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Abstract BackgroundGlobal developmental delay or intellectual disability usually accompanies various genetic disorders as a part of the syndrome, which may include seizures, autism spectrum disorder and multiple congenital abnormalities. Next-generation sequencing (NGS) techniques have improved the identification of pathogenic variants and genes related to developmental delay. This study aimed to evaluate the yield of whole exome sequencing (WES) and neurodevelopmental disorder gene panel sequencing in a pediatric cohort from Ukraine. Additionally, the study computationally predicted the effect of variants of uncertain significance (VUS) based on recently published genetic data from the country’s healthy population. MethodsThe study retrospectively analyzed WES or gene panel sequencing findings of 417 children with global developmental delay, intellectual disability, and/or other symptoms. Variants of uncertain significance were annotated using CADD-Phred and SIFT prediction scores, and their frequency in the healthy population of Ukraine was estimated. ResultsA definitive molecular diagnosis was established in 66 (15.8%) of the individuals. WES diagnosed 22 out of 37 cases (59.4%), while the neurodevelopmental gene panel identified 44 definitive diagnoses among the 380 tested patients (12.1%). Non-diagnostic findings (VUS and carrier) were reported in 350 (83.2%) individuals. The most frequently diagnosed conditions were developmental and epileptic encephalopathies associated with severe epilepsy and GDD/ID (associated genesARX, CDKL5, STXBP1, KCNQ2, SCN2A, KCNT1, KCNA2). Additionally, we annotated 221 VUS classified as potentially damaging, AD or X-linked, potentially increasing the diagnostic yield by 30%, but 18 of these variants were present in the healthy population of Ukraine. ConclusionsThis is the first comprehensive study on genetic causes of GDD/ID conducted in Ukraine. This study provides the first comprehensive investigation of the genetic causes of GDD/ID in Ukraine. It presents a substantial dataset of diagnosed genetic conditions associated with GDD/ID. The results support the utilization of NGS gene panels and WES as first-line diagnostic tools for GDD/ID cases, particularly in resource-limited settings. A comprehensive approach to resolving VUS, including computational effect prediction, population frequency analysis, and phenotype assessment, can aid in further reclassification of deleterious VUS and guide further testing in families. 

Abstract Lymphedema is localized swelling due to lymphatic system dysfunction, often affecting arms and legs due to fluid accumulation. It occurs in 20% to 94% of patients within 2–5 years after breast cancer treatment, with around 20% of women developing breast cancer-related lymphedema. This condition involves the accumulation of protein-rich fluid in interstitial spaces, leading to symptoms like swelling, pain, and reduced mobility that significantly impact quality of life. The early diagnosis of lymphedema helps mitigate the risk of deterioration and prevent its progression to more severe stages. Healthcare providers can reduce risks through exercise prescriptions and self-manual lymphatic drainage techniques. Lymphedema diagnosis currently relies on physical examinations and limb volume measurements, but challenges arise from a lack of standardized criteria and difficulties in detecting early stages. Recent advancements in computational imaging and decision support systems have improved diagnostic accuracy through enhanced image reconstruction and real-time data analysis. The aim of this comprehensive review is to provide an in-depth overview of the research landscape in computational diagnostic techniques for lymphedema. The computational techniques primarily include imaging-based, electrical, and machine learning (ML) approaches, which utilize advanced algorithms and data analysis. These modalities were compared based on various parameters to choose the most suitable techniques for their applications. Lymphedema detection faces challenges like subtle symptoms and inconsistent diagnostics. The research identifies bioimpedance spectroscopy (BIS), Kinect sensor and ML integration as the promising modalities for early lymphedema detection. BIS can effectively identify lymphedema as early as four months post-surgery with sensitivity of 44.1% and specificity of 95.4% in diagnosing lymphedema whereas ML and artificial neural network achieved an impressive average cross-validation accuracy of 93.75%, with sensitivity at 95.65% and specificity at 91.03%. ML and imaging can be integrated into clinical practice to enhance diagnostic accuracy and accessibility. 

