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The regenerative capabilities of the liver represent a paradigm for understanding tissue repair in solid organs. Regeneration after partial hepatectomy in rodent models is well understood, while regeneration in the context of clinically relevant chronic injuries is less studied. Given the growing incidence of fatty liver disease, cirrhosis, and liver cancer, interest in liver regeneration is increasing. Here, we will review the principles, genetics, and cell biology underlying liver regeneration, as well as new approaches being used to study heterogeneity in liver tissue maintenance and repair.

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Real-world multi-objective optimization problems encounter different types of uncertainty that may affect the quality of solutions. One common type is the stochastic noise that contaminates the objective functions. Another type of uncertainty is the different forms of dynamism including changes in the objective functions. Although related work in the literature targets only a single type, in this paper, we study Dynamic Multi-objective Optimization problems (DMOPs) contaminated with stochastic noises by dealing with the two types of uncertainty simultaneously. In such problems, handling uncertainty becomes a critical issue since the evolutionary process should be able to distinguish between changes that come from noise and real environmental changes that resulted from different forms of dynamism. To study both noisy and dynamic environments, we propose a flexible mechanism to incorporate noise into the DMOPs. Two novel techniques called Multi-Sensor Detection Mechanism (MSD) and Welford-Based Detection Mechanism (WBD) are proposed to differentiate between real change points and noise points. The proposed techniques are incorporated into a set of Dynamic Multi-objective Evolutionary Algorithms (DMOEAs) to analyze their impact. Our empirical study reveals the effectiveness of the proposed techniques for isolating noise from real dynamic changes and diminishing the noise effect on performance.

• Genodermatoses are a broad spectrum of heritable disorders that affect the skin, and may or may not affect other organ systems. • Classification and nomenclature of these disorders is evolving as we learn more about the genetic basis and pathogenesis of these conditions. • Genodermatoses that present in the neonatal period are discussed in this chapter.

A new section on the approach to diagnostic histological interpretation, is the overture to this chapter on inherited and developmental disorders. This initial section is split chronologically into the early neonatal and infantile period and later childhood and adulthood; with the intention of reflecting clinical practice as closely and succinctly as possible. Disorders of the biliary tree, bile formation and secretion, and hepatocyte metabolism are the core of this chapter, a merger of chapters 3 and 4 of the previous edition. Considerations on the pathogenetic and/or clinical overlap between developmental, genetic and metabolic disorders were the rationale behind this change. The complexity of hepatocyte metabolism is reflected into the miriad of related pathological conditions. Recent technological advances, particularly in genomics in the last five years, have resulted in a plethora of new entities and changes in terminology, challenging the authors to balance detail and application to clinical practice. Tables and figures from previous editions have been largely kept due to their quality and contemporary relevance, whilst new ones have been added to accommodate new advances (e.g. classification of mitochondrial disorders), a compromise to bridge between the two editions for the accustomed reader. Liver involvement in immunodeficiency and miscellaneous disorders precede the final section on anatomical anomalies. Vascular anomalies are now included in the chapters on vascular disorders.

Studying the placenta can provide information about the mechanistic pathways of pregnancy disease. However, analyzing placental tissues and manipulating placental function in real-time during pregnancy is not feasible. The ex vivo placental perfusion model allows observing important aspects of the physiology and pathology of the placenta, while maintaining its viability and functional integrity, and without causing harm to mother or fetus. In this review, we describe and compare setups for this technically complex model and summarize outcomes from various published studies. We hope that our review will encourage wider use of ex vivo placental perfusion, which in turn would generate more knowledge to improve pregnancy outcomes.

Hepatocellular carcinoma (HCC) is the primary liver cancer that occurs the most frequently. The risk of developing HCC is highest in those with chronic liver diseases, such as cirrhosis brought on by hepatitis B or C infection and the most common type of liver cancer. Knowledge-based interpretations are essential for understanding the HCC microarray dataset due to its nature, which includes high dimensions and hidden biological information in genes. When analyzing gene expression data with many genes and few samples, the main problem is to separate disease-related information from a vast quantity of redundant gene expression data and their noise. Clinicians are interested in identifying the specific genes responsible for HCC in individual patients. These responsible genes may differ between patients, leading to variability in gene selection. Moreover, ML approaches, such as classification algorithms, are similar to black boxes, and it is important to interpret the ML model outcomes. In this paper, we use a reliable pipeline to determine important genes for discovering HCC from microarray analysis. We eliminate redundant and unnecessary genes through gene selection using principal component analysis (PCA). Moreover, we detect responsible genes with the random forest algorithm through variable importance ranking calculated from the Gini index. Classification algorithms, such as random forest (RF), naïve Bayes classifier (NBC), logistic regression, and k-nearest neighbor (kNN) are used to classify HCC from responsible genes. However, classification algorithms produce outcomes based on selected genes for a large group of patients rather than for specific patients. Thus, we apply the local interpretable model-agnostic explanations (LIME) method to uncover the AI-generated forecasts as well as recommendations for patient-specific responsible genes. Moreover, we show our pathway analysis and a dendrogram of the pathway through hierarchical clustering of the responsible genes. There are 16 responsible genes found using the Gini index, and CCT3 and KPNA2 show the highest mean decrease in Gini values. Among four classification algorithms, random forest showed 96.53% accuracy with a precision of 97.30%. Five-fold cross-validation was used in order to collect multiple estimates and assess the variability for the RF model with a mean ROC of 0.95±0.2. LIME outcomes were interpreted for two random patients with positive and negative effects. Therefore, we identified 16 responsible genes that can be used to improve HCC diagnosis or treatment. The proposed framework using machine-learning-classification algorithms with the LIME method can be applied to find responsible genes to diagnose and treat HCC patients.

