Artificial Intelligence Measurement of Preoperative Radiographs in Adolescent Idiopathic Scoliosis Based on Multiple-View Semantic Segmentation.

STUDY DESIGN: Cross-sectional study. OBJECTIVES: Imaging classification of adolescent idiopathic scoliosis (AIS) is directly related to the surgical strategy, but the artificial classification is complex and depends on doctors' experience. This study investigated deep learning-based automated classification methods (DL group) for AIS and validated the consistency of machine classification and manual classification (M group). METHODS: A total of 506 cases (81 males and 425 females) and 1812 AIS full spine images in the anteroposterior (AP), lateral (LAT), left bending (LB) and right bending (RB) positions were retrospectively used for training. The mean age was 13.6 ± 1.8. The mean maximum Cobb angle was 46.8 ± 12.0. U-Net semantic segmentation neural network technology and deep learning methods were used to automatically segment and establish the alignment relationship between multiple views of the spine, and to extract spinal features such as the Cobb angle. The type of each test case was automatically calculated according to Lenke's rule. An additional 107 cases of adolescent idiopathic scoliosis imaging were prospectively used for testing. The consistency of the DL group and M group was compared. RESULTS: Automatic vertebral body segmentation and recognition, multi-view alignment of the spine and automatic Cobb angle measurement were implemented. Compare to the M group, the consistency of the DL group was significantly higher in 3 aspects: type of lateral convexity (0.989 vs 0.566), lumbar curvature modifier (0.932 vs 0.738), and sagittal plane modifier (0.987 vs 0.522). CONCLUSIONS: Deep learning enables automated Cobb angle measurement and automated Lenke classification of idiopathic scoliosis whole spine radiographs with higher consistency than manual measurement classification.

Deep Learning in Gene Regulatory Network Inference: A Survey.

Understanding the intricate regulatory relationships among genes is crucial for comprehending the development, differentiation, and cellular response in living systems. Consequently, inferring gene regulatory networks (GRNs) based on observed data has gained significant attention as a fundamental goal in biological applications. The proliferation and diversification of available data present both opportunities and challenges in accurately inferring GRNs. Deep learning, a highly successful technique in various domains, holds promise in aiding GRN inference. Several GRN inference methods employing deep learning models have been proposed; however, the selection of an appropriate method remains a challenge for life scientists. In this survey, we provide a comprehensive analysis of 12 GRN inference methods that leverage deep learning models. We trace the evolution of these major methods and categorize them based on the types of applicable data. We delve into the core concepts and specific steps of each method, offering a detailed evaluation of their effectiveness and scalability across different scenarios. These insights enable us to make informed recommendations. Moreover, we explore the challenges faced by GRN inference methods utilizing deep learning and discuss future directions, providing valuable suggestions for the advancement of data scientists in this field.

Comparative transcriptomic and metabolomic analyses provide insights into the responses to high temperature stress in Alfalfa (Medicago sativa L.).

High temperature stress is one of the most severe forms of abiotic stress in alfalfa. With the intensification of climate change, the frequency of high temperature stress will further increase in the future, which will bring challenges to the growth and development of alfalfa. Therefore, untargeted metabolomic and RNA-Seq profiling were implemented to unravel the possible alteration in alfalfa seedlings subjected to different temperature stress (25 ℃, 30 ℃, 35 ℃, 40 ℃) in this study. Results revealed that High temperature stress significantly altered some pivotal transcripts and metabolites. The number of differentially expressed genes (DEGs) markedly up and down-regulated was 1876 and 1524 in T30_vs_CK, 2, 815 and 2667 in T35_vs_CK, and 2115 and 2, 226 in T40_vs_CK, respectively. The number for significantly up-regulated and down-regulated differential metabolites was 173 and 73 in T30_vs_CK, 188 and 57 in T35_vs_CK, and 220 and 66 in T40_vs_CK, respectively. It is worth noting that metabolomics and transcriptomics co-analysis characterized enriched in plant hormone signal transduction (ko04705), glyoxylate and dicarboxylate metabolism (ko00630), from which some differentially expressed genes and differential metabolites participated. In particular, the content of hormone changed significantly under T40 stress, suggesting that maintaining normal hormone synthesis and metabolism may be an important way to improve the HTS tolerance of alfalfa. The qRT-PCR further showed that the expression pattern was similar to the expression abundance in the transcriptome. This study provides a practical and in-depth perspective from transcriptomics and metabolomics in investigating the effects conferred by temperature on plant growth and development, which provided the theoretical basis for breeding heat-resistant alfalfa.

