Febrile Temperature Critically Controls the Differentiation and Pathogenicity of T Helper 17 Cells.

Fever, an evolutionarily conserved physiological response to infection, is also commonly associated with many autoimmune diseases, but its role in T cell differentiation and autoimmunity remains largely unclear. T helper 17 (Th17) cells are critical in host defense and autoinflammatory diseases, with distinct phenotypes and pathogenicity. Here, we show that febrile temperature selectively regulated Th17 cell differentiation in vitro in enhancing interleukin-17 (IL-17), IL-17F, and IL-22 expression. Th17 cells generated under febrile temperature (38.5°C-39.5°C), compared with those under 37°C, showed enhanced pathogenic gene expression with increased pro-inflammatory activities in vivo. Mechanistically, febrile temperature promoted SUMOylation of SMAD4 transcription factor to facilitate its nuclear localization; SMAD4 deficiency selectively abrogated the effects of febrile temperature on Th17 cell differentiation both in vitro and ameliorated an autoimmune disease model. Our results thus demonstrate a critical role of fever in shaping adaptive immune responses with implications in autoimmune diseases.

The HLA-I landscape confers prognosis and antitumor immunity in breast cancer.

Breast cancer is a highly heterogeneous disease with varied subtypes, prognoses and therapeutic responsiveness. Human leukocyte antigen class I (HLA-I) shapes the immunity and thereby influences the outcome of breast cancer. However, the implications of HLA-I variations in breast cancer remain poorly understood. In this study, we established a multiomics cohort of 1156 Chinese breast cancer patients for HLA-I investigation. We calculated four important HLA-I indicators in each individual, including HLA-I expression level, somatic HLA-I loss of heterozygosity (LOH), HLA-I evolutionary divergence (HED) and peptide-binding promiscuity (Pr). Then, we evaluated their distribution and prognostic significance in breast cancer subtypes. We found that the four breast cancer subtypes had distinct features of HLA-I indicators. Increased expression of HLA-I and LOH were enriched in triple-negative breast cancer (TNBC), while Pr was relatively higher in hot tumors within TNBCs. In particular, a higher Pr indicated a better prognosis in TNBCs by regulating the infiltration of immune cells and the expression of immune molecules. Using the matched genomic and transcriptomic data, we found that mismatch repair deficiency-related mutational signature and pathways were enriched in low-Pr TNBCs, suggesting that targeting mismatch repair deficiency for synthetic lethality might be promising therapy for these patients. In conclusion, we presented an overview of HLA-I indicators in breast cancer and provided hints for precision treatment for low-Pr TNBCs.

FTO-mediated m6A mRNA demethylation aggravates renal fibrosis by targeting RUNX1 and further enhancing PI3K/AKT pathway.

Chronic kidney disease (CKD) is a global health burden, with ineffective therapies leading to increasing morbidity and mortality. Renal interstitial fibrosis is a common pathway in advanced CKD, resulting in kidney function and structure deterioration. In this study, we investigate the role of FTO-mediated N6-methyladenosine (m6A) and its downstream targets in the pathogenesis of renal fibrosis. M6A modification, a prevalent mRNA internal modification, has been implicated in various organ fibrosis processes. We use a mouse model of unilateral ureteral obstruction (UUO) as an in vivo model and treated tubular epithelial cells (TECs) with transforming growth factor (TGF)-ß1 as in vitro models. Our findings revealed increased FTO expression in UUO mouse model and TGF-ß1-treated TECs. By modulating FTO expression through FTO heterozygous mutation mice (FTO+/- ) in vivo and small interfering RNA (siRNA) in vitro, we observed attenuation of UUO and TGF-ß1-induced epithelial-mesenchymal transition (EMT), as evidenced by decreased fibronectin and N-cadherin accumulation and increased E-cadherin levels. Silencing FTO significantly improved UUO and TGF-ß1-induced inflammation, apoptosis, and inhibition of autophagy. Further transcriptomic assays identified RUNX1 as a downstream candidate target of FTO. Inhibiting FTO was shown to counteract UUO/TGF-ß1-induced RUNX1 elevation in vivo and in vitro. We demonstrated that FTO signaling contributes to the elevation of RUNX1 by demethylating RUNX1 mRNA and improving its stability. Finally, we revealed that the PI3K/AKT pathway may be activated downstream of the FTO/RUNX1 axis in the pathogenesis of renal fibrosis. In conclusion, identifying small-molecule compounds that target this axis could offer promising therapeutic strategies for treating renal fibrosis.

