiographic features. This includes age of onset and location of presenting skeletal manifestations, chronological order of joint affection, longitudinal disease progression, specifics of skeletal radiographic pathology and craniofacial features. Nevertheless, physicians are cautioned against differential diagnosis of similar genetic skeletal dysplasias and juvenile idiopathic arthritis.

Due to the global warming and dynamic changes in pathogenic virulence, leaf rust caused by Puccinia triticina has greatly expanded its epidermic region and become a severe threat to global wheat production. Genetic bases of wheat resistance to leaf rust mainly relies on the leaf rust resistance (Lr) gene or quantitative trait locus (QLr). Although these genetic loci have been insensitively studied during the last two decades, an updated overview of Lr/QLr in a genome-wide level is urgently needed. This review summarized recent progresses in genetic studies of wheat resistance to leaf rust. Wheat germplasms with great potentials in genetic improvement of resistance to leaf rust were highlighted. Key information about the genetic loci carrying Lr/QLr were summarized. A genome-wide chromosome distribution map for all the Lr/QLr was generated based on the released wheat reference genome. In conclusion, this review has provided valuable sources for both wheat breeders and researchers to understand the genetics of resistance to leaf rust in wheat.

Widely used in hydraulics, the Colebrook equation for flow friction relates implicitly to the input parameters; the Reynolds number, Re and the relative roughness of inner pipe surface, ε/D with the output unknown parameter; the flow friction factor, λ; λ=f(λ, Re, ε/D). In this paper, a few explicit approximations to the Colebrook equation; λ≈f(Re, ε/D), are generated using the ability of artificial intelligence to make inner patterns to connect input and output parameters in explicit way not knowing their nature or the physical law that connects them, but only knowing raw numbers, {Re, ε/D}→{λ}. The fact that the used genetic programming tool does not know the structure of the Colebrook equation which is based on computationally expensive logarithmic law, is used to obtain better structure of the approximations which is less demanding for calculation but also enough accurate. All generated approximations are with low computational cost because they contain a limited number of logarithmic forms used although for normalization of input parameters or for acceleration, but they are also sufficiently accurate. The relative error regarding the friction factor λ, in best case is up to 0.13% with only two logarithmic forms used. As the second logarithm can be accurately approximated by the Padé approximation, practically the same error is obtained also using only one logarithm.

Recently natural gas (NG) global market attracted much attention in case it is cleaner than oil, and simultaneously in most regions is cheaper than renewable energy sources. However, price fluctuations, environmental concerns, technological development, emerging unconventional resources, energy security challenges, and shipment are some of the forces that made the NG market more dynamic and complex. From a policy-making perspective, it is vital to uncover demand-side future trends. This paper proposed an intelligent forecasting model to forecast NG global demand, however investigating a multi-dimensional purified input vector. The model starts with a data mining (DM) step to purify input features, identify the best time lags, and to pre-process selected input vector. Then a hybrid artificial neural network (ANN) which equipped with genetic optimizer is applied to set up ANN’s characteristics. Among 13 available input features, six features (e.g. Alternative and Nuclear Energy, CO2 Emissions, GDP per Capita, Urban Population, Natural Gas Production, Oil Consumption) selected as the most critical feature via the DM step. Then, the hybrid prediction model is designed to extrapolate the consumption of future trends. The proposed model overcomes competitive models refer to different error based evaluation statistics. Besides, as the model proposed the best input feature set, results compared to the model which used the raw input set, with no DM purification process.

The current clinical model for genetic-testing is based on clinical-criteria/family-history(FH) and a pre-defined mutation probability threshold. It requires people to develop cancer before identifying unaffected individuals in the family to target prevention. This process is inefficient, resource intense and misses >50% of individuals/mutation carriers at risk. Population genetic-testing can overcome these limitations. It is technically feasible to test populations on a large scale; genetic-testing costs are falling and the acceptability/awareness is rising. MEDLINE/EMBASE/Pubmed/CINAHL/PsychINFO databases were searched using a free-text and MeSH terms; reference lists of publications retrieved screened; additionally web-based platforms, Google, and clinical-trial registries were searched. Quality of studies were evaluated using appropriate check-lists. A number of studies have evaluated population-based BRCA-testing in the Jewish-population. This has been found to be acceptable, feasible, clinically-effective, safe, associated with high satisfaction rates and extremely cost-effective. Data support change in guidelines to population-based BRCA-testing in the Jewish-population. Population panel-testing for BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 gene mutations is the most cost-effective genetic-testing strategy in general-population women and can prevent thousands more breast/ovarian cancers than current clinical-criteria based approaches. A few ongoing studies are evaluating population-based genetic-testing for multiple cancer susceptibility genes in the general-population but more implementation studies are needed. A future population-testing programme could also target other chronic diseases.

Antisense oligonucleotide (ASO)-mediated exon skipping has become a valuable tool for investigating gene function and developing gene therapy. Machine learning-based computational methods such as eSkip-Finder have been developed to predict the efficacy of ASOs via exon skipping. However, these methods are computationally demanding, and the accuracy of predictions remains suboptimal. In this study, we propose a new approach to reduce computational burden and improve prediction performance by using feature selection within machine learning algorithms and ensemble learning techniques. We evaluated our approach using a dataset of experimentally validated exon skipping events, dividing it into training and testing sets. Our results demonstrate that using a 3-way voting approach with random forest, gradient boosting, and XGBoost can significantly reduce computation time to under ten seconds while improving prediction performance, as measured by R2 for both 2’-O-methyl nucleotides (2OMe) and phosphorodiamidate morpholino oligomers (PMOs). Additionally, the feature importance ranking derived from our approach is in good agreement with previously published results. Our findings suggest that our approach has the potential to enhance the accuracy and efficiency of predicting ASO efficacy via exon skipping. It could also facilitate the development of novel therapeutic strategies. This study could contribute to the ongoing efforts to improve ASO design and optimize gene therapy approaches.

Nowadays industrial dryers are used instead of traditional methods for drying. In designing dryers suitable for controlling the process of drying and reaching a high quality product, it is necessary to predict the instantaneous moisture loss during drying. For this purpose, ten mathematical-experimental models with a neural network model based on the kinetic data of pistachio drying are studied. The data obtained from the cabinet dryer will be evaluated at four temperatures of inlet air and different air velocities. The pistachio seeds will be placed in a thin layer on an aluminum sheet on a drying tray and weighed by a scale attached to the computer at different times. In the neural network, data are divided into three parts: educational (60%), validation (20%) and test (20%). Finally, the best mathematical-experimental model using genetic algorithm and the best neural network structure for predicting instantaneous moisture are selected based on the least squared error and the highest correlation coefficient.

There is a growing number of evidence-based indications for pharmacogenetic (PGx) testing. We aimed to evaluate clinical relevance of a 16-gene panel test for PGx-guided pharmacotherapy. In an observational cohort study we included subjects tested with a PGx panel for variants of ABCB1, COMT, CYP1A2, CYP2B6, CYP3A4, CYP3A5, CYP2C9, CYP2C19, CYP2D6, CYP4F2, DPYD, OPRM1, POR, SLCO1B1, TPMT and VKORC1. PGx-guided pharmacotherapy management was supported by the PGx expert system SONOGEN XP. The primary study outcome was PGx-based changes and recommendations regarding current and potential future medication. PGx-testing was triggered by specific drug-gene pairs in 102 subjects, and by screening in 33. Based on PharmGKB expert guidelines we identified at least one “actionable” variant in all 135 (100%) tested patients. Drugs that triggered PGx-testing were clopidogrel in 60, tamoxifen in 15, polypsychopharmacotherapy in 9, opioids in 7, and other in 11 patients. Among those, PGx variants resulted in clinical recommendations to change PGx-triggering drugs in 33 (32.4 %), and other current pharmacotherapy in 23 (22.5%). Additional costs of panel vs. single gene tests are moderate, and the efficiency of PGx panel testing challenges traditional cost-benefit calculations for single drug-gene pairs. However, PGx-guided pharmacotherapy requires specialized expert consultations with interdisciplinary collaborations.