Purpose: Intestinal fibrosis is a common complication of inflammatory bowel diseases. However, the possible involvement of epithelial-mesenchymal transition (EMT) has been scarcely investigated. This systematic review aims to search through research papers that are focusing on messenger RNA (mRNA) and protein expression profile in EMT in fistula or in intestinal fibrosis.Methods: Electronic exploration was performed until April 24, 2019 through PubMed, Ovid, Science Direct, and Scopus databases with the terms of “fistula” OR “intestinal fibrosis” AND “epithelial-mesenchymal transition”. Two independent reviewers scrutinized the suitability of the title and abstract before examining the full text that met the inclusion criteria. For each study, the sample types that were used, methods for analysis, and genes expressed were identified. The list of genes was further analyzed using DAVID (Database for Annotation, Visualization, and Integrated Discovery) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway.Results: There were 896 citations found; however, only 3 studies fulfilled the requirements. Among the EMT-related genes, 5 were upregulated genes at mRNA level while 6 were at protein level. However, only 2 downregulated genes were found at each mRNA and protein level. Of the 4 inflammation-related genes found, 3 genes were upregulated at mRNA level and 1 at protein level. These genes were confirmed to be involved in the development of inflammatory induced fibrosis and fistula through EMT. Results from quantitative real-time polymerase chain reaction analysis were consistent with the process of EMT, confirmed by the western blot protein analysis.Conclusion: Many significant genes which are involved in the process of EMT in fistula and intestinal fibrosis have been identified. With high-end technology many more genes could be identified. These genes will be good molecular targets in the development of biomarkers for precision drug targeting in the future treatment of intestinal fibrosis and fistula.

A novel form of cell death, cuproptosis, was recently identified to be mediated by the binding of copper to lipoylated enzymes of the tricarboxylic acid cycle. Cuproptosis-related genes (CRGs) may play a crucial role in the progression of pancreatic adenocarcinoma (PAAD), which often exhibits metabolic reprogramming. In the present study, univariate Cox regression analysis and Kaplan–Meier survival analysis were performed to identify prognostic CRGs. Data from the Cancer Therapeutics Response Portal and the Genomics of Drug Sensitivity in Cancer database were downloaded for drug sensitivity analysis. DLAT was identified as the only prognostic CRG in PAAD (HR = 2.72; 95% CI, 1.10–6.74). Functional enrichment analyses indicated that the basic function of DLAT is closely related to metabolism, and multiple tumor-promoting and immune response-related pathways were enriched in DLAT-high PAAD samples. The influence of DLAT and related genes on cancer immunity was evaluated by comprehensive immune infiltration analyses, which revealed the value of these genes as biomarkers for evaluating the sensitivity to immunotherapy. Additionally, high DLAT expression induced drug resistance, and significantly increased resistance to commonly used chemotherapeutics in PAAD, such as gemcitabine, oxaliplatin, 5-fluorouracil, and irinotecan. In conclusion, our study preliminarily revealed the prognostic value of DLAT, which is correlated with PAAD progression, chemoresistance, and immune infiltration, providing a valuable reference for PAAD treatment. However, our findings need to be confirmed by further in vivo and in vitro experiments.

Dietary nutrients are associated with the development of cardiovascular disease (CVD) both through traditional pathways (inducing hyperlipidemia and chronic inflammation) and through the emergence of a metaorganism-pathogenesis pathway (through the gut microbiota, its metabolites, and host). Several molecules from food play an important role as CVD risk-factor precursors either themselves or through the metabolism of the gut microbiome. Animal-based dietary proteins are the primary source of CVD risk-factor precursors; however, some plants also possess these precursors, though at relatively low levels compared with animal-source food products. Various medications have been developed to treat CVD through the gut-microbiota–circulation axis, and they exhibit potent effects in CVD treatment. Nevertheless, such medicines are still being improved, and there are many research gaps that need to be addressed. Furthermore, some medications have unpleasant or adverse effects. Numerous foods and herbs impart beneficial effects upon health and disease. In the past decade, many studies have focused on treating and preventing CVD by modulating the gut microbiota and their metabolites. This review provides an overview of the available information, summarizes current research related to the gut-microbiota–heart axis, enumerates the foods and herbs that are CVD-risk precursors, and illustrates how metabolites become CVD risk factors through the metabolism of gut microbiota. Moreover, we present perspectives on the application of foods and herbs—including prebiotics, probiotics, synbiotics, postbiotics, and antibiotic-like substances—as CVD prevention agents to modulate gut microbiota by inhibiting gut-derived CVD risk factors. Taxonomy (classification by EVISE) Cardiovascular disease, gut microbiota, herbal medicine, preventive medicine, dietary therapy, nutrition supplements.

Clozapine is an atypical antipsychotic used in refractory schizophrenia, also efficient in alleviating dyskinesia in Parkinson’s disease. Despite its potency, this drug is associated with severe metabolic side effects, including increased risk for diabetes. We report the case of a 45-year-old overweight woman with Parkinson’s disease who presented with rapid-onset hyperglycaemia within 2 months after starting clozapine for refractory dyskinaesia. She had a history of gestational diabetes. At presentation, her blood glucose level was 505 mg/dL and glycated haemoglobin 12.4%, with no catabolic symptoms. Clozapine was suspended and metformin was started, but adequate glycaemic control was achieved only with insulin therapy, along with exenatide and empagliflozin afterwards. We assume that clozapine acted as a trigger for rapid deterioration of glycaemic control through direct pathophysiological mechanisms, rather than an indirect slowly evolving weight gain-related metabolic syndrome pathway. Clinicians should be aware of this complication, enabling timely diagnosis and proper treatment.

Growing evidence from animal and human studies show that opioids have a major impact on the composition and function of gut microbiota. This leads to disruption in gut permeability and altered microbial metabolites, driving both systemic and neuroinflammation, which in turn impacts central nervous system (CNS) homeostasis. Tolerance and dependence are the major comorbidities associated with prolonged opioid use. Inflammatory mediators and signaling pathways have been implicated in both opioid tolerance and dependence. We provide evidence that targeting the gut microbiome during opioid use through prebiotics, probiotics, antibiotics, and fecal microbial transplantation holds the greatest promise for novel treatments for opioid abuse. Basic research and clinical trials are required to examine what is more efficacious to yield new insights into the role of the gut-brain axis in opioid abuse.

Results of computational analysis and visualization of differences in gene structures using polarization coding are presented. A two-dimensional phase screen, where each element of which corresponds to a specific basic nucleotide (adenine, cytosine, guanine, or thymine), displays the analyzed nucleotide sequence. Readout of the screen with a coherent beam characterized by a given polarization state forms a diffracted light field with a local polarization structure that is unique for the analyzed nucleotide sequence. This unique structure is described by spatial distributions of local values of the Stokes vector components. Analysis of these distributions allows the comparison of nucleotide sequences for different strains of pathogenic microorganisms and frequency analysis of the sequences. The possibilities of this polarization-based technique are illustrated by the model data obtained from a comparative analysis of the spike protein gene sequences for three different model variants (Wuhan, Delta, and Omicron) of the SARS-CoV-2 virus. Various modifications of polarization encoding and analysis of gene structures and a possibility for instrumental implementation of the proposed method are discussed.