OBJECTIVES:To identify triggering receptor expressed in myeloid cells-like transcript-1 positive (TLT-1⁺) microparticles (MPs) and evaluate if their presence is associated with clinical outcomes and/or disease severity in acute respiratory distress syndrome (ARDS). DESIGN:Retrospective cohort study. SETTING:ARDS Network clinical trials. PATIENTS:A total of 564 patients were diagnosed with ARDS. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Using flow cytometry, we demonstrated the presence of TLT-1⁺platelet-derived microparticles (PMP) that bind fibrinogen in plasma samples from fresh donors. We retrospectively quantified TLT-1, glycoprotein (Gp) 1b, or α_IIbβ_IIIaimmunopositive microparticles in plasma samples from patients with ARDS enrolled in the ARMA, KARMA, and LARMA (Studies 01 and 03 lower versus higher tidal volume, ketoconazole treatment, and lisofylline treatment Clincial Trials) ARDS Network clinical trials and evaluated the relationship between these measures and clinical outcomes. No associations were found between Gp1b⁺MPs and clinical outcomes for any of the cohorts. When stratified by quartile, associations were found for survival, ventilation-free breathing, and thrombocytopenia with α_IIbβ_IIIa⁺and TLT-1⁺MPs (χ²p< 0.001). Notably, 63 of 64 patients in this study who failed to achieve unassisted breathing had TLT⁺PMP in the 75th percentile. In all three cohorts, patients whose TLT⁺MP counts were higher than the median had higher Acute Physiology and Chronic Health Evaluation III scores, were more likely to present with thrombocytopenia and were 3.7 times (p< 0.001) more likely to die than patients with lower TLT⁺PMP after adjusting for other risk factors. CONCLUSIONS:Although both α_IIbβ_IIIa⁺and TLT⁺microparticles (α_IIbβ_IIIa, TLT-1) were associated with mortality, TLT-1⁺MPs demonstrated stronger correlations with Acute Physiology and Chronic Health Evaluation III scores, unassisted breathing, and multiple system organ failure. These findings warrant further exploration of the mechanistic role of TLT-1⁺PMP in ARDS or acute lung injury progression. 

Abstract Hematocrit (Hct) is a powerful tool often used in a clinical setting for the diagnosis of blood conditions such as anemia. It is also used in the research field as a hematological parameter in both human and mouse models. Measuring Hct, however, involves the use of expensive standardized equipment (such as a CritSpin™ Microhematocrit Centrifuge). Here, we describe a novel, simple, and affordable method to determine the Hct in untreated wild‐type (WT) mice and phenylhydrazine (PHZ)‐induced anemic mice with reasonable accuracy, using a benchtop centrifuge commonly available in laboratories. Hct of murine samples processed with a benchtop centrifuge, when compared to the standardized method CritSpin™, showed comparable results. This approach for determining Hct of murine can prove useful to research laboratories that cannot afford specialized equipment for Hct studies. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Affordable Method for Hematocrit Determination in Murine Models Basic Protocol 2: Murine Sample Validation Support Protocol: Phenylhydrazine‐induced anemia in wild‐type (WT) mice 

Background:Thrombosis is initiated by tissue factor (TF, gene nameF3) binding to coagulationFVII, with tissue factor pathway inhibitor (TFPI) inhibiting this complex. Alterations in TF orTFPI expression significantly affect thrombosis. Reducing TFPI expression by 50% (Tfpi+/-) inmice results in a perinatal lethal phenotype on the Factor V Leiden homozygous(F5^L/L)prothrombotic background. We used theF5^L/LTfpi+/- lethal phenotype to conduct a dominantsensitized whole genome ENU mutagenesis screen to suppress theF5^L/LTfpi+/- lethality. Weidentified a Modifier of Factor 5 Leiden 6 (MF5L6) line with 72% penetrance and 85F5^L/LTfpi+/- offspring. A significant linkage peak (LOD=4.35),explaining half the suppressing effect andcontainingF3(Chromosome 3) was identified. Goals/Hypothesis:To identify the genomic variant controlling F3 expression in the MF5L6 line. Methods:To quantifyF3expression in the surviving mice from MF5L6, quantitative PCR onliver, lung, and heart tissues from MF5L6 was performed. We used Sanger DNA and highthroughput sequencing to identify candidate TF regulatory variants in the F3 locus. Theprothrombin time assay was used to test the effects of reduced TF expression on in vitro bloodcoagulation. Results:Two distinct expression profiles in the lung and liver of the MF5L6 mice wereobserved, those that had a 50% reduction inF3mRNA and those that did not. Heart tissuesexhibited one expression profile, suggesting that the variant regulates F3 expressiontissue-specifically. Sanger sequencing of theF3coding region revealed no coding mutations inMF5L6 mice. Whole genome sequencing identified two novel candidate variants (in unknownF3 regulatory elements) in the 200 kilobase upstream region ofF3. The 50% reduction inF3resulted in significant changes in coagulation by the prothrombin assay (n=18,p<0.0009). Conclusion:We identified novel candidate variants for regulatingF3gene expression and aredetermining their mechanism of action. Investigation of these variants will provide new insightsinto the regulation ofF3and enable us to identify the variant(s) responsible for the remainder ofthe thrombosis suppressing effect in MF5L6. Our findings provide new insights into the geneticregulation of thrombosis.