Flood routing in flood forecasting issue, calculation the height of flood bands, determining the river boundaries, and estimation of protective facilities for flood –exposed building is applicable. In many cases, due to the lack of measuring stations, the status of the upstream flood generating hydrograph is not known. The purpose of this study is to present an integrated method comprising of an optimization model and a hydrodynamic numerical model for flood modeling to determine the upstream hydrograph using the provided hydrograph at the downstream measuring station of a river. The routing procedure consists of three steps: (1) generating a hypothetical upstream hydrograph using genetic algorithm method; (2) hydrodynamic modeling using a numerical simulation model for flood routing according to the hypothetical hydrograph which is generated in the first step; (3) compare the calculated and observed hydrograph in downstream by using a fitness function. This recommended procedure was named as Reverse Flood Routing Method (RFRM) and was then applied to Karun River, the largest river in Iran. Comparing the generated upstream hydrograph by the RFRM model with the corresponding measured hydrograph at Ahvaz hydrometric station, as an ungauged river location, shows the high accuracy of the recommended model in this study.

Genetic Programming (GP) is a powerful Machine Learning (ML) algorithm that can produce readable white-box models. Although successfully used for solving an array of problems in different scientific areas, GP is still not well known in Remote Sensing. The M3GP algorithm, a variant of the standard GP algorithm, performs Feature Construction by evolving hyper-features from the original ones. In this work, we use the M3GP algorithm on several sets of satellite images over different countries to create hyper-feature from satellite bands to improve the classification of land cover types. We add the evolved hyper-features to the reference datasets and observe a significant improvement of the performance of three state-of-the-art ML algorithms (Decision Trees, Random Forests and XGBoost) on multiclass classifications and no significant effect on the binary classifications. We show that adding the M3GP hyper-features to the reference datasets brings better results than adding the well-known spectral indices NDVI, NDWI and NBR. We also compare the performance of the M3GP hyper-features in the binary classification problems with those created by other Feature Construction methods like FFX and EFS.

Yeasts belonging to the Metschnikowia genus are particularly interesting for the unusual formation of only two needle-shaped ascospores during their mating cycle. Presently, the meiotic process that can lead to only two spores from a diploid zygote is poorly understood. The expression of fluorescent nuclear proteins should allow the meiotic process to be visualized in vivo; however, no large-spored species of Metschnikowia has ever been transformed. Accordingly, we aimed to develop a transformation method for Metschnikowia borealis, a particularly large-spored species of Metschnikowia, with the goal of enabling the genetic manipulations required to study biological processes in detail. Genetic analyses confirmed that M. borealis, and many other Metchnikowiacea, are CUG-Ser yeasts. Codon-optimized selectable markers lacking CUG codons were used to successfully transform M. borealis by electroporation and lithium acetate, and transformants appeared to be the result of random integration. Mating experiments confirmed that transformed-strains were capable of generating large asci and undergoing recombination. Finally, random integration was used to transform an additional 18 yeast strains, and all attempts successfully generated transformants. The results provide a simple method to transform many yeasts from an array of different clades and can be used to study or develop many species for various applications.

Abstract: Chloroplast is a new hotspot in the field of plant transformation system of plant genetic engineering. Initially developed in Chlamydomonas and tobacco, it is now feasible in a broad range of species. They exploit the homologous recombination and segregation pathways acting on chloroplast genomes and are based on direct repeats, transient co-integration or co-transformation and segregation of trait and marker genes. Foreign site-specific recombinases and their target sites provide an alternative and effective method for removing marker genes from plastids.Chloroplast genetic engineering has many advantages over nuclear genetic enginering, especially site-specific introduction of foreign genes ,leading to the absence of gene siliency and positon effect,which providing the available to explore the regulation and mechanism of chloroplast genes`expression in vitro .It also can identify the structure and function of the chloroplast genome , the expression of chloroplast affect the nulear genome. In this paper, the basic methodology of chloroplast transformation, the current techniques and applications, and the future possibilities for Chloroplast genetic engineering was reviewed[1-3].

The Kummer surface was constructed in 1864. It corresponds to the desingularisation of the quotient of a 4-torus by 16 complex double points. Kummer surface is kwown to play a role in some models of quantum gravity. Following our recent model of the DNA genetic code based on the irreducible characters of the finite group G5:=(240,105)≅Z5⋊2O (with 2O the binary octahedral group), we now find that groups G6:=(288,69)≅Z6⋊2O and G7:=(336,118)≅Z7⋊2O can be used as models of the symmetries in hexamer and heptamer proteins playing a vital role for some biological functions. Groups G6 and G7 are found to involve the Kummer surface in the structure of their character table. An analogy between quantum gravity and DNA/RNA packings is suggested.

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species’ distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum such as increased genetic diversity at lower latitudes. To explore this question in detail in the kelp Saccharina latissima, we used microsatellites and double digest RAD-sequencing derived SNPs on S. latissima sporophytes sampled within 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northern localities compared to the southern ones in contrast to the expected phylogeographic pattern. This suggests that the southernmost S. latissima populations are negatively affected by the recent climatic changes but also that the recolonization of S. latissima range following the LGM may have occurred from northerly refugia. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We discuss the potential adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

Dioscorea praehensilis Berth is one of the wild yam species resistance to many yam disease (yam anthracnose disease and yam mosaic virus) grow in Ghana especially in the cocoa grown regions of the country. It is a crucial crop that has been known to contribute to poverty reduction and food gap. Genetic diversity in this yam species has been discovered to be eroding and neglected. In this study we evaluated the genetic diversity among 43 D. praehensilis collected from Ghana using simple sequence repeat (SSR). Using 11 SSR marker, a total of 99 number of alleles were generated with an average of 8.48 alleles per locus. The mean gene diversity was 0.81, mean polymorphism information content was 0.82 while mean Shannon information index was 1.94. Principal coordinate analysis (PCoA) revealed a contribution of 40.16% of the first three coordinate axes and grouped the 43 morphotypes into 2 groups while hierarchical cluster through UPGMA revealed the presence of 3 main clusters. Molecular variance (AMOVA) alongside the Fst revealed low genetic diversity and differentiation among accessions and population. Result of this study assess the genetic diversity and will facilitate the use D. praehensilis as sources of resistance gene into yam breeding program.

: Urinary schistosomiasis caused by the parasite Schistosoma haematobium is the most common form of schistosomiasis. This parasite has a high potential for genetic exchange within parasite populations giving rise to the genetic diversity that is important for its survival. Genetic differ-ences may lead to some parasite strains being more immunogenic which may have a negative impact on management and control of schistosomiasis. Therefore, understanding these genetic differences in the parasite may lead to better management of the disease. A literature search was done on PubMed, African Journals online and Google scholar using predefined search terms such as urinary schistosomiasis, S. haematobium, genetic diversity in sub-Saharan Africa in com-bination with Boolean operators (AND, OR). The search included studies published from 2000-2020 that emphasised on genetic diversity of Schistosoma haematobium in sub-Saharan Africa. Sixteen studies from 18 sub-Saharan African countries that met the inclusion criteria were se-lected. Most studies conducted in these countries showed a high genetic diversity of Schistosoma haematobium studies with microsatellite markers being the most commonly used method for ge-netic diversity determination. Fisher’s exact test showed that the distribution of genetic diversity in sub-Saharan African regions was not statistically significant (p=0.768). The highest number of studies on genetic diversity of Schistosoma haematobium were conducted in West Africa with Ni-geria and Zimbabwe in Southern Africa conducting the most studies, 4/36 (11%) each. Results obtained show the need for continued monitoring of genetic variations in Schistosoma haemato-bium in sub- Saharan Africa. This will aid in understanding the epidemiology of disease, ad-vancing novel treatment and vaccine strategies.

