Background Despite advances in chronic myeloid leukemia (CML) genetics, the role of nitric oxide (NO) and hydrogen sulfide (H2S) gene mutations and their relationship to apoptotic genes is unclear. Therefore, this study investigated NO- and H2S-producing genes\' mutations and their interactions with apoptotic genes using Sanger sequencing and next-generation sequencing (NGS). Methodology A complete blood count (CBC) was carried out to measure the total number of white blood cells, while IL-6 levels were assessed in both control and CML patients using an ELISA technique. Sanger sequencing was used to analyze mutations in the CTH and NOS3 genes, whereas NGS was applied to examine mutations on all chromosomes. Results White blood cell (WBC) and granulocyte counts were significantly higher in CML patients compared to controls (p<0.0001), and monocyte counts were similarly higher (p<0.05). Interleukin-6 (IL-6) levels were significantly elevated in CML patients than controls (p<0.0001), indicating a possible link to CML etiology or progression. Multiple mutations have been identified in both genes, notably in CTH exon 12 and the NOS3 genes VNTR, T786C, and G894T. This study also measured IL-6 concentrations using IL-6 assays, identifying its potential as a CML prognostic diagnostic. WBC counts, granulocyte counts, and mid-range absolute counts, or MID counts, were significantly higher in CML patients than in normal control individuals. NGS identified 1643 somatic and sex chromosomal abnormalities and 439 actively expressed genes in CML patients. The findings imply a genomic landscape beyond the BCR-ABL1 mutation in CML development compared to other databases. Conclusion In conclusion, this study advances the understanding of the genetic characteristics of CML by identifying mutations in the NO- and H2S-producing genes and their complex connections with genes involved in apoptosis. The comprehensive genetic profile obtained by Sanger sequencing and NGS provides possibilities for identifying novel targets for therapy and personalized treatments for CML, therefore contributing to developments in hematological diseases.

The development of next-generation sequencing (NGS) has enabled the discovery of cancer-specific driver gene alternations, making precision medicine possible. However, accurate genetic testing requires a sufficient amount of tumor cells in the specimen. The evaluation of tumor content ratio (TCR) from hematoxylin and eosin (H&E)-stained images has been found to vary between pathologists, making it an important challenge to obtain an accurate TCR. In this study, three pathologists exhaustively labeled all cells in 41 regions from 41 lung cancer cases as either tumor, non-tumor or indistinguishable, thus establishing a \"gold standard\" TCR. We then compared the accuracy of the TCR estimated by 13 pathologists based on visual assessment and the TCR calculated by an AI model that we have developed. It is a compact and fast model that follows a fully convolutional neural network architecture and produces cell detection maps which can be efficiently post-processed to obtain tumor and non-tumor cell counts from which TCR is calculated. Its raw cell detection accuracy is 92% while its classification accuracy is 84%. The results show that the error between the gold standard TCR and the AI calculation was significantly smaller than that between the gold standard TCR and the pathologist\'s visual assessment (p<0.05). Additionally, the robustness of AI models across institutions is a key issue and we demonstrate that the variation in AI was smaller than that in the average of pathologists when evaluated by institution. These findings suggest that the accuracy of tumor cellularity assessments in clinical workflows is significantly improved by the introduction of robust AI models, leading to more efficient genetic testing and ultimately to better patient outcomes.

UNASSIGNED: Türkiye confirmed its first case of SARS-CoV-2 on March 11, 2020, coinciding with the declaration of the global COVID-19 pandemic. Subsequently, Türkiye swiftly increased testing capacity and implemented genomic sequencing in 2020. This paper describes Türkiye\'s journey of establishing genomic surveillance as a middle-income country with limited prior sequencing capacity and analyses sequencing data from the first two years of the pandemic. We highlight the achievements and challenges experienced and distill globally relevant lessons.
UNASSIGNED: We tracked the evolution of the COVID-19 pandemic in Türkiye from December 2020 to February 2022 through a timeline and analysed epidemiological, vaccination, and testing data. To investigate the phylodynamic and phylogeographic aspects of SARS-CoV-2, we used Nextstrain to analyze 31,629 high-quality genomes sampled from seven regions nationwide.
UNASSIGNED: Türkiye\'s epidemiological curve, mirroring global trends, featured four distinct waves, each coinciding with the emergence and spread of variants of concern (VOCs). Utilizing locally manufactured kits to expand testing capacity and introducing variant-specific quantitative reverse transcription polymerase chain reaction (RT-qPCR) tests developed in partnership with a private company was a strategic advantage in Türkiye, given the scarcity and fragmented global supply chain early in the pandemic. Türkiye contributed more than 86,000 genomic sequences to global databases by February 2022, ensuring that Turkish data was reflected globally. The synergy of variant-specific RT-qPCR kits and genomic sequencing enabled cost-effective monitoring of VOCs. However, data analysis was constrained by a weak sequencing sampling strategy and fragmented data management systems, limiting the application of sequencing data to guide the public health response. Phylodynamic analysis indicated that Türkiye\'s geographical position as an international travel hub influenced both national and global transmission of each VOC despite travel restrictions.
UNASSIGNED: This paper provides valuable insights into the testing and genomic surveillance systems adopted by Türkiye during the COVID-19 pandemic, proposing important lessons for countries developing national systems. The findings underscore the need for robust testing and sampling strategies, streamlined sample referral, and integrated data management with metadata linkage and data quality crucial for impactful epidemiological analysis. We recommend developing national genomic surveillance strategies to guide sustainable and integrated expansion of capacities built for COVID-19 and to optimize the effective utilization of sequencing data for public health action.

