Integrating Multi-Organ Imaging-Derived Phenotypes and Genomic Information for Predicting the Occurrence of Common Diseases.

As medical imaging technologies advance, these tools are playing a more and more important role in assisting clinical disease diagnosis. The fusion of biomedical imaging and multi-modal information is profound, as it significantly enhances diagnostic precision and comprehensiveness. Integrating multi-organ imaging with genomic information can significantly enhance the accuracy of disease prediction because many diseases involve both environmental and genetic determinants. In the present study, we focused on the fusion of imaging-derived phenotypes (IDPs) and polygenic risk score (PRS) of diseases from different organs including the brain, heart, lung, liver, spleen, pancreas, and kidney for the prediction of the occurrence of nine common diseases, namely atrial fibrillation, heart failure (HF), hypertension, myocardial infarction, asthma, type 2 diabetes, chronic kidney disease, coronary artery disease (CAD), and chronic obstructive pulmonary disease, in the UK Biobank (UKBB) dataset. For each disease, three prediction models were developed utilizing imaging features, genomic data, and a fusion of both, respectively, and their performances were compared. The results indicated that for seven diseases, the model integrating both imaging and genomic data achieved superior predictive performance compared to models that used only imaging features or only genomic data. For instance, the Area Under Curve (AUC) of HF risk prediction was increased from 0.68 ± 0.15 to 0.79 ± 0.12, and the AUC of CAD diagnosis was increased from 0.76 ± 0.05 to 0.81 ± 0.06.

The functional role of m6A demethylase ALKBH5 in cardiomyocyte hypertrophy.

Cardiomyocyte hypertrophy is a major outcome of pathological cardiac hypertrophy. The m6A demethylase ALKBH5 is reported to be associated with cardiovascular diseases, whereas the functional role of ALKBH5 in cardiomyocyte hypertrophy remains confused. We engineered Alkbh5 siRNA (siAlkbh5) and Alkbh5 overexpressing plasmid (Alkbh5 OE) to transfect cardiomyocytes. Subsequently, RNA immunoprecipitation (RIP)-qPCR, MeRIP-qPCR analysis and the dual-luciferase reporter assays were applied to elucidate the regulatory mechanism of ALKBH5 on cardiomyocyte hypertrophy. Our study identified ALKBH5 as a new contributor of cardiomyocyte hypertrophy. ALKBH5 showed upregulation in both phenylephrine (PE)-induced cardiomyocyte hypertrophic responses in vitro and transverse aortic constriction (TAC)/high fat diet (HFD)-induced pathological cardiac hypertrophy in vivo. Knockdown or overexpression of ALKBH5 regulated the occurrence of hypertrophic responses, including the increased cardiomyocyte surface areas and elevation of the hypertrophic marker levels, such as brain natriuretic peptide (BNP) and atrial natriuretic peptide (ANP). Mechanically, we indicated that ALKBH5 activated JAK2/STAT3 signaling pathway and mediated m6A demethylation on Stat3 mRNA, but not Jak2 mRNA, resulting in the phosphorylation and nuclear translocation of STAT3, which enhances the transcription of hypertrophic genes (e.g., Nppa) and ultimately leads to the emergence of cardiomyocytes hypertrophic growth. Our work highlights the functional role of ALKBH5 in regulating the onset of cardiomyocyte hypertrophy and provides a potential target for hypertrophic heart diseases prevention and treatment. ALKBH5 activated JAK2/STAT3 signaling pathway and mediated m6A demethylation on Stat3 mRNA, but not Jak2 mRNA, resulting in the phosphorylation and nuclear translocation of STAT3, which enhances the transcription of hypertrophic genes (e.g., Nppa) and ultimately leads to the emergence of cardiomyocytes hypertrophic growth.

Discovery of Novel Azaindoles as Potent and Selective PI3Kδ Inhibitors for Treatment of Multiple Sclerosis.