Cervical cancer is the fourth common cancer amongst women worldwide. Environmental factors such as smoking and obesity, and recurrent infection by high-risk human papillomavirus subtypes are known to promote progression towards invasive cervical disease. Infection by high-risk HPV is necessary in most cases but not sufficient to develop invasive cervical cancer. Despite a predicted genetic heritability of between 27-36%, known genetic susceptibility loci that may be tumorigenic or influence host response to infection, only account for a small fraction of heritable risk factors so far. Various biobank-driven population based studies and meta-analyses have found corroborative evidence for several risk variants at the 6p21.3 locus (HLA), while many reports of variants outside the HLA region remain to be validated in other cohorts. Here, we review cervical cancer susceptibility variants arising from recent genome-wide association studies and meta-analysis in large cohorts and propose 2q14 (PAX8), 17q12 (GSDMB), and 5p15.33 (CLPTM1L) as consistently replicated non-HLA cervical cancer susceptibility loci. We further discuss the available evidence for these loci, knowledge gaps, future perspectives, and the potential impact of these findings on precision medicine strategies to combat cervical cancer.

The rapid and extensive loss of biodiversity globally has resulted in an increased urgency to capture and conserve the diversity which is present, including genetic diversity within species. However, for many species there is currently no detailed genetic data available to inform the collection and use of material held in ex situ collections and this can hamper the consideration of genetic issues and reduce the likelihood collection represent the diversity present. Even in the absence of direct genetic data, however, it is possible to consider genetic issues using the existing theoretical and empirical evidence-based and biological, ecological and demographic data for a given species. Here a framework to facilitate the consideration of genetic diversity and genetic issues, even where genetic data is lacking, is presented.

Gas sensor arrays, also known as electronic noses, leverage a diverse set of materials to identify the components of complex gas mixtures. Metal-organic frameworks (MOFs) have emerged as promising materials for electronic noses due to their high-surface areas and chemical as well as structural tunability. Using our recently reported genetic algorithm design approach, we examined a set of 50 MOFs and searched through the over 1.125x1015 unique array combinations to identify optimal arrays for the detection of CO₂ in air. We found that despite individual MOFs having lower selectivity for O2 or N2 relative to CO₂, intelligently selecting the right combinations of MOFs enabled accurate prediction of the concentrations of all components in the mixture (i.e. CO₂, O₂, N₂). We also analyzed the physical properties of the elements in the arrays to develop an intuition for improving array design. Notably, we find that diversity among the surface areas in the MOFs leads to improved sensing. Consistent with the observation, we found that, as one might expect, the best arrays consistently had more structural diversity than the worst arrays.

Capirona (Calycophyllum spruceanum Benth) is a tree species of commercial importance widely distributed in South American forests and is traditionally used for its medicinal properties and wood quality. Studies on this tree species have been focused mainly on wood properties, propagation and growth. Genetic studies on capirona are very limited to date. Today it is possible to explore genetic diversity and population structure in a fast and reliable manner by using molecular markers. We here used 10 Random Amplified Polymorphic DNAs (RAPDs) markers to analyze genetic diversity and population structure of 59 samples of capirona that were sampled from four provinces located in the eastern region of the Peruvian amazon. A total of 186 bands were manually scored, generating a 59 x 186 presence/absence matrix. We used R software to calculate genetic distances based on provesti coefficient. A dendrogram was generated using the UPGMA clustering algorithm and showed four groups that correspond to the geographic origin of the capirona samples. Similarly, a discriminant analysis of principal components (DAPC) confirmed that capirona is grouped into four clusters. However, we also noticed few accessions are intermingled. Genetic diversity estimation was conducted considering the four groups (populations) identified by adegenet package in R. Nei's genetic diversity estimate varied from 0.26 to 0.39 and Shannon index ranged from 2.48 to 2.83. AMOVA analysis revealed the greatest variation exist within populations (69.7%) and indicated that variability among populations is 31.5%. To our best knowledge, this is the first investigation employing molecular markers in capirona in Peru considering their natural distribution, and sheds light towards its modern genetic improvement and for the sustainable management of forests in Peru.

Covalent DNA protein crosslinks (DPCs) are common lesions that block replication. We examine here the consequence of DPCs on mutagenesis involving replicational template-switch reactions in Escherichia coli. 5-azacytidine (5azaC) is a potent mutagen for template-switching, dependent on DNA cytosine methylase (Dcm), implicating the trapped Dcm-DNA covalent complex as the initiator for mutagenesis. The leading strand of replication is more mutable than the lagging strand, explained by blocks to the replicative helicase and/or fork regression. We find that template-switch mutagenesis induced by 5-azaC does not require DSB repair via RecABCD. The ability to induce the SOS response is anti-mutagenic by an unknown mechanism. Mutants in recB, but not recA, exhibit high constitutive rates of template-switching and we suggest that RecBCD-mediated DNA degradation prevents template-switching associated with fork regression. A mutation in the DnaB fork helicase also promotes high levels of template-switching. We also find that other DPC-inducers, formaldehyde (a non-specific crosslinker) and ciprofloxacin (a topoisomerase II poison) are also strong mutagens for template-switching. Induction of mutations and genetic rearrangements that occur by template-switching may constitute a previously unrecognized component of the genotoxicity and genetic instability promoted by DPCs.

Bemisia tabaci (Gennadius) is a polyphagous, highly destructive pest capable of vectoring viruses in most agricultural crops. Currently, information on the distribution and genetic diversity of B. tabaci in South Sudan is not available. The objectives of this study were to investigate the genetic variability of B. tabaci infesting sweet potato and cassava in South Sudan. Field surveys were conducted between August 2017 and July and August 2018 in 10 locations in Juba County, Central Equatoria State, South Sudan. Sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) were used to determine the phylogenetic relationships between sampled B. tabaci. Six distinct genetic groups of B. tabaci were identified including three non-cassava haplotypes (Mediterranean (MED), Indian Ocean (IO) and Uganda) and three cassava haplotypes (Sub-Saharan Africa 1 sub-group 1 (SSA1-SG1), SSA1-SG3 and SSA2). MED predominated on sweet potato and SSA2 on cassava in all the sampled locations. The Uganda haplotype was also widespread, occurring in five of the sampled locations. This study provides important information on the diversity of B. tabaci species in South Sudan. A comprehensive assessment of the genetic diversity, geographical distribution, population dynamics and host range of B. tabaci species in South Sudan is vital for its effective management.

The physics–biology continuum relies on the fact that life emerged from prebiotic molecules. Here, I argue that life emerged from the physical coupling between the synthesis of nucleic acids and the synthesis of amino acid polymers. Owing to this physical coupling, amino acid polymers (or proto-phenotypes) maintained the physicochemical parameter equilibria (proto-homeostasis) in the immediate environment of their encoding nucleic acids (or proto-genomes). This protected the proto-genome physicochemical integrity (i.e., atomic composition) from environmental physicochemical stresses, and therefore increased the probability of reproducing the proto-genome without variation. From there, genomes evolved depending on the biological activities they generated in response to environmental fluctuations. Thus, a genome generating an internal environment whose physicochemical parameters guarantee homeostasis and genome integrity has a higher probability to be reproduced without variation and therefore to reproduce the same phenotype in offspring. Otherwise, the genome is modified by the imbalances of the internal physicochemical parameters it generates, until new emerging biological activities maintain homeostasis. In sum, evolution depends on feedforward and feedback loops between genome and phenotype, since the internal physicochemical conditions that a genome generates in response to environmental fluctuations in turn either guarantee the stability or direct the variation of the genome.

CRISPR-Cas9 technology allows the modification of DNA sequences in vivo at the location of interest. Although CRISPR-Cas9 can produce genomic changes that do not require DNA vector carriers, the use of transgenesis for stable integration of DNA coding for gene-editing tools into plant genomes is still the most used approach and it can generate unintended transgenic integrations, while Cas9 prolonged expression can increase cleavage at off-target sites. In addition, the selection of genetically modified cells from millions of treated cells, especially plant cells, is still challenging. These downfalls can be avoided with the delivery of preassembled ribonucleoprotein complexes (RNPs) composed of purified recombinant enzyme Cas9 and in vitro- transcribed guide RNA (gRNA) molecules in a protoplast system. We therefore aimed to develop the first DNA-free protocol for gene-editing in maize and introduced RNPs into their protoplasts with PEG 4000. We performed effective transformation of maize protoplasts using different gRNAs sequences targeting the inositol phosphate kinase gene and applying two different exposure times to RNPs. Using low-cost Sanger sequencing protocol, we observed an efficiency rate of 0.85 up to 5.85%, which is equivalent to DNA-free protocols used in other plant species. A positive correlation was displayed between exposure time and mutation frequency. Mutation frequency was gRNA sequence- and exposure time-dependent. In summary, we demonstrated the suitability of RNP transfection as an effective screening platform for gene-editing in maize. This efficient and relatively easy assay method for selection of gRNA suitable for editing of gene of interest will be highly useful for genome editing in maize, since genome size and GC-content are large and high in maize genome, respectively. Nevertheless, the large amplitude of mutations at target site requires scrutiny when checking mutations at off-target sites and potential safety concerns.