PiRNA CFAPIR inhibits cardiac fibrosis by regulating the muscleblind-like protein MBNL2.

Myocardial fibroblasts transform into myofibroblasts during the progression of cardiac fibrosis, together with excessive cardiac fibroblast proliferation. Hence, the prevention and treatment of cardiac fibrosis are significant factors for inhibiting the development of heart failure. P-element Induced WImpy testis-interacting RNAs (PiRNA) are widely expressed in the heart, but their involvement in cardiac fibrosis has not yet been confirmed. We identified differentially expressed PiRNAs using Arraystar PiRNA expression profiling in Angiotensin II models of cardiac fibrosis in vivo and in vitro. We then explored cardiac-fibrosis-associated PiRNA-related proteins, RNA-protein interactomes, immunoprecipitation, and pulldown. We detected fibrosis markers and pathway-related proteins using immunofluorescence, qRT-PCR, and Western blot. We uncovered cardiac fibrosis associated PiRNA (CFAPIR) that was obviously dysregulated during cardiac fibrosis, whereas its overexpression reversed fibrosis in vivo and in vitro. Mechanistically, CFAPIR competitively bound muscleblind like protein 2 (MBNL2) and the cyclin-dependent kinase inhibitor P21 to regulate the TGF-ß1/SMAD3 signaling pathway.

Pharmacovigilance study of GLP-1 receptor agonists for metabolic and nutritional adverse events.

Aims: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are employed extensively in the management of type 2 diabetes and obesity. However, there is a paucity of real-world data on their safety and tolerability for metabolic and nutritional adverse events in large sample populations. This study aimed to analyse the metabolic and nutritional safety signatures of different GLP-1 RAs by exploring the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: AEs data were extracted from the FDA Adverse Event Reporting System database for each GLP-1 RA from the time of its launch until the second quarter of 2023. The reported odds ratio (ROR), proportional reporting ratio (PRR), Empirical Bayesian Geometric Mean and Bayesian Confidence Propagation Neural Network were employed to identify AE signals. Results: A system organ class of metabolism and nutrition disorders was employed to filter AE reports, resulting in the identification of 10,450 reports for exenatide, 2,860 reports for liraglutide, 240 reports for albiglutide, 4,847 reports for dulaglutide, 2,905 reports for semaglutide, 1,089 reports for tirzepatide, and 13 reports for lixisenatide. Semaglutide (ROR, 3.34; 95%CI, 3.22), liraglutide (ROR, 2.78; 95%CI, 2.69), and exenatide (ROR, 2.15; 95%CI, 2.11) were associated with metabolism and nutrition disorders. The number of AE signals detected were as follows: albiglutide (n = 1), lixisenatide (n = 2), tirzepatide (n = 11), exenatide (n = 12), liraglutide (n = 16), semaglutide (n = 20), dulaglutide (n = 22). Dehydration was the most frequent AE contributing to serious outcomes for liraglutide (n = 318, 23.93%), dulaglutide (n = 434, 20.90%), semaglutide (n = 370, 25.10%) and tirzepatide (n = 70, 32.86%). The time to onset (TTO) of AE was statistically different between exenatide and the other GLP-1 RAs (p < 0.001), and the Weibull parameters for dehydration for liraglutide, dulaglutide, and semaglutide analyses all showed an early failure-type profile. Conclusion: Our study suggests that exenatide, liraglutide, and semaglutide are more susceptible to metabolic and nutritional AEs than other GLP-1 RAs. Liraglutide, dulaglutide, semaglutide, and tirzepaptide's potential to induce dehydration, necessitates special attention. Despite certain deficiencies, GLP-1 RAs have considerable potential for the treatment of eating disorders.

