Machine learning-based identification and validation of aging-related genes in cardiomyocytes from patients with atrial fibrillation.

BACKGROUND: Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder among the elderly. This study aims to elucidate the genetic underpinnings of AF in the context of aging. METHODS: We analyzed 12,403 genes from the GSE2240 database and 279 age-related genes from the CellAge database. Machine learning algorithms, including support vector machines and random forests, were employed to identify genes significantly associated with AF. RESULTS: Among the genes studied, 76 were found to be potential candidates in the development of AF. Notably, four genes - PTTG1, AR, RAD21, and YAP1 - stood out with a Receiver Operating Characteristic Area Under the Curve (ROC AUC) of 0.9, signifying high predictive power. Logistic regression, validated through 10-fold cross-validation and Bootstrap resampling, was determined as the most suitable model for internal validation. CONCLUSIONS: The discovery of these four genes could improve diagnostic accuracy for AF in the aged population. Additionally, our drug prediction model indicates that bisphenol A and cisplatin, among other substances, could be promising in treating age-associated AF, offering potential pathways for clinical intervention.

Aggregation-Induced Emission Luminogen: Role in Biopsy for Precision Medicine.

Biopsy, including tissue and liquid biopsy, offers comprehensive and real-time physiological and pathological information for disease detection, diagnosis, and monitoring. Fluorescent probes are frequently selected to obtain adequate information on pathological processes in a rapid and minimally invasive manner based on their advantages for biopsy. However, conventional fluorescent probes have been found to show aggregation-caused quenching (ACQ) properties, impeding greater progresses in this area. Since the discovery of aggregation-induced emission luminogen (AIEgen) have promoted rapid advancements in molecular bionanomaterials owing to their unique properties, including high quantum yield (QY) and signal-to-noise ratio (SNR), etc. This review seeks to present the latest advances in AIEgen-based biofluorescent probes for biopsy in real or artificial samples, and also the key properties of these AIE probes. This review is divided into: (i) tissue biopsy based on smart AIEgens, (ii) blood sample biopsy based on smart AIEgens, (iii) urine sample biopsy based on smart AIEgens, (iv) saliva sample biopsy based on smart AIEgens, (v) biopsy of other liquid samples based on smart AIEgens, and (vi) perspectives and conclusion. This review could provide additional guidance to motivate interest and bolster more innovative ideas for further exploring the applications of various smart AIEgens in precision medicine.

Construction of an interpretable model for predicting survival outcomes in patients with middle to advanced hepatocellular carcinoma (≥5 cm) using lasso-cox regression.

Background: In this retrospective study, we aimed to identify key risk factors and establish an interpretable model for HCC with a diameter ≥ 5 cm using Lasso regression for effective risk stratification and clinical decision-making. Methods: In this study, 843 patients with advanced hepatocellular carcinoma (HCC) and tumor diameter ≥ 5 cm were included. Using Lasso regression to screen multiple characteristic variables, cox proportional hazard regression and random survival forest models (RSF) were established. By comparing the area under the curve (AUC), the optimal model was selected. The model was visualized, and the order of interpretable importance was determined. Finally, risk stratification was established to identify patients at high risk. Result: Lasso regression identified 8 factors as characteristic risk factors. Subsequent analysis revealed that the lasso-cox model had AUC values of 0.773, 0.758, and 0.799, while the lasso-RSF model had AUC values of 0.734, 0.695, and 0.741, respectively. Based on these results, the lasso-cox model was chosen as the superior model. Interpretability assessments using SHAP values indicated that the most significant characteristic risk factors, in descending order of importance, were tumor number, BCLC stage, alkaline phosphatase (ALP), ascites, albumin (ALB), and aspartate aminotransferase (AST). Additionally, through risk score stratification and subgroup analysis, it was observed that the median OS of the low-risk group was significantly better than that of the middle- and high-risk groups. Conclusion: We have developed an interpretable predictive model for middle and late HCC with tumor diameter ≥ 5 cm using lasso-cox regression analysis. This model demonstrates excellent prediction performance and can be utilized for risk stratification.

Organophosphorus Hydrolase-like Nanozyme with an Activity-Quenched Aggregation-Induced Emission Effect: A Self-Reporting and Specific Assay of Nerve Agents.

