A rapid and simple non-radioactive assay for measuring uptake by solute carrier transporters.

Introduction: Solute carrier (SLC) transport proteins play a crucial role in maintaining cellular nutrient and metabolite homeostasis and are implicated in various human diseases, making them potential targets for therapeutic interventions. However, the study of SLCs has been limited due to the lack of suitable tools, particularly cell-based substrate uptake assays, necessary for understanding their biological functions and for drug discovery purposes. Methods: In this study, a cell-based uptake assay was developed using a stable isotope-labeled compound as the substrate for SLCs, with detection facilitated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This assay aimed to address the limitations of existing assays, such as reliance on hazardous radiolabeled substrates and limited availability of fluorescent biosensors. Results: The developed assay was successfully applied to detect substrate uptakes by two specific SLCs: L-type amino acid transporter 1 (LAT1) and sodium taurocholate co-transporting polypeptide (NTCP). Importantly, the assay demonstrated comparable results to the radioactive method, indicating its reliability and accuracy. Furthermore, the assay was utilized to screen for novel inhibitors of NTCP, leading to the identification of a potential NTCP inhibitor compound. Discussion: The findings highlight the utility of the developed cell-based uptake assay as a rapid, simple, and environmentally friendly tool for investigating SLCs' biological roles and for drug discovery purposes. This assay offers a safer alternative to traditional methods and has the potential to contribute significantly to advancing our understanding of SLC function and identifying therapeutic agents targeting SLC-mediated pathways.

Machine learning in predicting pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer using MRI: A systematic review and meta-analysis.

OBJECTIVES: To evaluate the performance of machine learning models in predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using computed tomography (CT) and magnetic resonance imaging (MRI). METHODS: We searched PubMed, Embase, Cochrane Library, and Web of Science for studies published before January 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to assess the methodological quality of the included studies, random-effects models were used to calculate sensitivity and specificity, I2 values were used for heterogeneity measurements, and subgroup analyses were carried out to detect potential sources of heterogeneity. RESULTS: A total of 1690 patients from 24 studies were included. The meta-analysis calculated a pooled area under the curve (AUC) of 0.92 (95%CI-0.89-0.94), pooled sensitivity of 0.81 (95%CI-0.73-0.88), and pooled specificity of 0.88 (95%CI-0.82-0.92). We investigated 4 studies that mainly contributed to heterogeneity. After performing meta-analysis again excluding these 4 studies, the heterogeneity was significantly reduced. In subgroup analysis, the pooled AUC of the deep learning model was 0.95 and was 0.88 for the traditional statistical model; the pooled AUC of studies that used diffusion-weighted imaging (DWI) was 0.90, and was 0.92 in studies that did not use DWI; the pooled AUC of studies conducted in China was 0.94, and was 0.83 in studies conducted in other countries. CONCLUSIONS: Machine learning has promising potential in predicting tumor response to nCRT in patients with locally advanced rectal cancer. Together with clinical information, machine-learning based models may bring us closer toward precision medicine. ADVANCES IN KNOWLEDGE: Compared to traditional machine learning models, deep learning-based studies are able to obtain higher AUC, although they are less predominant and more heterogeneous. Together with clinical information, machine-learning based models may bring us closer toward precision medicine.

Visual Tracking in Amblyopia: A Continuous Psychophysical Approach.