Elevation of p53 sensitizes obese kidney to adriamycin-induced aberrant lipid homeostasis via repressing HNF4α-mediated FGF21 sensitivity.

INTRODUCTION: Lipid metabolism disorders have been confirmed to be closely related to kidney injury caused by adriamycin (ADR) and obesity, respectively. However, it has not been explored whether lipid metabolism disorders are related to kidney injury caused by ADR aggravated by obesity, and the specific molecular mechanism needs to be further clarified. OBJECTIVES: This study was designed to examine the role of p53-fibroblast growth factor 21 (FGF21) axis in ADR-induced renal injury aggravated by high fat diet (HFD). METHODS: We engineered Fgf21 KO mice and used long-term (4 months) and short-term (0.5 months) HFD feeding, and ADR-injected mice, as well as STZ-induced type 1 diabetic mice and type 2 (db/db) diabetic mice to produce a in vivo model of nephrotoxicity. The specific effects of p53/FGF21 on regulation of lipid metabolism disorders and its downstream mediators in kidney were subsequently elucidated using a combination of functional and pathological analysis, RNA-sequencing, molecular biology and in vitro approaches. RESULTS: Long-term HFD feeding mice exhibited compromised effects of FGF21 on alleviation of renal dysfunction and lipid accumulation following ADR administration. However, these impairments were reversed by p53 inhibitor (pifithrin-α, PFT-α). PFT-α sensitized FGF21 actions in kidney tissues, while knockout of Fgf21 impaired the protective effects of PFT-α on lipid metabolism. Mechanistically, p53 impaired the renal expression of FGF recepter-1 (FGFR1) and thereby developed gradually into FGF21 resistance via inhibiting hepatocyte nuclear factor alpha (HNF4α)-mediated transcriptional activation of Fgfr1. More importantly, exogenous supplementation of FGF21 or PFT-α could not only alleviate ADR-induced lipid metabolism disorder aggravated by HFD, but also reduce lipid accumulation caused by diabetic nephropathy. CONCLUSION: Given the difficulties in developing the long-acting recombinant FGF21 analogs for therapeutic applications, sensitizing obesity-impaired FGF21 actions by suppression of p53 might be a therapeutic strategy for maintaining renal metabolic homeostasis during chemotherapy.

Association between C-reactive protein/albumin ratio and all-cause mortality in patients with stroke: Evidence from NHANES cohort study.

BACKGROUND AND AIMS: The inflammatory nutritional status is widely associated with the long-term prognosis of non-fatal stroke. The objective of this study is to examine the correlation between the C-reactive protein to albumin ratio (CAR), a new marker indicating both inflammatory and nutritional status, and the overall mortality rate among stroke patients. METHODS AND RESULTS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) database and corresponding public-use mortality data from the linked National Death Index (NDI). The study utilized maximally selected rank statistics to determine the optimal cutoff points for the CAR. Subsequently, participants were stratified into higher- and lower-CAR groups based on these cutoff points. The Kaplan-Meier survival method was used to study overall survival probability. Multivariable Cox proportional regression models were employed to calculate the Hazard Ratio (HR) and corresponding confidence interval (CI). Restricted cubic spline (RCS) model was applied to detect potential non-linear relationship between CAR and mortality risk. Furthermore, stratified and sensitive analyses were performed to examine the robustness and reliability of the results. The study, encompassing 1043 participants with an average age of 64.61 years, identified a cutoff value of 0.32 for CAR, with notable variances observed across gender and age cohorts. Over an average follow-up period of 116 months, 679 instances of all-cause mortality were documented. Kaplan-Meier survival analysis unveiled noteworthy disparities in survival probabilities between groups categorized by high and low CAR levels (p = 0.00081). Continuous CAR analysis consistently demonstrated a positive correlation between elevated CAR values and heightened risk (HR = 1.78 (1.36, 2.33)) of all-cause mortality among stroke patients. Similarly, individuals in the high CAR group exhibited adjusted HR of 1.34 (0.96, 1.89) for all-cause mortality compared to their low CAR counterparts. Subgroup and sensitive analysis consistently reinforced these findings. Smoothing curve fitting further validated CAR's significance as a prognostic indicator of all-cause mortality, indicating a linear relationship. CONCLUSION: Elevated CAR is associated with increased long-term risk of mortality for individuals who have experienced a stroke, suggesting that CAR could serve as a survival indicator.