Given the promising prospect of aggregation-induced emission luminogens (AIEgens) in fluorescence assays, it is interesting and significant to endow AIEgens with molecular recognition capability (such as enzyme-like activity). Here, an AIE nanomaterial with intrinsic enzyme-like activity (named as "AIEzyme") is designed and synthesized via a facile coordination polymerization of Zr4+ and AIE ligands. AIEzyme possesses enhanced and stable fluorescence in different solvents because of the AIE effect of ligands in the rigid structure of a coordination polymer. On the other hand, the organophosphorus hydrolase (OPH)-mimicking activity of AIEzyme exhibits excellent affinity and specific activity. Interestingly, the OPH-like activity can quench the inherent fluorescence of AIEzyme by the hydrolysate of a typical organophosphorus nerve agent (OPNA), diethyl-4-nitrophenylphosphate. Due to the sensitive activity-induced quenching effect for AIE, the self-reporting fluorescence assay method based on AIEzyme was established, which shows ultrahigh sensitivity, high selectivity, good storage stability, and acceptable reliability for a real sample assay. Moreover, the simultaneous colorimetric method broadens the detection range and the application scenarios. The proposed assay method avoided the interference of O2 during detection because the OPH-like activity does not derive from the generation of ROS. As a bonus, AIEzyme can also be used for the degradation of OPNAs by OPH-like activity, and the process can be self-monitored by AIE quenching. This work would provide a new opportunity for expanding the application of AIEgens and artificial enzymes by endowing AIEgens with enzyme-like activity.

Nano boron carbide effectively boost Fenton-like performance of hematite mediated systems: Roles of hematite exposed facets and synergistic catalysis between Fe and B.

The inherent properties of exposed facets of iron minerals played key roles in heterogeneous reactions at the mineral interface, and the addition of co-catalysts has been elucidated to further enhance the reactions for contaminants degradation. Here, synergistic Fenton-like catalytic reactivity of different hematite dominant exposed facets ({001}, {012}, {100}, and {113}) with nano boron carbide (B4C) was revealed. In 5 h, as compared with the cumulative •OH in the B4C/H2O2 system (96.9 µM), while that in the {001}/B4C/H2O2 system was decreased by 19.6%, those in the {012}/B4C/H2O2, {100}/B4C/H2O2, and {113}/B4C/H2O2 systems were increased by 53.8%, 75.9%, and 84.0%, respectively. Significantly, {113}/B4C/H2O2 system exhibited strong capability for degradation of a broad spectrum of organic pollutants, including typical phenol, endocrine disruptor (bisphenol A), antibiotic (sulfanilamide), dyes (Rhodamine B and methylene blue), and pesticide (atrazine). During the Fenton-like reactions, higher synergy factor, Fe(III)/Fe(II) cycling rate, and amount of Fe-O-B bond in the {113}/B4C/H2O2 system were shown than those in other systems, thus exhibiting its desirable catalytic performance for •OH production and pollutants oxidation. Iron species and X-ray photoelectron spectroscopy (XPS) analyses indicated that B-B bond and interfacial suboxide boron (e.g., B-O) could provide electrons to facilitate Fe(III) reduction for boosting the Fe(III)/Fe(II) cycling. Density functional theory (DFT) results demonstrated the formation of Fe-O-B bond on hematite {113}, {100}, and {012} facets, which were beneficial to the breakage of O-O bond of bound H2O2 molecule and thus improved the generation of •OH. This study emphasized the essential role of B4C in developing tailored hematite facets as a contaminant remediation substrate, and provided important insights into the design of efficient heterogeneous Fenton-like systems.

Reversible uncompetitive inhibition of metal-organic framework nanozymes: specific colorimetric assay of methidathion without enzymes.

An Fe-based metal-organic framework (Fe-MOF) nanozyme with MIL-88B(Fe) structure was facilely prepared by an ultrasonic method. Its oxidase-like activity could be specifically inhibited by methidathion, which conformed to a reversible uncompetitive inhibition mechanism. Furthermore, a specific and enzyme-free colorimetric assay of methidathion was established using Fe-MOF as the ideal recognition element.

Fatty acid synthesis promoted by PA1895-1897 operon delays quorum sensing activation in Pseudomonas aeruginosa.