Purpose: This study aimed to explore the underlying mechanisms of the observed visuomotor deficit in amblyopia. Methods: Twenty-four amblyopic (25.8 ± 3.8 years; 15 males) and 22 normal participants (25.8 ± 2.1 years; 8 males) took part in the study. The participants were instructed to continuously track a randomly moving Gaussian target on a computer screen using a mouse. In experiment 1, the participants performed the tracking task at six different target sizes. In experiments 2 and 3, they were asked to track a target with the contrast adjusted to individual's threshold. The tracking performance was represented by the kernel function calculated as the cross-correlation between the target and mouse displacements. The peak, latency, and width of the kernel were extracted and compared between the two groups. Results: In experiment 1, target size had a significant effect on the kernel peak (F(1.649, 46.170) = 200.958, P = 4.420 × 10-22). At the smallest target size, the peak in the amblyopic group was significantly lower than that in the normal group (0.089 ± 0.023 vs. 0.107 ± 0.020, t(28) = -2.390, P = 0.024) and correlated with the contrast sensitivity function (r = 0.739, P = 0.002) in the amblyopic eyes. In experiments 2 and 3, with equally visible stimuli, there were still differences in the kernel between the two groups (all Ps < 0.05). Conclusions: When stimulus visibility was compensated, amblyopic participants still showed significantly poorer tracking performance.

Degradation of the α-Carboxyl Terminus 11 Peptide: In Vivo and Ex Vivo Impacts of Time, Temperature, Inhibitors, and Gender in Rat.

In previous research, a synthetic α-carboxyl terminus 1 (αCT1) peptide derived from connexin 43 (Cx43) and its variant (αCT11) showed beneficial effects in an ex vivo ischemia-reperfusion (I/R) heart injury model in mouse. In an in vivo mouse model of cryo-induced ventricular injury, αCT1 released from adhesive cardiac patches reduced Cx43 remodeling and arrhythmias, as well as maintained cardiac conduction. Whether intravenous injection of αCT1 or αCT11 produces similar outcomes has not been investigated. Given the possibility of peptide degradation in plasma, this study utilized in vivo I/R cardiac injury and ex vivo blood plasma models to examine factors that may limit the therapeutic potential of peptide therapeutics in vivo. Following tail vein administration of αCT11 (100 µM) in blood, no effect on I/R infarct size was observed in adult rat hearts on day 1 (D1) and day 28 (D28) after injury (p > 0.05). There was also no difference in the echocardiographic ejection fraction (EF%) between the control and the αCT11 groups (p > 0.05). Surprisingly, αCT11 in blood plasma collected from these rats was undetectable within ∼10 min after tail vein injection. To investigate factors that may modulate αCT11 degradation in blood, αCT11 was directly added to blood plasma isolated from normal rats without I/R and peptide levels were measured under different experimental conditions. Consistent with in vivo observations, significant αCT11 degradation occurred in plasma within 10 min at 22 and 37 °C and was nearly undetectable by 30 min. These responses were reduced by the addition of protease/phosphatase (PTase/PPTase) inhibitors to the isolated plasma. Interestingly, no significant differences in αCT11 degradation in plasma were noted between male and female rats. We conclude that fast degradation of αCT11 is likely the reason that no beneficial effects were observed in the in vivo I/R model and inhibition or shielding from PTase/PPTase activity may be a strategy that will assist with the viability of peptide therapeutics.

Precise modulation and use of reactive oxygen species for immunotherapy.

Reactive oxygen species (ROS) play an important role in regulating the immune system by affecting pathogens, cancer cells, and immune cells. Recent advances in biomaterials have leveraged this mechanism to precisely modulate ROS levels in target tissues for improving the effectiveness of immunotherapies in infectious diseases, cancer, and autoimmune diseases. Moreover, ROS-responsive biomaterials can trigger the release of immunotherapeutics and provide tunable release kinetics, which can further boost their efficacy. This review will discuss the latest biomaterial-based approaches for both precise modulation of ROS levels and using ROS as a stimulus to control the release kinetics of immunotherapeutics. Finally, we will discuss the existing challenges and potential solutions for clinical translation of ROS-modulating and ROS-responsive approaches for immunotherapy, and provide an outlook for future research.

A Virus-Inspired Inhalable Liponanogel Induces Potent Antitumor Immunity and Regression in Metastatic Lung Tumors.