Advanced Separator Materials for Enhanced Electrochemical Performance of Lithium-Sulfur Batteries: Progress and Prospects.

Lithium-sulfur (Li-S) batteries are promising energy storage devices owing to their high theoretical specific capacity and energy density. However, several challenges, including volume expansion, slow reaction kinetics, polysulfide shuttle effect and lithium dendrite formation, hinder their commercialization. Separators are a key component of Li-S batteries. Traditional separators, made of polypropylene and polyethylene, have certain limitations that should be addressed. Therefore, this review discusses the basic properties and mechanisms of Li-S battery separators, focuses on preparing different functionalized separators to mitigate the shuttle effect of polysulfides. This review also introduces future research trends, emphasizing the potential of separator functionalization in advancing the Li-S battery technology.

Rapid and sensitive detection of etomidate based on functionalized copper nanoclusters fluorescent probe.

Etomidate as a non-barbiturate sedative, has central inhibitory effect and addiction and has been listed as a controlled drug in some countries due to the abusing trend nowadays. Therefore, rapid and sensitive detection of etomidate is of great significance. In this work, a novel fluorescent sensing probe (CuNCs@MIPs) based on copper nanoclusters (CuNCs) and molecular imprinted polymers (MIPs) has been firstly reported. CuNCs was environment-friendly synthesized using poly(vinylpyrrolidone) as a template and ascorbic acid as a reducing agent. After functionalized with molecular imprinting technique, the CuNCs@MIPs probe has special binding cavities on surface to target etomidate, causing the fluorescence intensity rapidly decrease, which confirmed it has excellent sensitivity, selectivity and stability. Under optimal conditions, the fluorescent sensing probe presented high precision linear relationship for etomidate in range of 10-500 ng/ml with detection limit of 10 ng/ml, and the whole detection process was completed within 10 min. This sensing method has also been applied to real samples detection, still demonstrated excellent feasibility in electronic cigarette liquids and urine. More importantly, compared with previous methods, this fluorescent sensing method has advantages such as rapid, simple and easy to operate. Collectively, the proposed CuNCs@MIPs sensing probe has good fluorescence characteristics and simple synthesis strategy, showed a great potential in etomidate detection and application.

From Ethylene Glycol to Glycolic Acid: Electrocatalytic Conversion on Pt-Group Metal Surfaces.

Ethylene glycol (EG) is one of the most attractive platform molecules derived from biomass and waste plastics. Thus, the selective electrooxidation of ethylene glycol (EGOR) into value-added chemicals (especially glycolic acid (GA)) can promote its recycling and upgrading. However, the understanding of the EG-to-GA process on Pt-group metal (PGM) electrodes is far limited now. It has been shown that the Pt and Pd electrodes could show considerable EGOR activity but not Rh and Ir electrodes. Meanwhile, EGOR mainly produces the glycolate, oxalate, and formate on Pt and Pd electrodes, whereas it can obtain minute amounts of glycolate and oxalate on Rh and Ir electrodes. Impressively, the selectivity of glycolate on Pt and Pd electrodes can be over 85% (apparent Faradaic efficiency) in alkaline media, although the stability should be further improved through interfacial tuning and/or engineering. This work might deepen the fundamental understanding of the EGOR process on the nature of PGM electrodes.

Aberrant activation of p53-TRIB3 axis contributes to diabetic myocardial insulin resistance and sulforaphane protection.