Genetic code expansion has emerged as an enabling tool to provide insight into functions of understudied proteinogenic species such as small proteins and peptides, and to probe protein biophysics in the cellular context. Here we discuss recent technical advances and applications of genetic code expansion in cellular imaging of complex mammalian protein species, along with considerations and challenges upon using the method.

PD-1/PD-L1 axis is one key therapeutic target against tumor cell immune escape. Structurally essential to the PD-1/PD-L1-linked immune escape is the binding interface of the PD-1/PD-L1 complex structure. Incorporating currently available PD-1/PD-L1-related experimental structures, this article unveils two sets of experimentally observed inter-molecular electrostatic interactions which stabilize the binding interface of the PD-1/PD-L1 complex structure. For the first time, this article proposes an evolutionary structural hypothesis that, as a result of natural selection, PD-1 is able to genetically mutate itself to structurally disrupt the PD-1/PD-L1 axis towards the restoration of T cell-mediated anti-tumor immunity.

Artemia franciscana, native to America, has recently colonized non-indigenous populations in Eurasia, Mediterranean regions and Australia. In present we sought to evaluate the potential effects of colonization of A. franciscana on genetic differentiation in the new environments in UAE. We used the COI marker to determine population genetic structure and identify the origins of exotic populations in UAE. Our findings have confirmed the colonization of both localities by A. franciscana. Genetic variation of invasive A. franciscana were exclusively lower than native population in Great Salt Lake and San Francisco Bay. Results have showed the studied population could not possibly have colonized directly from natural American localities, perhaps resulting from secondary introduction events from other non-indigenous populations. Genetic analysis have yielded different demographic patterns for invasive studied populations. Al Wathba Wetland Reserve (AWWR) population have represented demographic expansion. In contrast, Godolphin Lakes (GL) population was at demographic equilibrium. Neutrality tests have documented the excess of both recent and historical mutations in the COI gene pool of invasive AWWR Artemia throughout establishment in the new environment.

This article challenges the notion of the randomness of mutations in eukaryotic cells by unveiling stress-induced human non-random genome editing mechanisms. To account for the existence of such mechanisms, I have developed molecular concepts of the cell environment and cell environmental stressors and, making use of a large quantity of published data, hypothesized the origin of some crucial biological leaps along the evolutionary path of life on Earth under the pressure of natural selection, in particular, 1) virus-cell mating as a primordial form of sexual recombination and symbiosis; 2) Lamarckian CRISPR-Cas systems; 3) eukaryotic gene development; 4) antiviral activity of retrotransposon-guided mutagenic enzymes and finally; 5) the exaptation of antiviral mutagenic mechanisms to stress-induced genome editing mechanisms directed at “hypertranscribed” endogenous genes. Genes transcribed at their maximum rate (hypertranscribed), yet still unable to meet new chronic environmental demands generated by “pollution”, are inadequate and generate more and more intronic retrotransposon transcripts. In this scenario, RNA-guided mutagenic enzymes (e.g. AID/APOBECs), which have been shown to bind to retrotransposon RNA-repetitive sequences, would be surgically targeted by intronic retrotransposons on opened chromatin regions of the same “hypertranscribed” genes. RNA-guided mutagenic enzymes may therefore “Lamarkianly” generate single nucleotide polymorphisms (SNP) and copy number variations (CNV), as well as transposon transposition and chromosomal translocations in the restricted areas of hyperfunctional and inadequate genes, leaving intact the rest of the genome. CNV and SNP of hypertranscribed genes may allow cells to surgically explore a new fitness scenario, which increases their adaptability to stressful environmental conditions. Like the mechanisms of immunoglobulin somatic hypermutation, non-random genome editing mechanisms may generate several cell mutants, and those codifying for the most environmentally-adequate proteins would have a survival advantage and would therefore be Darwinianly selected. Non-random genome editing mechanisms represent a link between environmental changes and biological novelty and plasticity, and provide a molecular basis to reconcile gene-centered and “ecological” views of evolution.

Germplasm is a long-term resource management mission and investment for civilization. For both food and nutritional health, the present changing environmental scenario has become an urgent universal concern. Multiple excellent studies have been previously performed, although the advancement and innovation of practices will require the exploration of the potentiality of crop germplasm. In this study, we emphasized (i) germplasm activates, current challenges and ongoing trends of the crop germplasm, and (ii) how the system biology will be helpful to understand the complex traits such as water use efficiency (WUE), and nitrogen use efficiency (NUE) to mitigate challenges for sustainable development under growing food requirement and climate change conditions. We focused on a vision for transforming PGR into a bio-digital resource system, for the development of climate-smart crops for sustainable food production. Moreover, this review attempted to address current challenges, research gaps and describe the advanced integrated strategies that could provide a platform for future crop improvement research.

Understanding the mechanism, how entirely new (EntNew) gene/protein or the first ancestral gene/protein of a family was created, should be one of the most important issues in the biological sciences. However, the mechanism is totally unknown still now. On the other hand, it is well known that mature protein is generally rigid and one catalytic center exists on the protein. Creation of such a mature EntNew gene/protein should be, of course, carried out through random process, because it cannot be designed in advance. However, the EntNew gene/protein never be created by random polymerization of the respective monomeric units, because of the extraordinary large sequence diversities of ~10¹⁸⁰ and ~10¹³⁰, respectively. Protein 0^th-order structure or a specific amino acid composition, in which immature but water-soluble protein can be produced even through random process, holds the key for solving the difficult problem. As it was fragmentally described in the previous papers how and where EntNew gene/protein was created, I describe in detail in this review three processes generating EntNew gene/protein with some flexibility under three genetic codes, the universal genetic code, SNS primitive code and GNC primeval code, and discuss why the mature gene/protein could be created through the processes.

This study aims to analyze the pedigrees of calves affected by one of three congenital defects: aplasia genitalis, atresia ani et recti and hernia cerebralis. The defects were diagnosed by veterinary surgeons in the Czech surveillance program for bovine genetic disorders. The sires fathering affected calves were born in the Czech Republic or imported from 1986-2001. The cases occurred on farms across the Czech Republic. The pedigree of each case was examined for common maternal and paternal ancestors (inbreeding loops) and for ancestors shared by other cases of the defect. The 13 calves affected by aplasia genitalis had common ancestors in all cases. The results indicate hereditary causation with recessive inheritance. Additionally, in atresia ani et recti, some of the pedigrees of 25 affected calves support hereditary causation, and repeating ancestors were found for 11 calves. In contrast, our analysis of 11 hernia cerebralis cases did not confirm the genetic background. We demonstrated that the pedigree analysis of congenital defects could help in controlling genetic health, although the final goal in terms of inherited defects is the description of causal genes and mutations. Measures to control sires that father affected calves should be appropriate under the current knowledge, which include culling or prudent use of breeding with the monitoring of descendants.

