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R.A. Fisher's 1922 paper On the dominance ratio has a strong claim to be the foundation paper for modern population genetics. It greatly influenced subsequent work by Haldane and Wright, and contributed 3 major innovations to the study of evolution at the genetic level. First, the introduction of a general model of selection at a single locus, which showed how variability could be maintained by heterozygote advantage. Second, the use of the branching process approach to show that a beneficial mutation has a substantial chance of loss from the population, even when the population size is extremely large. Third, the invention of the concept of a probability distribution of allele frequency, caused by random sampling of allele frequencies due to finite population size, and the first use of a diffusion equation to investigate the properties of such a distribution. Although Fisher was motivated by an inference that later turned out to lack strong empirical support (a substantial contribution of dominance to quantitative trait variability), and his use of a diffusion equation was marred by a technical mistake, the paper introduced concepts and methods that pervade much subsequent work in population genetics. [ABSTRACT FROM AUTHOR]

Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery. [ABSTRACT FROM AUTHOR]

Background: Hidradenitis suppurativa (HS) is a complex, chronic inflammatory skin disorder whose pathophysiology is poorly understood. Genetic studies have shown that HS is predisposed by mutations in the γ-secretase gene, but only a proportion of familial and partial sporadic cases have been shown to possess such mutations. HS has high genetic heterogeneity and is thought to be triggered by a combination of genetics and environmental factors. Aims: The study aimed to investigate the genetic causes of HS in a large cohort of patients and to update the mutation spectrum of γ-secretase complex genes. Methods: We conducted mutational screening of 95 sporadic HS cases and one large family with both HS and acne conglobata (AC) to identify mutations in the coding and splice junction region of γ-secretase complex genes (nicastrin (NCSTN), presenilin 1 (PSEN1), presenilin enhancer 2 (PSENEN), and aph-1 homolog B, gamma-secretase subunit (APH1B)). Results: Our study identified a nucleotide substitution of 1876C>T in the NCSTN gene, which caused a stop codon (p. Arg626X) in the affected members of a large family with HS and AC. No pathogenic variants were detected in 95 sporadic cases of HS, indicating there is possible genetic heterogeneity. Conclusion: We report a new family with a nonsense mutation in the NCSTN gene that supports the role of the γ-secretase complex genes in HS with AC. The updated γ-secretase mutation spectrum for HS now includes 78 mutations. [ABSTRACT FROM AUTHOR]

Sickle cell disease (SCD) is a lethal, life-long condition characterized by a mutation in the gene that codes for hemoglobin. To alleviate the pain experienced by sickle cell (SC) patients, adequate nutrition levels are vital as deficiencies of vitamins or minerals may cause other symptoms. This review aims to provide an overview of the nutrient status of SC patients and propose research areas where further study is required. The review summarizes twelve primary research papers that assessed the levels of vitamins A, C, D, E, B-2, B-6, B-12, folate, magnesium, iron, zinc, and copper in SC patients. Most SC patients exhibited suboptimal levels of vitamin A, while deficiencies in vitamin D and B-2 were prevalent. Their zinc and vitamins B-6, B-12, C, and E levels were generally adequate, while elevated folate and copper levels were observed. The magnesium levels in SC patients were lower than those in the healthy population. Determining the status of iron concentration in SC patients was challenging due to the limitations associated with the measurement methods employed in the reviewed papers. There were notable differences in some of the measurement methods used for the same nutrient levels. More research is needed to find the optimal amount of vitamin A supplement for SC patients. The effect of zinc supplementation on copper levels and the cause of low zinc levels in SC patients remains unexplored. [ABSTRACT FROM AUTHOR]

In the past 20 years, targeted therapy for cholangiocarcinoma has attracted certain attention. There is a significant upward in papers focusing on this field. In this study, we used bibliometric and visual methods to explore the current status and future directions in cholangiocarcinoma-targeted therapy research. A total of 1057 papers published in English from 2003 to 2022 were extracted from the Web of Science Core Collection SCI-expanded database. Furthermore, Citespace, Vosviewer, and Excel 2016 were utilized to conduct bibliometric and visual analysis. The volume of annual publications has steadily increased over the past two decades. The USA has published the largest number of publications, and the Mayo Clinic acted as the dominant institution. Cancers, Frontiers in Oncology, and Hepatology were the prolific resources in this research field. Moreover, the co-cited reference analysis uncovered the landmark paper in this field. With regard to research hotspots and frontiers, the burst keywords analysis showed that growth factor receptors and pathogenesis might become the hot topics of future research. To sum up, our study displays the current research status and future directions in the targeted therapy for cholangiocarcinoma. More comprehensive and in-depth investigations should focus on critical genetic mutations and their molecular mechanisms to prompt the molecular-targeted therapy. [ABSTRACT FROM AUTHOR]

Background: Mutations in PDE6A and PDE6B are known to cause autosomal recessive RP in humans, On the other hand, mutations in PDE6G are rare but can lead to severe early-onset RP. Case presentation: An 8-year-old Chinese boy was referred to our hospital for poor vision issues. Refraction with cycloplegia showed high hyperopia with astigmatism both eyes. Funduscopic examination revealed typical bone spicule-type pigment deposits in the periphery and midperiphery. The patient was given glasses and a whole exome sequencing containing mitochondrial genes was performed. The results of genetic testing showed that there was a heterozygous frameshift mutation and a segment deletion in the proband's PDE6G gene. Analysis of the parental genes showed that frameshift mutation was inherited from the proband's mother and segment deletion from his father. Conclusions: In this paper, we give a firsthand report that the complex heterozygous mutations of PDE6G gene can causes autosomal recessiveRP (arRP), which expands the understanding of the pathogenic genes of RP. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, affecting millions each year. It emerges from the colon or rectum, parts of the digestive system, and is closely linked to both genetic and environmental factors. In CRC, genetic mutations such as APC, KRAS, and TP53, along with epigenetic changes like DNA methylation and histone modifications, play crucial roles in tumor development and treatment responses. This paper delves into the complex biological underpinnings of CRC, highlighting the pivotal roles of genetic alterations, cell death pathways, and the intricate network of signaling interactions that contribute to the disease's progression. It explores the dysregulation of apoptosis, autophagy, and other cell death mechanisms, underscoring the aberrant activation of these pathways in CRC. Additionally, the paper examines how mutations in key molecular pathways, including Wnt, EGFR/MAPK, and PI3K, fuel CRC development, and how these alterations can serve as both diagnostic and prognostic markers. The dual function of autophagy in CRC, acting as a tumor suppressor or promoter depending on the context, is also scrutinized. Through a comprehensive analysis of cellular and molecular events, this research aims to deepen our understanding of CRC and pave the way for more effective diagnostics, prognostics, and therapeutic strategies. Highlights: Colorectal cancer (CRC) is one of the leading causes of death among patients. CRC has been characterized with changes at the genetic and epigenetic factors. The molecular factors can be used as diagnostic and prognostic factors in CRC. The cell death mechanisms demonstrate dysregulation in CRC. Autophagy has aberrant activation in CRC and exerts dual function. [ABSTRACT FROM AUTHOR]