INTRODUCTION: Insulin resistance (IR) is associated with multiple pathological features. Although p53- or TRIB3-orchestrated IR is extensively studied in adipose tissue and liver, the role of p53-TRIB3 axis in myocardial IR remains unknown, and more importantly target-directed therapies of myocardial IR are missing. OBJECTIVES: Considering the beneficial effects of sulforaphane (SFN) on cardiovascular health, it is of particular interest to explore whether SFN protects against myocardial IR with a focus on the regulatory role of p53-TRIB3 axis. METHODS: Mouse models including cardiac specific p53-overexpressing transgenic (p53-cTg) mice and Trib3 knockout (Trib3-KO) mice, combined with primary cardiomyocytes treated with p53 activator (nutlin-3a) and inhibitor (pifithrin-α, PFT-α), or transfected with p53-shRNA and Trib3-shRNA, followed by multiple molecular biological methodologies, were used to investigate the role of p53-TRIB3 axis in SFN actions on myocardial IR. RESULTS: Here, we report that knockdown of p53 rescued cardiac insulin-stimulated AKT phosphorylation, while up-regulation of p53 by nutlin-3a or p53-cTg mice blunted insulin sensitivity in cardiomyocytes under diabetic conditions. Diabetic attenuation of AKT-mediated cardiac insulin signaling was markedly reversed by SFN in p53-Tgfl/fl mice, but not in p53-cTg mice. Importantly, we identified TRIB3 was elevated in p53-cTg diabetic mice, and confirmed the physical interaction between p53 and TRIB3. Trib3-KO diabetic mice displayed improved insulin sensitivity in the heart. More specifically, the AMPKα-triggered CHOP phosphorylation and degradation was essential for p53 on the transcriptional regulation of Trib3. CONCLUSION: Overall, these results indicate that inhibiting the p53-TRIB3 pathway by SFN plays an unsuspected key role in improvement of myocardial IR, which may be a promising strategy for attenuating diabetic cardiomyopathy (DCM) in diabetic patients.

A Systematic Hierarchical Virtual Screening Model for RhlR Inhibitors Based on PCA, Pharmacophore, Docking, and Molecular Dynamics.

RhlR plays a key role in the quorum sensing of Pseudomonas aeruginosa. The current structure-activity relationship (SAR) studies of RhlR inhibitors mainly focus on elucidating the functional groups. Based on a systematic review of previous research on RhlR inhibitors, this study aims to establish a systematic, hierarchical screening model for RhlR inhibitors. We initially established a database and utilized principal component analysis (PCA) to categorize the inhibitors into two classes. Based on the training set, pharmacophore models were established to elucidate the structural characteristics of ligands. Subsequently, molecular docking, molecular dynamics simulations, and the calculation of binding free energy and strain energy were performed to validate the crucial interactions between ligands and receptors. Then, the screening criteria for RhlR inhibitors were established hierarchically based on ligand structure characteristics, ligand-receptor interaction, and receptor affinity. Test sets were finally employed to validate the hierarchical virtual screening model by comparing it with the current SAR studies of RhlR inhibitors. The hierarchical screening model was confirmed to possess higher accuracy and a true positive rate, which holds promise for subsequent screening and the discovery of active RhlR inhibitors.

DHA dietary intervention caused different hippocampal lipid and protein profile in ApoE-/- and C57BL/6J mice.

BACKGROUND: Changes in protein and lipid levels may occur in the Alzheimer's disease brain, and DHA can have beneficial effects on it. To investigate the impact of DHA dietary intervention on brain protein and lipid profile in ApoE-/- mice and C57 mice. METHOD: Three-month-old ApoE-/- mice and C57 mice were randomly divided into two groups respectively, and fed with control diet and DHA-fortified diet for five months. Cortical TC, HDL-C and LDL-C levels and cholesterol metabolism-related protein expression were measured by ELISA or immunohistochemistry methods. Hippocampus were collected for proteomic and lipidomics analysis by LC-MS/MS and differential proteins and lipid metabolites were screened and further analyzed by GO functional annotation and KEGG pathway enrichment analysis. RESULTS: DHA intervention decreased cortical TC level in both C57 and ApoE-/- mice (P < 0.05), but caused different change of cortical HDL-C, LDL-C level and LDL-C/HDL-C ratio in C57 and ApoE-/- mice (P < 0.05). Discrepant cortical and hippocampal LDLR, ABCG1, Lox1 and SORT1 protein expression was found between C57 and ApoE-/- mice (P < 0.05), and DHA treatment caused different changes of these proteins in C57 and ApoE-/- mice (P < 0.05). Differential hippocampal proteins and lipids profile were found in C57 and ApoE-/- mice before and after DHA treatment, which were mainly involved in vesicular transport and phospholipid metabolic pathways. CONCLUSION: ApoE genetic defect caused abnormal cholesterol metabolism, and affected protein and lipid profile, as well as discrepant response of hippocampal protein and lipids profile in the brain of mice given DHA fortified diet intervention.