Glucagon-like peptide-1(GLP-1) is a multifunctional polypeptide throughout the lifespan via activating Glucagon-like peptide-1 receptor (GLP-1R).GLP-1 can affect food ingestion, enhance the secretion of insulin from pancreatic islets induced by glucose and be utilized to treat type 2 diabetes mellitus(T2DM).But, accumulating evidences from the decades suggest that activation GLP-1R can not only regulate the blood glucose, but also sustain the homeostasis of intracellular environment and protect neuron from various damaged responses such as oxidative stress, inflammation, excitotoxicity, ischemia and so on. And more and more pre-clinical and clinical studies identified that GLP-1 and its analogues may play a significant role in improving multiple central nervous system (CNS) diseases including neurodegenerative diseases, epilepsy, mental disorders, ischemic stroke, hemorrhagic stroke, traumatic brain injury, spinal cord injury, chronic pain, addictive disorders, other diseases neurological complications and so on. In order to better reveal the relationship between GLP-1/GLP-1R axis and the growth, development and survival of neurons, herein, this review is aimed to summarize the multi-function of GLP-1/GLP-1R axis in CNS diseases.

Objective Patients with systemic lupus erythematosus (SLE) display symptoms that are not always related to disease activity and may distort clinical trial results. Recently, a clinical categorization based on the presence of type 1 (inflammatory manifestations) and/or type 2 (widespread pain, fatigue, depression) symptoms has been proposed in SLE. Our aim was to develop a type 2 score derived from the Short-Form health survey (SF-36) to categorize SLE patients and to compare immunological and transcriptomic profiles between groups. Methods Seventeen items from the SF-36 were selected to build a type 2 score for 50 SLE patients (100 visits; LUPUCE cohort) and the SLEDAI was used to define type 1 symptoms. Patients were categorized in four groups: minimal (no symptoms), type 1, type 2 and mixed (both type 1 and type 2 symptoms). Clinical, immunological and transcriptomic profiles were compared between the groups. Results Type 2 scores ranged from 0 to 31, with a cut-off value of 14 (75th percentile). The sample categorization was: minimal in 39%, type 1 in 37%, type 2 in 9% and mixed in 15%. Type 2 patients were older than minimal patients and had a longer disease duration than type 1 and mixed patients. Immunological data and modular interferon signatures did not differ between the groups. Conclusion Patients with SLE can be categorized into four clinical groups using the SLEDAI score and our SF-36-derived type 2 score. This categorization is non-redundant with immunological or transcriptomic profiles and could prove useful to stratify patients in clinical trials.

Celiac peptide-generating α- and γ-gliadins consist of a disordered N-terminal domain extended by an α-helical-folded C-terminal domain. Celiac peptides, primarily located along the disordered part of α- and γ-gliadin molecules, are nicely exposed and directly accessible to proteolytic enzymes occurring in the gastric (pepsin) and intestinal (trypsin, chymotrypsin) fluids. More than half of the potential celiac peptides identified so far in gliadins exhibit cleavage sites for pepsin. However, celiac peptides proteolytically truncated by one or two amino acid residues could apparently retain some activity toward HLA-DQ2 and HLA-DQ8 receptors in docking experiments. Together with the uncleaved peptides, these still active partially degraded CD peptides account for the incapacity of the digestion process to inactivate CD peptides from gluten proteins. In contrast, sourdough fermentation processes involve other proteolytic enzymes susceptible to the deep degradation of celiac peptides. In particular, sourdough supplemented by fungal prolyl endoproteases enhances the degrading capacities of the sourdough fermentation process toward celiac peptides. Nevertheless, since tiny amounts of celiac peptides sufficient to trigger deleterious effects on CD people can persist in sourdough-treated bread and food products, it is advisable to avoid consumption of sourdough-treated food products for people suffering from celiac disease. As an alternative, applying the supplemented sourdough process to genetically modified low gluten or celiac-safe wheat lines should result in food products that are safer for susceptible and CD people.

Many current bioinformatics algorithms have been implemented in parallel programming code. Some of them have already reached the limits imposed by Amdahl’s law, but many can still be improved. In our paper, we present an approach allowing us to generate a high-performance code for calculating the number of RNA pairs. The approach allows us to generate parallel tiled code of the maximal dimension of tiles, which for the discussed algorithm is 3D. Experiments carried out by us on two modern multi-core computers, an Intel(R) Xeon(R) Gold 6326 (2.90 GHz, 2 physical units, 32 cores, 64 threads, 24 MB Cache) and Intel(R) i7(11700KF (3.6 GHz, 8 cores, 16 threads, 16 MB Cache), demonstrate a significant increase in performance and scalability of the generated parallel tiled code. For the Intel(R) Xeon(R) Gold 6326 and Intel(R) i7, target code speedup increases linearly with an increase in the number of threads. An approach presented in the paper to generate target code can be used by programmers to generate target parallel tiled code for other bioinformatics codes whose dependence patterns are similar to those of the code implementing the counting algorithm.

Danon disease (DD) is an X-linked multisystem disorder with clinical features characterized by the triad of hypertrophic cardiomyopathy, skeletal muscle weakness, and mental retardation. Cardiac involvement can be fatal in the absence of an effective treatment option such as heart transplantation. Molecular studies have proved that LAMP-2 protein deficiency, mainly LAMP-2B isoform, resulting from LAMP2 gene mutation, is the culprit for DD. Autophagy impairment due to LAMP-2 deficiency mediated the accumulation of abnormal autophagic vacuoles in cells. While it is not ideal for mimicking DD phenotypes in humans, the emergence of LAMP-2-deficient animal models and induced pluripotent stem cells from DD patients provided powerful tools for exploring DD mechanism. In both in vitro and in vivo studies, much evidence has demonstrated that mitochondria dysfunction and fragmentation can result in DD pathology. Fundamental research contributes to the therapeutic transformation. By targeting the molecular core, several potential therapies have demonstrated promising results in partial phenotypes improvement. Among them, gene therapies anticipate inaugurate a class of symptom control and prevention drugs as their in vivo effects are promising, and one clinical trial is currently underway.