Pulmonary delivery of immunostimulatory agents such as poly(I:C) to activate double-stranded RNA sensors MDA5 and RIG-I within lung-resident antigen-presenting cells is a potential strategy to enhance antitumor immunity by promoting type I interferon secretion. However, following pulmonary delivery, poly(I:C) suffers from rapid degradation and poor endosomal escape, thus limiting its potency. Inspired by the structure of a virus that utilizes internal viral proteins to tune the loading and cytosolic delivery of viral nucleic acids, we developed a liponanogel (LNG)-based platform to overcome the delivery challenges of poly(I:C). The LNG consisted of an anionic polymer hyaluronic acid-based nanogel core coated by a lipid shell, which served as a protective layer to stabilize the nanogel core in the lungs. The nanogel core was protonated within acidic endosomes to enhance the endosomal membrane permeability and cytosolic delivery of poly(I:C). After pulmonary delivery, LNG-poly(I:C) induced 13.7-fold more IFNß than poly(I:C) alone and 2-fold more than poly(I:C) loaded in the state-of-art lipid nanoparticles (LNP-poly(I:C)). Moreover, LNG-poly(I:C) induced more potent CD8+ T cell immunity and stronger therapeutic effects than LNP-poly(I:C). The combination of LNG-poly(I:C) and PD-L1 targeting led to regression of established lung metastases. Due to the ease of manufacturing and the high biocompatibility of LNG, pulmonary delivery of LNG may be broadly applicable to the treatment of different lung tumors and may spur the development of innovative strategies for cancer immunotherapy.

A Pump-Free Strategy for the Controllable Generation of Alginate Microgels as Cellular Microcarriers.

Microgels are advanced scaffolds for tissue engineering due to their proper biodegradability, good biocompatibility, and high specific surface area for effective oxygen and nutrient transfer. However, most of the current monodispersed microgel fabrication systems rely heavily on various precision pumps, which highly increase the cost and complexity of their downstream application. In this work, we developed a simple and facile system for the controllable generation of uniform alginate microgels by integrating a gas-shearing strategy into a glass microfluidic device. Importantly, the cell-laden microgels can be rapidly prepared in a pump-free manner under an all-aqueous environment. The three-dimensional cultured green fluorescent protein-human A549 cells in alginate microgels exhibited enhanced stemness and drug resistance compared to those under two-dimensional conditions. The pancreatic cancer organoids in alginate microgels exhibited some of the key features of pancreatic cancer. The proposed microgels showed decent monodispersity, biocompatibility, and versatility, providing great opportunities in various biomedical applications such as microcarrier fabricating, organoid engineering, and high-throughput drug screening.

Liquid crystal monomers disrupt photoreceptor patterning of zebrafish larvae via thyroid hormone signaling.

Liquid crystal monomers (LCMs) are the raw material for liquid crystal displays, and their use is steadily increasing in electronic products. Recently, LCMs have been reported to be novel endocrine disrupting chemicals, however, the mechanisms underlying their potential for thyroid hormone disruption and visual toxicity are not well understood. In this study, six widely used fluorinated LCMs (FLCMs) were selected to determine putative mechanisms underlying FLCM-induced toxicity to the zebrafish thyroid and visual systems. Exposure to FLCMs caused damage to retinal structures and reduced cell density of ganglion cell layer, inner nuclear layer, and photoreceptor layer approximately 12.6-46.1%. Exposure to FLCMs also disrupted thyroid hormone levels and perturbed the hypothalamic-pituitary-thyroid axis by affecting key enzymes and protein in zebrafish larvae. A thyroid hormone-dependent GH3 cell viability assay supported the hypothesis that FLCMs act as thyroid hormone disrupting chemicals. It was also determined that FLCMs containing aliphatic ring structures may have a higher potential for T3 antagonism compared to FLCMs without an aliphatic ring. Molecular docking in silico suggested that FLCMs may affect biological functions of thyroxine binding globulin, membrane receptor integrin, and thyroid receptor beta. Lastly, the visual motor response of zebrafish in red- and green-light was significantly inhibited following exposure to FLCMs. Taken together, we demonstrate that FLCMs can act as thyroid hormone disruptors to induce visual dysfunction in zebrafish via several molecular mechanisms.