Objective: In this paper we report how the United Kingdom's National Institute for Health and Care Excellence (NICE) search filters for treating and managing COVID-19 were validated for use in MEDLINE (Ovid) and Embase (Ovid). The objective was to achieve at least 98.9% for recall and 64% for precision. Methods: We did two tests of recall to finalize the draft search filters. We updated the data from an earlier peer-reviewed publication for the first recall test. For the second test, we collated a set of systematic reviews from Epistemonikos COVID-19 L.OVE and extracted their primary studies. We calculated precision by screening all the results retrieved by the draft search filters from a targeted sample covering 2020-23. We developed a gold-standard set to validate the search filter by using all articles available from the "Treatment and Management" subject filter in the Cochrane COVID-19 Study Register. Results: In the first recall test, both filters had 99.5% recall. In the second test, recall was 99.7% and 99.8% in MEDLINE and Embase respectively. Precision was 91.1% in a deduplicated sample of records. In validation, we found the MEDLINE filter had recall of 99.86% of the 14,625 records in the gold-standard set. The Embase filter had 99.88% recall of 19,371 records. Conclusion: We have validated search filters to identify records on treating and managing COVID-19. The filters may require subsequent updates, if new SARS-CoV-2 variants of concern or interest are discussed in future literature. [ABSTRACT FROM AUTHOR]

KRAS is a pathogenic gene frequently implicated in non-small cell lung cancer (NSCLC). However, biopsy as a diagnostic method has practical limitations. Therefore, it is important to accurately determine the mutation status of the KRAS gene non-invasively by combining NSCLC CT images and genetic data for early diagnosis and subsequent targeted therapy of patients. This paper proposes a Semi-supervised Multimodal Multiscale Attention Model (S2MMAM). S2MMAM comprises a Supervised Multilevel Fusion Segmentation Network (SMF-SN) and a Semi-supervised Multimodal Fusion Classification Network (S2MF-CN). S2MMAM facilitates the execution of the classification task by transferring the useful information captured in SMF-SN to the S2MF-CN to improve the model prediction accuracy. In SMF-SN, we propose a Triple Attention-guided Feature Aggregation module for obtaining segmentation features that incorporate high-level semantic abstract features and low-level semantic detail features. Segmentation features provide pre-guidance and key information expansion for S2MF-CN. S2MF-CN shares the encoder and decoder parameters of SMF-SN, which enables S2MF-CN to obtain rich classification features. S2MF-CN uses the proposed Intra and Inter Mutual Guidance Attention Fusion (I2MGAF) module to first guide segmentation and classification feature fusion to extract hidden multi-scale contextual information. I2MGAF then guides the multidimensional fusion of genetic data and CT image data to compensate for the lack of information in single modality data. S2MMAM achieved 83.27% AUC and 81.67% accuracy in predicting KRAS gene mutation status in NSCLC. This method uses medical image CT and genetic data to effectively improve the accuracy of predicting KRAS gene mutation status in NSCLC. [ABSTRACT FROM AUTHOR]

To date, the role of NODAL in normal and abnormal L-R asymmetry has been well established. In a recent paper, mutations of this gene have been reported in heterotaxy but also in transposition with D- or L-ventricular loop. The effects of NODAL and other laterality genes can be recognized separately in all three cardiac segments: for topology and septation of the atria, for ventricular looping, and for spiralization and alignment of the great arteries. [ABSTRACT FROM AUTHOR]

Simple Summary: Biliary tract malignancies, including cholangiocarcinoma (CCA) and gallbladder neoplasms, present intricate challenges in diagnosis and treatment. This comprehensive overview highlights the diversity of CCA subtypes, their genetic underpinnings, and the pivotal role of etiological factors. Despite diagnostic complexities, advancements in genomic sequencing reveal promising therapeutic targets, such as FGFR2 alterations and IDH1 mutations. Dr. James Cleary's insights underscore the potential of these targets in reshaping the treatment landscape. This paper provides insights into the conventional understanding of biliary tract malignancies and emphasizes the critical need for ongoing research to optimize outcomes in this challenging cancer subtype. By elucidating diverse FGFR2 alterations and the potential of IDH1 inhibition, the aim is to pave the way for targeted therapeutic interventions. As we delve deeper into understanding the intricate complexities of biliary tract malignancies, this research seeks to drive precision medicine forward, offering hope for improved treatment strategies and outcomes in the face of this formidable cancer. This paper provides insights into the conventional understanding of biliary tract malignancies, with a specific focus on cholangiocarcinoma (CCA). We then delve into the groundbreaking ideas presented by Dr. James Cleary. CCA, originating from biliary tree cells, manifests diverse subtypes contingent upon anatomical localization and differentiation status. These variants exhibit discrete genetic aberrations, yielding disparate clinical phenotypes and therapeutic modalities. Intrahepatic, perihilar, and distal CCAs intricately involve distinct segments of the biliary tree, further categorized as well-differentiated, moderately differentiated, or poorly differentiated adenocarcinomas based on their histological differentiation. Understanding the etiological factors contributing to CCA development assumes paramount importance. Stratifying these factors into two groups, those unrelated to fluke infestations (e.g., viral hepatitis and fatty liver conditions) and those associated with fluke infestations (e.g., chronic liver inflammation), facilitates predictive modeling. The epidemiology of CCA exhibits global variability, with Southeast Asia notably displaying higher incidences attributed primarily to liver fluke infestations. Jaundice resulting from bile duct obstruction constitutes a prevalent clinical manifestation of CCA, alongside symptoms like malaise, weight loss, and abdominal pain. Diagnostic challenges arise due to the symptomatic overlap with other biliary disorders. Employing comprehensive liver function tests and imaging modalities such as computed tomography assumes a pivotal role in ensuring accurate diagnosis and staging. However, the definitive confirmation of CCA necessitates a biopsy. Treatment modalities, predominantly encompassing surgical resection and radiation therapy, hold curative potential, although a considerable subset of patients is deemed unresectable upon exploration. Challenges intensify, particularly in cases classified as cancer of unknown origin, underscoring the imperative for early intervention. Advancements in genomic sequencing have revolutionized precision medicine in CCA. Distinct genomic markers, including fibroblast growth factor receptor 2 (FGFR2) alterations and isocitrate dehydrogenase 1 (IDH1) mutations, have emerged as promising therapeutic targets. FGFR2 alterations, encompassing mutations and rearrangements, play pivotal roles in oncogenesis, with FGFR inhibitors demonstrating promise despite identified resistance mechanisms. Similarly, IDH1 inhibitors face challenges with resistance, despite encouraging early clinical trial results, prompting exploration of novel irreversible inhibitors. Dr. James Cleary's illuminating discourse underscores the significance of diverse FGFR2 alterations and the potential of IDH1 inhibition in reshaping the treatment landscape for CCA. These findings unveil critical avenues for targeted therapeutic interventions, emphasizing the critical need for ongoing research to optimize outcomes in this challenging cancer subtype, incorporating innovative insights from Dr. Cleary. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper delves into the latest developments in the emerging therapies for cholangiocarcinoma, with a focus on precision medicine, immunotherapy, and targeted therapies. We explore the potential of genomic profiling to tailor treatments to individual patients, as well as the promising results of immunotherapeutic agents in clinical trials. Furthermore, we examine the role of specific molecular targets and their inhibitors in slowing disease progression. The findings discussed in this paper offer hope for improved outcomes and prolonged survival in cholangiocarcinoma patients using more effective and personalized treatment strategies. Cholangiocarcinoma is a heterogeneous group of biliary tract cancers that has a poor prognosis and globally increasing incidence and mortality. While surgical resection remains the only curative option for the treatment of cholangiocarcinoma, the majority of cancers are unresectable at the time of diagnosis. Additionally, the prognosis of cholangiocarcinoma remains poor even with the current first-line systemic therapy regimens, highlighting the difficulty of treating locally advanced, metastatic, or unresectable cholangiocarcinoma. Through recent developments, targetable oncogenic driver mutations have been identified in the pathogenesis of cholangiocarcinoma, leading to the utilization of molecular targeted therapeutics. In this review, we comprehensively discuss the latest molecular therapeutics for the treatment of cholangiocarcinoma, including emerging immunotherapies, highlighting promising developments and strategies. [ABSTRACT FROM AUTHOR]

Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid cancer ranks as the 5th most prevalent cancer in the USA, with thousands diagnosed annually. This paper presents an ensemble learning model leveraging deep learning techniques such as Long Short-Term Memory (LSTM), Gated Recurrent Units (GRUs), and Bi-directional LSTM (Bi-LSTM) to detect thyroid cancer mutations early. The model is trained on a dataset sourced from asia.ensembl.org and IntOGen.org, consisting of 633 samples with 969 mutations across 41 genes, collected from individuals of various demographics. Feature extraction encompasses techniques including Hahn moments, central moments, raw moments, and various matrix-based methods. Evaluation employs three testing methods: self-consistency test (SCT), independent set test (IST), and 10-fold cross-validation test (10-FCVT). The proposed ensemble learning model demonstrates promising performance, achieving 96% accuracy in the independent set test (IST). Statistical measures such as training accuracy, testing accuracy, recall, sensitivity, specificity, Mathew's Correlation Coefficient (MCC), loss, training accuracy, F1 Score, and Cohen's kappa are utilized for comprehensive evaluation. [ABSTRACT FROM AUTHOR]

Third-generation tyrosine kinase inhibitors are the first-line gold standard in treating advanced non-small-cell lung cancer bearing common EGFR mutations, but data documenting clinical efficacy in uncommon mutations are currently limited. In this paper, we describe the case of a patient bearing uncommon compound EGFR mutations in exon 20, who experienced a near-complete response to third-line Osimertinib, with metabolic complete response of pulmonary, nodal and ostheolytic lesions. This radiological assessment corresponded to an ECOG PS improvement (from three to one) and a substantial clinical benefit for the patients. Out of two mutations, S768I was associated with poor response to third-generation TKI and V774M had unknown clinical significance, highlighting the complexity of the correct management of these kinds of mutations. We reviewed the literature to document the up-to-date preclinical and clinical data concerning third-generation tyrosine kinase inhibitors for the treatment of patients bearing uncommon EGFR mutations. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer arises through the accumulation of somatic mutations in key biological pathways. This paper aims to develop a probabilistic approach to delineate the temporal order of mutations during cancer development based on mutation profile data from a cohort of patients. A unique feature of our method is that it incorporates intra-tumor heterogeneity (ITH) information, which refers to the heterogeneous cell populations within a tumor and characterizes the evolutionary history of the tumor. We showed that by integrating ITH, pathways, and functional annotation information, our method yielded high accuracy in inferring the temporal order of pathway mutations during carcinogenesis. The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types. [ABSTRACT FROM AUTHOR]

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations. [ABSTRACT FROM AUTHOR]

Enamel formation is a highly complex and regulated process. However, specific genetic mutations can cause dysregulation, resulting in defects in the enamel quantity, structure and composition. Inherited disorders such as amelogenesis imperfecta exclusively affect the formation of enamel. Nevertheless, enamel defects can also present as a feature of many inherited systemic diseases and syndromes. The defects present in a spectrum of mild to severe enamel pitting, mottling and loss of email, causing psychological and functional concerns for patients. Early diagnosis and intensive caries prevention along with a multidisciplinary specialist input are required in most cases. In this paper, we provide a comprehensive discussion of inherited enamel defects. [ABSTRACT FROM AUTHOR]

Over most of the 20th century, evolutionary biologists predominantly subscribed to a strong form of "micro‐mutationism," in which adaptive phenotypic divergence arises from allele frequency changes at many loci, each with a small effect on the phenotype. To be sure, there were well‐known examples of large‐effect alleles contributing to adaptation, yet such cases were generally regarded as atypical and unrepresentative of evolutionary change in general. In 1998, Allen Orr published a landmark theoretical paper in Evolution, which showed that both small‐ and large‐effect mutations are likely to contribute to "adaptive walks" of a population to an optimum. Coupled with a growing set of empirical examples of large‐effect alleles contributing to divergence (e.g., from QTL studies), Orr's paper provided a mathematical formalism that converted many evolutionary biologists from micro‐mutationism to a more pluralistic perspective on the genetic basis of evolutionary change. We revisit the theoretical insights emerging from Orr's paper within the historical context leading up to 1998, and track the influence of this paper on the field of evolutionary biology through an examination of its citations over the last two decades and an analysis of the extensive body of theoretical and empirical research that Orr's pioneering paper inspired. [ABSTRACT FROM AUTHOR]

In this paper, Mueller polarimetry is applied to study the three groups of common barley leaf samples (Hordeum vulgare) in the visible spectrum (λ = 632.8 nm): Chlorina mutant, Chlorina etiolated mutant and Cesaer varieties. These samples differed in internal leaf structure from genetic mutation or by illumination during growth. Our main concern is to discriminate and characterize these three groups of leaf samples by depolarization metrics: degree of polarization (DoP), average degree of polarization (Average DoP), depolarization index (DI(M)), and Q(M) and R(M) metrics. The results obtained show that all depolarization metrics are sensitive to the sample's polarization properties. The most effective observable is the Q(M) metric in both forward and backward scattering. The DoP metric showed presence of depolarization anisotropy, which is significantly different for forward and backward scattering for all three groups of samples. Dichroism is observed for both forward and backward scattering, with lower dichroism in forward scattering. [ABSTRACT FROM AUTHOR]

Background: Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies. Results: The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development. Conclusion: This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations. [ABSTRACT FROM AUTHOR]