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system and the unmet need for MS treatment demands new therapeutic development. Particularly, PI3Kδ is a high-value target for autoimmune disease, while the investigation of PI3Kδ inhibitors for MS therapy is relatively scarce. Herein, we report a novel class of azaindoles as PI3Kδ inhibitors for MS treatment. Compound 31, designed via nitrogen bioisosterism, displayed excellent PI3Kδ inhibitory activity and selectivity. In vitro assay showed that 31 exhibited superior activity on T lymphocytes to inhibit the proliferation of CD4+, CD8+, and CD3+ T cells. In the experimental autoimmune encephalomyelitis (EAE) model, 31 showed a comparable therapeutical efficacy with Dexamethasone to significantly ameliorate EAE symptoms. Mechanistic studies showed that compound 31 could significantly inhibit the PI3K/AKT/mTOR signaling pathway and inhibited T-cell proliferation and differentiation. Overall, this work provides a new structural PI3Kδ inhibitor and a new vision for MS therapy.

Insights into the Inherited Basis of Valvular Heart Disease.

PURPOSE OF REVIEW: Increases in the availability of genetic data and advances in the tools and methods for their analyses have enabled well-powered genetic association studies that have significantly enhanced our understanding of the genetic factors underlying both rare and common valve diseases. Valvular heart diseases, such as congenital valve malformations and degenerative valve lesions, increase the risk of heart failure, arrhythmias, and sudden death. In this review, we provide an updated overview of our current understanding of the genetic mechanisms underlying valvular heart diseases. With a focus on discoveries from the past 5 years, we describe recent insights into genetic risk and underlying biological pathways. RECENT FINDINGS: Recently acquired knowledge around valvular heart disease genetics has provided important insights into novel mechanisms related to disease pathogenesis. Newly identified risk loci associated valvular heart disease mainly regulate the composition of the extracellular matrix, accelerate the endothelial-to-mesenchymal transition, contribute to cilia formation processes, and play roles in lipid metabolism. Large-scale genomic analyses have identified numerous risk loci, genes, and biological pathways associated with degenerative valve disease and congenital valve malformations. Shared risk genes suggest common mechanistic pathways for various valve pathologies. More recent studies have combined cardiac magnetic resonance imaging and machine learning to offer a novel approach for exploring genotype-phenotype relationships regarding valve disease. Progress in the field holds promise for targeted prevention, particularly through the application of polygenic risk scores, and innovative therapies based on the biological mechanisms for predominant forms of valvular heart diseases.

Leaf nutrient traits of planted forests demonstrate a heightened sensitivity to environmental changes compared to natural forests.

Leaf nutrient content (nitrogen, phosphorus) and their stoichiometric ratio (N/P) as key functional traits can reflect plant survival strategies and predict ecosystem productivity responses to environmental changes. Previous research on leaf nutrient traits has primarily focused on the species level with limited spatial scale, making it challenging to quantify the variability and influencing factors of forest leaf nutrient traits on a macro scale. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the differences in leaf nutrient traits between forest types (planted forests, natural forests) and their driving factors. Results show that leaf nutrient traits (leaf nitrogen content (LN), leaf phosphorus content (LP), and leaf N/P ratio) of planted forests are significantly higher than those of natural forests (P< 0.05). The impact of climatic and soil factors on the variability of leaf nutrient traits in planted forests is greater than that in natural forests. With increasing forest age, natural forests significantly increase in leaf nitrogen and phosphorus content, with a significant decrease in N/P ratio (P< 0.05). Climatic factors are key environmental factors dominating the spatial variability of leaf nutrient traits. They not only directly affect leaf nutrient traits of planted and natural forest communities but also indirectly through regulation of soil nutrients and stand factors, with their direct effects being more significant than their indirect effects.

Elevation Influences Belowground Biomass Proportion in Forests by Affecting Climatic Factors, Soil Nutrients and Key Leaf Traits.