PA1895-1897 is a quorum sensing (QS) operon regulated by the anti-activator LuxR homologue QscR in Pseudomonas aeruginosa. We aimed to investigate its impact on bacterial metabolism, and whether it contributes to the delayed QS activation. We performed liquid chromatograph-mass spectrometer-based metabolomics using wildtype PAO1, PA1895-1897-knockout mutant, and mutant with pJN105.PA1895-1897 overexpression vector. The impact of metabolites on QS signaling molecule (3OC12-HSL and C4-HSL) concentrations, pyocyanin production, and QS gene (lasR, lasI, rhlR, and rhlI) expression was examined. Metabolomics analysis found that fatty acid biosynthesis had the highest fold enrichment among all metabolic pathways in PA1895-1897-overexpressed mutants. Among these enriched fatty acids, palmitoleic acid and acetic acid were the predominantly abundant ones that significantly affected by PA1895-1897 operon. When different doses of exogenous palmitoleic acid or acetic acid were added to the cultures of PA1895-1897 knockout mutants, their levels of 3OC12-HSL, C4-HSL, and pyocyanin were decreased in a dose-dependent manner. High doses of palmitoleic acid and acetic acid suppressed the mRNA expression of lasR, rhlR, and rhlI. Inhibition of fatty acid biosynthesis increased the production of 3OC12-HSL, C4-HSL, and pyocyanin in PA1895-1897-overexpressed cultures. Our data suggest that fatty acid synthesis is promoted by PA1895-1897 operon, and contributes the delayed expression of QS phenotypes, furthering the understanding about the regulation of bacterial QS activation.

Prevalence, Risk Factors and Pain Subtypes of Post-COVID Pain in Nonhospitalized Older Adults: A Cross-Sectional Study.

BACKGROUND: Post-COVID pain (PCP) is a condition that ensues from an infection of coronavirus disease 2019 (COVID-19). Some researchers have explored the prevalence of PCP and its characteristics in the individuals who experience it. However, most individuals involved in the previous studies were middle-aged, and those studies focused mainly on hospital patients and musculoskeletal PCP. Existing data on PCP and its subtypes among older adults and outpatients are scanty. OBJECTIVE: Our study aims to identify PCP's prevalence and associated risk factors and to compare the quality of life (QoL), sleep quality, and anxiety and depression levels in nonhospitalized elderly COVID-19 survivors with different PCP subtypes. STUDY DESIGN: A cross-sectional study. SETTING: The study was conducted from April 2023 to June 2023 after the first outbreak of the Omicron variant of SARS-CoV-2 in the Taikang Yanyuan Continuing Care Retirement Community (CCRC) in China. METHODS: Eligible participants were surveyed using the Numeric Rating Scale (NRS), Douleur Neuropathique-4 questionnaire (DN4), EuroQol 5D-5L questionnaire (EQ-5D-5L), Pittsburgh Sleep Quality Index (PSQI), Generalized Anxiety Disorder 7 (GAD-7) scale, and Patient Health Questionnaire-9 (PHQ-9) scale. COVID-19 symptoms and laboratory parameters were obtained through an electronic healthcare system. Descriptive analysis was performed based on the presence of PCP and PCP subtypes. Multivariable logistic regression analysis and multiple linear regression were used for risk-factor analysis and adjustment of confounding factors. RESULTS: A total of 668 individuals (female: 59.3%, median age: 84 years) who had been infected with COVID-19 for a median duration of 145 (126-168) days were enrolled in our study. PCP was observed in 9.4% (63/668) of elderly COVID-19 survivors. Number of COVID-19 symptoms (aOR 1.31, 95%CI 1.05-1.64, P = 0.018) and previous chronic pain (aOR 4.24, 95%CI 1.59-11.27, P = 0.004) were risk factors associated with PCP. Individuals with neuropathic PCP exhibited higher NRS scores (5 [5-6] vs. 3 [3-4], P < 0.001) and more use of analgesic drugs (70.0%, 7/10 vs. 20.8%, 11/53, P = 0.005) for pain management. Neuropathic PCP was associated with lower scores on the EQ-5D index (B = -0.210, 95% CI -0.369 to -0.051, P = 0.011) and EQ-VAS (B = -10.808, 95% CI -21.149 to -0.468, P = 0.041) and higher PHQ-9 scores (B = 3.154, 95% CI 0.674-5.634, P = 0.014). LIMITATIONS: It is difficult to establish a strong causality between PCP and SARS-CoV-2 infection due to the study's cross-sectional nature. Selection bias could not be eliminated, since our study relied on volunteer participation. Due to neuropathic PCP's lower prevalence than nonneuropathic PCP, larger sample sizes and multicenter studies are crucial for a comprehensive understanding of the neuropathic PCP condition. CONCLUSION: Our study found a PCP prevalence of 9.4% in nonhospitalized older adults who had survived COVID-19. Number of COVID-19 symptoms and history of previous chronic pain seemed to be potential risk factors for PCP. Neuropathic PCP was associated with lower QoL and a more severe depression level.