UNASSIGNED: Amivantamab (JNJ-372) and mobocertinib (TAK-788) have been reported to have favorable therapeutic effect for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) exon 20 insertion (ex20ins) mutations. Thus, accurate detection of EGFR ex20ins mutations is crucial for subsequent individualized therapy. The aim of this study was to compare the two common methods of next generation sequencing (NGS) and amplification refractory mutation system polymerase chain reaction (ARMS-PCR) for detecting EGFR ex20ins mutations in Chinese NSCLC patients.
UNASSIGNED: We retrospectively analyzed EGFR mutations, especially for ex20ins, in 3,606 NSCLC patients detected by NGS and 1,785 patients by ARMS.
UNASSIGNED: Among the 3,606 NGS patients, a total of 2,077 EGFR mutations and 95 EGFR ex20ins were identified, accounting for 57.6% and 2.6%, respectively. While 48.4% of EGFR mutations and 1.1% of ex20ins were detected in 1,785 ARMS patients, which were significantly lower than those of NGS (P<0.01). Thirty-four unique ex20ins variants were identified by NGS, and eight of them was reported for the first time. However, ARMS was designed to detect only several known EGFR ex20ins variants, and even did not include the most common variants in Chinese NSCLC patients.
UNASSIGNED: NGS is more advantageous and strongly recommended for the detection of EGFR ex20ins mutations. Considering the fast and cost-effective ARMS detection method, it is suggested that the primers design should be updated according to the characteristics of EGFR ex20ins mutations in Chinese NSCLC patients.

OBJECTIVE: The IPEC-J2 cell line is used as an in vitro small intestine model for swine, but it is also used as a model for the human intestine, presenting a relatively unique setting. By combining electric cell-substrate impedance sensing, with next-generation-sequencing technology, we showed that mRNA gene expression profiles and related pathways can depend on the growth phase of IPEC-J2 cells. Our investigative approach welcomes scientists to reproduce or modify our protocols and endorses putting their gene expression data in the context of the respective growth phase of the cells.
RESULTS: Three time points are presented: (TP1) 1 h after medium change (= 6 h after seeding of cells), (TP2) the time point of the first derivative maximum of the cell growth curve, and a third point at the beginning of the plateau phase (TP3). Significantly outstanding at TP1 compared to TP2 was upregulated PLEKHN1, further FOSB and DEGS2 were significantly downregulated at TP2 compared to TP3. Any provided data can be used to improve next-generation experiments with IPEC-J2 cells.

Chronic lymphocytic leukemia (CLL) is a low-grade B-cell lymphoproliferative disorder. It is the most prevalent type of leukemia in the western countries, with a median age at diagnosis of 70 years. In 2023, it is estimated that there will be 18,740 new cases of CLL, and an estimated 4,490 people will die of this disease. It represents 1.0% of all new cancer cases in the U.S. The rate of new cases was 4.6 per 100,000 men and women per year based on 2016-2020 cases, age-adjusted. Death rates from CLL are higher among older adults, or those 75 and older. The death rate was 1.1 per 100,000 men and women per year based on 2016-2020 deaths, age-adjusted. A common question that patients with CLL ask during their first clinic visit is: \"How long will it be before I would need treatment?\" Although this might seem like a simple question, the answer is not straight forward. CLL is a heterogenous disease, with a variable clinical course. Some patients may present with an aggressive disease requiring early initiation of treatment, while others have an indolent course and some, having so called smoldering CLL, may never need treatment. The variability in disease course can make predicting disease prognosis a complicated process. This brings forth the importance of establishing prognostic models that can predict disease course, time to treatment, and survival outcomes in such a heterogenous disease. The Rai and Binet staging systems were developed in the late 1970s to early 1980s. They separated patients into different stages based on clinical characteristics and laboratory findings. These simple staging systems are still in use; however, several prognostic markers need to be added for an individualized assessment and, with the recent development of genomic techniques leading to better understanding of CLL at the molecular level, newer prognostic markers have emerged.

