Search

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]

Highlights • We considered the effects of time-varying migration path on the metapopulation rock-paper-scissors game. • The dynamics are represented by the reaction-diffusion equations with time-dependent diffusion coefficients in diffusively coupled reactors. • We numerically obtained the solutions of the time-dependent reaction-diffusion-equations. • We found that phase transitions occur by varying a mutation rate. • The phase transitions depend highly on the frequency change of migration path. Abstract Migration paths of animals are rarely the same. The paths may change according to seasonal and circadian rhythms. We study the effect of temporal migration on population dynamics of rock-paper-scissors (RPS) games with mutation by using the metapopulation dynamic model with two patches. Via mutation, an individual R changes to S with rate μ. All agents move by random walk between two patches and the RPS game is performed in each patch. The migration path between two patches is switched on or off periodically. The dynamics are represented by the reaction-diffusion equations with time-dependent diffusion coefficients in diffusively coupled reactors. We obtain the solutions of time-dependent reaction-diffusion equations numerically and analytically. The time-varying migration path induces complex behavior for the RPS dynamics, depending on the frequency of the periodical path. We find that the phase transitions occur by varying mutation rate μ. The phase transition depends highly on the frequency. [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]

The rock–paper–scissors (RPS) game is known as one of the simplest cyclic dominance models. This game is key to understanding biodiversity. Three species, rock ( R ), paper ( P ) and scissors ( S ), can coexist in nature. In the present paper, we first present a metapopulation model for RPS game with mutation. Only mutation from R to S is allowed. The total population consists of spatially separated patches, and the mutation occurs in particular patches. We present reaction–diffusion equations which have two terms: reaction and migration terms. The former represents the RPS game with mutation, while the latter corresponds to random walk. The basic equations are solved analytically and numerically. It is found that the mutation induces one of three phases: the stable coexistence of three species, the stable phase of two species, and a single-species phase. The phase transitions among three phases occur by varying the mutation rate. We find the conditions for coexistence are largely changed depending on metapopulation models. We also find that the mutation induces different paradoxes in different patches. [ABSTRACT FROM AUTHOR]

Advances in synthetic biology have led to an arsenal of proof-of-principle bacterial circuits that can be leveraged for applications ranging from therapeutics to bioproduction. A unifying challenge for most applications is the presence of selective pressures that lead to high mutation rates for engineered bacteria. A common strategy is to develop cloning technologies aimed at increasing the fixation time for deleterious mutations in single cells. We adopt a complementary approach that is guided by ecological interactions, whereby cyclical population control is engineered to stabilize the functionality of intracellular gene circuits. Three strains of Escherichia coli were designed such that each strain could kill or be killed by one of the other two strains. The resulting “rock-paper-scissors” dynamic demonstrates rapid cycling of strains in microfluidic devices and leads to an increase in the stability of gene circuit functionality in cell culture. [ABSTRACT FROM AUTHOR]

Human immunodeficiency virus (HIV) is a chronic infection that can be managed by antiretroviral treatment (ART). However, periods of suboptimal viral suppression during lifelong ART can select for HIV drug resistant (DR) variants. Transmission of drug resistant virus can lessen or abrogate ART efficacy. Therefore, testing of individuals for drug resistance prior to initiation of treatment is recommended to ensure effective ART. Sensitive and inexpensive HIV genotyping methods are needed in low-resource settings where most HIV infections occur. The oligonucleotide ligation assay (OLA) is a sensitive point mutation assay for detection of drug resistance mutations in HIV pol. The current OLA involves four main steps from sample to analysis: (1) lysis and/or nucleic acid extraction, (2) amplification of HIV RNA or DNA, (3) ligation of oligonucleotide probes designed to detect single nucleotide mutations that confer HIV drug resistance, and (4) analysis via oligonucleotide surface capture, denaturation, and detection (CDD). The relative complexity of these steps has limited its adoption in resource-limited laboratories. Here we describe a simplification of the 2.5-hour plate-format CDD to a 45-minute paper-format CDD that eliminates the need for a plate reader. Analysis of mutations at four HIV-1 DR codons (K103N, Y181C, M184V, and G190A) in 26 blood specimens showed a strong correlation of the ratios of mutant signal to total signal between the paper CDD and the plate CDD. The assay described makes the OLA easier to perform in low resource laboratories. [ABSTRACT FROM AUTHOR]