Network pharmacology and molecular docking technology for exploring the effect and mechanism of high-dose vitamin c on ferroptosis of tumor cells: A review.

To investigate the mechanism by which high-dose vitamin C (HVC) promotes ferroptosis in tumor cells via network pharmacology, vitamin C-related and ferroptosis-related targets were obtained from the PharmMapper and GeneCards databases, respectively, and their common targets were compared using the Venn diagram. Common targets were imported into the STRING database for protein-protein interaction analysis, and core targets were defined. Core targets were enriched for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways using the R language packages. A map of the core target-based interaction network and a map of the mechanism by which HVC regulates ferroptosis were constructed. A total of 238 vitamin C-related and 721 ferroptosis-related targets were identified, of which 21 targets were common to both. Furthermore, ALDOA, AHCY, LDHB, HSPA8, LGALS3, and GSTP1 were identified as core targets. GO enrichment analysis suggested that the main biological processes included the extrinsic apoptotic signaling pathway and pyruvate metabolic process. KEGG enrichment analysis suggested that HVC regulates ferroptosis mainly through the amino acid and carbohydrate metabolic pathways. The targets were validated by molecular docking. In conclusion, HVC may promote ferroptosis in tumor cells by regulating metabolic pathways, and there is a synergistic effect between HVC and type I ferroptosis inducers. Glycolysis-dependent tumors may be beneficial for HVC therapy. Our study provides a reference for further clinical studies on HVC antitumor therapy.

Biomonitoring urinary pesticide metabolites in preschool children by supported liquid extraction and ultra-high performance liquid chromatography-tandem mass spectrometry and their association with oxidative stress.

Investigating pesticide exposure and oxidative stress in preschool children is essential for elucidating the determinants of environmental health in early life, with human biomonitoring of urinary pesticide metabolites serving as a critical strategy for achieving this objective. This study demonstrated biomonitoring of 2 phenoxyacetic acid herbicides, 2 organophosphorus pesticide metabolites, and 4 pyrethroid pesticide metabolites in 159 preschool children and evaluated their association with oxidative stress biomarker 8-hydroxydeoxyguanosine. An enzymatic deconjugation process was used to release urinary pesticide metabolites, which were then extracted and enriched by supported liquid extraction, and quantified by ultra-high performance liquid chromatography-tandem mass spectrometry with internal standard calibration. Dichloromethane: methyl tert­butyl ether (1:1, v/v) was optimized as the solvent for supported liquid extraction, and we validated the method for linear range, recovery, matrix effect and method detection limit. Method detection limit of the pesticide metabolites ranged from 0.01 µg/L to 0.04 µg/L, with satisfactory recoveries ranging from 70.5 % to 95.5 %. 2,4,5-Trichlorophenoxyacetic acid was not detected, whereas the other seven pesticide metabolites were detected with frequencies ranging from 10.1 % to 100 %. The concentration of urinary pesticide metabolites did not significantly differ between boys and girls, with the median concentrations being 9.39 µg/L for boys and 4.90 µg/L for girls, respectively. Spearman correlation analysis indicated that significant positive correlations among urinary metabolites. Bayesian kernel machine regression revealed a significant positive association between urinary pesticide metabolites and 8-hydroxydeoxyguanosine. Para-nitrophenol was the pesticide metabolite that contributed significantly to the elevated level of oxidative stress.

Prevalence and outcomes of atrial fibrillation in patients suffering prostate cancer: a national analysis in the United States.