Multi-omics Mendelian randomization integrating GWAS, eQTL and pQTL data revealed GSTM4 as a potential drug target for migraine.

INTRODUCTION: Migraine, as a complex neurological disease, brings heavy burden to patients and society. Despite the availability of established therapies, existing medications have limited efficacy. Thus, we aimed to find the drug targets that improve the prognosis of migraine. METHOD: We used Mendelian Randomization (MR) and Summary-data-based MR (SMR) analyses to study possible drug targets of migraine by summary statistics from FinnGen cohorts (nCase = 44,616, nControl = 367,565), with further replication in UK Biobank (nCase = 26,052, nControl = 487,214). Genetic instruments were obtained from eQTLGen and UKB-PPP to verify the drug targets at the gene expression and protein levels. The additional analyses including Bayesian co-localization, the heterogeneity in dependent instruments(HEIDI), Linkage Disequilibrium Score(LDSC), bidirectional MR, multivariate MR(MVMR), heterogeneity test, horizontal pleiotropy test, and Steiger filtering were implemented to consolidate the findings further. Lastly, drug prediction analysis and phenome-wide association study(PheWAS) were employed to imply the possibility of drug targets for future clinical applications. RESULT: The MR analysis of eQTL data showed that four drug targets (PROCR, GSTM4, SLC4A1, and TNFRSF10A) were significantly associated with migraine risk in both the FinnGen and UK Biobank cohorts. However, only GSTM4 exhibited consistent effect directions across the two outcomes(Discovery cohort: OR(95%CI) = 0.94(0.93-0.96); p = 2.70e - 10; Replication cohort: OR(95%CI) = 0.93(0.91-0.94); p = 4.21e - 17). Furthermore, GSTM4 passed the SMR at p < 0.05 and HEIDI test at p > 0.05 at both the gene expression and protein levels. The protein-level MR analysis revealed a strong correlation between genetically predicted GSTM4 with a lower incidence of migraine and its subtypes(Overall migraine: OR(95%CI) = 0.91(0.87-0.95); p = 6.98e-05; Migraine with aura(MA): OR(95%CI) = 0.90(0.85-0.96); p = 2.54e-03; Migraine without aura(MO): OR(95%CI) = 0.90(0.83-0.96); p = 2.87e-03), indicating a strong co-localization relationship (PPH4 = 0.86). Further analyses provided additional validation for the possibility of GSTM4 as a migraine treatment target. CONCLUSION: This study identifies GSTM4 as a potential druggable gene and promising therapeutic target for migraine.

Atomic Layer Deposition of CeO2 Film with a Novel Heteroleptic Ce(III) Complex.

In this paper, four heteroleptic Ce(III) complexes, including Ce(thd)3-phen (thd = 2,2,6,6-tetramethyl-3,5-heptanedione, phen = 1, 10-phenanthroline (1), Ce(thd)3-MEDA (MEDA = N-Methylethylenediamine (2), Ce(thd)3-MOMA (MOMA = N-(2-Methoxyethyl)methylamine (3), and Ce(thd)3-DMDE (DMDE = N,N″-dimethyl ethanol amine (4), were synthesized and characterized with 1H-NMR, elemental analysis, and X-ray single-crystal diffraction. The thermogravimetric analysis and vapor pressure results indicated that the complexing ability of a nitrogen-containing bidentate ligand with a cerium ion was stronger than that of a mixed oxygen-nitrogen-containing bidentate ligand. Complex 2 was selected as an ALD precursor to deposit a CeO2 film on a SiO2/Si (100) wafer. The self-limited deposition results demonstrated that complex 2 was a potential ALD precursor.