Forest biomass allocation is a direct manifestation of biological adaptation to environmental changes. Studying the distribution patterns of forest biomass along elevational gradients is ecologically significant for understanding the specific impacts of global change on plant resource allocation strategies. While aboveground biomass has been extensively studied, research on belowground biomass remains relatively limited. Furthermore, the patterns and driving factors of the belowground biomass proportion (BGBP) along elevational gradients are still unclear. In this study, we investigated the specific influences of climatic factors, soil nutrients, and key leaf traits on the elevational pattern of BGBP using data from 926 forests at 94 sites across China. In this study, BGBP data were calculated from the root biomass to the depth of 50 cm. Our findings indicate considerable variability in forest BGBP at a macro scale, showing a significant increasing trend along elevational gradients (p < 0.01). BGBP significantly decreases with increasing temperature and precipitation and increases with annual mean evapotranspiration (MAE) (p < 0.01). It decreases significantly with increasing soil phosphorus content and increases with soil pH (p < 0.01). Key leaf traits (leaf nitrogen (LN) and leaf phosphorus (LP)) are positively correlated with BGBP. Climatic factors (R2 = 0.46) have the strongest explanatory power for the variation in BGBP along elevations, while soil factors (R2 = 0.10) and key leaf traits (R2 = 0.08) also play significant roles. Elevation impacts BGBP directly and also indirectly through influencing such as climate conditions, soil nutrient availability, and key leaf traits, with direct effects being more pronounced than indirect effects. This study reveals the patterns and controlling factors of forests' BGBP along elevational gradients, providing vital ecological insights into the impact of global change on plant resource allocation strategies and offering scientific guidance for ecosystem management and conservation.

Structural optimization of multistage depressurization sleeve of axial flow control valve based on Stacking integrated learning.

Due to the requirements of the working environment, the marine axial flow control valve needs to reduce the noise as much as possible while ensuring the flow capacity to meet the requirements. To improve the noise reduction effect of the axial flow control valve, this paper proposes a Stacking integrated learning combined with particle swarm optimization (PSO) method to optimize a multi-stage step-down sleeve of the axial flow control valve. The liquid dynamic noise and flow value of the axial flow control valve are predicted by computational fluid dynamics. Based on the preliminary evaluation of its performance, the structural parameters of the multi-stage pressure-reducing sleeve are parameterized by three-dimensional modeling software. The range of design variables is constrained to form the design space, and the design space is sampled by the optimal Latin hypercube method to form the sample space. An automated solution platform is built to solve noise and flow values under different structural parameters. The Stacking method is used to fuse the three base learners of decision tree regression, Kriging, and support vector regression to obtain a structural optimization fusion model with better prediction accuracy, and the accuracy of the fusion model is evaluated by three different error metrics of coefficient of determination (R2), Root Mean Squared Error, and Mean Absolute Error. Then the PSO particle swarm optimization algorithm is used to optimize the fusion model to obtain the optimal structural parameter combination. The optimized multi-stage depressurization structure parameters are as follows: hole diameter t1 = 3.8 mm, hole spacing t2 = 1 mm, hole drawing angle t3 = 6.4°, hole depth t4 = 3.4 mm, and two-layer throttling sleeve spacing t5 = 4 mm. The results show that the peak sound pressure level of the noise before and after optimization is 91.32 dB(A) and 78.2 dB(A), respectively, which is about 14.4% lower than that before optimization. The optimized flow characteristic curve still maintains the percentage flow characteristic and meets the requirement of flow capacity Kv ≥ 60 at the maximum opening. The optimization method provides a reference for the structural optimization of the axial flow control valve.

Climate Factors Influence Above- and Belowground Biomass Allocations in Alpine Meadows and Desert Steppes through Alterations in Soil Nutrient Availability.

Biomass is a direct reflection of community productivity, and the allocation of aboveground and belowground biomass is a survival strategy formed by the long-term adaptation of plants to environmental changes. However, under global changes, the patterns of aboveground-belowground biomass allocations and their controlling factors in different types of grasslands are still unclear. Based on the biomass data of 182 grasslands, including 17 alpine meadows (AMs) and 21 desert steppes (DSs), this study investigates the spatial distribution of the belowground biomass allocation proportion (BGBP) in different types of grasslands and their main controlling factors. The research results show that the BGBP of AMs is significantly higher than that of DSs (p < 0.05). The BGBP of AMs significantly decreases with increasing mean annual temperature (MAT) and mean annual precipitation (MAP) (p < 0.05), while it significantly increases with increasing soil nitrogen content (N), soil phosphorus content (P), and soil pH (p < 0.05). The BGBP of DSs significantly decreases with increasing MAP (p < 0.05), while it significantly increases with increasing soil phosphorus content (P) and soil pH (p < 0.05). The random forest model indicates that soil pH is the most important factor affecting the BGBP of both AMs and DSs. Climate-related factors were identified as key drivers shaping the spatial distribution patterns of BGBP by exerting an influence on soil nutrient availability. Climate and soil factors exert influences not only on grassland biomass allocation directly, but also indirectly by impacting the availability of soil nutrients.

