Expanding deep phenotypic spectrum associated with atypical pathogenic structural variations overlapping 15q11-q13 imprinting region.

BACKGROUND: The 15q11-q13 region is a genetic locus with genes subject to genomic imprinting, significantly influencing neurodevelopment. Genomic imprinting is an epigenetic phenomenon that causes differential gene expression based on the parent of origin. In most diploid organisms, gene expression typically involves an equal contribution from both maternal and paternal alleles, shaping the phenotype. Nevertheless, in mammals, including humans, mice, and marsupials, the functional equivalence of parental alleles is not universally maintained. Notably, during male and female gametogenesis, parental alleles may undergo differential marking or imprinting, thereby modifying gene expression without altering the underlying DNA sequence. Neurodevelopmental disorders, such as Prader-Willi syndrome (PWS) (resulting from the absence of paternally expressed genes in this region), Angelman syndrome (AS) (associated with the absence of the maternally expressed UBE3A gene), and 15q11-q13 duplication syndrome (resulting from the two common forms of duplications-either an extra isodicentric 15 chromosome or an interstitial 15 duplication), are the outcomes of genetic variations in this imprinting region. METHODS: Conducted a genomic study to identify the frequency of pathogenic variants impacting the 15q11-q13 region in an ethnically homogenous population from Bangladesh. Screened all known disorders from the DECIPHER database and identified variant enrichment within this cohort. Using the Horizon analysis platform, performed enrichment analysis, requiring at least >60% overlap between a copy number variation and a disorder breakpoint. Deep clinical phenotyping was carried out through multiple examination sessions to evaluate a range of clinical symptoms. RESULTS: This study included eight individuals with clinically suspected PWS/AS, all previously confirmed through chromosomal microarray analysis, which revealed chromosomal breakpoints within the 15q11-q13 region. Among this cohort, six cases (75%) exhibited variable lengths of deletions, whereas two cases (25%) showed duplications. These included one type 2 duplication, one larger atypical duplication, one shorter type 2 deletion, one larger type 1 deletion, and four cases with atypical deletions. Furthermore, thorough clinical assessments led to the diagnosis of four PWS patients, two AS patients, and two individuals with 15q11-q13 duplication syndrome. CONCLUSION: Our deep phenotypic observations identified a spectrum of clinical features that overlap and are unique to PWS, AS, and Dup15q syndromes. Our findings establish genotype-phenotype correlation for patients impacted by variable structural variations within the 15q11-q13 region.

Immune checkpoint inhibitor-induced myopericarditis.

A woman in her 30s with a medical history of metastatic rectal adenocarcinoma, currently on pembrolizumab, which started a few weeks ago, was admitted for abdominal pain. During the hospital stay, she experienced sharp chest pain. Troponin was 1885 ng/mL which peaked at 7338 ng/mL. ECG was unremarkable. The echocardiogram showed an Ejection fraction (EF) of 55%-60% and basal-inferior wall hypokinesis. Left heart catheterisation showed no coronary abnormalities. Cardiac MRI showed a non-coronary area of focal T1 and T2 hyperintense signal and transmural delayed gadolinium enhancement in the mid-basal inferior/inferoseptal wall consistent with myocardial damage. Pericardium showed increased thickness and adhesions at the right ventricular outflow tract consistent with pericarditis. Steroid therapy was initiated, and a marked clinical response was achieved. Immune checkpoint inhibitor-induced myocarditis and pericarditis is a rare complication associated with a high mortality rate, if untreated. Diagnosis requires a multidisciplinary approach, and early detection is critical to preventing a fatal outcome.

Ventriculoperitoneal Shunt Failure and Cerebrospinal Fluid Protein: A Meta-Analysis and Systematic Review.