Investigating the eye-catching effect in the entrance zone of highway tunnels through heart rate variability analysis.

OBJECTIVE: This study aimed to investigate the influence of visual attraction conditions on drivers' cognitive workload and physiological responses, assessed through heart rate variability (HRV) indicators. The study examined four experimental scenarios, including a baseline condition and three visual attractions (landscape-style architecture, tip slogan, and billboard) at tunnel entrances. METHODS: HRV indicators, including RMSSD, SDNN, LF, and LF/HF ratio, were analyzed to assess cognitive workload and physiological states. The study collected data from a sample of drivers under each experimental scenario and compared the HRV measures across conditions. RESULTS: The presence of visual attractions at tunnel entrances significantly impacted drivers' HRV. The introduction of visual attractions resulted in decreased RMSSD and SDNN values, indicating increased cognitive workload and reduced adaptability of the autonomic nervous system. Moreover, visual attractions led to increased LF values and LF/HF ratio, suggesting heightened sympathetic activation and potential cognitive engagement. CONCLUSIONS: Visual attractions have a significant impact on drivers' cognitive workload and physiological responses. Designing tunnel entrances with a balance between visual attractiveness and cognitive demands is essential to optimize drivers' cognitive performance and overall driving experience. These findings provide valuable insights for transportation authorities and designers to create safer and more user-friendly tunnel environments.

Effects of helmet usage on moped riders' injury severity in moped-vehicle crashes: Insights from partially temporal constrained random parameters bivariate probit models.

Mopeds are small and move unpredictably, making them difficult for other drivers to perceive. This lack of visibility, coupled with the minimal protection that mopeds provide, can lead to serious crashes, particularly when the rider is not wearing a helmet. This paper explores the association between helmet usage and injury severity among moped riders involved in collisions with other vehicles. A series of joint bivariate probit models are employed, with injury severity and helmet usage serving as dependent variables. Data on two-vehicle moped crashes in Florida from 2019 to 2021 are collected and categorized into three periods: before, during, and after the COVID-19 pandemic. Crash involvement ratios are calculated to examine the safety risk elements of moped riders in various categories, while significant temporal shifts are also explored. The correlated joint random parameters bivariate probit models with heterogeneity in means demonstrate their superiority in capturing interactive unobserved heterogeneity, revealing how various variables significantly affect injury outcomes and helmet usage. Temporal instability related to the COVID-19 pandemic is validated through likelihood ratio tests, out-of-sample predictions, and calculations of marginal effects. Additionally, several parameters are noted to remain temporally stable across multiple periods, prompting the development of a partially temporally constrained modeling approach to provide insights from a long-term perspective. Specifically, it is found that male moped riders are less likely to wear helmets and are negatively associated with injury/fatality rates. Moped riders on two-lane roads are also less likely to wear helmets. Furthermore, moped riders face a lower risk of injury or fatality during daylight conditions, while angle crashes consistently lead to a higher risk of injuries and fatalities across the three periods. These findings provide valuable insights into helmet usage and injury severity among moped riders and offer guidance for developing countermeasures to protect them.

Reduced heart rate variability is associated with altered clinical laboratory profile in people living with HIV.