MBNL2 promotes aging-related cardiac fibrosis via inhibited SUMOylation of Krüppel-like factor4.

Aging-related cardiac fibrosis represents the principal pathological progression in cardiovascular aging. The Muscleblind-like splicing regulator 2 (MBNL2) has been unequivocally established as being associated with cardiovascular diseases. Nevertheless, its role in aging-related cardiac fibrosis remains unexplored. This investigation revealed an elevation of MBNL2 levels in the aged heart and senescent cardiac fibroblasts. Notably, the inhibition of MBNL2 demonstrated a capacity to mitigate H2O2-induced myofibroblast transformation and aging-related cardiac fibrosis. Further mechanistic exploration unveiled that aging heightened the expression of SENP1 and impeded the SUMO1 binding with KLF4, and SUMOylation of KLF4 effectively increased by the inhibition of MBNL2. Additionally, the inhibition of TGF-ß1/SMAD3 signaling attenuated the impact of over-expression of MBNL2 in inducing senescence and cardiac fibrosis. MBNL2, by orchestrating SUMOylation of KLF4, upregulating the TGF-ß1/SMAD3 signaling pathway, emerges as a significant promoter of aging-related cardiac fibrosis. This discovery identifies a novel regulatory target for managing aging-related cardiac fibrosis.

Complete genome sequence of Bifidobacterium animalis B01.

Bifidobacterium, a class of strictly anaerobic Gram-positive bacteria, existed mainly in the gut of humans and many mammals. Here, we report the complete genome sequence of Bifidobacterium animalis B01, whose genome length is 1,935,423 bp with a GC content of 60.49%.

Spatially confined dual-emission nanoprobes assembled from silicon nanoparticles and gold nanoclusters for ratiometric biosensing.

Gold nanoclusters (AuNCs) possess weak intrinsic fluorescence, limiting their sensitivity in biosensing applications. This study addresses these limitations by developing a spatially confined dual-emission nanoprobe composed of silicon nanoparticles (SiNPs) and AuNCs. This amplified and stabilized fluorescence mechanism overcomes the limitations associated with using AuNCs alone, achieving superior sensitivity in the sensing platform. The nanoprobe was successfully employed for ratiometric detection of bleomycin (BLM) in serum samples, operating at an excitation wavelength of 365 nm, with emission wavelengths at 480 nm and 580 nm. The analytical performance of the system is distinguished by a linear detection range of 0-3.5 µM, an impressive limit of detection (LOD) of 35.27 nM, and exceptional recoveries ranging from 96.80 to 105.9%. This innovative approach significantly enhances the applicability and reliability of AuNC-based biosensing in complex biological media, highlighting its superior analytical capabilities.

Eye disorders associated with selective serotonin reuptake inhibitors: a real-world disproportionality analysis of FDA adverse event reporting system.

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are widely used in depression and other psychiatric disorders. Despite their efficacy, there is a growing concern about the risk of eye disorders. This study aims to explore the potential correlation between eye disorders and SSRIs utilizing real-world data. RESEARCH DESIGN AND METHODS: The data were extracted from the US FDA Adverse Event Reporting System database from 2004Q1 to 2023Q3. The analysis focused on the clinical characteristics, the ranking of adverse reactions, the time-to-onset, and the severity proportion of SSRI-related eye disorders. RESULTS: Our analysis revealed that SSRIs were significantly associated with eye disorders, with a higher risk of vision blurred with escitalopram, angle closure glaucoma with citalopram, and photopsia with paroxetine. The most common eye disorders were vision blurred, visual impairment, mydriasis, etc. Most of these adverse events occurred within the first 30 days of treatment. The reported incidence of severe eye disorders was 38.6% for SSRIs, with fluoxetine exhibiting the highest rate at 45.9%. CONCLUSION: Our study demonstrates a significant association between SSRIs and the risk of eye disorders. These findings provide crucial insights for clinicians when prescribing SSRIs and underscore the need to monitor eye health in patients receiving these medications.