Ventriculoperitoneal shunts (VPS) are used to manage hydrocephalus but suffer from high failure rates. Our objectives were to (1) conduct a meta-analysis to objectively weigh this conflicting evidence, and (2) conduct a systematic review compiling and synthesizing what is known about the association between CSF proteins and shunt failure. A literature search was performed in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Embase, PubMed, and CENTRAL databases were searched from inception to June 2023. The articles were screened based on the inclusion criteria. A meta-analysis was conducted using R statistical software (R Foundation for Statistical Computing, Vienna, Austria); heterogeneity, subgroup, sensitivity, risk of bias, and publication bias analyses were performed. Thirty-one studies were selected for the systematic review, of which eight were selected for the meta-analysis. Perioperative CSF protein level was compared between 351 shunt failures and 1,094 shunt survivals; the mean difference of 24.37 mg/dL favoring shunt failure was significant (95% confidence interval=2.44-46.29 mg/dL). Our systematic review yielded a hypothesized pathogenesis: proteins attached to imperfections in the shunt surface lead to secondary attachment of cells, particularly astrocytes, and tertiary attachment of ependymal cells and the choroid plexus. Owing to the limitations of this meta-analysis, including lack of robustness due to missing data, heterogeneity, and certainty of the evidence, future research is needed to better understand the relationship between perioperative CSF protein levels and shunt failure.

The impact of multiple stenosis and aneurysms on arterial diseases: A cardiovascular study.

The comparative effect of serial stenosis and aneurysms arteries on blood flow is examined to identify atherosclerotic diseases. The finite element approach has been used to solve the continuity, momentum, and Oldroyd-B partial differential equations to analyze the blood flow. Newtonian and non-Newtonian both cases are taken for the viscoelastic response of blood. In this study, the impact of multiple stenotic and aneurysmal arteries on blood flow have been studied to determine the severity of atherosclerosis diseases through the analysis of blood behavior. The novel aspect of the study is its assessment of the severity of atherosclerotic disorders for the occurrence of serial stenosis and aneurysm simultaneously in the blood vessel wall in each of the four cases. The maximum abnormal arterial blood flow effect is found for the presence of serial stenoses compared to aneurysms which refers to the severity of atherosclerosis. At the hub of stenosis, the blood velocity magnitude and wall shear stress (WSS) are higher, whereas the arterial wall normal gradient values are lower. For all cases, the contrary results are observed at the hub of the aneurysmal model. The blood flow has been affected significantly by the increases in Reynolds number for both models. The influence of stenotic and aneurysmal arteries on blood flow is graphically illustrated in terms of the velocity profile, pressure distribution, and WSS. Medical experts may use this study's findings to assess the severity of cardiovascular diseases.

ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application.

Chronic kidney diseases (CKDs) are a significant public health issue with potential for severe complications such as hypertension, anemia, and renal failure. Timely diagnosis is crucial for effective management. Leveraging machine learning within healthcare offers promising advancements in predictive diagnostics. In this paper, we developed a machine learning-based kidney diseases prediction (ML-CKDP) model with dual objectives: to enhance dataset preprocessing for CKD classification and to develop a web-based application for CKD prediction. The proposed model involves a comprehensive data preprocessing protocol, converting categorical variables to numerical values, imputing missing data, and normalizing via Min-Max scaling. Feature selection is executed using a variety of techniques including Correlation, Chi-Square, Variance Threshold, Recursive Feature Elimination, Sequential Forward Selection, Lasso Regression, and Ridge Regression to refine the datasets. The model employs seven classifiers: Random Forest (RF), AdaBoost (AdaB), Gradient Boosting (GB), XgBoost (XgB), Naive Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT), to predict CKDs. The effectiveness of the models is assessed by measuring their accuracy, analyzing confusion matrix statistics, and calculating the Area Under the Curve (AUC) specifically for the classification of positive cases. Random Forest (RF) and AdaBoost (AdaB) achieve a 100% accuracy rate, evident across various validation methods including data splits of 70:30, 80:20, and K-Fold set to 10 and 15. RF and AdaB consistently reach perfect AUC scores of 100% across multiple datasets, under different splitting ratios. Moreover, Naive Bayes (NB) stands out for its efficiency, recording the lowest training and testing times across all datasets and split ratios. Additionally, we present a real-time web-based application to operationalize the model, enhancing accessibility for healthcare practitioners and stakeholders. Web app link: https://rajib-research-kedney-diseases-prediction.onrender.com/.

A mathematical model for the transmission of co-infection with COVID-19 and kidney disease.