Purpose. Artificial intelligence (AI) techniques are used in precision medicine to explore novel genotypes and phenotypes data. The main aims of precision medicine include early diagnosis, screening, and personalized treatment regime for a patient based on genetic-oriented features and characteristics. The main objective of this study was to review AI techniques and their effectiveness in neoplasm precision medicine. Materials and Methods. A comprehensive search was performed in Medline (through PubMed), Scopus, ISI Web of Science, IEEE Xplore, Embase, and Cochrane databases from inception to December 29, 2021, in order to identify the studies that used AI methods for cancer precision medicine and evaluate outcomes of the models. Results. Sixty-three studies were included in this systematic review. The main AI approaches in 17 papers (26.9%) were linear and nonlinear categories (random forest or decision trees), and in 21 citations, rule-based systems and deep learning models were used. Notably, 62% of the articles were done in the United States and China. R package was the most frequent software, and breast and lung cancer were the most selected neoplasms in the papers. Out of 63 papers, in 34 articles, genomic data like gene expression, somatic mutation data, phenotype data, and proteomics with drug-response which is functional data was used as input in AI methods; in 16 papers' (25.3%) drug response, functional data was utilized in personalization of treatment. The maximum values of the assessment indicators such as accuracy, sensitivity, specificity, precision, recall, and area under the curve (AUC) in included studies were 0.99, 1.00, 0.96, 0.98, 0.99, and 0.9929, respectively. Conclusion. The findings showed that in many cases, the use of artificial intelligence methods had effective application in personalized medicine. [ABSTRACT FROM AUTHOR]

In 1931, Hermann J. Muller's postdoctoral student, George D. Snell (Nobel Prize recipient––1980) initiated research to replicate with mice Muller's X-ray-induced mutational findings with fruit flies. Snell failed to induce the two types of mutations of interest, based on fly data (sex-linked lethals/recessive visible mutations) even though the study was well designed, used large doses of X-rays, and was published in Genetics. These findings were never cited by Muller, and the Snell paper (Snell, Genetics 20:545–567, 1935) did not cite the 1927 Muller paper (Muller, Science 66:84, 1927). This situation raises questions concerning how Snell wrote the paper (e.g., ignoring the significance of not providing support for Muller's findings in a mammal). The question may be raised whether professional pressures were placed upon Snell to downplay the significance of his findings, which could have negatively impacted the career of Muller and the LNT theory. While Muller would receive worldwide attention, and receive the Nobel Prize in 1946 "for the discovery that mutations can be induced by X-rays," Snell's negative mutation data were almost entirely ignored by his contemporary and subsequent radiation genetics/mutation researchers. This raises questions concerning how the apparent lack of interest in Snell's negative findings helped Muller professionally, including his success in using his fruit fly data to influence hereditary and cancer risk assessment and to obtain the Nobel Prize. [ABSTRACT FROM AUTHOR]

Lung cancer is the malignant tumor with the highest incidence and mortality rate worldwide. For lung adenocarcinoma, identifying specific gene mutations, fusions, and giving corresponding targeted drugs can greatly improve the survival time of the patients. Among them, anaplastic lymphoma kinase (ALK) fusion occurs in 3%-7% of non-small cell lung cancer (NSCLC). In clinical practice, a variety of detection methods can be used to determine the ALK fusion status, but false negative test results are possible. This paper retrospectively analyzed the diagnosis and treatment of a patient with lung adenocarcinoma, judged the ALK fusion status by various detection methods. Among them, immunohistochemistry (IHC)(Ventana D5F3), RNA based next-generation sequencing (RNA-based NGS) confirmed positive echinoderm microtubule associated protein like 4 (EML4)-ALK fusion, while DNA-based NGS was negative. This paper analyzed the detection methods of ALK fusion, in order to clarify which detection method is the most accurate and simple to choose in different clinical cases and guide the subsequent treatment. [ABSTRACT FROM AUTHOR]

Introduction: The etiology of mental disorders is largely influenced by genetic elements. Several studies have shown that genetic elements influence major mental disorders (MDs). However, the quantity and type of the genetic input remain unknown and require further research. Objective: In this review, we aim to investigate the impact of genetic markers on the development of mental disorders. Methodology: In our study, we included English studies from online databases such as Web of Science, Scopus, Google Scholar, PubMed, and the Cochrane Library using the following keywords “genetic factors”, “genetic markers”, “mental disorders”, “anxiety”, “depression”, and “schizophrenia” till March 2024. Results: The result of the search utilizing the strategy of our search was 2107 studies. We selected the articles that were relevant to our topic by screening these articles. After eliminating the remaining papers based on title and abstract screening, we conducted a full-text screening of 318 publications. In the end, we consulted 68 articles to learn more about our subject and compose this evaluation. Scientific Novelty: Most of the previous studies discovered that genetic elements contribute to major MDs. However, the nature and extent of the genetic contribution have not been determined. In our review, we discussed the genetic contribution to the occurrence of MDs. Practical Significance of the Results Obtained: The influence of genetic research on individuals with MDs and their families was one of our review’s main concerns. Understanding the extent of genetic elements’ contribution to MDs may have implications for society, research, patient outcomes, and quality of life. Conclusion: This comprehensive study demonstrates that the development and onset of MDs are affected by several elements, which can be genetic polymorphisms and genetic mutations. The potentiality of genetics studies to detect the occurrence of MDs may help in the early recognition of these conditions. It could assist in identifying people who are more susceptible to developing specific disorders according to their genetic profile. [ABSTRACT FROM AUTHOR]

Galectins are innate immune system regulators associated with disease progression in cancer. This paper aims to investigate the correlation between mutated cancer-critical genes and galectin levels in breast cancer patients to determine whether galectins and genetic profiles can be used as biomarkers for disease and potential therapy targets. Prisma Health Cancer Institute's Biorepository provided seventy-one breast cancer samples, including all four stages spanning the major molecular subtypes and histologies. Hotspot mutation statuses of cancer-critical genes were determined using multiplex PCR in tumor samples from the same patients by Precision Genetics and the University of South Carolina Functional Genomics Core Facility. The galectin-1, -3, and -9 levels in patients' sera were analyzed using Enzyme-linked Immunosorbent Assay (ELISA). An analysis was performed using JMP software to compare mean and median serum galectin levels between samples with and without specific cancer-critical genes, including pooled t-test, Wilcoxon Rank Sum Test, ANOVA, and Steel Dwass Test ( α = 0.05 ). Our analysis indicates that KIT mutations correlate with elevated serum levels of galectin-9 in patients with breast cancer. In patients with Luminal A subtype, FLT3 mutation correlates with lower serum galectin-1 and -9 levels and TP53 mutations correlate with higher serum galectin-3 levels. Patients with invasive ductal carcinoma had significantly higher serum galectin-3 levels than patients with ductal carcinoma in situ. Patients with both TP53 and PIK3CA mutations exhibit elevated serum galectin-3 levels, while patients with one or neither mutation show no significant difference in serum galectin-3 levels. In addition, metastatic breast cancer samples were more likely to have a KIT or PIK3CA mutation compared to primary breast cancer samples. The relationship between genetic mutations and galectin levels has the potential to identify appropriate candidates for combined therapy, targeting genetic mutations and galectins. Further understanding of the effect of genetic mutations and galectin levels on cancer progression and metastasis could aid in the search for biomarkers for breast cancer diagnosis, disease progression, and prognosis. [ABSTRACT FROM AUTHOR]