The present cultivated enset clonal landraces in Ethiopia originated from few wild progenitors. However, enset has a mixed mode of reproduction in which, the wild enset reproduces sexually through seeds, while cultivated enset is generally propagated vegetatively. The objective of this study was to understand the genetic structures of enset cultivars and estimate their genetic variability by evaluating the morphological data generated from progenies of cultivated and wild enset clones. Hence, seeds collected from six cultivated and four wild enset genotypes were used for this study. Data on four qualitative and six quantitative morphological traits were recorded from the progenies of the 10 enset genotypes. Progenies of seven enset genotypes segregated with 3:1 genetic ratio while progenies of the remaining genotypes segregated differently for the qualitative traits considered. With regard to the quantitative traits, the progenies of the 10 enset genotypes differed significantly for five of the six traits except pseudostem length. Generally the cultivated clones performed better than the wild types. This study demonstrated the possibility of creating genetic variation through selfing of the existing clones of enset for traits of interest and makes improvements either through selection or crossing the elite types to develop novel cultivar

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

In this report we describe the case of a healthy, young, athletic woman who developed acute lymphoblastic leukaemia (ALL)/lymphoblastic lymphoma (LBL) after receiving the second dose of the Pfizer/BioNTech modified mRNA (modRNA) COVID-19 genetic vaccine (marketed as Comirnaty^®). The first dose of the genetic vaccine did not appear to illicit any noticeable side effects, but within 24 hours of the second dose the patient suffered widespread and intensifying bone pain, fever, vomiting, and general malaise. Due to the persistence of the symptoms, the patient underwent a series of tests and examinations including a full laboratory workup, a consult with a clinical immunologist and rheumatologist, a Positron Emission Tomography (PET) imaging, as well as an osteomedullary biopsy. These together led to a definitive diagnosis of ALL. A time interval of 16 weeks from the second vaccination to the diagnosis of cancer was noted. Several similar cases with identical pathology which developed after the modRNA COVID-19 vaccination, are described in case reports in the scientific literature. The massive and indiscriminate use of genetic vaccines to fight COVID-19 is raising serious concerns about their safety and about the technology platform as a whole for this purpose. Growing evidence is accumulating regarding the biodistribution and persistence of the modRNA which can reach, thanks to the lipid nanoparticles, a multitude of tissues and organs of the body, including the bone marrow and other blood-forming organs and tissues. Moreover, there is evidence that the modRNA vaccines display a particular tropism for the bone marrow, influencing the immune system at multiple levels and being able to trigger not only autoimmune-based pathologies, but also neoplastic mechanisms. The aim of this article is to assess, on the basis of the available scientific literature, the risk of developing haematopoietic cancers after modRNA vaccination, and to investigate the potential genetic mechanisms involved in the pathogenesis of disease.

Cardiovascular disease (CVD) comprises a group of heart and circulatory disorders, which are regarded as a global medical issue with high prevalence and mortality rates. Currently, vascular regenerative surgery represents the most employed therapeutic option to treat ischemic disorders, even though not all the patients are amenable to surgical revascularization. Therefore, more efficient therapeutic approaches are urgently required to promote neovascularization. Therapeutic angiogenesis represents an emerging strategy that aims at reconstructing the damaged vascular network by stimulating local angiogenesis and/or promoting de novo blood vessel formation according to a process known as vasculogenesis. Circulating endothelial colony forming cells (ECFCs), in turn, represent truly endothelial precursors able to aggregate into bidimensional tube networks and to originate patent vessels. Accordingly, ECFCs provide the most rationale and promising cellular candidate for therapeutic purposes. The current review provides a brief outline on the origin and characterization of ECFCs and a summary of the progress in preclinical studies aiming at assessing their efficacy in a variety of ischemic disorders, including AMI, PAD, ischemic brain disease and retinopathy. We also describe how to enhance the vasoreparative potential of ECFCs by boosting specific pro-angiogenic signalling pathways either pharmacologically or through gene manipulation. Taken together, these observations suggest that ECFCs represent a useful strategy to treat ischemic diseases.

The emergence of multi-drug resistant E. coli is an important matter of increasing considerable concern to global public health. The aim of this study was to investigate the incidence, antibiotic resistance pattern, phylogroups and genetic variation of E. coli isolates from raw milk, vegetable salad and ground meat samples. Methods: Culture-based techniques, Kirby-Bauer disk diffusion susceptibility testing, PCR and RAPD assays were used to determine the incidence rate, antimicrobial resistance pattern, phylogenetic groups and genetic diversity of the E. coli isolates. Results: E. coli isolates were highly resistant to amoxicillin (79.16%), trime-thoprim-sulfamethoxazole (70.83%), amoxicillin-clavulanic acid (62.50%), tetracycline (54.16%), chloramphenicol (54.16%), nitrofurantoin (54.16%), ampicillin (45.83%), streptomycin (45.83%), and kanamycin (33.33%); and completely susceptible to norfloxacin and azithromycin. 70.83% of the isolates were multi-drug resistant. Most E. coli isolates (46%) belonged to phylogroup A. RAPD with UBC245 primer categorized the isolates into 11 clusters. A high level of genetic di-versity was found among the isolates; however, 33.3% of the isolates were grouped in a major cluster (R5). Conclusions: Antibiotic resistance patterns are randomly distributed among the ge-netic clusters. Novel, practical, efficient food safety control and surveillance systems of multi-drug resistant foodborne pathogens are required to control the foodborne pathogen contamina-tion.

Nuclear pollution is an urgent environmental issue as a consequence of rapid industrialization and nuclear accidents in the past. Remediation of nuclear polluted sites using microbial vital activity (bioremediation) is a promising approach to recover contaminated areas in an environmentally friendly and cost-saving way. At the same time, the number of known bacterial and archaeal species able to withstand extremely high doses of ionizing radiation is steadily growing every year, together with growing knowledge about mechanisms of radioresistance. This opens up new opportunities for developing new biotechnological solutions. However, these data are often not systemized and it can be difficult to access. Here, we present the Determinants of Radioresistance Database, or DetR DB (http://extremebiolab.com/detr-db/), gathering a comprehensive catalog of radioresistant microbes and their molecular and genetic determinants of enhanced ionizing radiation tolerance. The database provides search tools including taxonomy, common gene name, and BLAST. DetR DB will be a useful tool for research community by facilitating the extraction of the necessary information to help further analysis of radiation-resistant mechanisms.

The most widely distributed bla_CTX-M gene on a global scale is bla_CTX-M-15. The dissemination has been associated with clonal spread and different types of mobile genetic elements. This study aimed to review and describe the genetic environments of bla_CTX-M-15 gene detected from Enterobacteriaceae in published literature from Africa. A literature search for relevant articles was done through PubMed, and Google Scholars electronic databases, 43 articles from 17 African countries were included in the review based on the eligibility criteria. Insertion sequences were reported as part of the genetic environment of bla_CTX-M-15 gene in 32 studies, integrons in 13 studies, and plasmids in 23 studies. In this review, five insertion sequences including ISEcp1, IS26, orf447, IS903, and IS3 have been detected associated with the genetic environment of bla_CTX-M-15 in Africa. Seven different genetic patterns were seen in bla_CTX-M-15 genetic environment. Insertion sequence ISEcp1 was commonly located upstream of the end of the bla_CTX-M-15 gene while insertion sequence orf477 was located downstream. In some studies, ISEcp1 was truncated upstream of bla_CTX-M-15 by insertion sequences IS26 and IS3. Class 1 integron (Intl1) was most reported to be associated with bla_CTX-M-15 (13 studies), with Intl1/dfrA17–aadA5 being the most common gene cassette array. IncFIA-FIB-FII multi-replicons and IncHI2 replicon types were the most common plasmid replicon types that horizontally transfer bla_CTX-M-15 gene. Aminoglycoside modifying enzymes, and plasmid-mediated quinolone resistance genes were commonly collocated with bla_CTX-M-15 gene on plasmids. This review revealed the predominant role of ISEcp1, Intl1and IncF plasmid in the mobilization and continental dissemination of the bla_CTX-M-15 gene in Africa.