The world suffers from the acute respiratory syndrome COVID-19 pandemic, which will be scary if other co-existing illnesses exacerbate it. The co-occurrence of the COVID-19 virus with kidney disease has not been available in the literature. So, further research needs to be conducted to reveal the transmission dynamics of COVID-19 and kidney disease. This study aims to create mathematical models to understand how COVID-19 interacts with kidney diseases in specific populations. Therefore, the initial step was to formulate a deterministic Susceptible-Infected-Recovered (SIR) mathematical model to depict the co-infection dynamics of COVID-19 and kidney disease. A mathematical model with seven compartments has been developed using nonlinear ordinary differential equations. This model incorporates the invariant region, disease-free and endemic equilibrium, along with the positivity solution. The basic reproduction number, calculated via the next-generation matrix, allows us to assess the stability of the equilibrium. Sensitivity analysis is also utilised to understand the influence of each parameter on disease spread or containment. The results show that a surge in COVID-19 infection rates and the existence of kidney disease significantly enhances the co-infection risks. Numerical simulations further clarify the potential outcomes of treating COVID-19 alone, kidney disease alone, and co-infected cases. The study of the potential model can be utilised to maximise the benefits of simulation to minimise the global health complexity of COVID-19 and kidney disease.

A Rare Case of Neonatal Hypomagnesemia with Secondary Hypocalcemia Caused by a Novel Homozygous TRPM6 Gene Variant.

BACKGROUND Familial hypomagnesemia with secondary hypocalcemia (HSH) is a rare autosomal recessive disorder (OMIM# 602014) caused by mutations in the gene encoding transient receptor potential melastatin 6 (TRPM6)) on chromosome 9q22, a channel involved in epithelial magnesium resorption. While a plethora of studies have delineated various clinical manifestations pertinent to this mutation, the literature is devoid of connections between TRPM6 mutations and bleeding diathesis, or sudden infant death syndrome (SIDS). This report presents a case of familial HSH associated with the novel homozygous TRPM6 gene variant c.5281C>G p. (Arg1761Gly) chr9: 77354845. CASE REPORT This report details a 26-day-old neonate, born full term with optimal Apgar scores, who experienced an abrupt emergence of apnea, cyanosis, bilateral nasal bleeding, and diminished alertness. Despite the neonate's initially unremarkable clinical birth indicators, a meticulous assessment unveiled a pronounced family history of SIDS, including a sibling previously diagnosed with hypomagnesemia. Laboratory examination of the infant demonstrated severe hypomagnesemia and hypocalcemia, conditions which were promptly ameliorated following intravenous administration of magnesium and calcium. Whole-exome sequencing identified a homozygous TRPM6 gene mutation c.5281C>G p. (Arg1761Gly) at chr9: 77354845. This gene is crucial for magnesium regulation. The mutation involves a cytosine-to-guanine shift, resulting in an arginine to glycine amino acid substitution at position 1761 of the TRPM6 protein. CONCLUSIONS This report has highlighted that infantile hypomagnesemia may be associated with symptoms and signs that can mimic infection, or it can present with seizures. Although familial HSH is a rare genetic disorder that can be identified by genetic testing, correction of hypomagnesemia is the most important and immediate clinical management strategy.

Understanding the impact of socioeconomic and health factors on geriatric depression: A comparative study in rural and urban Bangladesh.

Background and Aims: The prevalence of depression among the elderly is a growing concern, and this study examines the differences between urban and rural areas in terms of geriatric depression. Methods: Using a two-stage random sampling approach in urban areas and a multistage random sampling approach in rural areas, the study surveyed 944 elderly individuals of both sexes. Results: The results indicate that the prevalence of depression was high, with 52.5% of the elderly population experiencing mild to severe depression. The study found that increasing age, female gender, nuclear family structure, and involvement of housewives or others were significant factors affecting depression in urban areas, while increasing age and elderly people without spouses were significant factors in rural areas. Additionally, the study identified hearing impairment, asthma, and arthritis as risk factors for depression in rural areas, and bronchitis, heart disease, and thyroid illness as significant factors in urban areas. Conclusion: These findings highlight the need for policymakers to focus on addressing the mental health needs of older people, particularly women and those without spouses.

Impact of Respiratory Viruses and SARS-CoV-2 on Febrile Seizures in Saudi Children: Insights into Etiologies, Gender, and Familial Associations.