Mitochondrial fumarate promotes ischemia/reperfusion-induced tubular injury.

AIM: Mitochondrial dysfunction, a characteristic pathological feature of renal Ischemic/reperfusion injury (I/RI), predisposes tubular epithelial cells to maintain an inflammatory microenvironment, however, the exact mechanisms through which mitochondrial dysfunction modulates the induction of tubular injury remains incompletely understood. METHODS: ESI-QTRAP-MS/MS approach was used to characterize the targeted metabolic profiling of kidney with I/RI. Tubule injury, mitochondrial dysfunction, and fumarate level were evaluated using qPCR, transmission electron microscopy, ELISA, and immunohistochemistry. RESULTS: We demonstrated that tubule injury occurred at the phase of reperfusion in murine model of I/RI. Meanwhile, enhanced glycolysis and mitochondrial dysfunction were found to be associated with tubule injury. Further, we found that tubular fumarate, which resulted from fumarate hydratase deficiency and released from dysfunctional mitochondria, promoted tubular injury. Mechanistically, fumarate induced tubular injury by causing disturbance of glutathione (GSH) hemostasis. Suppression of GSH with buthionine sulphoximine administration could deteriorate the fumarate inhibition-mediated tubule injury recovery. Reactive oxygen species/NF-κB signaling activation played a vital role in fumarate-mediated tubule injury. CONCLUSION: Our studies demonstrated that the mitochondrial-derived fumarate promotes tubular epithelial cell injury in renal I/RI. Blockade of fumarate-mediated ROS/NF-κB signaling activation may serve as a novel therapeutic approach to ameliorate hypoxic tubule injury.

Climate Factors Affect Above-Belowground Biomass Allocation in Broad-Leaved and Coniferous Forests by Regulating Soil Nutrients.

The allocation of plant biomass above and below ground reflects their strategic resource utilization, crucial for understanding terrestrial carbon flux dynamics. In our comprehensive study, we analyzed biomass distribution patterns in 580 broadleaved and 345 coniferous forests across China from 2005 to 2020, aiming to discern spatial patterns and key drivers of belowground biomass proportion (BGBP) in these ecosystems. Our research revealed a consistent trend: BGBP decreases from northwest to southeast in both forest types. Importantly, coniferous forests exhibited significantly higher BGBP compared to broadleaved forests (p < 0.001). While precipitation and soil nutrients primarily influenced biomass allocation in broadleaved forests, temperature and soil composition played a pivotal role in coniferous forests. Surprisingly, leaf traits had a negligible impact on BGBP (p > 0.05). Climatic factors, such as temperature and rainfall, influenced biomass partitioning in both strata by altering soil nutrients, particularly soil pH. These findings provide valuable insights into understanding carbon sequestration dynamics in forest ecosystems and improving predictions of the future trajectory of this critical carbon cycle component.

Multicomponent Reactions for Expeditious Construction of ß-Indole Carboxamide Amino Amides.

A multicomponent reaction of N-indole carboxylic acids, aldehydes, amines, and C2 building blocks can be transformed to structurally diverse ß-indole carboxamide amino amides. In this multicomponent reaction, the ynamides and triazenyl alkynes act as the C2 building block, and this protocol features readily available starting materials, high atom economy, and mild reaction conditions. Besides, the acyl triazene group in the product can be easily transformed to differential groups to expand the structural diversity.

Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes.

BACKGROUND: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. METHODS: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. RESULTS: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. CONCLUSIONS: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

Genetic Determinants of the Interventricular Septum Are Linked to Ventricular Septal Defects and Hypertrophic Cardiomyopathy.