Mucosal melanoma (MM) is a rare and aggressive form of melanoma with a poorer prognosis compared to other subtypes. Recent large-scale next-generation sequencing studies, including our own research, have demonstrated that the molecular characteristics and potential oncogenic drivers of MM differ significantly from those of cutaneous melanoma. The emergence of selective CDK4/6 inhibitors, already approved for use in breast cancer and undergoing phase III clinical trials for other solid tumors, represents a promising development in the treatment of MM. Recent studies have shown that CDK4/6 inhibitors not only induce cell cycle arrest but also play a crucial role in facilitating the interaction between tumor cells and the host immune system. Moreover, our findings indicate that dysregulation of cell cycle progression due to cyclin‐dependent kinase 4 (CDK4) amplification is a significant genetic characteristic in a substantial portion of MM cases. Targeting CDK4 in specific MM patients shows promise for precision cancer therapy, utilizing molecularly characterized MM patient-derived xenograft (PDX) models and clinical trials. This paper provides an overview of existing literature on CDK4/6 dysregulation in MM, as well as preclinical and clinical investigations on CDK4/6 inhibitors and potential combination therapies for MM treatment. [ABSTRACT FROM AUTHOR]

Accurate models describing the relationship between genotype and phenotype are necessary in order to understand and predict how mutations to biological sequences affect the fitness and evolution of living organisms. The apparent abundance of epistasis (genetic interactions), both between and within genes, complicates this task and how to build mechanistic models that incorporate epistatic coefficients (genetic interaction terms) is an open question. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values (known as genetical, biological or physiological epistasis), and can therefore be used to address fundamental questions related to sequence-to-function encodings. However, one of its main limitations is that it can only accommodate two alleles (amino acid or nucleotide states) per sequence position. In this paper we provide an extension of the Walsh-Hadamard transform that allows the calculation and modeling of background-averaged epistasis (also known as ensemble epistasis) in genetic landscapes with an arbitrary number of states per position (20 for amino acids, 4 for nucleotides, etc.). We also provide a recursive formula for the inverse matrix and then derive formulae to directly extract any element of either matrix without having to rely on the computationally intensive task of constructing or inverting large matrices. Finally, we demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic fitness landscapes, revealing that both pairwise and higher-order genetic interactions are enriched between physically interacting positions. Author summary: An important question in genetics is how the effects of mutations combine to alter phenotypes. Genetic interactions (epistasis) describe non-additive effects of pairs of mutations, but can also involve higher-order (three- and four-way etc.) combinations. Quantifying higher-order interactions is experimentally very challenging requiring a large number of measurements. Techniques based on deep mutational scanning (DMS) represent valuable sources of data to study epistasis. However, the best way to extract the relevant pairwise and higher-order epistatic coefficients (genetic interaction terms) from this data for the task of phenotypic prediction remains an unresolved problem. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values. Critically, this formalism currently only allows for two alleles (amino acid or nucleotide states) per sequence position, hampering applications in more biologically realistic scenarios. Here we present an extension of the Walsh-Hadamard transform that overcomes this limitation and demonstrate the utility of our theory by using it to model epistasis within both simulated and empirical multiallelic genetic landscapes. [ABSTRACT FROM AUTHOR]

This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait's average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher's fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-off relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species' weights to the lengths of DNA strands. [ABSTRACT FROM AUTHOR]

Simple Summary: The 2021 WHO classification of central nervous system (CNS) tumors is challenging for neuroradiologists due to the central role of the molecular profile of tumors. We performed a scoping review of recent literature to assess the existing data on the power of novel data analysis tools to predict new tumor classes by imaging. We found room for performance improvement for subgroups with lower incidence (e.g., 1p/19q codeleted or IDH1/2 mutated gliomas) and patients with rare diagnoses (e.g., pediatric gliomas, midline gliomas). More data regarding functional MRI techniques need to be collected. Studies explicitly designed to assess the generalizability of AI-aided tools for predicting molecular tumor subgroups are lacking. The 2021 WHO classification of CNS tumors is a challenge for neuroradiologists due to the central role of the molecular profile of tumors. The potential of novel data analysis tools in neuroimaging must be harnessed to maintain its role in predicting tumor subgroups. We performed a scoping review to determine current evidence and research gaps. A comprehensive literature search was conducted regarding glioma subgroups according to the 2021 WHO classification and the use of MRI, radiomics, machine learning, and deep learning algorithms. Sixty-two original articles were included and analyzed by extracting data on the study design and results. Only 8% of the studies included pediatric patients. Low-grade gliomas and diffuse midline gliomas were represented in one-third of the research papers. Public datasets were utilized in 22% of the studies. Conventional imaging sequences prevailed; data on functional MRI (DWI, PWI, CEST, etc.) are underrepresented. Multiparametric MRI yielded the best prediction results. IDH mutation and 1p/19q codeletion status prediction remain in focus with limited data on other molecular subgroups. Reported AUC values range from 0.6 to 0.98. Studies designed to assess generalizability are scarce. Performance is worse for smaller subgroups (e.g., 1p/19q codeleted or IDH1/2 mutated gliomas). More high-quality study designs with diversity in the analyzed population and techniques are needed. [ABSTRACT FROM AUTHOR]

Recessive dystrophic epidermolysis bullosa is a rare genodermatosis caused by a mutation of the Col7a1 gene. The Col7a1 gene codes for collagen type VII protein, a major component of anchoring fibrils. Mutations of the Col7a1 gene can cause aberrant collagen type VII formation, causing an associated lack or absence of anchoring fibrils. This presents clinically as chronic blistering, scarring, and fibrosis, often leading to the development of cutaneous squamous cell carcinoma. Patients also experience persistent pain and pruritus. Pain management and supportive bandaging remain the primary treatment options. The pathology of recessive dystrophic epidermolysis bullosa was first described in the 1980s, and there has since been a multitude of encouraging treatment options developed. However, in vivo research has been hindered by inadequate models of the disease. The various mouse models in existence possess longevity and surface area constraints, or do not adequately model a normal human disease state. In this paper, we describe a novel rat model of recessive dystrophic epidermolysis bullosa that offers an alternative to previous murine models. An 8-base pair deletion was induced in the Col7a1 gene of Lewis rats, which was subsequently found to cause a premature stop codon downstream. Homozygous mutants presented with a fragile and chronically blistered phenotype postnatally. Further histological analysis revealed subepidermal clefting and the absence of anchoring fibrils. The generation of this novel model offers researchers an easily maintained organism that possesses a larger surface area for experimental topical and transfused therapies to be tested, which may provide great utility in the future study of this debilitating disease. [ABSTRACT FROM AUTHOR]