Diabetic mellitus is a worldwide endocrine and metabolic disorder with insulin insensitivity or deficiency or both whose prevalence could rise up to 592 million by 2035. Consistent hyperglycemia leads to one of the most common comorbidities like Diabetic Peripheral Neuropathy (DPN). DPN is underlined with unpleasant sensory experience, such as tingling and burning sensation, hyperalgesia, numbness, etc. Globally, 50-60% of the diabetic population is suffering from such symptoms as microvascular complications. Consistent hyperglycemia during DM causes activation/inhibition of various pathways playing important role in the homeostasis of neurons and other cells. Disruption of these pathways results into apoptosis and mitochondrial dysfunctions, causing neuropathy. Among these, pathways like Polyol and PARP are some of the most intensively studied ones whereas those like Wnt pathway, Mitogen activated protein kinase (MAPK), mTOR pathway are comparatively newly discovered. Understanding of these pathways and their role in pathophysiology of DN underlines a few molecules of immense therapeutic value. The inhibitors or activators of these molecules can be of therapeutic importance in the management of DPN. This review, hence, focuses on these underlying molecular mechanisms intending to provide therapeutically effective molecular targets for the treatment of DPN.

Molecular genetics, genomics, and bioinformatics are interdisciplinary fields that associate with the structure and function of genes and genomes in living organisms, including camels. Molecular genetics control the development and function of cells and organisms. Therefore, the researchers use molecular genetics techniques to study the genetic makeup of camels, including identifying and characterizing specific genes and variations in their DNA sequences. In addition, the genomics have role in the entire genome, or the complete set of genetic information, of an organism. Through genomics, researchers can gain a comprehensive understanding of the genetic makeup of camels and how it relates to their physiology and physiology. Finally, bioinformatics has the application of computational and statistical techniques to the analysis of biological data, such as genetic sequences. their tools and methods are used to analyze and interpret the large amounts of data generated by molecular genetics and genomics studies. Overall, these fields can provide important insights into the biology and evolution of camels, and can aid in the development of new technologies and strategies for the conservation and management of "ships of the desert".

Helminth parasites secrete several types of biomolecules to ensure their entry and survival in their hosts. The proteins secreted to the extracellular environment participate in the pathogenesis and anthelmintic immune responses. The aim of this work was to identify and functionally annotate the excretory/secretory (ES) proteins of the monogenean ectoparasite Rhabdosynochus viridisi through bioinformatic approaches. A total of 1655 putative ES proteins were identified, 513 (31%) were annotated in the UniProtKB/Swiss-Prot database, and 269 (16%) were mapped to 212 known protein domains and 710 GO terms. We identified six putative multifunctional proteins. A total of 556 ES proteins were mapped to 179 KEGG pathways and 136 KO. ECPred predicted 223 enzymes (13.5%) and 1315 non-enzyme proteins (79.5%) from the secretome of R. viridisi. A total of 1045 (63%) proteins were predicted as antigen with a threshold 0.5. We also identified six venom allergen-like proteins. Our results suggest that ES proteins from R. viridisi are involved in immune evasion strategies and some may contribute to immunogenicity.

Spinal muscular atrophy (SMA) is a rare neuromuscular condition, characterized by loss of motor neurons as a result of a mutation in the survival motor neuron gene. This results in muscle wasting and in the most common and severe type, death before 24 months. Over the recent years there has been a dynamic shift in the therapeutic options for these patients involving both clinical trials in genetic modifying therapies to indirectly improve the survival motor neuron protein level and hence strength, muscle promotor therapies, up/down regulation of modifier genes and more recently gene therapy to replace the mutated survival motor neuron gene. This review addresses the pathogenesis of SMA and the resultant therapeutic approaches as well as the current state in clinical trials and future development.

Metabolomics-driven discoveries of biological samples remain hampered by the grand challenge of metabolite annotation and identification. Only few metabolites have an annotated spectrum in spectral libraries; hence, searching only for exact library matches generally returns a few hits. An attractive alternative is searching for so-called analogues as a starting point for structural annotations; analogues are library molecules which are not exact matches but display a high chemical similarity. However, current analogue search implementations are not yet very reliable and relatively slow. Here, we present MS2Query, a machine learning-based tool that integrates mass spectral embedding-based chemical similarity predictors (Spec2Vec and MS2Deepscore) as well as detected precursor masses to rank potential analogues and exact matches. Benchmarking MS2Query on reference mass spectra and experimental case studies demonstrate improved reliability and scalability. Thereby, MS2Query offers exciting opportunities to further increase the annotation rate of metabolomics profiles of complex metabolite mixtures and to discover new biology.

Genel olarak biyoloji bilgisinin bilgisayar aracılığıyla incelenmesi ve işlenmesi olarak tanımlanabilen biyoinformatik günümüzde hızla gelişen bir bilim dalıdır. Biyoinformatik, biyoteknoloji, sağlık, tarım, kimya, genom araştırmaları ve çok sayıda alanda giderek artan uygulamalarıyla dünyada biyoloji öğretiminin önemli bir parçası hâline gelmektedir. Bu bakımdan Türkiye'de biyoinformatik konusunda yetişmiş insan alt yapısının oluşturulması açısından öğretmen adaylarının konuya ilişkin görüşlerinin belirlenmesi önem kazanmaktadır. Bu araştırmanın amacı biyoloji öğretmen adaylarının biyoinformatik ve öğretimi konusunda görüşlerinin incelenmesidir. Nitel araştırma yöntemlerinden bütüncül tek durum deseninin kullanıldığı araştırmanın çalışma grubunu, bir devlet üniversitesinin eğitim fakültesi ve pedagojik formasyon programlarında öğrenimlerine devam eden 105 biyoloji öğretmen adayı oluşturmaktadır. Araştırmanın verileri ilgili alanyazın taramaları ve uzman görüşlerinin alınması aşamalarından sonra araştırmacılar tarafından geliştirilen yarı yapılandırılmış görüşme formu kullanılarak elde edilmiştir. Araştırma sonucunda elde edilen veriler betimsel ve içerik analizi bir arada kullanılarak çözümlenmiştir. Araştırma sonunda elde edilen sonuçlara göre öğretmen adaylarının konuya ilişkin olumlu görüşlere sahip olmalarının yanında, yeterli teorik ve uygulama bilgilerinin olmadığı belirlenmiştir. Bu kapsamda biyoinformatik eğitiminin mevcut öğretim programlarına entegrasyonu, ders içerikleri ve materyallerin oluşturulması önerilmektedir., Bioinformatics, which is generally defined as the study and processing of biology information through computers, is a rapidly developing scientific field today. It is becoming an important part of biology education worldwide with its increasing applications in biotechnology, health, agriculture, chemistry, genome research, and many other fields. Therefore, it is important to determine the views of teacher candidates on bioinformatics in Turkey in terms of creating a human infrastructure trained in the field. The purpose of this research is to examine the views of pre-service biology teachers’ on bioinformatics and its instruction. The study group of the research, which uses the holistic single case design among the qualitative research methods, consists of 105 pre-service biology teachers who are studying at the Faculty of Education and pedagogical formation programs of a state university. The data of the research were obtained using a semi-structured interview form developed by the researchers after the relevant literature search and obtaining expert opinions. The data obtained as a result of the research were analyzed by using descriptive and content analysis together. According to the results obtained at the end of the research, it was determined that the pre-service teachers did not have sufficient theoretical and practical knowledge, besides having positive views on the subject. Within this scope, it is recommended to integrate bioinformatics education into existing curricula, and to create learning contents and materials accordingly.