Purpose: Although the adverse effects of atrial fibrillation (AF) on cancers have been well reported, the relationship between the AF and the adverse outcomes in prostate cancer (PC) remains inconclusive. This study aimed to explore the prevalence of AF and evaluate the relationship between AF and clinical outcomes in PC patients. Methods: Patients diagnosed with PC between 2008 and 2017 were identified from the National Inpatient Sample database. The trends in AF prevalence were compared among PC patients and their subgroups. Multivariable regression models were used to assess the associations between AF and in-hospital mortality, length of hospital stay, total cost, and other clinical outcomes. Results: 256,239 PC hospitalizations were identified; 41,356 (83.8%) had no AF and 214,883 (16.2%) had AF. AF prevalence increased from 14.0% in 2008 to 20.1% in 2017 (P < .001). In-hospital mortality in PC inpatients with AF increased from 5.1% in 2008 to 8.1% in 2017 (P < .001). AF was associated with adverse clinical outcomes, such as in-hospital mortality, congestive heart failure, pulmonary circulation disorders, renal failure, fluid and electrolyte disorders, cardiogenic shock, higher total cost, and longer length of hospital stay. Conclusions: The prevalence of AF among inpatients with PC increased from 2008 to 2017. AF was associated with poor prognosis and higher health resource utilization. Better management strategies for patients with comorbid PC and AF, particularly in older individuals, are required.

SMG5 Inhibition Restrains Hepatocellular Carcinoma Growth and Enhances Sorafenib Sensitivity.

Hepatocellular carcinoma (HCC) has a pathogenesis that remains elusive with restricted therapeutic strategies and efficacy. This study aimed to investigate the role of SMG5, a crucial component in nonsense-mediated mRNA decay (NMD) that degrades mRNA containing a premature termination codon (PTC), in HCC pathogenesis and therapeutic resistance. We demonstrated an elevated expression of SMG5 in HCC and scrutinized its potential as a therapeutic target. Our findings revealed that SMG5 knockdown not only inhibited the migration, invasion, and proliferation of HCC cells but also influenced sorafenib resistance. Differential gene expression analysis between the control and SMG5 knockdown groups showed an upregulation of MAT1A in the latter. High expression of MAT1A, a catalyst for S-adenosylmethionine (SAM) production, as suggested by TCGA data, was indicative of a better prognosis for HCC. Further, an enzyme-linked immunosorbent assay showed a higher concentration of SAM in SMG5 knockdown cell supernatants. Furthermore, we found that exogenous SAM supplementation enhanced the sensitivity of HCC cells to sorafenib alongside changes in the expression of Bax and Bcl 2, apoptosis-related proteins. Our findings underscore the important role of SMG5 in HCC development and its involvement in sorafenib resistance, highlighting it as a potential target for HCC treatment.

Analyzing spatio-temporal changes and trade-offs/synergies of gross ecosystem product based on water-energy-food nexus.

The value of the ecosystem's ultimate goods and services for human welfare and long-term economic and social development is known as the gross ecosystem product (GEP). For the study of GEP accounting, the suggested water-energy-food (WEF) nexus offers a fresh viewpoint. This work aims to build a GEP accounting index system based on WEF, investigate its spatio-temporal evolution characteristics, and assess trade-offs and synergies between and within the water, energy, and food subsystems. Using the Three Gorges Reservoir area (TGRA) as an illustration, the findings revealed that, firstly, the comprehensive benefit of GEP based on WEF showed an upward trend in TGRA. Still, it was worth noting that the total production of the food ecosystem decreased. Secondly, the GEP based on WEF in five periods showed a spatial pattern of "high east and west, low middle." Thirdly, the Pearson correlation coefficient indicated that the GEP trade-off relationships based on WEF were dominant in TGRA, with the strongest trade-offs between AQV, SCV, APV, and LEV. In addition, in bivariate local spatial autocorrelation, the value of the six ecosystem service function relationships was dominated by the trade-off relationship, and the distribution of trade-offs and synergies showed significant heterogeneity at the county scale in the TGRA. Finally, hot spot analysis showed that the hot spots of the gross water and energy ecosystem products were scattered in the tail area of the study area. In contrast, the hot spots of the gross food ecosystem product were concentrated in the belly region. The findings of this study provided a basis for the scientific formulation of territorial spatial pattern optimization for water, energy, and agricultural resources in the TGRA and can more accurately reflect the status of the ecological environment and changes of WEF over time. Moreover, this paper also gives full play to the growth advantages of shipping and aquatic products, implements effective soil erosion prevention and control measures, and establishes water-saving mechanisms and other measures in terms of water resources. Subregional plans for industrial structure and strengthening of waste gas and wastewater treatment facilities regarding energy resources are developed. Implement the cultivated land protection system and promote the superiority of crop varieties and other measures in terms of food resources.