The expanding geriatric population, whose predisposition toward disabling morbidities and age-related diseases (ARD) is well-documented, has become a paramount social issue, exerting an onerous burden on both the healthcare industry and wider society. ARD manifest as the progressive deterioration of bodily tissues and organs, eventually resulting in the failure of these vital components. At present, no efficacious measures exist to hinder the onset of ARD. Copper, an essential trace element, is involved in a wide range of physiological processes across different cell types. In recent research, a novel variant of copper-dependent cell death, termed cuproptosis, has been identified. This mode of cellular demise stands apart from previously recognized types of cell death. Cuproptosis occurs when copper binds with acyl-CoA synthetase in the tricarboxylic acid (TCA) cycle, resulting in protein aggregation and protein toxicity stress, ultimately leading to cell death. In this paper, we provide a concise overview of the current understanding concerning the metabolism of copper, copper-related diseases, the hallmarks of copper toxicity, and the mechanisms that regulate copper toxicity. Additionally, we discuss the implications of cuproptosis mutations in the development of ARD, as well as the potential for targeting cuproptosis as a treatment for ARD. [ABSTRACT FROM AUTHOR]

The emerging field of genomic medicine offers an opportunity for biology and anatomy teachers to bring the topics of DNA, genetics, molecular processes, and evolution together into one experience. Through the genomic medicine paradigm, students see the unbroken connection between small biological topics such as mutations and their potential connection to disease phenotypes. In this paper, we present as a main example cystic fibrosis, which is an often-studied genetic disease in general biology class, for examination through the genomic medicine lens. Concepts such as genes, the plasma membrane, variation, mutations, the nucleus, and chromosomes can be used in a narrative and visual approach to genetics through the genomic medicine standpoint to engage and connect students with next-generation genomics and with the fundamental unit of life—the cell. It is through the genomic medicine lens that the cell's context and relationship to the evolving world takes place. [ABSTRACT FROM AUTHOR]

In the early 1900s, mutation breeding to select varieties with desirable traits using spontaneous mutation was actively conducted around the world, including Japan. In rice, the number of fixed mutations per generation was estimated to be 1.38-2.25. Although this low mutation rate was a major problem for breeding in those days, in the modern era with the development of next-generation sequencing (NGS) technology, it was conversely considered to be an advantage for efficient gene identification. In this paper, we proposed an in silico approach using NGS to compare the whole genome sequence of a spontaneous mutant with that of a closely related strain with a nearly identical genome, to find polymorphisms that differ between them, and to identify the causal gene by predicting the functional variation of the gene caused by the polymorphism. Using this approach, we found four causal genes for the dwarf mutation, the round shape grain mutation and the awnless mutation. Three of these genes were the same as those previously reported, but one was a novel gene involved in awn formation. The novel gene was isolated from Bozu-Aikoku, a mutant of Aikoku with the awnless trait, in which nine polymorphisms were predicted to alter gene function by their whole-genome comparison. Based on the information on gene function and tissue-specific expression patterns of these candidate genes, Os03g0115700/LOC_Os03g02460, annotated as a shortchain dehydrogenase/reductase SDR family protein, is most likely to be involved in the awnless mutation. Indeed, complementation tests by transformation showed that it is involved in awn formation. Thus, this method is an effective way to accelerate genome breeding of various crop species by enabling the identification of useful genes that can be used for crop breeding with minimal effort for NGS analysis. [ABSTRACT FROM AUTHOR]

Viola suavis var. pannonica (Violaceae) from central Europe is described here as a new variety to science. It is most similar to the blue-flowered V. suavis var. suavis and the white-flowered V. suavis var. catalonica and V. suavis subsp. naqshii, but exhibits differences in several characters, such as petal colour, spur shape, fimbriae length on the stipules, bracteoles position on the peduncle and lamina sinus shape. Although the new taxon is often considered a colour mutation of V. suavis var. suavis, previous genetic analyses revealed that these white-flowered plants do not arise recurrently at different locations (having multiple origins), but rather form a monophyletic evolutionary lineage. To date, the occurrence of V. suavis var. pannonica has been reported in the Slovak Republic, the Czech Republic and western Ukraine. In this paper, we report its occurrence in Austria and Hungary. Notes on its etymology, distribution, ecology, origin and hybridization, as well as photographs of the new variety (including the holotype) are also provided. [ABSTRACT FROM AUTHOR]

In biological systems, impulses are often used to model mutations in gene expression. In order to describe the instantaneity of the impulse, this paper employs a hybrid‐index model of impulsive Boolean networks with state‐triggered impulses. Based on this model, the time‐domain output controllability is investigated. Using the quotient mapping method, the hybrid‐domain solutions of this model are mapped to the time‐domain solutions, mathematically. Then a necessary and sufficient condition for output controllability in the time domain is presented. Finally, an example is given to demonstrate the correctness and effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Simple Summary: Oncolytic herpes simplex viruses (oHSVs) employ as natural entry receptors nectin1 or HVEM. In contrast, retargeted oHSVs (ReHVs) employ as an entry receptor a tumor-associated antigen that no longer interacts with nectin1/HVEM and, thus, spares normal cells. Prior to entry, both oHSVs and ReHVs attach to cells by interaction of gC and gB glycoproteins with heparan sulphates and chondroitin sulphates (glycosaminoglycans–GAGs). The systemic delivery of oncolytic viruses would be the ideal route for hard-to-reach or metastatic cancers that constitute unmet clinical needs. In an accompanying paper, we reported that the blood complement and the antiviral neutralizing antibodies represent the major blood factors that inactivate systemically administered ReHVs. Here, we asked whether ReHV adsorption to GAGs acts as a sink and subtracts the virus from circulation. We report that a genetic modification in gC, which reduced its interaction with GAGs, resulted in a longer half-life of circulating ReHV and a higher anticancer efficacy of systemically (but not intratumorally) administered ReHV. The role of the interaction with cell-surface glycosaminoglycans (GAGs) during in vivo HSV infection is currently unknown. The rationale of the current investigation was to improve the anticancer efficacy of systemically administered retargeted oHSVs (ReHVs) by decreasing their binding to GAGs, including those of endothelial cells, blood cells, and off-tumor tissues. As a proof-of-principle approach, we deleted seven amino acids critical for interacting with GAGs from the glycoprotein C (gC) of R-337 ReHV. The modification in the resulting R-399 recombinant prolonged the half-life in the blood of systemically administered R-399 and enhanced its biodistribution to tumor-positive lungs and to the tumor-negative liver. Ultimately, it greatly increased the R-399 efficacy against metastatic-like lung tumors upon IV administration but not against subcutaneous tumors upon IT administration. These results provide evidence that the increased efficacy seen upon R-399 systemic administration correlated with the slower clearance from the circulation. To our knowledge, this is the first in vivo evidence that the partial impairment of the gC interaction with GAGs resulted in a prolonged half-life of circulating ReHV, an increase in the amount of ReHV taken up by tissues and tumors, and, ultimately, an enhanced anticancer efficacy of systemically administered ReHV. [ABSTRACT FROM AUTHOR]