In this recent publication review the authors aimed to collect evidence of impact of nonsynonymous single nucleotide polymorphisms (nsSNP) in the renin–angiotensin–aldosterone system on patients’ phenotype not only regarding arterial hypertension and its complications, but also the impact on other diseases of interest outside the field of cardiovascular medicine. PubMed database records published between 2017–2020 were searched and all positive case-control studies or positive studies with human DNA were selected. The search identified 104 articles, of which 22 were included on the basis of the inclusion criteria. This paper presents the impact of 44 nsSNPs in panels for genes of renin, angiotensinogen, angiotensin-converting enzyme, angiotensin receptor and aldosterone on the clinical picture of investigated cohorts or on the peptide-protein interactions as consequence of nsSNPs. Genetic variability in nsSNPs of the RAAS is involved in the pathogenesis of arterial hypertension and its complications, and surprisingly also in the pathogenesis of conditions not associated with elevated blood pressure, like neoplasms or inflammatory diseases.

Introduction Adolescent idiopathic scoliosis (AIS) is a multifactorial condition with genetic predisposing factors, and several causes have been put forward for its aetiopathogenesis, including possible hormonal dysfunction. Melatonin seems to play significant role in AIS. Methods A systematic search in different database, to July 2021, was performed to define the role of melatonin in the pathophysiology of adolescent idiopathic scoliosis. Eight suitable studies were identified. Results The concentration and rhythm of melatonin secretion can play an important role by influencing the pathogenesis of adolescent idiopathic scoliosis. Conclusions Although there are many alterations of melatonin in subjects with adolescent idiopathic scoliosis, the many variables present do not allow to establish a direct cause–effect relationship. Level of evidence Level IV.

Inflammation is a natural process that occurs in the organism in response to harmful external agents. Despite being considered beneficial, exaggerated cases can cause severe problems for the body. The main inflammatory manifestations are pain, increased temperature, edema, decreased mobility, and quality of life for affected individuals. Diseases such as arthritis, cancer, allergies, infections, arteriosclerosis, neurodegenerative diseases, and metabolic problems are mainly characterized by an exaggerated inflammatory response. Inflammation is related to two categories of substances: pro- and anti-inflammatory mediators. Among the pro-inflammatory mediators is Tumor Necrosis Factor-α (TNF-α). It is associated with immune diseases, cancer, and psychiatric disorders which increase its excretion. Thus, it becomes a target widely used in discovering new antiinflammatory drugs. In this context, secondary metabolites biosynthesized by plants have been used for thousands of years and continue to be one of the primary sources of new drug scaffolds against inflammatory diseases. To decrease costs related to the drug discovery process, Computer-Aided Drug Design (CADD) techniques are broadly explored to increase the chances of success. In this review, the main natural compounds derived from alkaloids, flavonoids, terpene, and polyphenols as promising TNF-α inhibitors will be discussed. Finally, we applied a molecular modeling protocol involving all compounds described here, suggesting that their interactions with Tyr59, Tyr119, Tyr151, Leu57, and Gly121 residues are essential for the activity. Such findings can be useful for research groups worldwide to design new anti-inflammatory TNF-α inhibitors.

Convergent evolution has been described for several metabolic pathways across the kingdoms of life. However, there is hitherto no evidence for such an interkingdom process for antimicrobials. A new report suggests that marine animals have evolved the ability to biosynthesize antimicrobial polyketides, in parallel with bacteria.

Strains belonging to the Weissella genus are frequently recovered from spontaneously fermented foods. Their functional, microbial-modulating, and probiotic traits enhance not only the sensorial properties but also the nutritional value, beneficial effects, and safety of fermented products. Sporadic cases of opportunistic pathogenicity and antibiotic resistance have deprived safety status from all Weissella species, which thus remain understudied. Our study increased the number of available high-quality and taxonomically accurate W. paramesenteroides genomes by 25% (9 genomes reported, leading to a total of 36 genomes). We conducted a phylogenetic and comparative genomic analysis of the most dominant Weissella species (W. cibaria, W. paramesenteroides, W. viridescens, W. soli, W. koreensis, W. hellenica and W. thailadensis). The phylogenetic tree corroborated species assignment but also revealed phylogenetic diversity within the Weissella species, which is likely related to the adaptation of Weissella in different niches. Using robust alignment criteria, we showed the overall absence of resistance and virulence genes in Weissella spp., except for one W. cibaria isolate carrying blaTEM-181. Enrichment analysis showed the association of Weissella species several CAZymes, which are essential for biotechnological applications. Additionally, the combination of CAZyme metabolites with probiotics can potentially lead to beneficial effects for hosts, such as the inhibition of inflammatory processes and the reduction of cholesterol levels. Bacteriocins and mobile genetic elements MGEs (Inc11 plasmid and ISS1N insertion sequence) were less abundant, however W. thailadensis and W. viridescens showed significant association with specific bacteriocin-encoding genes. Lastly, an analysis of phenotypic traits underlined the need to carefully evaluate W. cibaria strains before use as food additives and suggested the possibility of employing W. paramesenteroides and W. hellenica in the fermentation process of vegetable products. More studies providing high-resolution characterization of Weissella strains from various sources are necessary to elucidate the safety of Weissella spp. and exploit their beneficial characteristics.