We consider a two-dimensional model of three species in rock-paper-scissors competition and study the self-organisation of the population into fascinating spiraling patterns. Within our individual-based metapopulation formulation, the population composition changes due to cyclic dominance (dominance-removal and dominance-replacement), mutations, and pair-exchange of neighboring individuals. Here, we study the influence of mobility on the emerging patterns and investigate when the pair-exchange rate is responsible for spiral waves to become elusive in stochastic lattice simulations. In particular, we show that the spiral waves predicted by the system's deterministic partial equations are found in lattice simulations only within a finite range of the mobility rate. We also report that in the absence of mutations and dominance-replacement, the resulting spiraling patterns are subject to convective instability and far-field breakup at low mobility rate. Possible applications of these resolution and far-field breakup phenomena are discussed. [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]

Artemisinin resistance (ART) has been confirmed in Greater Mekong Sub-region countries. Currently, C580Y mutation on Pfkelch13 gene is known as the molecular marker for the detection of ART. Rapid and accurate detection of ART in field study is essential to guide malaria containment and elimination interventions. A simple method for collection of malaria-infected blood is to spot the blood on filter paper and is fast and easy for transportation and storage in the field study. This study aims to evaluate LAMP-SNP assay for C580Y mutation detection by introducing an extra mismatched nucleotide at the 3' end of the FIP primer. The LAMP-SNP assay was performed in a water bath held at a temperature of 56°C for 45 min. LAMP-SNP products were interpreted by both gel-electrophoresis and HNB-visualized changes in color. The method was then tested with 120 P. falciparum DNA from dried blood spot samples. In comparing the LAMP-SNP assay results with those from DNA sequencing of the clinical samples, the 2 results fully agreed to detect C580Y. The sensitivity and specificity of the LAMP-SNP assay showed 100%. There were no cross-reactions with other Plasmodium species and other Pfkelch13 mutations. The LAMP-SNP assay performed in this study was rapid, reliable, and useful in detecting artemisinin resistance in the field study. [ABSTRACT FROM AUTHOR]

The origin of beneficial mutations is fundamentally important in understanding the processes by which natural selection works. Using phage-resistant mutants in Escherichia coli as their model for identifying the origin of beneficial mutations, Luria and Delbrück distinguished between two different hypotheses. Under the first hypothesis, which they termed "acquired immunity," the phages induced bacteria to mutate to immunity; this predicts that none of the resistant mutants were present before infection by the phages. Under the second hypothesis, termed "mutation to immunity," resistant bacteria arose from random mutations independent of the presence of the phages; this predicts that resistant bacteria were present in the population before infection by the phages. These two hypotheses could be distinguished by calculating the frequencies at which resistant mutants arose in separate cultures infected at the same time and comparing these frequencies to the theoretical results under each model. The data clearly show that mutations arise at a frequency that is independent of the presence of the phages. By inference, natural selection reveals the genetic variation that is present in a population rather than inducing or causing this variation. [ABSTRACT FROM AUTHOR]

Conference papers originating from the 27th International Symposium on Amyotrophic Lateral Sclerosis (ALS) and Motor Neurone Diseases with a focus on in vitro experimental modeling are presented. The conference papers cover a range of topics which include a cellular model of ALS with SQSTM1 mutations and the oligomerization and subcellular localization of missense/in-frame deletion ALS2 mutants in cultured cells. The development of a biomolecular fluorescence complementation assay is mentioned.