Introduction. ADCY5-related dyskinesia is a rare neurological disease caused by mutations in the gene encoding the adenylyl cyclase 5 (ADCY5) isoform, a protein that plays an important role in intracellular transmission. Variants in ADCY5 are associated with a spectrum of neurological disease encompassing dyskinesia, chorea, and dystonia. State of the-art. ADCY5 mutations result in clinically heterogeneous manifestations which comprise a range of core and less to highly variable symptoms. Due to the heterogeneous nature and difficulty in diagnosis of the disorder, available treatments are highly limited. Clinical implications. ADCY5-related dyskinesia was reported in 52 individuals in the literature over a five-year period (January 2017 to January 2022). We have listed all the symptoms and their frequency. The most common symptom reported in these patients was dystonia. Over 50% of patients developed dyskinesia and chorea. We report two cases of familial occurrence of symptomatic ADCY5-related dyskinesia. A 45-year-old patient presented with involuntary movements which had been occurring since childhood. The proband's neurological examination revealed dysarthria, involuntary myoclonic twitches, and choreic movements. The patient's 9-year-old son had developed involuntary movements, mainly chorea and dystonia. Future directions. This paper aims to summarise the recent literature on ADCY5-related neurological disorders and to present a new case of a Polish family with ADCY5 mutation. Genetic diagnostics are important in the context of possible future targeted treatments. [ABSTRACT FROM AUTHOR]

Simple Summary: The cornerstone of successful treatment of hematologic diseases, including multiple myeloma (MM), is early diagnosis and establishing a prognosis for the patient. Therefore, it is necessary to identify sensitive and specific markers for this disease. Non-coding RNAs including miRNAs are increasingly being recognized as potential diagnostic, predictive, and prognostic markers. These molecules are non-coding, single-stranded RNAs that regulate the expression of many target genes involved in key biological processes, such as cell proliferation, differentiation, and apoptosis. This paper aims to identify the role of non-coding RNAs including miRNAs as potential markers for diagnosis and prognosis in patients with MM. Multiple myeloma (MM) is the second most common hematologic malignancy in the world and accounts for 15% of primary hemocytopathies, with an ever-increasing number of new cases. It is asymptomatic in 30% of instances; hence, the determination of highly sensitive and specific markers is necessary to make a proper diagnosis. In the last 20 years, miRNAs, involved in regulating the expression of genes responsible for cell proliferation and differentiation, including tumor cells, have been identified as potential diagnostic and prognostic markers. The main aim of the following review was to outline the role of miRNAs in the diagnosis and prognosis of MM, considering their role in the pathogenesis of the disease and identifying their target genes and pathways. For this purpose, publications dating from 2013–2023 have been reviewed. Based on the available data, it is concluded that non-coding RNAs including miRNAs could be potential markers in MM. Furthermore, they may serve as therapeutic targets for certain drugs. [ABSTRACT FROM AUTHOR]

MIRAGE syndrome is a recently described congenital condition characterized genetically by heterozygous gain-of-function missense mutations in the growth repressor sterile alpha domain containing 9 (SAMD9) located on the arm of chromosome 7 (7q21.2). The syndrome is rare and is usually diagnosed in newborns and children with myelodysplasia, infection, restriction of growth, adrenal hypoplasia, genital phenotypes, and enteropathy, hence the acronym MIRAGE. The aims of this paper are (1) to present fetal ultrasound features in a case where MIRAGE syndrome was diagnosed prenatally and (2) to review the existing literature records on prenatal manifestations of MIRAGE syndrome. In our case, the fetus had severe early fetal growth restriction (FGR) with normal Doppler studies, atypical genitalia, oligohydramnios, and hyperechogenic bowel at the routine mid-gestation anomaly scan. Amniocentesis excluded infections and numeric or structural chromosomal abnormalities while whole exome sequencing (WES) of the fetal genetic material identified the specific mutation. Targeted testing in parents was negative, suggesting the "de novo" mutation in the fetus. We could not identify other specific case reports in the literature on the prenatal diagnosis of MIRAGE syndrome. In cases reported in the literature where the diagnosis of MIRAGE syndrome was achieved postnatally, there are mentions related to the marked FGR on prenatal ultrasound. Severe early-onset FGR with no other apparent cause seems to be a central prenatal feature in these babies, and WES should be offered, especially if there are other structural abnormalities. Prenatal diagnosis of MIRAGE syndrome is possible, allowing for reproductive choices, improved counseling of parents, and better preparation of neonatal care. [ABSTRACT FROM AUTHOR]

Simple Summary: Cholangiocarcinoma (CCA) manifests as a complex interplay of genetic and environmental factors, necessitating personalized approaches. This review covers the various causes, risk factors, and molecular aspects of CCA in oncology. It explores current diagnostic methods and treatments, such as targeted therapies and immunotherapy. Additionally, it addresses emerging strategies like microbiota modulation and the use of natural compounds. This review paper provides a comprehensive understanding of CCA, offering insights into current and evolving approaches for effective interventions in oncological care. Cholangiocarcinomas (CCA) pose a complex challenge in oncology due to diverse etiologies, necessitating tailored therapeutic approaches. This review discusses the risk factors, molecular pathology, and current therapeutic options for CCA and explores the emerging strategies encompassing targeted therapies, immunotherapy, novel compounds from natural sources, and modulation of gut microbiota. CCA are driven by an intricate landscape of genetic mutations, epigenetic dysregulation, and post-transcriptional modification, which differs based on geography (e.g., for liver fluke versus non-liver fluke-driven CCA) and exposure to environmental carcinogens (e.g., exposure to aristolochic acid). Liquid biopsy, including circulating cell-free DNA, is a potential diagnostic tool for CCA, which warrants further investigations. Currently, surgical resection is the primary curative treatment for CCA despite the technical challenges. Adjuvant chemotherapy, including cisplatin and gemcitabine, is standard for advanced, unresectable, or recurrent CCA. Second-line therapy options, such as FOLFOX (oxaliplatin and 5-FU), and the significance of radiation therapy in adjuvant, neoadjuvant, and palliative settings are also discussed. This review underscores the need for personalized therapies and demonstrates the shift towards precision medicine in CCA treatment. The development of targeted therapies, including FDA-approved drugs inhibiting FGFR2 gene fusions and IDH1 mutations, is of major research focus. Investigations into immune checkpoint inhibitors have also revealed potential clinical benefits, although improvements in survival remain elusive, especially across patient demographics. Novel compounds from natural sources exhibit anti-CCA activity, while microbiota dysbiosis emerges as a potential contributor to CCA progression, necessitating further exploration of their direct impact and mechanisms through in-depth research and clinical studies. In the future, extensive translational research efforts are imperative to bridge existing gaps and optimize therapeutic strategies to improve therapeutic outcomes for this complex malignancy. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a certain class of mutations in genomic sequences by studying the evolution of the entropy and relative entropy associated with the base frequencies of a given genomic sequence. Even if the method is, in principle, applicable to every sequence which varies randomly, the case of SARS-CoV-2 RNA genome is particularly interesting to analyze, due to the richness of the available sequence database containing more than a million sequences. Our model is able to track known features of the mutation dynamics like the Cytosine–Thymine bias, but also to reveal new features of the virus mutation dynamics. We show that these new findings can be studied using an approach that combines the mean field approximation of a Markov dynamics within a stochastic thermodynamics framework. [ABSTRACT FROM AUTHOR]