The interaction between gut microbes and gastrointestinal (GI) tract carcinogenesis has always attracted researchers' attention to identify therapeutic targets or potential prognostic biomarkers. Various studies have suggested that the microbiota do show inflammation and immune dysregulation, which led to carcinogenesis in GI tract. In this review, we have focused on the role of microbes present in the gut, intestine, or faeces in GI tract cancers, including esophageal cancer, gastric cancer, and colorectal cancer. Herein, we have discussed the importance of the microbes and their metabolites, which could serve as diagnostic biomarkers for cancer detection, especially in the early stage, and prognostic markers. To maximize the effect of the treatment strategies, an accurate evaluation of the prognosis is imperative for clinicians. There is a vast difference in the microbiota profiles within a population and across the populations depending upon age, diet, lifestyle, genetic makeup, use of antibiotics, and environmental factors. Therefore, the diagnostic efficiency of the microbial markers needs to be further validated. A deeper understanding of the GI cancer and the host microbiota is needed to acquire pivotal information about disease status.

Significance: Nonhealing wounds are a significant burden for the health care system all over the world. Existing treatment options are not enough to promote healing, highlighting the urgent need for improved therapies. In addition, the current advancements in tissue-engineered skin constructs and stem cell-based therapies are facing significant hurdles due to the absence of a renewable source of functional cells. Recent Advances: Induced pluripotent stem cell technology (iPSC) is emerging as a novel tool to develop the next generation of personalized medicine for the treatment of chronic wounds. The iPSC provides unlimited access to various skin cells to generate complex personalized three-dimensional skin constructs for disease modeling and autologous grafts. Furthermore, the iPSC-based therapies can target distinct wound healing phases and have shown accelerating wound closure by enhancing angiogenesis, cell migration, tissue regeneration, and modulating inflammation. Critical Issues: Since the last decade, iPSC has been revolutionizing the field of wound healing and skin tissue engineering. Despite the current progress, safety and heterogeneity among iPSC lines are still major hurdles in addition to the lack of large animal studies. These challenges need to be addressed before translating an iPSC-based therapy to the clinic. Future Directions: Future considerations should be given to performing large animal studies to check the safety and efficiency of iPSC-based therapy in a wound healing setup. Furthermore, strategies should be developed to overcome variation between hiPSC lines, develop an efficient manufacturing process for iPSC-derived products, and generate complex skin constructs with vasculature and skin appendages.

Pancreatic carcinoma is associated with one of the worst clinical outcomes throughout the globe because of its aggressive, metastatic, and drug-resistant nature. During the past decade, several studies have shown that oral, gut, and tumor microbiota play a critical role in the modulation of metabolism and immune responses. Growing pieces of evidence have proved beyond a doubt that the microbiota has a unique ability to influence the tumor microenvironment as well as the metabolism of chemotherapeutic agents or drugs. Given this, microbiota, known as the ecological community of microorganisms, stands to be an avenue of quality research. In this review, we provide detailed and critical information on the role of oral, gut, and pancreatic microbiota disruptions in the development of pancreatic carcinoma. Moreover, we comprehensively discuss the different types of microbiota, their potential role, and mechanism associated with pancreatic carcinoma. The microbiome provides the unique opportunity to enhance the effectiveness of chemotherapeutic agents and immunotherapies for pancreatic cancer by maintaining the right type of microbiota and holds a promising future to enhance the clinical outcomes of patients with pancreatic carcinoma.

The active role of bacteria in oncogenesis has long been a topic of debate. Although, it was speculated to be a transmissible cause of cancer as early as the 16th-century, yet the idea about the direct involvement of bacteria in cancer development has only been explored in recent decades. More recently, several studies have uncovered the mechanisms behind the carcinogenic potential of bacteria which are inflammation, immune evasion, pro-carcinogenic metabolite production, DNA damage and genomic instability. On the other side, the recent development on the understanding of tumor microenvironment and technological advancements has turned this enemy into an ally. Studies using bacteria for cancer treatment and detection have shown noticeable effects. Therapeutic abilities of bioengineered live bacteria such as high specificity, selective cytotoxicity to cancer cells, responsiveness to external signals and control after ingestion have helped to overcome the challenges faced by conventional cancer therapies and highlighted the bacterial based therapy as an ideal approach for cancer treatment. In this review, we have made an effort to compile substantial evidence to support the multidimensional role of bacteria in cancer. We have discussed the multifaceted role of bacteria in cancer by highlighting the wide impact of bacteria on different cancer types, their mechanisms of actions in inducing carcinogenicity, followed by the diagnostic and therapeutic potential of bacteria in cancers. Moreover, we have also highlighted the existing gaps in the knowledge of the association between bacteria and cancer as well as the limitation and advantage of bacteria-based therapies in cancer. A better understanding of these multidimensional roles of bacteria in cancer can open up the new doorways to develop early detection strategies, prevent cancer, and develop therapeutic tactics to cure this devastating disease.

Gut microbes (GMs), dominated by bacteria, play important roles in many physiological processes. The structures and functions of GMs are closely related to human health, the occurrence and development of diseases and the rapid recovery of the body. Gastrointestinal cancers are the major diseases affecting human health worldwide. With the development of metagenomic technology and the wide application of new generation sequencing technology, a large number of studies suggest that complex GMs are related to the occurrence and development of gastrointestinal cancers. Fecal microbiota transplantation (FMT) and probiotics can treat and prevent the occurrence of gastrointestinal cancers. This article reviews the latest research progress of microbes in gastrointestinal cancers from the perspectives of the correlation, the influence mechanism and the application, so as to provide new directions for the prevention, early diagnosis and treatment of gastrointestinal cancers.

Cancer is one of the leading global causes of death in both men and women. Colorectal cancer (CRC) alone accounts for ∼10 % of total new global cases and poses an over 4% lifetime risk of developing cancer. Recent advancements in the field of biotechnology and microbiology concocted novel microbe-based therapies to treat various cancers, including CRC. Microbes have been explored for human use since centuries, especially for the treatment of various ailments. The utility of microbes in cancer therapeutics is widely explored, and various bacteria, fungi, and viruses are currently in use for the development of cancer therapeutics. The human gut hosts about 100 trillion microbes that release their metabolites in active, inactive, or dead conditions. Microbial secondary metabolites, proteins, immunotoxins, and enzymes are used to target cancer cells to induce cell cycle arrest, apoptosis, and death. Various approaches, such as dietary interventions, the use of prebiotics and probiotics, and fecal microbiota transplantation have been used to modulate the gut microbiota in order to prevent or treat CRC pathogenesis. The present review highlights the role of the gut microbiota in CRC precipitation, the potential mechanisms and use of microorganisms as CRC biomarkers, and strategies to modulate microbiota for the prevention and treatment of CRC.