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]

Present Study analysis 201 publications (1972-2008) of Nobel laureate Jeffrey C Hall, an American eminent scientist in geneticist. His publications received 18,896 citations and first paper was reported in Scopus in 1972, subsequently, he published 200 research papers in various journals. The collaboration coefficient of scientist is 0.89 and forty-three (43) are two authored publications, 22 are single authored, scientist has authored highest publication in decade III (1990-1999) with 81(40.30%) publications. The paper entitled "A pdf neuropeptide gene mutation and ablation of PDF neurons each cause severe abnormalities of behavioral circadian rhythms in Drosophila" published in 'Cell' journal in 2000 has been cited highest 632 times with ranked 1 among all his publications. Study reveals out of 201 publications 193 (96.02%) papers are obtained all 18896 citations, and top 20(9.95%) publications are obtained 7566(40.04%) citations, and cited more than 200 times, scientist preferred 50 channel of communications are used to publish his research output, most publications 28(13.93%) were published in 'Genetics' (IF: 4.556) journal. [ABSTRACT FROM AUTHOR]

β-D-xylosidases are hemicellulases that catalyze the release of xylose units from short xylooligosaccharides. Their activity is the rate-limiting step in xylan hydrolysis. A major application of these enzymes is as eco-friendly biobleaching agents in the pulp and paper industry, where thermostable, alkaliphilic xylosidases are much preferred. Hence, the isolation and characterization of new thermo-alkaliphilic xylosidases from nature, or re-engineering existing ones is of importance for industrial applications. The thermophilic bacterium Geobacillus thermoleovorans IT-08 produces a meso-thermophilic β-D-xylosidase (EC 3.2.1.37), which has a unique primary structure compared to other xylosidases with only 32-35% amino acid sequence identity. Here, we describe the role of Asp121 in modulating the enzyme's pH-activity profile. Mutation of this residue into Val121 or Asn121 increased its pH optimum by 3 pH units with a significant decrease in its activities. Furthermore, all mutants showed a significant 40 °C increase in optimum temperature compared to wild-type enzyme. This study thus illustrates the importance of the p K a modulator residue Asp121 in shifting the pH- and temperature-activity profile of the enzyme. Changing Asp/Asn residues in enzymes, especially when the residue is located near the catalytic site, may be a useful strategy for adapting the enzyme to a high pH and high temperature environment. [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]

Despite much progress in our understanding of uveal melanoma (UM) over the past decades, this rare tumour is still often misclassified. Although UM, like other melanomas, is very probably derived from melanocytes, it is drastically different from cutaneous melanoma and most other melanoma subtypes in terms of epidemiology, aetiology, biology and clinical features, including an intriguing metastatic hepatotropism. UM carries distinctive prognostic chromosome alterations, somatic mutations and gene expression profiles, allowing an active tailored surveillance strategy and dedicated adjuvant clinical trials. There is no standard systemic treatment for disseminated UM at present. In contrast to cutaneous melanoma, UMs are not BRAF-mutated, thus curtailing the use of B-Raf inhibitors. Although these tumours are characterised by some immune infiltrates, immune checkpoint inhibitors are rarely effective, possibly due to a low mutation burden. UM patients across the world not only face rare cancer-related issues (e.g., specific management strategies, access to information and to expert centres), but also specific UM problems, which can be exacerbated by the common misconception that it is a subtype of cutaneous melanoma. As a European Consortium dedicated to research on UM and awareness on the disease, "UM Cure 2020" participants urge medical oncologists, pharmaceutical companies, and regulatory agencies to acknowledge UM as a melanoma with specific issues, in order to accelerate the development of new therapies for patients. [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]

A list of articles to be published in an upcoming issue of the journal is presented, as of November 2016, including articles on topics like tumor related to hematological diseases, leukaemogenesis mechanisms, and mutations in paediatric acute myeloid leukaemia.

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]