Background: We compared heart rate variability (HRV) indices between people living with HIV (PLWH) and HIV-negative individuals to ascertain the independent association between HIV infection and reduced HRV, and further investigated whether distinct clinical laboratory profiles exist between PLWH with and without reduced HRV. Methods: This cross-sectional analysis included 304 PLWH and 147 HIV-negative individuals with comparable age and sex. Thirty-two routine clinical laboratory indices (including hematology and biochemistry) closest to the survey were extracted from the Electronic Medical Record System. HRV indices were divided into two categories: low (lowest quartile, Q1) and moderate-to-high (combined, Q2‒Q4). Results: The time domain indices, ln(SDNN), ln(RMSSD), and ln(PNN50), as well as the frequency domain indices, ln(HF), ln(LF), and ln(VLF), were all significantly reduced in PLWH versus HIV-negative individuals (all p < 0.05). These associations remained for ln(SDNN), ln(PNN50), ln(HF) and ln(LF) even after adjusting for potential confounders in multivariable models. PLWH with low HRV indices exhibited distinct clinical laboratory profiles that were characterized by an elevation in fasting plasma glucose, white blood cell count, neutrophil count, neutrophil%, and a reduction in albumin, total protein, urine creatinine, lymphocyte%, red blood cell count (RBC) and nadir CD4 count. The final stepwise logistic regression models for low SDNN included older age, decreased total cholesterol levels, elevated neutrophil count, and the use of antidiabetic medications, whereas the final model for low LF included older age, reduced RBC and the use of antidiabetic medications. Conclusion: PLWH exhibit impaired parasympathetic activity, as evidenced by reduced SDNN, PNN50, LF and HF. Furthermore, PLWH who have reduced HRV indices exhibits distinct clinical laboratory profiles that are related to systematic inflammatory response and diabetes.

Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial.

BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of using an artificial intelligence (AI)-based rapid nutritional diagnostic system for routine nutritional screening of hospitalised patients. METHODS: A nationwide multicentre randomised controlled trial was conducted at 11 centres in 10 provinces. Hospitalised patients were randomised to either receive an assessment using an AI-based rapid nutritional diagnostic system as part of routine care (experimental group), or not (control group). The overall medical resource costs were calculated for each participant and a decision-tree was generated based on an intention-to-treat analysis to analyse the cost-effectiveness of various treatment modalities. Subgroup analyses were performed according to clinical characteristics and a probabilistic sensitivity analysis was performed to evaluate the influence of parameter variations on the incremental cost-effectiveness ratio (ICER). RESULTS: In total, 5763 patients participated in the study, 2830 in the experimental arm and 2933 in the control arm. The experimental arm had a significantly higher cure rate than the control arm (23.24% versus 20.18%; p = 0.005). The experimental arm incurred an incremental cost of 276.52 CNY, leading to an additional 3.06 cures, yielding an ICER of 90.37 CNY. Sensitivity analysis revealed that the decision-tree model was relatively stable. CONCLUSION: The integration of the AI-based rapid nutritional diagnostic system into routine inpatient care substantially enhanced the cure rate among hospitalised patients and was cost-effective. REGISTRATION: NCT04776070 (https://clinicaltrials.gov/study/NCT04776070).

Effects of Water and Nitrogen Regulation on Apple Tree Growth, Yield, Quality, and Their Water and Nitrogen Utilization Efficiency.

Apple tree productivity is influenced by the quantity of water and nutrients that are supplied during planting. To enhance resource utilization efficiency and optimize yields, a suitable strategy for supplying water and nitrogen must be established. A field experiment was conducted using a randomized block group design on five-year-old apple trees in Ningxia, with two irrigation lower limit levels (55%FC (W1) and 75%FC (W2)) and four N application levels (0 (N1), 120 (N2), 240 (N3), and 360 (N4) kg·ha-1). Our findings showed that leaf N content increased with a higher irrigation lower limit, but the difference was not statistically significant. However, the leaf N content significantly increased with increasing N application. The growth pattern of new shoots followed logistic curve characteristics, with the maximum new shoot growth rate and time of new shoot growth being delayed under high water and high nitrogen treatments. Apple yield and yield components (weight per fruit and number of fruits per plant) were enhanced under N application compared to no N application. The maximum apple yields were 19,405.3 kg·ha-1 (2022) and 29,607 kg·ha-1 (2023) at the N3 level. A parabolic relationship was observed between apple yield and N application level, with the optimal range of N application being 230-260 kg⸱ha-1. Apple quality indicators were not significantly affected by the irrigation lower limit but were significantly influenced by N application levels. The lower limit of irrigation did not have a significant impact on the quality indicators of the apples. Water and N utilization efficiencies improved with the W2 treatment at the same N application level. A negative relationship was observed between the amount of nitrogen applied and the biased productivity of nitrogen fertilizer. The utilization of nitrogen fertilizer was 127.6 kg·kg-1 (2022) and 200.3 kg·kg-1 (2023) in the W2N2 treatment. The apple yield was sustained, the quality of the fruit improved, and a substantial increase in water productivity was achieved with the W2N3 treatment. The findings of this study can be used as a reference for accurate field irrigation.