A multiomic study uncovers a bZIP23-PER1A-mediated detoxification pathway to enhance seed vigor in rice.

Seed vigor in crops is important in terms of improving grain quality and germplasm conservation; however, little is known about its regulatory mechanisms through the encoded proteome and gene network. Comparative analyses of transcriptome (RNA sequencing [RNA-seq]) and broadly targeted metabolic profiling of two subspecific rice cultivars with distinct seed vigor during accelerated aging revealed various biological pathways and metabolic processes as key influences explaining trait differences. RNA-seq coexpression regulatory network analyses identified several transcription factors, including bZIP23 and bZIP42, that act as nodes in the gene network. Importantly, transgenic seeds of overexpression of bZIP23 enhanced seed vigor, whereas its gene knockout reduced seed vigor, suggesting that the protein it encodes functions as a positive regulator. Similarly, overexpression and knockout of PER1A that encodes a key player in the detoxification pathway enhanced and decreased seed vigor, respectively. We further demonstrated a direct interaction of the PER1A promoter with bZIP23 in seeds, which activates the expression of PER1A, and the genetic evidence suggested that bZIP23 most likely functions in a common pathway with and acts upstream of PER1A to modulate seed vigor. In addition, the control of seed vigor by the bZIP23-PER1A module was connected with that of the abscisic acid signaling pathway. Collectively, we revealed the genetic architecture of variation in seed vigor and uncovered the bZIP23-PER1A-mediated detoxification pathway that enhances the trait in rice.

Lactococcus lactis HkyuLL 10 suppresses colorectal tumourigenesis and restores gut microbiota through its generated alpha-mannosidase.

OBJECTIVE: Probiotic Lactococcus lactis is known to confer health benefits to humans. Here, we aimed to investigate the role of L. lactis in colorectal cancer (CRC). DESIGN: L. lactis abundance was evaluated in patients with CRC (n=489) and healthy individuals (n=536). L. lactis was isolated from healthy human stools with verification by whole genome sequencing. The effect of L. lactis on CRC tumourigenesis was assessed in transgenic Apc Min/+ mice and carcinogen-induced CRC mice. Faecal microbiota was profiled by metagenomic sequencing. Candidate proteins were characterised by nano liquid chromatography-mass spectrometry. Biological function of L. lactis conditioned medium (HkyuLL 10-CM) and functional protein was studied in human CRC cells, patient-derived organoids and xenograft mice. RESULTS: Faecal L. lactis was depleted in patients with CRC. A new L. lactis strain was isolated from human stools and nomenclated as HkyuLL 10. HkyuLL 10 supplementation suppressed CRC tumourigenesis in Apc Min/+ mice, and this tumour-suppressing effect was confirmed in mice with carcinogen-induced CRC. Microbiota profiling revealed probiotic enrichment including Lactobacillus johnsonii in HkyuLL 10-treated mice. HkyuLL 10-CM significantly abrogated the growth of human CRC cells and patient-derived organoids. Such protective effect was attributed to HkyuLL 10-secreted proteins, and we identified that α-mannosidase was the functional protein. The antitumourigenic effect of α-mannosidase was demonstrated in human CRC cells and organoids, and its supplementation significantly reduced tumour growth in xenograft mice. CONCLUSION: HkyuLL 10 suppresses CRC tumourigenesis in mice through restoring gut microbiota and secreting functional protein α-mannosidase. HkyuLL 10 administration may serve as a prophylactic measure against CRC.