Tetrabromobisphenol-A/S and their derivatives in surface particulates from workshop floors of three representative e-waste recycling sites in China.

Surface particulates collected from the workshop floors of three major e-waste recycling sites (Taizhou, Qingyuan, and Guiyu) in China were analyzed for tetrabromobisphenol A/S (TBBPA/S) and their derivatives to investigate the environmental pollution caused by e-waste recycling activities. Mean concentrations of total TBBPA/S analogs in surface particulates were 31,471-116,059 ng/g dry weight (dw). TBBPA, TBBPA-BGE, and TBBPA-BDBPE were the most frequently detected in particulates with average concentration ranges of 17,929-78,406, 5601-15,842, and 5929-21,383 ng/g dw, respectively. Meanwhile, TBBPA, TBBPA-BGE, and TBBPA-BDBPE were the most abundant TBBPA/S analogs, accounting for around 96% of the total. The composition profiles of TBBPA/S analogs differed significantly among three e-waste sites. Similarly, principal component analysis uncovered different pollution patterns among different sites. The discrepancy in the profiles of TBBPA/S analogs largely relied on the e-waste types recycled in different areas. E-waste recycling led to the release of TBBPA/S analogs, and TBBPA/S analogs produced differentiation during migration from source (surface particulates) to nearby soil. More researches are necessary to find a definite relationship between pollution status and e-waste types and study differentiation behavior of TBBPA/S analogs in migration and diffusion from source to environmental medium.

Enhanced interactions among gut mycobiomes with the deterioration of glycemic control.

BACKGROUND: The gut mycobiome is closely linked to health and disease; however, its role in the progression of type 2 diabetes mellitus (T2DM) remains obscure. Here, a multi-omics approach was employed to explore the role of intestinal fungi in the deterioration of glycemic control. METHODS: 350 participants without hypoglycemic therapies were invited for a standard oral glucose tolerance test to determine their status of glycemic control. The gut mycobiome was identified through internal transcribed spacer sequencing, host genetics were determined by genotyping array, and plasma metabolites were measured with untargeted liquid chromatography mass spectrometry. FINDINGS: The richness of fungi was higher, whereas its dissimilarity was markedly lower, in participants with T2DM. Moreover, the diversity and composition of fungi were closely associated with insulin sensitivity and pancreatic ß-cell functions. With the exacerbation of glycemic control, the co-occurrence network among fungus taxa became increasingly complex, and the complexity of the interaction network was inversely associated with insulin sensitivity. Mendelian randomization analysis further demonstrated that the Archaeorhizomycetes class, Fusarium genus, and Neoascochyta genus were causally linked to impaired glucose metabolism. Furthermore, integrative analysis with metabolomics showed that increased 4-hydroxy-2-oxoglutaric acid, ketoleucine, lysophosphatidylcholine (20:3/0:0), and N-lactoyl-phenylalanine, but decreased lysophosphatidylcholine (O-18:2), functioned as key molecules linking the adverse effect of Fusarium genus on insulin sensitivity. CONCLUSIONS: Our study uncovers a strong association between disturbance in gut fungi and the progression of T2DM and highlights the potential of targeting the gut mycobiome for the management of T2DM. FUNDINGS: This study was supported by MOST and NSFC of China.