BACKGROUND Childhood febrile seizures occur between 5 months and 6 years of age in children without a previous history of seizure and are associated with high temperature in the absence of intracranial infection. This retrospective study identified 71 children aged 6 months to 5 years with febrile seizures between 2017 and 2021 at a single center in Saudi Arabia and aimed to identify an association between common respiratory virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MATERIAL AND METHODS Pediatric nasopharyngeal specimens were tested using a multiplex PCR respiratory panel detecting human coronaviruses (NL63, 229E, OC43, HKU1), influenza A/B, human adenovirus, parainfluenza viruses 1-4, respiratory syncytial virus, human metapneumovirus, rhinovirus/enterovirus, Middle East respiratory syndrome coronavirus, and, as of September 2021, SARS-CoV-2, confirmed using the Cepheid Xpert Xpress SARS-CoV2 RT-PCR kit. RESULTS In a cohort of 71 pediatric patients (median age, 19 months; 54.9% female), dominant pathogens included human rhinovirus/enterovirus (23.9%), influenza A/B (26.8%), and SARS-CoV-2 (14.1%). Concurrent infections were noted in 28.2%. Simple seizures occurred in 69%, and complex seizures in 31%. Females exhibited an 8.18-fold increased risk for complex seizures. Each additional fever day reduced complex seizure risk by 36%. Familial seizure history increased risk 8.76-fold. Human rhinovirus/enterovirus or parainfluenza infections inversely affected complex seizure likelihood compared with adenovirus. CONCLUSIONS In Saudi children with febrile seizures, distinct viral etiologies, sex, and familial links play pivotal roles. Given regional viral variations, region-tailored diagnostic and therapeutic strategies are paramount. A multicenter prospective cohort study is essential for comprehensive understanding.

Enhancing cell separation in a hybrid spiral dielectrophoretic microchannel: Numerical insights and optimal operating conditions.

Reliable separation of circulating tumor cells from blood cells is crucial for early cancer diagnosis and prognosis. Many conventional microfluidic platforms take advantage of the size difference between particles for their separation, which renders them impractical for sorting overlapping-sized cells. To address this concern, a hybrid inertial-dielectrophoretic microfluidic chip is proposed in this work for continuous and single-stage separation of lung cancer cell line A549 cells from white blood cells of overlapping size. The working mechanism of the proposed spiral microchannel embedded with planar interdigitated electrodes is validated against the experimental results. A numerical investigation is carried out over a range of flow conditions and electric field intensity to determine the separation efficiency and migration characteristics of the cell mixture. The results demonstrate the unique capability of the proposed microchannel to achieve high-throughput separation of cells at low applied voltages in both vertical and lateral directions. A significant lateral separation distance between the CTCs and the WBCs has been achieved, which allows for high-resolution and effective separation of cells. The separation resolution can be controlled by adjusting the strength of the applied electric field. Furthermore, the results demonstrate that the lateral separation distance is maximum at a voltage termed the critical voltage, which increases with the increase in the flow rate. The proposed microchannel and the developed technique can provide valuable insight into the development of a tunable and robust medical device for effective and high-throughput separation of cancer cells from the WBCs.

Real-world evidence on the effectiveness and safety of gliclazide MR 60 mg in Bangladeshi patients with Type II diabetes during fasting: a sub-analysis from the global DIA-RAMADAN study.

Aim: Many Muslims with Type II diabetes (T2DM) fast during Ramadan, which can put them at increased risk of hypoglycemia. This sub-analysis of the global DIA-RAMADAN study assessed the effectiveness and safety of gliclazide modified release (MR) 60 mg in the Bangladeshi cohort. Materials & methods: DIA-RAMADAN was an international, prospective, observational study conducted in adult T2DM patients intending to fast and receiving gliclazide MR 60 mg once daily for ≥90 days before Ramadan. Dosing was switched from morning to evening at the start of Ramadan. The primary outcome was the proportion of patients with ≥1 symptomatic hypoglycemic event. Secondary outcomes included changes between inclusion (V0) and end of study visit (V1) in glycated hemoglobin (HbA1c), body weight and fasting plasma glucose (FPG). Results: Among the 98 Bangladeshi patients, 80 (81.6%) were at moderate/low-risk (category 3) for fasting and 18 (18.4%) were high-risk (category 2), as per International Diabetes Federation and Diabetes and Ramadan International Alliance (IDF-DAR) guidelines. Gliclazide MR was being prescribed as monotherapy to 59 (60.2%) patients and in combination with metformin to 39 (39.8%). There was no incidence of severe hypoglycemic events. Mean (±SD) HbA1c change from V0 was -0.1 ± 0.8% (p = 0.159). Mean (±SD) changes in FPG and body weight were -0.8 ± 39.7 mg/dl (p = 0.876) and -0.0 ± 1.5 kg (p = 0.810), respectively. Conclusion: In a real-world setting, this sub-analysis in Bangladeshi patients shows that patients with T2DM treated with gliclazide MR 60 mg can fast safely during Ramadan with a very low risk of hypoglycemia, while maintaining glycemic control and body weight.