The article studies the Venetsiansky (Hydropark) Island (the Dnipro River, Kyiv, Ukraine) landscape structure applying the genetic landscape science method and the European landscape classification (LANMAP) approach. The aim of the article is to determine the best way to study the river islands landscapes analyzing the Venetsiansky Island landscape structure by the both methods. Methodology. The genetic landscape science method consists in the next steps: 1) the island’s territory information collecting; 2) the preliminary landscape map creating; 3) field study; 4) the final landscape map creating. The LANMAP method consists on: 1) the climate study; 2) the altitude study; 3) the parent material study; 4) the land cover study. The results. The genetic landscape science method demonstrates that the Venetsiansky Island is not a landscape, but a structural part of the landscape – the tract. The LANMAP study reveals that the Venetsiansky Island is naturally homogeneous, but land cover differs. The conclusion. The both methods’ study shows that the river island cannot be the entire landscape by the natural criteria, but only the part of it. The genetic landscape science explores the landscape forming while the LANMAP reveals the current state of the landscape.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the one of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. The BARD1-BRCA1 complex is involved in genetic stabilization at the cellular level. It allows to mark abnormal DNA fragments by attaching ubiquitin to them. In addition, it blocks (by ubiquitination of RNA polymerase II) the transcription of damaged DNA. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Endometriosis is an oestrogen-dependant reproductive disease, with genetic, vascular, neural, inflammatory and auto-immune characteristics. There are many theories about the etiology of endometriosis, however, all of these theories have limitations and do not explain all the locations that endometriosis is found or types of patients with endometriosis. The objective of this paper is to postulate the hypothesis that endometriosis is caused by Maternal Microchimerism, the presence of maternal cells in the fetus. A literature review was conducted, analysing the characteristics, current etiological theories of endometriosis, theory limitations and relationship of maternal microchimerism and endometriosis. At time of writing, there was no literature on maternal microchimerism and endometriosis. These results suggest that Maternal Microchimerism could be a cause of endometriosis. This could account for the genetic and auto-immune characteristics seen in people with endometriosis, inducing a micro-environment for vascular, neural and epigenetic changes. This could also account for account for endometriosis seen in non-menstruating patients, such as men, fetuses and post-menopausal women and endometriosis found in non-peritoneal locations. If the hypothesis of Maternal Microchimerism is correct, endometriosis could be considered a pregnancy-related disease that could affect all humans, changing the accepted demographics of patients and potentially new diagnostic techniques and treatment options for patients with endometriosis. Further studies are needed to test this hypothesis.

Fusarium Head Blight (FHB) is a destructive disease affecting the grain yield and quality of wheat, barley, rye and triticale. Developing varieties with genetic resistance is integral to successfully managing FHB. However, significant knowledge gap exists in the genetic diversity present in triticale for FHB resistance. This information is critical for breeding new varieties of triticale as its production continues to increase. In the present study, a set of 298 winter triticale accessions from a worldwide collection were screened for their type-2 FHB resistance in an artificially inoculated misted nursery with high levels of inoculum density. Most of the triticale accessions were susceptible to FHB, and only 8% of accessions showed resistance in the field nursery screening. The resistant accessions identified in the nursery screening were selected and further screened for three years in greenhouse conditions. Seven accessions were found to show robust FHB resistance over the three years of greenhouse testing. Thirteen accessions showed significantly lower levels of Deoxynivalenol accumulation when compared to the susceptible triticale control. The accessions identified in the study will be useful in triticale and wheat breeding programs for enhancing FHB resistance and reducing DON accumulation.

The prevalence of algorithms and computational tools in the modern-day has intersected with nearly every field. Generative design, specifically those using genetic algorithms, is an increasingly effective, yet cost efficient way to generate architectural designs in modern engineering. Thus, we adopt a genetic algorithm model in pursuit of maximizing the durability of a structure when it is stressed while minimizing the material cost. After the model is formulated, the algorithm is able to approximate with high accuracy the load a small-scale structure is able to bear, as well as iterate upon its designs to maximize a fitness function.

Satellite communication (Satcom) is an artificial geostationary satellite that facilitates a wide range of telecommunications. Considering its quality of service (QoS) and security is crucial in government/military applications. The most challenging situation for efficient Satcom is radio frequency interference (RFI) environment. Thus, it is necessary to ensure that transmissions are incorruptible or at least sense the quality of its spectrum. This paper presents a new method to recognize received signal characteristics using a hierarchical classification in a multi-layer perceptron neural network. We consider signal modulation and the type of RFI as the characteristics of a real-time video stream transmitted in the direct broadcast satellite. Four different modulation types are investigated in this study. Moreover, the combination of the communication signal with various kinds of interference and their effects on the classification method widely have been analyzed. Besides, two robust feature selection techniques have been developed to reduce the data-set dimensional, which leads to optimizing the classification process. The results show that the Genetic Algorithm (GA) slightly outperforms Principal Component Analysis (PCA) for feature selection. Furthermore, the robustness of the proposed techniques is assessed to detect unknown signals at different signal to noise ratios.

Rhodes grass (Chloris gayana Kunth) is one of the most important forage grasses used throughout the tropical and subtropical regions of the world. Enhancing the conservation and use of genetic resources requires the development of knowledge and understanding about the existing global diversity of the species. In this study, 104 Rhodes grass accessions, held in trust in the ILRI forage genebank, were characterized using DArTSeq markers to evaluate the genetic diversity and population structure, and to develop representative subsets, of the collection. The genotyping produced 193,988 SNP and 142,522 SilicoDArT markers with an average polymorphic information content of 0.18 and 0.26, respectively. Hierarchical clustering using selected informative markers showed the presence of two and three main clusters using SNP and SilicoDArT markers, respectively, with a cophenetic correction coefficient of 82 %. Bayesian population structure analysis also showed the presence of two main subpopulations using both marker types indicating the existence of significant genetic variation in the collection. A representative subset, containing 21 accessions from diverse origins, was developed using the SNP markers. In general, the results revealed substantial genetic diversity in the Rhodes grass collection and the generated molecular information, together with the developed subset, should help enhance the management, use and improvement of Rhodes grass germplasm in the future.

The genetic code evolved around the reading of the tRNA anticodon on the primitive ribosome, and tRNA-34 wobble and tRNA-37 modifications coevolved with the code. We posit that EF-Tu, the closing mechanism of the 30S ribosomal subunit, methylation of wobble U34 at the 5-carbon and suppression of wobbling at the tRNA-36 position were partly redundant and overlapping functions that coevolved to establish the code. The genetic code devolved in evolution of mitochondria to reduce the size of the tRNAome (all of the tRNAs of an organism or organelle). “Superwobbling” or four-way wobbling describes a major mechanism for shrinking the mitochondrial tRNAome. In superwobbling, unmodified wobble tRNA-U34 can recognize all four codon wobble bases (A, G, C and U), allowing a single unmodified tRNA-U34 to read a 4-codon box. During code evolution, to suppress superwobbling in 2-codon sectors, U34 modification by methylation at the 5-carbon position appears essential. As expected, at the base of code evolution, tRNA-37 modifications mostly related to the identity of the adjacent tRNA-36 base. TRNA-37 modifications help maintain the translation frame during elongation.

Dalbergia sissoo (shisham), an important timber yielding multipurpose tree species of the Indian subcontinent, has been afflicted with large scale mortality due to wilt in natural forests and plantations, causing huge economic losses. Fusarium solani f. sp. dalbergiae (Fsd) has been identified as one of the causal organisms for wilt disease in D. sissoo. Present study comprises in vitro screening of ten selected genotypes of D. sissoo against two strains of Fsd in a dual culture set up under axenic condition. Callus and plantlets of ten genotypes of host plant were multiplied in vitro and were inoculated with conidial suspension of two strains of Fsd at three concentrations; 1× 10¹, 1× 10³, and 1× 10⁵ conidia/ml. Gnotobiotic evaluation of dual culture set up shows variations among D. sissoo genotypes in their response towards in vitro Fsd infection; and two genotypes (14 and 66) exhibited resistance against the pathogen strains. Callus of genotypes 14 and 66 significantly restricted the fungal mycelium growth whereas callus of remaining eight genotypes were completely infested by Fsd mycelium within 9 days. Similarly, plantlets of genotype 14 and 66, had lesser disease severity and remained green, and had fewer necrotic lesions in the roots whereas plantlets of remaining eight genotypes died within 15 days.