Occupational Exposure to Silica Dust and Silicosis Risk in Chinese Noncoal Mines: Qualitative and Quantitative Risk Assessment.

BACKGROUND: Despite increasing awareness, silica dust-induced silicosis still contributes to the huge disease burden in China. Worryingly, recent silica dust exposure levels and silicosis risk in Chinese noncoal mines remain unclear. OBJECTIVE: We aimed to determine recent silica dust exposure levels and assess the risk of silicosis in Chinese noncoal mines. METHODS: Between May and December 2020, we conducted a retrospective cohort study on 3 noncoal mines and 1 public hospital to establish, using multivariable Cox regression analyses, prediction formulas of the silicosis cumulative hazard ratio (H) and incidence (I) and a cross-sectional study on 155 noncoal mines in 10 Chinese provinces to determine the prevalence of silica dust exposure (PDE), free silica content, and total dust and respirable dust concentrations. The qualitative risk of silicosis was assessed using the International Mining and Metals Commission's risk-rating table and the occupational hazard risk index; the quantitative risk was assessed using prediction formulas. RESULTS: Kaplan-Meier survival analysis revealed significant differences in the silicosis probability between silica dust-exposed male and female miners (log-rank test χ21=7.52, P=.01). A total of 126 noncoal mines, with 29,835 miners and 4623 dust samples, were included; 13,037 (43.7%) miners were exposed to silica dust, of which 12,952 (99.3%) were male. The median PDE, free silica content, total dust concentration, and respirable dust concentration were 61.6%, 27.6%, 1.30 mg/m3, and 0.58 mg/m3, respectively, indicating that miners in nonmetal, nonferrous metal, small, and open-pit mines suffer high-level exposure to silica dust. Comprehensive qualitative risk assessment showed noncoal miners had a medium risk of silicosis, and the risks caused by total silica dust and respirable silica dust exposure were high and medium, respectively. When predicting H and I over the next 10, 20, and 30 years, we assumed that the miner gender was male. Under exposure to current total silica dust concentrations, median I10, I20, and I30 would be 6.8%, 25.1%, and 49.9%, respectively. Under exposure to current respirable silica dust concentrations, median I10, I20, and I30 would be 6.8%, 27.7%, and 57.4%, respectively. These findings showed that miners in nonmetal, nonferrous metal, small, and open-pit mines have a higher I and higher qualitative silicosis risk. CONCLUSIONS: Chinese noncoal miners, especially those in nonmetal, nonferrous metal, small, and open-pit mines, still suffer high-level exposure to silica dust and a medium-level risk of silicosis. Data of both total silica dust and respirable silica dust are vital for occupational health risk assessment in order to devise effective control measures to reduce noncoal mine silica dust levels, improve miners' working environment, and reduce the risk of silicosis.

Hearing restoration by gene replacement therapy for a multisite-expressed gene in a mouse model of human DFNB111 deafness.

Gene therapy has made significant progress in the treatment of hereditary hearing loss. However, most research has focused on deafness-related genes that are primarily expressed in hair cells with less attention given to multisite-expressed deafness genes. MPZL2, the second leading cause of mild-to-moderate hereditary deafness, is widely expressed in different inner ear cells. We generated a mouse model with a deletion in the Mpzl2 gene, which displayed moderate and slowly progressive hearing loss, mimicking the phenotype of individuals with DFNB111. We developed a gene replacement therapy system mediated by AAV-ie for efficient transduction in various types of cochlear cells. AAV-ie-Mpzl2 administration significantly lowered the auditory brainstem response and distortion product otoacoustic emission thresholds of Mpzl2-/- mice for at least seven months. AAV-ie-Mpzl2 delivery restored the structural integrity in both outer hair cells and Deiters cells. This study suggests the potential of gene therapy for MPZL2-related deafness and provides a proof of concept for gene therapy targeting other deafness-related genes that are expressed in different cell populations in the cochlea.