Decision tree ensemble with Bayesian optimization to predict the spatial dynamics of chlorophyll-a concentration: A case study in Bay of Bengal.

An accurate prediction of the spatial distribution of phytoplankton biomass, as represented by Chlorophyll-a (CHL-a) concentrations, is important for assessing ecological conditions in the marine environment. This study developed a hyperparameter-optimized decision tree-based machine learning (ML) models to predict the geographical distribution of marine phytoplankton CHL-a in the Bay of Bengal. To predict CHL-a over a large spatial extent, satellite-derived remotely sensed data of ocean color features (CHL-a, colored dissolved organic matter, photosynthetically active radiation, particulate organic carbon) and climatic factors (nighttime sea surface temperature, surface absorbed longwave radiation, sea level pressure) from 2003 to 2022 are used to train and test the models. Results obtained from this study have shown the highest concentrations of CHL-a occurred near the Bay's coastal belts and river estuaries. Analysis revealed that aside from photosynthetically active radiation, organic components exhibited a stronger positive relationship with CHL-a than climatic features, which are correlated negatively. Results showed the chosen decision tree methods to all possess higher R2 and lower root mean square error (RMSE) errors. Furthermore, XGBoost outperforms all other models in predicting the geographic distribution of CHL-a. To assess the model efficacy on seasonal basis, a best performing XGBoost model was validated in the Bay of Bengal region which has shown a good performance in predicting the spatial distribution of Chl-a as well as the pixel values during the summer, winter and monsoon seasons. This study provides the best ML model to researchers for predicting CHL-a in the Bay of Bengal. Further it helps to improve our knowledge of CHL-a spatial dynamics and assist in monitoring marine resources in the Bay of Bengal. It worth noting that the water quality in the Indian Ocean is very dynamic in nature, therefore, additional efforts are needed to test the efficacy of this study model over different seasons and spatial gradients.

Mutational spectrum and phenotypic variability of Duchenne muscular dystrophy and related disorders in a Bangladeshi population.

Duchenne muscular dystrophy (DMD) is a severe rare neuromuscular disorder caused by mutations in the X-linked dystrophin gene. Several mutations have been identified, yet the full mutational spectrum, and their phenotypic consequences, will require genotyping across different populations. To this end, we undertook the first detailed genotype and phenotype characterization of DMD in the Bangladeshi population. We investigated the rare mutational and phenotypic spectrum of the DMD gene in 36 DMD-suspected Bangladeshi participants using an economically affordable diagnostic strategy involving initial screening for exonic deletions in the DMD gene via multiplex PCR, followed by testing PCR-negative patients for mutations using whole exome sequencing. The deletion mapping identified two critical DMD gene hotspot regions (near proximal and distal ends, spanning exons 8-17 and exons 45-53, respectively) that comprised 95% (21/22) of the deletions for this population cohort. From our exome analysis, we detected two novel pathogenic hemizygous mutations in exons 21 and 42 of the DMD gene, and novel pathogenic recessive and loss of function variants in four additional genes: SGCD, DYSF, COL6A3, and DOK7. Our phenotypic analysis showed that DMD suspected participants presented diverse phenotypes according to the location of the mutation and which gene was impacted. Our study provides ethnicity specific new insights into both clinical and genetic aspects of DMD.

Carcinoid heart disease: a potentially fatal complication of carcinoid syndrome.

Carcinoid heart disease is a unique and serious cardiac complication of the neuroendocrine tumour that affects the right side of the heart, especially the tricuspid and pulmonic valves, eventually causing right heart failure. We present a middle-aged man with a history of well-differentiated neuroendocrine tumours of the small intestine with extensive metastases to the liver, mesentery and spine who is receiving monthly octreotide therapy. He presented with generalised fatigue, severe ascites and worsening dyspnoea. Both the transthoracic echocardiography and transoesophageal echocardiography revealed severe tricuspid and pulmonic regurgitations. He was considered a poor surgical candidate, underwent transcatheter pulmonic valve replacement with two bioprosthetic valve-in-valve implantations and was discharged in a stable condition.