The intentional use of viruses for cancer therapy dates back over a century. As viruses are inherently immunogenic and naturally optimized delivery vehicles, repurposing viruses for drug delivery, tumor antigen presentation, or selective replication in cancer cells represents a simple and elegant approach to cancer treatment. While early virotherapy was fraught with harsh side effects and low response rates, virus-based therapies have recently seen a resurgence due to newfound abilities to engineer and tune oncolytic viruses, virus-like particles, and virus-mimicking nanoparticles for improved safety and efficacy. However, despite their great potential, very few virus-based therapies have made it through clinical trials. In this review, we present an overview of virus-inspired approaches for cancer therapy, discuss engineering strategies to enhance their mechanisms of action, and highlight their application for overcoming the challenges of traditional cancer therapies.

Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are ‘variants of uncertain significance’. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can ‘tolerate’ missense variants and which ones are ‘essential’ and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins.

Contains fulltext : 286883.pdf (Publisher’s version ) (Open Access) The levels of the thousands of metabolites in the human plasma metabolome are strongly influenced by an individual's genetics and the composition of their diet and gut microbiome. Here, by assessing 1,183 plasma metabolites in 1,368 extensively phenotyped individuals from the Lifelines DEEP and Genome of the Netherlands cohorts, we quantified the proportion of inter-individual variation in the plasma metabolome explained by different factors, characterizing 610, 85 and 38 metabolites as dominantly associated with diet, the gut microbiome and genetics, respectively. Moreover, a diet quality score derived from metabolite levels was significantly associated with diet quality, as assessed by a detailed food frequency questionnaire. Through Mendelian randomization and mediation analyses, we revealed putative causal relationships between diet, the gut microbiome and metabolites. For example, Mendelian randomization analyses support a potential causal effect of Eubacterium rectale in decreasing plasma levels of hydrogen sulfite-a toxin that affects cardiovascular function. Lastly, based on analysis of the plasma metabolome of 311 individuals at two time points separated by 4 years, we observed a positive correlation between the stability of metabolite levels and the amount of variance in the levels of that metabolite that could be explained in our analysis. Altogether, characterization of factors that explain inter-individual variation in the plasma metabolome can help design approaches for modulating diet or the gut microbiome to shape a healthy metabolome.

There is an increase in the incidence of cardiovascular diseases with aging and it is one of the leading causes of death worldwide. The main cardiovascular pathologies include atherosclerosis, myocardial infarction, hypertension and stroke. Chronic inflammation is one of the significant contributors to the age-related vascular diseases. Therefore, it is important to understand the molecular mechanisms of the persistent inflammatory conditions occurring in the blood vessels as well as the signaling pathways involved. Herein, we performed an extant search of literature involving PubMed, ISI, WoS and Scopus databases for retrieving all relevant articles with the most recent findings illustrating the potential role of various inflammatory mediators along with their proposed activated pathways in the pathogenesis and progression of vascular aging. We also highlight the major pathways contributing to age-related vascular disorders. The outlined molecular mechanisms, pathways and mediators of vascular aging represent potential drug targets that can be utilized to inhibit and/or slow the pathogenesis and progression of vascular aging.

Chronic, non-healing, dermal wounds form a worldwide medical problem with limited and inadequate treatment options and high societal burden and costs. With the advent of regenerative therapies exploiting extracellular matrix (ECM) components, its efficacy to augment wound healing is to be explored. This systematic review was performed to assess and compare the current therapeutic efficacy of ECM hydrogels on dermal wound healing. The electronic databases of Embase, Medline Ovid, and Cochrane Central were searched for in vivo and clinical studies on the therapeutic effect of ECM-composed hydrogels on dermal wound healing (April 13, 2021). Two reviewers selected studies independently. Studies were assessed based on ECM content, ECM hydrogel composition, additives, and wound healing outcomes, such as wound size, angiogenesis, and complications. Of the 2102 publications, 9 rodent-based studies were included while clinical studies were not published at the time of the search. Procedures to decellularize tissue or cultured cells and subsequently generate hydrogels were highly variable and in demand of standardization. ECM hydrogels with or without additives reduced wound size and also seem to enhance angiogenesis. Serious complications were not reported. To date, preclinical studies preclude to draw firm conclusions on the efficacy and working mechanism of ECM-derived hydrogels on dermal wound healing. The use of ECM hydrogels can be considered safe. Standardization of decellularization protocols and implementation of quality and cytotoxicity controls will enable obtaining a generic and comparable ECM product. Impact statementExtracellular matrix (ECM)-based hydrogels are biocompatible and harbor growth factors that can instruct tissue healing. Their application is a novelty in (pre)clinical wound healing treatment. This systematic review provides an overview of the current evidence for ECM hydrogels in enhancing wound healing and an extensive overview of the decellularization procedures used. Lastly, challenges and future directions to standardize decellularization procedures and implement quality controls are proposed.

Clozapine-induced myocarditis or any clozapine-induced inflammation may be a hypersensitivity reaction due to titration that was too rapid for the patient's clozapine metabolism. Clozapine metabolism is influenced by ancestry, sex, smoking and the presence of confounders including obesity, infections, and inhibitors (e.g., valproate) causing the patient to behave as a clozapine poor metabolizer (PM). A published study in a Turkish hospital identified 1 case of clozapine-induced pancreatitis and hepatitis and 9 cases of clozapine-induced myocarditis. To explore the hypothesis that the 10 patients were clozapine PMs, their serum clozapine concentrations were investigated using concentration-to-dose (C/D) ratios and their titrations carefully reviewed.Dividing the trough serum concentration by the dose produces the clozapine C/D ratio. The dose required to reach 350ng/ml was considered the minimum therapeutic dosage and was used to classify patients according to clozapine PM status. Titration speed was assessed.All 10 patients were possibly clozapine PMs (3 of them had as minimum therapeutic doses: 72, 82 or 83mg/day). Nine of the 10 patients may have behaved as clozapine PMs due to obesity and/or valproate co-prescription during titration. One also had an undiagnosed infection. Of the 10 patients, 9 had at least 1 of 3 factors: too-rapid titration in the first or second weeks, or a final dosage that was too high.Future studies using clozapine levels and considering the role of clozapine PM status should explore whether or not all cases of clozapine-induced inflammation could be explained by lack of individualized titration.