Plankton monitoring by microscopy offers long-term ecological perspective of plankton communities but is biased towards those organisms that can be distinguished using the microscope. Genetic identification of marine plankton has become standard but is still not used. This study is a comprehensive study genetically measured taxa in the Western Channel of UK using a small-volume automated water sampler deployed on the CPR platform. The study present one year of high-throughput sequencing data focussing on smaller plankton and separate community to that measured by microscopy that can complement each other for a holistic view of plankton. Quantitative tests of two harmful algae show relatively high abundance of the Pelagophyte Aureococcus anophagefferens during 2011 with low nitrite levels. Three years of Pseudo-nitzschia delicatissima quantitative monitoring also shows a greater abundance of this potentially harmful taxa in 2011. Flow cytometry reveals distinct seasonal cycles with distinct timings.

During the 1970s, Tunisian durum wheat landraces were replaced progressively by modern cultivars. These landraces are nowadays maintained by smallholder farmers in some ecological niches and are threatened gradually by extinction resulting on the narrowing of the genetic diversity. This study aims to investigate patterns of phenotypic variability using twelve quantitative traits in a panel of 189 durum wheat landraces and seven checks, based on farmer’s population name attribution and genetic structure. Our results showed high phenotypic variability among and within landraces and checks for the majority of the studied traits. The principal components analysis showed similar grouping using farmers name attribution and genetic structure using K = 6, which confirmed the identification of a new gene pool in the oases of Tunisia, represented by the sub-population Jenah Zarzoura and the robustness and high relationships between phenotypic and genome-wide genetic structure using DArTseq method. These findings will enhance the conservation efforts of these landraces and their use in breeding efforts at national and international levels to adapt to dry conditions.

Pairs of pyrrolysyl-tRNA synthetase (PylRS) and tRNAPyl from Methanosarcina mazei and Methanosarcina barkeri are widely used for site-specific incorporations of non-canonical amino acids into proteins (genetic code expansion). Previously, we achieved full productivity of cell-free protein synthesis for bulky non-canonical amino acids, including Ne-((((E)-cyclooct-2-en-1-yl)oxy)carbonyl)-L-lysine (TCO*Lys), by using Methanomethylophilus alvus PylRS with structure-based mutations in and around the amino acid binding pocket (first-layer and second-layer mutations, respectively). Recently, the PylRS•tRNAPyl pair from a methanogenic archaeon ISO4-G1 was used for genetic code expansion. In the present study, we determined the crystal structure of the methanogenic archaeon ISO4-G1 PylRS (ISO4-G1 PylRS) and compared it with those of structure-known PylRSs. Based on the ISO4-G1 PylRS structure, we attempted the site-specific incorporation of Ne-(p-ethynylbenzyloxycarbonyl)-L-lysine (pEtZLys) into proteins, but it was much less efficient than that of TCO*Lys with M. alvus PylRS mutants. Thus, the first-layer mutations (Y125A and M128L) of ISO4-G1 PylRS, with no additional second-layer mutations, increased the protein productivity with pEtZLys up to 578% of that with TCO*Lys, at high enzyme concentrations in the cell-free protein synthesis.

Cancer is fundamentally a disease of perturbed genes. Although many mutations can be marked in the genome of a cancer or transformed cell, the initiation and progression were shown to be driven by only a few mutational events viz. driver mutations that progressively govern and execute the functional impacts. The driver mutations are thus believed to dictate and dysregulate the subsequent cellular proliferative function/decisions thereby producing a cancerous state. Therefore, identifying the driver events from the genomic alterations in a patient’s cancer cell gained large attention recently for designing better targeting therapies towards paving way for the precision cancer medicine. With rolling advancements in high-throughput omics technologies, analysis of genetic variations and gene expression profiles for cancer patients has become a routine clinical practice. However, it is anticipated that protein structural alterations resulting from such driver mutations can provide more direct and clinically relevant evidence of disease states than genetic signatures alone. This review comprehensively discusses various aspects and approaches that have been developed for the prediction of cancer drivers using genetic signatures and protein structures, and their potential application in developing precision cancer therapies.Keywords:

This article explains how resistance alleles have become rare or have disappeared from honey bee populations in Europe (and probably also in North America). Honeybees have the highest recombination frequency of all animals, indicating that pathogenic bacteria, viruses, fungi and microsporidia are an important source of selection. To respond to new virulent strains of pathogens, honeybees need to have access to rare alleles that could foster immunity against a new pathogen. By mating in a large panmictic population, new rare alleles can be recruited, which can then be combined into new genotypes through recombination with useful alleles of other genes. Bee breeders, by selecting small samples from a large population tend to select common alleles and lose the rare ones. Rare alleles can become important when a new virulent pathogen arrives. The loss of rare alleles makes bees vulnerable to disease and parasites and explains, together with the problems caused by modern agriculture, why managed bees have high mortality rates.

In addition to the canonical loss-of-function mutations, mutations in proteins may additionally result in gain-of-function through the binary activation of cryptic ‘structural capacitance elements’. Our previous bioinformatic analysis allowed us to propose a new mechanism of protein evolution - structural capacitance – that arises via the generation of new elements of microstructure upon mutations that cause a disorder-to-order (DO) transition in previously disordered regions of proteins. Here we propose that the DO transition is a necessary follow-on from expected early codon-anticodon and tRNA acceptor stem-amino acid usage, via the accumulation of structural capacitance elements - reservoirs of disorder in proteins. We develop this argument further to posit that structural capacitance is an inherent consequence of the evolution of the genetic code.

In recent years, the ecological and economic values of forest plants have been gradually recognized worldwide. However, the growing global demand for new forest plant varieties with higher wood production capacity and better stress tolerance cannot be satisfied by conventional phenotype-based breeding, marker-assisted selection, and genomic selection. In the recent past, diverse omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics, have been developed rapidly, providing powerful tools for the precision genetic breeding of forest plants. Genomics lays a solid foundation for understanding complex biological regulatory networks, while other omics technologies provide different perspectives at different levels. Multi-omics integration has combined the different omics technologies, becoming a powerful tool for genome-wide functional element identification in forest plant breeding. This review summarizes the recent progress of omics technologies and their applications in the genetic studies of forest plants. It will provide forest plant breeders with an elementary knowledge of multi-omics techniques for future breeding programs.

The primary considerations while producing rice (Oryza sativa L.) include improving its nutritional quality and production. To tackle widespread hunger globally, better nutritional, high-yielding rice cultivars need to be developed. The conventional ways are to increase the production of rice and add balanced nutrients in the daily diet to fulfill the need of yield and nutrient quality. This article focuses on nutritional strategies for rice and illustrates the availability of omics technologies. Current advancements providing many methodologies and approaches for exploring genetic resources and for understanding the molecular mechanisms involved in trait formation have been highlighted. Studying the genetic influences of various characteristics has been proven to expedite crop breeding processes. In this perspective, genome-wide association research, genome selection (GS), and QTL mapping are all genetic analysis that helps in increasing the nutritional content of rice. Implementation of several omic techniques are effective approaches to enhance and regulate the nutritional quality of rice cultivars. Advancements in different types of omics including genomics and pangenomics, transcriptomics, metabolomics, nutrigenomics, and proteomics are also relevant to rice development initiatives. This review article compiles genes, locus, mutants and all omic approaches for rice enhancement. This knowledge will be very useful for now and for the future regarding rice studies.

Hand gesture recognition has many valuable applications in engineering and health care. This study proposes a novel model which can accurately distinguish hand gestures using forearm muscles' surface electromyogram (sEMG) signals. A deep learning algorithm with hyper parameters impacting the final model’s accuracy and a convolutional neural network (CNN) were employed in the recognition stage. The number of convolutional layers, kernels per layer, and neurons in the dense layer were selected for optimization, while the remaining parameters, such as the learning rate, batch size, and number of epochs, were chosen based on trial and error and prior knowledge. The optimal values for the selected hyperparameters were obtained using a genetic algorithm to achieve maximum recognition accuracy. The UC2018 Dual-Myo database was used for training and testing the model based on EMG signals characterizing the activity of eight different hand gestures. The final structure of the model consisted of two convolutional layers with 131 and 28 kernels, a dense layer with 111 neurons, and a softmax layer with eight neurons. Upon optimizing the hyperparameters using the genetic algorithm, the accuracy of the proposed model increased from 91.86% to 96.4% at best and 95.3% on average in real-time applications and 99.6% in an offline mode. Future work is warranted towards improving the architecture and the computational cost.