Oleuropein alleviates myocardial ischemia-reperfusion injury by suppressing oxidative stress and excessive autophagy via TLR4/MAPK signaling pathway.

BACKGROUND: Myocardial ischemia/reperfusion injury (MIRI) is an important complication of reperfusion therapy, and has a lack of effective prevention and treatment methods. Oleuropein (OP) is a natural strong antioxidant with many protective effects on cardiovascular diseases, but its protective effect on MIRI has not yet been studied in depth. METHODS: Tert-Butyl hydroperoxide (tBHP) was used to establish an in vitro oxidative stress model. Cell viability was detected by 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) and lactate dehydrogenase (LDH). Flow cytometry and fluorescence assays were performed for evaluating the ROS levels and mitochondrial membrane potential (MMP). Immunofluorescence analysis detected the NRF2 nuclear translocation and autophagy indicators. Further, Western blotting and quantitative real-time PCR were performed to evaluate the expression levels of proteins and mRNAs. Molecular docking, CETSA, and molecular interaction analysis explored the binding between OP and TLR4. The protective effects of OP in vivo were determined using a preclinical MIRI rat model. RESULTS: OP protected against tBHP-treated injury, reduced ROS levels and reversed the damaged MMP. Mechanistically, OP activated NRF2-related antioxidant pathways, inhibited autophagy and attenuated the TLR4/MAPK signaling pathway in tBHP-treated H9C2 cells with a high binding affinity to TLR4 (KD = 37.5 µM). The TLR4 inhibitor TAK242 showed a similar effect as OP. In vivo, OP could alleviate cardiac ischemia/reperfusion injury and it ameliorated adverse cardiac remodeling. Consistent with in vitro studies, OP inhibited TLR4/MAPK and autophagy pathway and activated NRF2-dependent antioxidant pathways in vivo. CONCLUSION: This study shows that OP binds to TLR4 to regulate oxidative stress and autophagy for protecting damaged cardiomyocytes, supporting that OP can be a potential therapeutic agent for MIRI.

A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline.

BACKGROUND: Although sequencing technologies have boosted the measurement of the genomic diversity of plant crops, it remains challenging to accurately genotype millions of genetic variants, especially structural variations, with only short reads. In recent years, many graph-based variation genotyping methods have been developed to address this issue and tested for human genomes. However, their performance in plant genomes remains largely elusive. Furthermore, pipelines integrating the advantages of current genotyping methods might be required, considering the different complexity of plant genomes. RESULTS: Here we comprehensively evaluate eight such genotypers in different scenarios in terms of variant type and size, sequencing parameters, genomic context, and complexity, as well as graph size, using both simulated and real data sets from representative plant genomes. Our evaluation reveals that there are still great challenges to applying existing methods to plants, such as excessive repeats and variants or high resource consumption. Therefore, we propose a pipeline called Ensemble Variant Genotyper (EVG) that can achieve better genotyping performance in almost all experimental scenarios and comparably higher genotyping recall and precision even using 5× reads. Furthermore, we demonstrate that EVG is more robust with an increasing number of graphed genomes, especially for insertions and deletions. CONCLUSIONS: Our study will provide new insights into the development and application of graph-based genotyping algorithms. We conclude that EVG provides an accurate, unbiased, and cost-effective way for genotyping both small and large variations and will be potentially used in population-scale genotyping for large, repetitive, and heterozygous plant genomes.

BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.

Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model to predict ADRs from known associations is essential for enhanced efficiency and cost-effectiveness. Here, we propose BiMPADR, a novel model that integrates drug gene expression into adverse reaction features using a message passing neural network on a bipartite graph of drugs and adverse reactions, leveraging publicly available data. By combining the computed adverse reaction features with the structural fingerprints of drugs, we predict the association between drugs and adverse reactions. Our models obtained high AUC (area under the receiver operating characteristic curve) values ranging from 0.861 to 0.907 in an external drug validation dataset under differential experiment conditions. The case study on multiple BET inhibitors also demonstrated the high accuracy of our predictions, and our model's exploration of potential adverse reactions for HWD-870 has contributed to its research and development for market approval. In summary, our method would provide a promising tool for ADR prediction and drug safety assessment in drug discovery and development.

Artificial intelligence powered advancements in upper extremity joint MRI: A review.

Magnetic resonance imaging (MRI) is an indispensable medical imaging examination technique in musculoskeletal medicine. Modern MRI techniques achieve superior high-quality multiplanar imaging of soft tissue and skeletal pathologies without the harmful effects of ionizing radiation. Some current limitations of MRI include long acquisition times, artifacts, and noise. In addition, it is often challenging to distinguish abutting or closely applied soft tissue structures with similar signal characteristics. In the past decade, Artificial Intelligence (AI) has been widely employed in musculoskeletal MRI to help reduce the image acquisition time and improve image quality. Apart from being able to reduce medical costs, AI can assist clinicians in diagnosing diseases more accurately. This will effectively help formulate appropriate treatment plans and ultimately improve patient care. This review article intends to summarize AI's current research and application in musculoskeletal MRI, particularly the advancement of DL in identifying the structure and lesions of upper extremity joints in MRI images.

Associations between genomic aberrations, increased nuchal translucency, and pregnancy outcomes: a comprehensive analysis of 2,272 singleton pregnancies in women under 35.

Objectives: Regarding increased nuchal translucency (NT), the cutoff values used are heterogeneous in clinical practice, this study aims to assess the efficacy of prenatal detection for chromosomal abnormalities and pregnancy outcomes in fetuses with varying NT thicknesses, in order to provide data that supports informed prenatal diagnosis and genetic counseling for such cases. Methods: We included 2,272 pregnant women under 35 with singleton pregnancies who underwent invasive prenatal diagnosis between 2014 and 2022. The cohort comprised 2,010 fetuses with increased NT (≥2.5 mm) and 262 fetuses with normal NT but exhibiting a single soft marker. Prenatal diagnoses were supported by chromosomal microarray (CMA) and copy number variation sequencing (CNV-seq) analyses. Results: The detection rates of numerical chromosomal abnormalities were 15.4% (309/2,010) and 17.3% (297/1,717) in the NT ≥2.5 and ≥ 3.0 groups, respectively. Pathogenic/likely pathogenic CNV incidence increased with NT thickness (χ2 = 8.60, p < 0.05), peaking at 8.7% (22/254) in the NT 4.5-5.4 mm group. Structural defects were found in 18.4% of fetuses with NT values between 2.5 mm and 2.9 mm. Chromosomal abnormality rates in the isolated increased NT groups of 2.5-2.9 mm and 3.0-3.4 mm were 6.7% (16/239) and 10.0% (47/470), respectively, with no statistical significance (χ2 = 2.14, p > 0.05). Fetuses with NT thickness between 2.5 and 2.9 mm combined with the presence of soft markers or non-lethal structural abnormalities exhibited a significantly higher chromosomal abnormality risk (19.0%) compared to fetuses with isolated increased NT ranging from 3.5 to 4.4 mm (13.0%). Pregnancy termination rates increased with NT thickness (χ2 = 435.18, p < 0.0001), ranging from 12.0% (30/249) in the NT 2.5-2.9 mm group to 87.0% (141/162) in the NT ≥ 6.5 mm group. Conclusion: CMA or CNV-seq exhibited good performance in identifying genomic aberrations in pregnancies with increased NT thickness. NT ranging from 2.5 mm to 2.9 mm elevated the risk of fetal chromosomal abnormalities, particularly when combined with other soft markers.