A novel protein SPECC1-415aa encoded by N6-methyladenosine modified circSPECC1 regulates the sensitivity of glioblastoma to TMZ.

BACKGROUND: Circular RNAs (circRNAs) can influence a variety of biological functions and act as a significant role in the progression and recurrence of glioblastoma (GBM). However, few coding circRNAs have been discovered in cancer, and their role in GBM is still unknown. The aim of this study was to identify coding circRNAs and explore their potential roles in the progression and recurrence of GBM. METHODS: CircSPECC1 was screened via circRNAs microarray of primary and recurrent GBM samples. To ascertain the characteristics and coding ability of circSPECC1, we conducted a number of experiments. Afterward, through in vivo and in vitro experiments, we investigated the biological functions of circSPECC1 and its encoded novel protein (SPECC1-415aa) in GBM, as well as their effects on TMZ sensitivity. RESULTS: By analyzing primary and recurrent GBM samples via circRNAs microarray, circSPECC1 was found to be a downregulated circRNA with coding potential in recurrent GBM compared with primary GBM. CircSPECC1 suppressed the proliferation, migration, invasion, and colony formation abilities of GBM cells by encoding a new protein known as SPECC1-415aa. CircSPECC1 restored TMZ sensitivity in TMZ-resistant GBM cells by encoding the new protein SPECC1-415aa. The m6A reader protein IGF2BP1 can bind to circSPECC1 to promote its expression and stability. Mechanistically, SPECC1-415aa can bind to ANXA2 and competitively inhibit the binding of ANXA2 to EGFR, thus resulting in the inhibition of the phosphorylation of EGFR (Tyr845) and its downstream pathway protein AKT (Ser473). In vivo experiments showed that the overexpression of circSPECC1 could combine with TMZ to treat TMZ-resistant GBM, thereby restoring the sensitivity of TMZ-resistant GBM to TMZ. CONCLUSIONS: CircSPECC1 was downregulated in recurrent GBM compared with primary GBM. The m6A reader protein IGF2BP1 could promote the expression and stability of circSPECC1. The sequence of SPECC1-415aa, which is encoded by circSPECC1, can inhibit the binding of ANXA2 to EGFR by competitively binding to ANXA2 and inhibiting the phosphorylation of EGFR and AKT, thereby restoring the sensitivity of TMZ-resistant GBM cells to TMZ.

Cross-species single-cell spatial transcriptomic atlases of the cerebellar cortex.

The molecular and cellular organization of the primate cerebellum remains poorly characterized. We obtained single-cell spatial transcriptomic atlases of macaque, marmoset, and mouse cerebella and identified primate-specific cell subtypes, including Purkinje cells and molecular-layer interneurons, that show different expression of the glutamate ionotropic receptor Delta type subunit 2 (GRID2) gene. Distinct gene expression profiles were found in anterior, posterior, and vestibular regions in all species, whereas region-selective gene expression was predominantly observed in the granular layer of primates and in the Purkinje layer of mice. Gene expression gradients in the cerebellar cortex matched well with functional connectivity gradients revealed with awake functional magnetic resonance imaging, with more lobule-specific differences between primates and mice than between two primate species. These comprehensive atlases and comparative analyses provide the basis for understanding cerebellar evolution and function.

Photoresponsive Two-Dimensional Magnetic Junctions for Reconfigurable In-Memory Sensing.

Magnetic tunneling junctions (MTJs) lie in the core of magnetic random access memory, holding promise in integrating memory and computing to reduce hardware complexity, transition latency, and power consumption. However, traditional MTJs are insensitive to light, limiting their functionality in in-memory sensing─a crucial component for machine vision systems in artificial intelligence applications. Herein, the convergence of magnetic memory with optical sensing capabilities is achieved in the all-two-dimensional (2D) magnetic junction Fe3GaTe2/WSe2/Fe3GaTe2, which combines 2D magnetism and optoelectronic properties. The clean intrinsic band gap and prominent photoresponse of interlayer WSe2 endow the tunneling barrier with optical tunability. The on-off states of junctions and the magnetoresistance can be flexibly controlled by the intensity of the optical signal at room temperature. Based on the optical-tunable magnetoresistance in all-2D magnetic junctions, a machine vision system with the architecture of in-memory sensing and computing is constructed, which possesses high performance in image recognition. Our work exhibits the advantages of 2D magneto-electronic devices and extends the application scenarios of magnetic memory devices in artificial intelligence.