BACKGROUND: A large proportion of genetic risk remains unexplained for structural heart disease involving the interventricular septum (IVS) including hypertrophic cardiomyopathy and ventricular septal defects. This study sought to develop a reproducible proxy of IVS structure from standard medical imaging, discover novel genetic determinants of IVS structure, and relate these loci to diseases of the IVS, hypertrophic cardiomyopathy, and ventricular septal defect. METHODS: We estimated the cross-sectional area of the IVS from the 4-chamber view of cardiac magnetic resonance imaging in 32 219 individuals from the UK Biobank which was used as the basis of genome wide association studies and Mendelian randomization. RESULTS: Measures of IVS cross-sectional area at diastole were a strong proxy for the 3-dimensional volume of the IVS (Pearson r=0.814, P=0.004), and correlated with anthropometric measures, blood pressure, and diagnostic codes related to cardiovascular physiology. Seven loci with clear genomic consequence and relevance to cardiovascular biology were uncovered by genome wide association studies, most notably a single nucleotide polymorphism in an intron of CDKN1A (rs2376620; ß, 7.7 mm2 [95% CI, 5.8-11.0]; P=6.0×10-10), and a common inversion incorporating KANSL1 predicted to disrupt local chromatin structure (ß, 8.4 mm2 [95% CI, 6.3-10.9]; P=4.2×10-14). Mendelian randomization suggested that inheritance of larger IVS cross-sectional area at diastole was strongly associated with hypertrophic cardiomyopathy risk (pIVW=4.6×10-10) while inheritance of smaller IVS cross-sectional area at diastole was associated with risk for ventricular septal defect (pIVW=0.007). CONCLUSIONS: Automated estimates of cross-sectional area of the IVS supports discovery of novel loci related to cardiac development and Mendelian disease. Inheritance of genetic liability for either small or large IVS, appears to confer risk for ventricular septal defect or hypertrophic cardiomyopathy, respectively. These data suggest that a proportion of risk for structural and congenital heart disease can be localized to the common genetic determinants of size and shape of cardiovascular anatomy.

Genetics and pathophysiology of mitral valve prolapse.

Mitral valve prolapse (MVP) is a common condition affecting 2-3% of the general population, and the most complex form of valve pathology, with a complication rate up to 10-15% per year in advanced stages. Complications include mitral regurgitation which can lead to heart failure and atrial fibrillation, but also life-threatening ventricular arrhythmia and cardiovascular death. Sudden death has been recently brought to the forefront of MVP disease, increasing the complexity of management and suggesting that MVP condition is not properly understood. MVP can occur as part of syndromic conditions such as Marfan syndrome, but the most common form is non-syndromic, isolated or familial. Although a specific X-linked form of MVP was initially identified, autosomal dominant inheritance appears to be the primary mode of transmission. MVP can be stratified into myxomatous degeneration (Barlow), fibroelastic deficiency, and Filamin A-related MVP. While FED is still considered a degenerative disease associated with aging, myxomatous MVP and FlnA-MVP are recognized as familial pathologies. Deciphering genetic defects associated to MVP is still a work in progress; although FLNA, DCHS1, and DZIP1 have been identified as causative genes in myxomatous forms of MVP thanks to familial approaches, they explain only a small proportion of MVP. In addition, genome-wide association studies have revealed the important role of common variants in the development of MVP, in agreement with the high prevalence of this condition in the population. Furthermore, a potential genetic link between MVP and ventricular arrhythmia or a specific type of cardiomyopathy is considered. Animal models that allow to advance in the genetic and pathophysiological knowledge of MVP, and in particular those that can be easily manipulated to express a genetic defect identified in humans are detailed. Corroborated by genetic data and animal models, the main pathophysiological pathways of MVP are briefly addressed. Finally, genetic counseling is considered in the context of MVP.

Intraoperative body temperature and emergence delirium in elderly patients after non-cardiac surgery: A secondary analysis of a prospective observational study.

BACKGROUND: Emergence delirium (ED) is a kind of delirium that occured in the immediate post-anesthesia period. Lower body temperature on post-anesthesia care unit (PACU) admission was an independent risk factor of ED. The present study was designed to investigate the association between intraoperative body temperature and ED in elderly patients undergoing non-cardiac surgery. METHODS: This study was a secondary analysis of a prospective observational study. Taking baseline body temperature as a reference, intraoperative absolute and relative temperature changes were calculated. The relative change was defined as the amplitude between intraoperative lowest/highest temperature and baseline reference. ED was assessed with the confusion assessment method for intensive care unit at 10 and 30 min after PACU admission and before PACU discharge. RESULTS: A total of 874 patients were analyzed with a mean age of 71.8 ±â€Š5.3 years. The incidence of ED was 38.4% (336/874). When taking 36.0°C, 35.5°C, and 35.0°C as thresholds, the incidences of absolute hypothermia were 76.7% (670/874), 38.4% (336/874), and 17.5% (153/874), respectively. In multivariable logistic regression analysis, absolute hypothermia (lowest value <35.5°C) and its cumulative duration were respectively associated with an increased risk of ED after adjusting for confounders including age, education, preoperative mild cognitive impairment, American Society of Anesthesiologists grade, duration of surgery, site of surgery, and pain intensity. Relative hypothermia (decrement >1.0°C from baseline) and its cumulative duration were also associated with an increased risk of ED, respectively. When taking the relative increment >0.5°C as a threshold, the incidence of relative hyperthermia was 21.7% (190/874) and it was associated with a decreased risk of ED after adjusting above confounders. CONCLUSIONS: In the present study, we found that intraoperative hypothermia, defined as either absolute or relative hypothermia, was associated with an increased risk of ED in elderly patients after non-cardiac surgery. Relative hyperthermia, but not absolute hyperthermia, was associated with a decreased risk of ED. REGISTRATION: Chinese Clinical Trial Registry (No. ChiCTR-OOC-17012734).