Saccharomyces cerevisiae are a phenotypically diverse species that adapt to a wide variety of environments by exploiting standing genetic diversity and selecting for advantageous mutations. Glyphosate and copper-based herbicides/ fungicides affect non-target organisms, these incidental exposures can impact microbial populations. In this study, glyphosate resistance was found in the historical collection of yeast which was collected over the last century, but only in yeast isolated after the introduction of glyphosate. The highest glyphosate-resistant yeasts were isolated from agricultural sites. However, herbicide application at these sites was not recorded. In an effort to assess glyphosate resistance and impact on non-target microorganisms, yeast were harvested from 15 areas with known herbicidal histories, including an organic farm, conventional farm, remediated coal mine, suburban locations, state park, and a national forest. Yeast representing 23 genera were isolated from 237 samples of plant, soil, spontaneous fermentation, nut, flower, fruit, feces, and tree material samples. Saccharomyces, Candida, Metschnikowia, Klyveromyces, Hanseniaspora, and Pichia were other genera commonly found across our sampled environments. Managed areas had less species diversity and at the brewery, only Saccharomyces and Pichia were isolated. A conventional farm growing RoundUp Ready™ corn had the lowest phylogenetic diversity and the highest glyphosate resistance. The mine was sprayed with multiple herbicides including a commercial formulation of glyphosate; however, the yeast did not have elevated glyphosate resistance. In contrast to the conventional farm, the mine was exposed to glyphosate only one year prior to sample isolation. Glyphosate resistance is an example of the anthropogenic selection of nontarget organisms.

Scrub typhus (ST) is one of the most neglected tropical diseases, a leading cause of acute undifferentiated febrile illness in areas of the ‘tsutsugamushi triangle’, diagnosed frequently in South Asian countries. The bacteria Orientia tsutsugamushi is the causative agent of the disease, which enters to human body through the bite of trombiculid mite (Chigger) of the genus Leptotrombidium deliense.The diagnosis of the disease becomes challenging as its early symptoms mimic other febrile illnesses like dengue, influenza, and corona viruses. Lack of rapid, reliable, and cost-effective diagnostic methods further complicates the identification process. Northeast India, a mountainous region with a predominantly rural tribal population, has witnessed a resurgence of scrub typhus cases in recent years. Various ecological factors, including rodent population, habitat characteristics, and climatic conditions, influence its prevalence. Entomological investigations have confirmed the abundance of vector mites, highlighting the importance of understanding their distribution and the probability of transmission of scrub typhus in the region. Proper diagnosis, awareness campaigns, and behavioral interventions are essential for controlling scrub typhus outbreaks and reducing its impact on public health in Northeast India. Further research and community-based studies are necessary to accurately assess the disease burden and implement effective prevention strategies.

Recent studies indicated that Plasmodium vivax can infect Duffy-negative individuals, but the varied diagnostic and methodological approaches have limited our ability to characterize P. vivax across Africa. Here, we utilized a standardized approach to compare epidemiological and genetic attributes of P. vivax from Botswana, Ethiopia, and Sudan, where Duffy-positive and Duffy-negative individuals coexist. Among 1,215 febrile patients, the proportions of Duffy negativity range from 20-36% in East Africa to 84% in Southern Africa. Considerable differences were observed in P. vivax prevalence among Duffy-negative populations ranging from averaged 9.2% in Sudan to 86% in Botswana. P. vivax parasite density in Duffy-negative infections is significantly lower than in Duffy-positive infections. Phylogenetic analyses of 229 PvDBP sequences indicated that Duffy-negative P. vivax were not monophyletic but occurred in multiple well-supported clades, suggesting independent origins. Duffy-negative Africans are clearly not resistant to P. vivax and the public health significance should no longer be neglected.

Exome sequencing has been commonly used in rare diseases by selecting multiplex families or singletons with an extreme phenotype (EP) to search for rare variants in coding regions. The EP strategy covers both extreme ends of a disease spectrum and it has been also used to investigate the contribution of rare variants to heritability in complex clinical traits. We have conducted a systematic review to find evidence supporting the use of EP strategies to search for rare variants in genetic studies of complex diseases, to highlight the contribution of rare variation to the genetic structure of multiallelic conditions. After performing the quality assessment of the retrieved records, we selected 19 genetic studies considering EP to demonstrate genetic association. All the studies successfully identified several rare variants, de novo mutations and many novel candidate genes were also identified by selecting an EP. There is enough evidence to support that the EP approach in patients with an early onset of the disease can contribute to the identification of rare variants in candidate genes or pathways involved in complex diseases. EP patients may contribute to a better understanding of the underlying genetic architecture of common heterogeneous disorders such as tinnitus or age-related hearing loss.

The genetic code conceals a ‘code within the codons’, which hints at biophysical interactions between amino acids and their cognate nucleotides. But research over decades has failed to corroborate systematic biophysical interactions across the code. Using molecular dynamics simulations and NMR, we have analysed interactions between the 20 standard proteinogenic amino acids and four RNA mononucleotides in three charge states. Our simulations show that 50% of amino acids bind best with their anticodonic middle base in the -1 charge state common to the backbone of RNA, while 95% of amino acids interact most strongly with at least one of their codonic or anticodonic bases. Preference for the cognate anticodonic middle base was greater than 99% of randomized assignments. We verify a selection of our results using NMR, and highlight challenges with both techniques for interrogating large numbers of weak interactions. Finally, we extend our simulations to a range of amino acids and dinucleotides, and corroborate similar preferences for cognate nucleotides. Despite some discrepancies between the predicted patterns and those observed in biology, the existence of weak stereochemical interactions means that random RNA sequences could template non-random peptides. This offers a compelling explanation for the emergence of genetic information in biology.

The last two decades have witnessed a surge in investigations proposing stem cells as a promising strategy to treat stroke. Since growth factor release is considered as one of the most important aspects of cell-based therapy, stem cells over-expressing growth factors are hypothesized to yield higher levels of therapeutic efficiency. In pre-clinical studies of the last 15 years that were investigating the efficiency of stem cell therapy for stroke, a variety of stem cell types were genetically modified to over-express various factors. In this review we summarize the current knowledge on the therapeutic efficiency of stem cell-derived growth factors, encompassing techniques employed and time points to evaluate. In addition, we discuss several types of stem cells, including the recently developed model of epidermal neural crest stem cells, and genetically modified stem cells over-expressing specific factors, which could elevate the restorative potential of naive stem cells. The restorative potential is based on enhanced survival/differentiation potential of transplanted cells, apoptosis inhibition, infarct volume reduction, neovascularization or functional improvement. Since the majority of studies have focused on the short-term curative effects of genetically engineered stem cells, we emphasize the need to address their long-term impact.

Hospital readmission and length of stay prediction provide info to manage hospitals’ bed capacity and the number of required staff, especially during pandemics. We present a hybrid deep model called Genetic Algorithm-Optimized Convolutional Neural Network (GAOCNN) with a unique preprocessing method to predict hospital readmission and the length of stay in patients having various conditions. GAOCNN uses one-dimensional convolutional layers to predict hospital readmission and length of stay. The parameters of the layers are optimized using a genetic algorithm. To show the performance of the proposed model in patients with various conditions, we evaluate the model under three healthcare datasets; the Diabetes 130-US hospitals dataset, the COVID-19 dataset, and the MIMIC-III dataset. The diabetes 130-US hospitals dataset has information on both readmission and the length of stay, while COVID-19 and MIMIC-III datasets just include information on the length of stay. Experimental results show that the proposed model’s accuracy for hospital readmission is 97.2% for diabetic patients. Also, the accuracy of the length of stay prediction is 89%, 99.4%, and 94.1% for diabetic, COVID-19, and ICU patients, respectively. These results confirm the superiority of the proposed model compared to existing methods. Our findings offer a platform for managing healthcare funds and resources for patients with various diseases.