Highly sensitive biosensors for real-time monitoring of histamine at acupoint PC6 in rats based on graphene-modified acupuncture needles.

Acupoints are the local initial response sites of acupuncture therapeutic effects. As a biomarker, histamine is released into the acupoint region and plays its role concurrently as acupuncture needles are inserted into acupoints. Hence, real-time monitoring of histamine at acupoints is important to elucidate the effectiveness of the acupoint-activation process in acupuncture. Therefore, we developed highly sensitive acupuncture/Au particles/graphene biosensors by electrodeposition, brushing, and annealing methods based on bare acupuncture needles. We achieved a histamine detection limit of approximately 4.352 (±3.419) × 10-12 mol L-1 and good sensitivity of approximately 6.296 (±3.873) µA µM-1, with satisfactory specificity, repeatability, and stability in vitro, rendering them more competitive and suitable for real-time monitoring in vivo without causing additional damage. Subsequently, we conducted real-time histamine monitoring at non-acupoint and acupoint PC6 in rats, respectively. Our results showed minimal changes at the non-acupoint, whereas a trend of initial increase followed by a decrease was observed at acupoint PC6. The change in histamine concentration at acupoint PC6 reflected its involvement in the acupoint-activation procedure. Moreover, its peak position at ∼18 min could provide guidance for optimizing needle retaining time for maximum therapeutic effect. This work presents the first real-time in vivo monitoring of histamine at acupoints with high sensitivity and underscores the specificity of histamine release between non-acupoint and acupoint PC6, demonstrating great potential for elucidating the acupoint-activation mechanisms in acupuncture. Additionally, this work expands the application of nanomaterials in the integration of medicine and engineering, which is an important aspect of the future development of materials science.

Unveiling responses and mechanisms of spice crop chive exposure to three typical pesticides using metabolomics combined with transcriptomics, physiology and biochemistry.

Pesticides are frequently used to control target pests in the production of spice crops such as chives (Allium ascalonicum). However, little information is available on the responses and underlying mechanisms of pesticide exposure in this crop. Our findings revealed that the uptake, transportation, and subcellular distribution of three typical pesticides-the fungicide pyraclostrobin (PAL), insecticide acetamiprid (ATP), and herbicide pendimethalin (PND) in chives, as well as their physiological, biochemical, metabolic, and transcriptomic responses-were dependent on pesticide properties, especially hydrophobicity. The distribution of PAL and PND in chives decreased in the order root > stem > leaf, but the distribution order of ATP was the opposite. The proportion of PAL and PND in the solid phase of the root cells gradually increased, but ATP mainly existed in the cell-soluble component, indicating that the latter had an upward translocation ability and thus mainly accumulated in the leaves. Malondialdehyde levels in chive leaves were not significantly affected by exposure to these pesticides; however, the activities of superoxide dismutase (SOD) and catalase (CAT) in chive leaves increased significantly. Moreover, these pesticides exhibited critical differences in chive responses through the interaction of metabolites and regulation of differentially expressed genes. PAL dramatically influenced five carbohydrate metabolic pathways (34.35 %), disturbing the starch-to-sucrose balance. ATP strongly affected five amino acid (AC) metabolic pathways (33.38 %), enhancing four free amino acid levels. PND notably affected eight fatty acid (FA) metabolic pathways (25.38 %), increasing two unsaturated and decreasing one saturated FA. Simultaneously, PND, ATP, and PND accumulated in the chives could be detoxified through metabolic pathways mediated by cytochrome P450 (P450) and glycosyltransferase (GT)/glutathione S-transferase (GST), producing phase I (7, 4, and 5) and II (11, 13, and 10) metabolites, respectively. This study provides important molecular insights into the responses and underlying mechanisms of spice crop exposure to pesticides.