[EN] Growth and development of hair follicles (HF) is a complex and dynamic process in most mammals. As HF growth and development regulate rabbit wool yield, exploring the role of genes involved in HF growth and development may be relevant. In this study, the coding sequence of the Angora rabbit (Oryctolagus cuniculus) WIF1 gene was cloned. The length of the coding region sequence was found to be 1140 bp, which encodes 379 amino acids. Bioinformatics analysis indicated that the WIF1 protein was unstable, hydrophilic and located in the extracellular region, contained a putative signal peptide and exhibited a high homology in different mammals. Moreover, WIF1 was significantly downregulated in the high wool production in the Angora rabbit group. Overexpression and knockdown studies revealed that WIF1 regulates HF growth and development-related genes and proteins, such as LEF1 and CCND1. WIF1 activated β-catenin/TCF transcriptional activity, promoted cell apoptosis and inhibited cellular proliferation. These results indicate that WIF1 might be important for HF development. This study, therefore, provides a theoretical foundation for investigating WIF1 in HF growth and development., This research was funded by This research was funded by National Natural Science Foundation of China (Grant No. 32102529), China Agriculture Research System of MOF and MARA (CARS-43-A-1).

Potato is an industrial plant that is produced and consumed globally due to its cheapness, high yield in the unit area, high nutritional values. It is used in many different fields. It has been stated that wild species with various characteristics can be used in studies to increase productivity because they have greater rate of genetic variation than their domesticated relatives. One of the wild species of potato found in nature is S. commersonii Dunal. It is more resistant to many stresses than cultivated potato S. tuberosum L. Also, its tuber has better quality due to the fact that it contains a higher proportion of dry matter. With the aim of determining the effects of miRNAs in tuber production and root characteristics relation we aimed to detect miRNAs in two transcriptome libraries of S. commersonii. In this study miRNAs were evaluated for the first time in the wild potato transcriptome data using in silico analysis. A number of miRNAs were identified, and their potential roles in tuber were discussed.

Background: Pulmonary hypertension (PH) is a complex disease caused by a wide range of underlying conditions, Tanshinone IIA (Tan IIA) has been widely used in PH patients. The study aimed to explore the possible molecular mechanism of Tan IIA against PH by network pharmacology and molecular docking. Methods: Tan IIA and PH-related targets were retrieved from public databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein–protein interaction (PPI) network were used to investigate the protein targets and mechanism. The binding activity of core targets and Tan IIA were verified by molecular docking. Results: A total of 26 overlapping target proteins between Tan IIA and PH were screened. PPI network identified HSP90AA1, PTPN11, ATM, CA2, TERT, PRKDC, and APEX1 as key pharmacological targets. The results of GO function enrichment analysis included regulation of smooth muscle cell proliferation and migration, regulation of mitotic cell cycle, and regulation of G1/S transition of mitotic cell cycle. KEGG pathway analysis showed that nitrogen metabolism, NF-kappa B signaling pathway, cell cycle, necroptosis, apoptosis, and JAK-STAT signaling pathway were associated with Tan IIA in PH. The molecular docking results showed that Tan IIA can closely bind three core targets (HSP90AA1, PTPN11, and CA2). Conclusions: The present work initially clarified the effective therapeutic targets, biological processes, and signaling pathways of Tan IIA treatment of PH, which lay a foundation for further research on the pharmacological effects of Tan IIA.

Background: Stroke is a serious neurovascular problem and the leading cause of disability and death worldwide. The disrupted demand to supply ratio of blood and glucose during cerebral ischemia develops hypoxic shock, and subsequently necrotic neuronal death in the affected regions. Multiple causal factors like age, sex, race, genetics, diet, and lifestyle play an important role in the occurrence as well as progression of post-stroke deleterious events. These biological and environmental factors may be contributed to vasculature variable architecture and abnormal neuronal activity. Since recombinant tissue plasminogen activator is the only clinically effective clot bursting drug, there is a huge unmet medical need for newer therapies for the treatment of stroke. Innumerous therapeutic interventions have shown promise in the experimental models of stroke but failed to translate it into clinical counterparts. Methods: Original publications regarding pathophysiology, preclinical experimental models, new targets and therapies targeting ischemic stroke have been reviewed since the 1970s. Results: We highlighted the critical underlying pathophysiological mechanisms of cerebral stroke and preclinical stroke models. We discuss the strengths and caveats of widely used ischemic stroke models, and commented on the potential translational problems. We also describe the new emerging treatment strategies, including stem cell therapy, neurotrophic factors and gut microbiome-based therapy for the management of post-stroke consequences. Results : We highlighted the critical underlying pathophysiological mechanisms of cerebral stroke and preclinical stroke models. We discuss the strengths and caveats of widely used ischemic stroke models, and commented on the potential translational problems. We also describe the new emerging treatment strategies, including stem cell therapy, neurotrophic factors and gut microbiome-based therapy for the management of post-stroke consequences. Conclusion: There are still many inter-linked pathophysiological alterations with regards to stroke, animal models need not necessarily mimic the same conditions of stroke pathology and newer targets and therapies are the need of the hour in stroke research.

Melatonin is the main hormone involved in the control of the sleep-wake cycle. It is easily synthesisable and can be administered orally, which has led to interest in its use as a treatment for insomnia. Moreover, as production of the hormone decreases with age, in inverse correlation with the frequency of poor sleep quality, it has been suggested that melatonin deficit is at least partly responsible for sleep disorders. Treating this age-related deficit would therefore appear to be a natural way of restoring sleep quality, which is lost as patients age. However, despite the undeniable theoretical appeal of this approach to insomnia, little scientific evidence is available that supports any benefit of this substitutive therapy. Furthermore, the most suitable dose ranges and pharmaceutical preparations for melatonin administration are yet to be clearly defined. This review addresses the physiology of melatonin, the different pharmaceutical preparations, and data on its clinical usefulness.

Acute Lung Injury (ALI) and its severe form Acute Respiratory Distress Syndrome (ARDS) are the major cause of ICU death worldwide. ALI/ARDS is characterized by severe hypoxemia and inflammation that leads to poor lung compliance. Despite many advances in understanding and management, ALI/ARDS is still causing significant morbidity and mortality. Long non-coding RNA (lncRNA) is a fast-growing topic in lung inflammation and injury. lncRNA is a class of non-coding RNA having a length of more than 200 nucleotides. It has been a center of research for understanding the pathophysiology of various diseases in the past few years. Multiple studies have shown that lncRNAs are abundant in acute lung injury/injuries in mouse models and cell lines. By targeting these long non-coding RNAs, many investigators have demonstrated the alleviation of ALI in various mouse models. Therefore, lncRNAs show great promise as a therapeutic target in ALI. This review provides the current state of knowledge about the relationship between lncRNAs in various biological processes in acute lung injury and its use as a potential therapeutic target.