4mC-CGRU: Identification of N4-Methylcytosine (4mC) sites using convolution gated recurrent unit in Rosaceae genome.

An epigenetic modification is DNA N4-methylcytosine (4mC) that affects several biological functions without altering the DNA nucleotides, including DNA conformation, cell development, replication, stability, and DNA structural changes. To prevent restriction enzyme from damaging self-DNA, 4mC performs a critical role in restriction-modification functions. Existing studies mainly focused on finding hand-crafted features to identify 4mC locations, but these methods are inefficient due to high time consuming and high costs. In our research work, we propose a 4mC-CGRU which is a deep learning-based computational model with a standard encoding method to identify the 4mC sites from DNA sequences that learned autonomous feature selection in the Rosaceae genome, particularly in Rosa chinensis (R. chinensis) and Fragaria vesca (F. vesca). The proposed model consists of a convolutional neural network (CNN) and a gated recurrent unit network (GRU)-based model for identifying 4mC sites from Fragaria vesca and Rosa chinensis in the genomes. The CNN model extracts useful features from the datasets and the GRU classifies the DNA sequences. Thus, our approach can automatically extract important features to detect relative sites from DNA sequence. The performance analysis shows that the proposed model consistently outperforms over the state-of-the-art works in detecting 4mC sites.

Clinical Outcomes of Aortic Stenosis in Amyloidosis: A United States National Cohort Study.

BACKGROUND: Literature regarding outcomes associated with surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR) among amyloidosis (AM) with aortic stenosis (AS) is limited. OBJECTIVES: We aim to study the mortality and in-hospital clinical outcomes among AM with AS associated with SAVR or TAVR. METHODS: We performed a retrospective study of all hospitalisation encounters associated with a diagnosis of AM with AS, using the Nationwide Readmissions Database for the years 2012-2019. Primary outcomes were in-hospital mortality, and 30-day readmissions. RESULTS: A total of 4,820 index hospitalisations of AS (mean age 78.35±10.11; female 37.76%) among AM were reported. Total 464 patients had mechanical intervention, 251 patients (54.1%) TAVR and 213 patients (45.9%) SAVR. A total of 317 patients (6.77%) with AS died; TAVR 4.4%, SAVR 11.9% (p=0.01) and 6.66% died among the subgroup who did not have any mechanical intervention. Higher complication rates were observed among patients who had SAVR than those who had TAVR including acute kidney injury (39.8% vs 22.4%; p=0.01), septic shock (12.1% vs 4.4%; p=0.05) and cardiogenic shock (22% vs 4.4%; p<0.001). Acute heart failure was higher among patients who had TAVR (40.2% vs 27.5%; p=0.04) than those who had SAVR. All conduction block and ischaemic stroke were similar between the two groups (p=0.09 and p=0.1). The overall 30-day readmission rate among AM with AS encounters was 16.82%, higher among TAVR compared to SAVR subgroups (21.25% vs 11.17%; p=0.001). CONCLUSIONS: Among AM with AS hospitalisations, TAVR had mortality benefits compared to SAVR and non-mechanical intervention subgroups. Moreover, higher 30-day mortality rate were observed among SAVR subgroup, which may suggest that TAVR should be strongly considered in AM patients complicated by AS.

Neuronal SNCA transcription during Lewy body formation.

Misfolded α-synuclein (α-syn) is believed to contribute to neurodegeneration in Lewy body disease (LBD) based on considerable evidence including a gene-dosage effect observed in relation to point mutations and multiplication of SNCA in familial Parkinson's disease. A contradictory concept proposes early loss of the physiological α-syn as the major driver of neurodegeneration. There is a paucity of data on SNCA transcripts in various α-syn immunoreactive cytopathologies. Here, the total cell body, nuclear, and cytoplasmic area density of SNCA transcripts in neurons without and with various α-syn immunoreactive cytopathologies in the substantia nigra and amygdala in autopsy cases of LBD (n = 5) were evaluated using RNAscope combined with immunofluorescence for disease-associated α-syn. Single-nucleus RNA sequencing was performed to elucidate cell-type specific SNCA expression in non-diseased frontal cortex (n = 3). SNCA transcripts were observed in the neuronal nucleus and cytoplasm in neurons without α-syn, those containing punctate α-syn immunoreactivity, irregular-shaped compact inclusion, and brainstem-type and cortical-type LBs. However, SNCA transcripts were only rarely found in the α-syn immunoreactive LB areas. The total cell body SNCA transcript area densities in neurons with punctate α-syn immunoreactivity were preserved but were significantly reduced in neurons with compact α-syn inclusions both in the substantia nigra and amygdala. This reduction was also observed in the cytoplasm but not in the nucleus. Only single SNCA transcripts were detected in astrocytes with or without disease-associated α-syn immunoreactivity in the amygdala. Single-nucleus RNA sequencing revealed that excitatory and inhibitory neurons, oligodendrocyte progenitor cells, oligodendrocytes, and homeostatic microglia expressed SNCA transcripts, while expression was largely absent in astrocytes and microglia. The preserved cellular SNCA expression in the more abundant non-Lewy body type α-syn cytopathologies might provide a pool for local protein production that can aggregate and serve as a seed for misfolded α-syn. Successful segregation of disease-associated α-syn is associated with the exhaustion of SNCA production in the terminal cytopathology, the Lewy body. Our observations inform therapy development focusing on targeting SNCA transcription in LBD.