Multiple myeloma (MM) is the second most common hematological malignancy, which remains incurable despite recent advances in treatment strategies. Like other forms of cancer, MM is characterized by genomic instability, caused by defects in DNA repair. Along with mutations in DNA repair genes and genotoxic drugs used to treat MM, non-canonical secondary DNA structures (four-stranded G-quadruplex structures) can affect accumulation of somatic mutations and chromosomal abnormalities in the tumor cells of MM patients. Here, we tested the hypothesis that G-quadruplex structures may influence the distribution of somatic mutations in the tumor cells of MM patients. We sequenced exomes of normal and tumor cells of 11 MM patients and analyzed the data for the presence of G4 context around points of somatic mutations. To identify molecular mechanisms that could affect mutational profile of tumors, we also analyzed mutational signatures in tumor cells as well as germline mutations for the presence of specific SNPs in DNA repair genes or in genes regulating G-quadruplex unwinding. In several patients, we found that sites of somatic mutations are frequently located in regions with G4 context. This pattern correlated with specific germline variants found in these patients. We discuss the possible implications of these variants for mutation accumulation and specificity in MM and propose that the extent of G4 context enrichment around somatic mutation sites may be a novel metric characterizing mutational processes in tumors.

The aim of this study was to identify genetic markers in the HBB Cluster; HBS1L-MYB intergenic region; and BCL11A, KLF1, FOX3, and ZBTB7A genes associated with the heterogeneous phenotypes of Sickle Cell Anemia (SCA) using next-generation sequencing, as well as to assess their influence and prevalence in an Angolan population. Hematological, biochemical, and clinical data were considered to determine patients\' severity phenotypes. Samples from 192 patients were sequenced, and 5,019,378 variants of high quality were registered. A catalog of candidate modifier genes that clustered in pathophysiological pathways important for SCA was generated, and candidate genes associated with increasing vaso-occlusive crises (VOC) and with lower fetal hemoglobin (HbF) were identified. These data support the polygenic view of the genetic architecture of SCA phenotypic variability. Two single nucleotide polymorphisms in the intronic region of 2q16.1, harboring the BCL11A gene, are genome-wide and significantly associated with decreasing HbF. A set of variants was identified to nominally be associated with increasing VOC and are potential genetic modifiers harboring phenotypic variation among patients. To the best of our knowledge, this is the first investigation of clinical variation in SCA in Angola using a well-customized and targeted sequencing approach.

In this study, we adopt an interdisciplinary approach, integrating agronomic field experiments with soil chemistry, molecular biology techniques, and statistics to investigate the impact of organic residue amendments, such as vinasse (a by-product of sugarcane ethanol production), on soil microbiome and greenhouse gas (GHG) production. The research investigates the effects of distinct disturbances, including organic residue application alone or combined with inorganic N fertilizer on the environment. The methods assess soil microbiome dynamics (composition and function), GHG emissions, and plant productivity. Detailed steps for field experimental setup, soil sampling, soil chemical analyses, determination of bacterial and fungal community diversity, quantification of genes related to nitrification and denitrification pathways, measurement and analysis of gas fluxes (N2O, CH4, and CO2), and determination of plant productivity are provided. The outcomes of the methods are detailed in our publications (Lourenço et al., 2018a; Lourenço et al., 2018b; Lourenço et al., 2019; Lourenço et al., 2020). Additionally, the statistical methods and scripts used for analyzing large datasets are outlined. The aim is to assist researchers by addressing common challenges in large-scale field experiments, offering practical recommendations to avoid common pitfalls, and proposing potential analyses, thereby encouraging collaboration among diverse research groups.•Interdisciplinary methods and scientific questions allow for exploring broader interconnected environmental problems.•The proposed method can serve as a model and protocol for evaluating the impact of soil amendments on soil microbiome, GHG emissions, and plant productivity, promoting more sustainable management practices.•Time-series data can offer detailed insights into specific ecosystems, particularly concerning soil microbiota (taxonomy and functions).

Exercise plays an important role in regulating energy homeostasis, which affects the diversity of the intestinal microbial community in humans and animals. To the best of the authors\' knowledge, few studies have reported the associations between horse gut microbiota along with their predicted metabolic activities and the athletic ability of Jeju horses and Thoroughbreds living in Korea. This study was conducted to investigate the association between the gut microbiota and athletic performance in horses. This study sequenced the V3 and V4 hypervariable regions of the partial 16S rRNA genes obtained from racehorse fecal samples and compared the fecal microbiota between high- and low-performance Jeju horses and Thoroughbreds. Forty-nine fecal samples were divided into four groups: high-performance Jeju horses (HJ, n = 13), low-performance Jeju horses (LJ, n = 17), high-performance Thoroughbreds (HT, n = 9), and low-performance Thoroughbreds (LT, n = 10). The high-performance horse groups had a higher diversity of the bacterial community than the low-performance horse groups. Two common functional metabolic activities of the hindgut microbiota (i.e., tryptophan and succinate syntheses) were observed between the low-performance horse groups, indicating dysbiosis of gut microbiota and fatigue from exercise. On the other hand, high-performance horse groups showed enriched production of polyamines, butyrate, and vitamin K. The racing performance may be associated with the composition of the intestinal microbiota of Jeju horses and Thoroughbreds in Korea.