Follow-up value of serum AFP and aminotransferases in chronic hepatitis B progression.

Introduction: Chronic viral hepatitis (CH) is a stage prior to cirrhosis and primary cancer. Standard protocols for CH assessment during the long follow-up period are of great importance for precise treatment and living quality improvement. In this study, we aimed to analyze multiple serum indexes in chronic hepatitis B (CHB)-infected patients and to discuss their combined values in clinical applications. Methods: Total 503 lines of laboratory data from 2012 to 2021 were extracted from103 CHB patients who were followed-up in our hospital. They were divided into the remission group and the progression group according to their complete clinical information and laboratory data. A series of models of serum indexes were analyzed to illustrate the fluctuation trend of @ach index in a time-dependent manner. Results: The models revealed that abundant serum alpha-fetoprotein (AFP) in the remission group was characteristically associated with hepatocyte destruction markers aspartate aminotransferase (AST) and alanine aminotransferase and favored a much longer progression-free period (P 0.0001). A model-derived equation consisting of serum AFP and AST values showed a good performance (83% reliability) to distinguish the two groups. Discussion: This study clearly demonstrates the intrinsic quantitative relationship between serum AFP and liver aminotransferases involving antivirus treatment response. The model-based equation compensates for serum hepatitis B virus DNA detection during outpatient follow-up and it may serve as a useful laboratory tool for CHB progression assessment.

A review of methods for predicting DNA N6-methyladenine sites.

Deoxyribonucleic acid(DNA) N6-methyladenine plays a vital role in various biological processes, and the accurate identification of its site can provide a more comprehensive understanding of its biological effects. There are several methods for 6mA site prediction. With the continuous development of technology, traditional techniques with the high costs and low efficiencies are gradually being replaced by computer methods. Computer methods that are widely used can be divided into two categories: traditional machine learning and deep learning methods. We first list some existing experimental methods for predicting the 6mA site, then analyze the general process from sequence input to results in computer methods and review existing model architectures. Finally, the results were summarized and compared to facilitate subsequent researchers in choosing the most suitable method for their work.

Study on inversion method of wall erosion information of on-orbit Hall thruster based on low-frequency oscillation signals and neural networks.

Hall thrusters function as power plants on spacecraft, and its development is crucial for the aerospace industry. The wall erosion of the on-orbit Hall thruster cannot be measured by the control center through ground measurement, but can obtain the discharge current low-frequency oscillation data. Therefore, this study proposes an inversion method to obtain the wall erosion information based on low-frequency oscillation signals and neural networks. Firstly, we use an improved one-dimensional quasi-neutral dynamic fluid mathematical model to build a low-frequency oscillation simulation platform which obtains the corresponding data by varying the cross-sectional area. Secondly, a nonlinear neural network model is established based on the obtained low-frequency oscillation data to invert the wall erosion information. The training function, transfer function, number of hidden layer nodes, and other parameters affecting the results are analyzed and the best model parameters are obtained. The Elman neural network is established and compared with the BP neural network and RBF neural network. The training results of the Elman neural network algorithm present small and stable errors, and the results of multiple predictions remain consistent. The root means square error, average absolute error, and average absolute percentage are 0.0084, 0.0637, and 0.045%, respectively.

Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse.

AIMS: Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. METHODS AND RESULTS: We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. CONCLUSION: We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-ß signalling molecules and spectrin ß. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.