Single-cell reconstruction and mutation enrichment analysis identifies dysregulated cardiomyocyte and endothelial cells in congenital heart disease.

Congenital heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. To catalog the putative candidate CHD risk genes, we collected 16,349 variants [single-nucleotide variants (SNVs) and Indels] impacting 8,308 genes in 3,166 CHD cases for a comprehensive meta-analysis. Using American College of Medical Genetics (ACMG) guidelines, we excluded the 0.1% of benign/likely benign variants and the resulting dataset consisted of 83% predicted loss of function variants and 17% missense variants. Seventeen percent were de novo variants. A stepwise analysis identified 90 variant-enriched CHD genes, of which six (GPATCH1, NYNRIN, TCLD2, CEP95, MAP3K19, and TTC36) were novel candidate CHD genes. Single-cell transcriptome cluster reconstruction analysis on six CHD tissues and four controls revealed upregulation of the top 10 frequently mutated genes primarily in cardiomyocytes. NOTCH1 (highest number of variants) and MYH6 (highest number of recurrent variants) expression was elevated in endocardial cells and cardiomyocytes, respectively, and 60% of these gene variants were associated with tetralogy of Fallot and coarctation of the aorta, respectively. Pseudobulk analysis using the single-cell transcriptome revealed significant (P < 0.05) upregulation of both NOTCH1 (endocardial cells) and MYH6 (cardiomyocytes) in the control heart data. We observed nine different subpopulations of CHD heart cardiomyocytes of which only four were observed in the control heart. This is the first comprehensive meta-analysis combining genomics and CHD single-cell transcriptomics, identifying the most frequently mutated CHD genes, and demonstrating CHD gene heterogeneity, suggesting that multiple genes contribute to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.NEW & NOTEWORTHY Congential heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. We present a comprehensive analysis combining genomics and CHD single-cell transcriptome. Our study identifies 90 potential candidate CHD risk genes of which 6 are novel. The risk genes have heterogenous expression suggestive of multiple genes contributing to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.

Separation of CTCs from WBCs using DEP-assisted inertial manipulation: A numerical study.

Isolation and detection of circulating tumor cells (CTCs) hold significant importance for the early diagnosis of cancer and the assessment of therapeutic strategies. However, the scarcity of CTCs among peripheral blood cells presents a major challenge to their detection. Additionally, a similar size range between CTCs and white blood cells (WBCs) makes conventional microfluidic platforms inadequate for the isolation of CTCs. To overcome these challenges, in this study, a novel inertial-dielectrophoretic microfluidic channel for size-independent, single-stage separation of CTCs from WBCs has been presented. The proposed device utilizes a spiral microchannel embedded with interdigitated electrodes. A numerical model is developed and validated to investigate the influence of various parameters related to the channel design, fluid flow, and electrode configuration. It was found that optimal separation of CTCs could be obtained at a relatively low voltage, termed the critical voltage. Furthermore, at the critical voltage of 7.5 V, the hybrid microchannel is demonstrated to be capable of separating CTCs from different WBC subtypes including granulocytes, monocytes, T-, and B-lymphocytes. The unique capabilities of the hybrid spiral microchannel allow for this size-independent isolation of CTCs from a mixture of WBCs. Overall, the proposed technique can be readily utilized for continuous and high-throughput separation of cancer cells.