Background: Niemann-Pick Disease type C is a fatal autosomal recessive lipid storage disorder caused by NPC1 or NPC2 gene mutations and characterized by progressive, disabling neurological deterioration and hepatosplenomegaly. Herein, we identified a novel compound heterozygous mutations of the NPC1 gene in a Chinese pedigree. Case presentation: This paper describes an 11-year-old boy with aggravated walking instability and slurring of speech who presented as Niemann-Pick Disease type C. He had the maternally inherited c.3452 C > T (p. Ala1151Val) mutation and the paternally inherited c.3557G > A (p. Arg1186His) mutation using next-generation sequencing. The c.3452 C > T (p. Ala1151Val) mutation has not previously been reported. Conclusions: This study predicted that the c.3452 C > T (p. Ala1151Val) mutation is pathogenic. This data enriches the NPC1 gene variation spectrum and provides a basis for familial genetic counseling and prenatal diagnosis. [ABSTRACT FROM AUTHOR]

Background: NR2F1 mutations are associated with Bosch-Boonstra-Schaaf optic atrophy syndrome (BBSOAS). Although ~ 46.7% of BBSOAS patients present with epilepsy, which is always drug-resistant and associated with higher rates of behavioral and cognitive problems, the treatment and outcomes of NR2F1-related epilepsy have rarely been described. Here, we present new cases of BBSOAS-related epilepsy and summarize all previously reported cases to explore the effective treatment for this type of epilepsy. Methods: We identified six new Chinese cases of BBSOAS with epilepsy. Five different de novo heterozygous NR2F1 mutations were identified in these cases, including two novel mutations c.365G > T, p.Cys122Phe and c.449G > T, p.Gly150Val. By combining the six cases and 14 previously reported cases, we analyzed the characteristics and treatment outcomes of NR2F1-related epilepsy. Results: Twelve of the 20 patients (60%) had infantile epileptic spasms, while the other patients had generalized tonic/tonic-clonic, focal, myoclonic, absence, or unclassified seizures. Several anti-seizure medications, steroids, and a ketogenic diet were administered in these cases. However, seizures were controlled in only 50% of previously reported cases, while all of the six new cases became seizure-free after perampanel as an add-on treatment. The average time from the addition of perampanel to seizure control was 7.33 ± 4.59 months (range, 1–12 months). The median time to seizure freedom was 14 months (1–32 months, > 19 months in 3 cases). The average dosage of perampanel needed for epilepsy control was 0.22 ± 0.17 mg/kg per day. Conclusions: In this paper, we comprehensively summarized the clinical characteristics, treatments and outcomes of NR2F1-related epilepsy for the first time. Perampanel exhibits dramatic efficacy for NR2F1-related epilepsy. This will help optimize the treatment of this type of epilepsy and provide clues for its pathogenic mechanisms. The two novel mutations expand the genotype spectrum of this disease. [ABSTRACT FROM AUTHOR]

Collodion Baby is a descriptive term for newborns with the entire surface of the body wrapped in a rigid yellowish membrane that resembles solid and translucent parchment paper. A rare disorder that often occurs in preterm babies with low birth weight. Collodion babies can have defects in protein and fat metabolism due to genetic mutations. Management with emollients, fluid and electrolyte balance and overcoming infection. Case Report: Reported newborn came to the emergency room of Soeselo Hospital referral from Puskesmas with Collodion Baby and low birth weight. Yellowish skin is obtained throughout the body such as translucent thick parchment, fissures with some erosion and ecropions in both eyes. The patient is placed in an incubator with a temperature of 30-32o C, emollient therapy, topical antibiotics on fissures and erosions, prophylactic antibiotics and antibiotic creams for ectropion. Discussion: Collodion baby is a condition at risk of serious complications including: risk of infection, hypernatremic dehydration, fluid and electrolyte imbalances and temperature instability caused by epidermal lipid disorders and protein homeostasis, resulting in increased transepidermal water loss (TEWL) caused by mutations in the transglutaminase 1-TGM1, ALOXE3 or ALOX12B, ABCA12, HIPAL4/ichthyin, ABHD5 genes responsible for epidermal homeostasis. Conclusion: Collodion Baby is a disorder with severe corneal damage. The importance of proper and comprehensive management with the aim of minimizing complications can reduce morbidity and mortality. [ABSTRACT FROM AUTHOR]

The two cell-adhesion molecules, Neurexin-1 and Neuroligin-1, are essential for synapse function in neural networks. Interruptions to the function of these two proteins are associated with predestination for cognitive disorders, such as Autism spectrum disorder (ASD). In this paper, we study the effects of genetic missense mutations located on the cell interface between NRXN-1 and NLGN-1 on the development of neurodevelopmental disorders by identifying and determining the effects of mutations on bond strengths between NRXN-1 and NLGN-1 on the synaptic interface by building a computational platform. This was done by mapping all ASD-associated point mutations found in a web-based database on the computationally modeled structure of NRXN-1, then determining which mutations interact with NLGN-1. Then, the binding strength of the two proteins without the influence of the mutations was compared to the binding strength with the mutations so that the effects of the mutation were established. Based on our structural models and calculations of binding free energy, we found that these mutations can change the binding affinity of Neurexin-neuroligin interaction. Thus, we suggest that the changes in bond strength between Neurexin and Neuroligin at neural synapses can affect neural circuits, leading to autism-associated symptoms. [ABSTRACT FROM AUTHOR]

Background: Pre‐implantation genetic testing for monogenic disorders (PGT‐M) is an effective approach to reducing the incidence of birth defects by preventing the transmission of inherited diseases to offspring. However, there are still controversies regarding the detection methods and transplantation of embryos. This paper aims to evaluate the effectiveness of different detection technologies applied to PGT‐M through a retrospective analysis of clinical detection data. Methods: The carrier status of pathogenic mutations and chromosomal copy number variants (CNVs) in 892 embryos was characterized using next‐generation sequencing (NGS), single‐nucleotide polymorphism (SNP) array, and PCR‐based detection technologies. Clinical data from PGT‐M cases were retrospectively analyzed to assess the effectiveness of these detection methods in identifying genetic abnormalities in embryos. Results: A total of 829 embryos were analyzed, with 63 being unsuccessful. Our study revealed that the success rate of detecting deletional mutations using Gap‐PCR 84.9%, which is lower than that of SNP array (98.7%) and NGS (92.5%). However, no significant difference was observed when detecting point mutations using any of the methods. These findings suggest that, when detecting deletional mutations, SNP array and NGS are more suitable choices compared to Gap‐PCR. While SNP array may have a lower resolution and success rate (80.5%) in analyzing CNVs compared to NGS (95.5%), it may still be useful for revealing certain abnormal types. Conclusion: In conclusion, this study found that SNP analysis is advantageous for identifying polygenic and deletional mutations, whereas NGS is more cost‐efficient for detecting common monogenic diseases. Additionally, SNP‐based haplotyping and PCR‐based direct detection of mutations can be used together to enhance the accuracy and success rates of PGT‐M. Our findings offer valuable insights for PGT technicians in choosing suitable detection methods for patients. [ABSTRACT FROM AUTHOR]