Achieving High Rate and Long Cycle Performance of Na2FePO4F Cathode Through Co-Modification of Ti Doping and Carbon Coating.

Layered Na2FePO4F (NFPF) cathode material has received widespread attention due to its green nontoxicity, abundant raw materials, and low cost. However, its poor inherent electronic conductivity and sluggish sodium ion transportation seriously impede its capacity delivery and cycling stability. In this work, NFPF by Ti doping and conformal carbon layer coating via solid-state reaction is modified. The results of experimental study and density functional theory calculations reveal that Ti doping enhances intrinsic conductivity, accelerates Na-ion transport, and generates more Na-ion storage sites, and pyrolytic carbon from polyvinylpyrrolidone (PVP) uniformly coated on the NFPF surface improves the surface/interface conductivity and suppresses the side reactions. Under the combined effect of Ti doping and carbon coating, the optimized NFPF (marked as 5T-NF@C) exhibits excellent electrochemical performance, with a high capacity of 108.4 mAh g-1 at 0.2C, a considerable capacity of 80.0 mAh g-1 even at high current density of 10C, and a high capacity retention rate of 81.8% after 2000 cycles at 10C. When assembled into a full cell with a hard carbon anode, 5T-NF@C also show good applicability. This work indicates that co-modification of Ti doping and carbon coating makes NFPF achieve high rate and long cycle performance for sodium-ion batteries.

Lidar AOD inversion and aerosol extinction profile correction method based on GA-BP neural network.

Lidar is an effective remote sensing method to obtain the vertical distribution of aerosols, and how to select the aerosol extinction-backscattering ratio (AE-BR) during the inversion process is a key step to guarantee the accuracy of the lidar inversion of aerosol optical thickness (AOD) and aerosol extinction coefficient profile (AECP). In this paper, an inversion algorithm for AOD and AECP based on a genetic BP (GA-BP) neural network is proposed. Simultaneous measurements are carried out using CE318 sun photometer and lidar, and the mapping relationship between the lidar echo signal and AOD is established based on the genetic BP (GA-BP) neural network method, which achieves the accurate inversion of AOD with an absolute error mean value of 0.0156. Based on the AOD output from the GA-BP neural network, the real-time best AE- BR to improve the inversion accuracy of AECP. Finally, practical tests show that the method achieves accurate inversion of AOD, determines the range of AE-BR from 20-50sr, realizes real-time dynamic correction of AECP, and has strong generalization ability and applicability in practical situations.

Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Common Subtypes of Small Renal Masses: A Multicenter Comparative Study.

BACKGROUND: Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension. PURPOSE: To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs. STUDY TYPE: Retrospective. POPULATION: 797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses. FIELD STRENGTH/SEQUENCES: 3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging. ASSESSMENT: Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions. STATISTICAL TESTS: Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05. RESULTS: The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993). CONCLUSION: The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

First Insight into Fetal Exposure to Legacy and Emerging Plasticizers Revealed by Infant Hair and Meconium: Occurrence, Biotransformation, and Accumulation.

Epidemiological studies have demonstrated the embryonic and developmental toxicity of plasticizers. Thus, understanding the in utero biotransformation and accumulation of plasticizers is essential to assessing their fate and potential toxicity in early life. In the present study, 311 infant hair samples and 271 paired meconium samples were collected at birth in Guangzhou, China, to characterize fetal exposure to legacy and emerging plasticizers and their metabolites. Results showed that most of the target plasticizers were detected in infant hair, with medians of 9.30, 27.6, and 0.145 ng/g for phthalate esters (PAEs), organic phosphate ester (OPEs), and alternative plasticizers (APs), and 1.44, 0.313, and 0.066 ng/g for the metabolites of PAEs, OPEs, and APs, respectively. Positive correlations between plasticizers and their corresponding primary metabolites, as well as correlations among the oxidative metabolites of bis(2-ethylhexyl) phthalate (DEHP) and 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH), were observed, indicating that infant hair retained the major phase-I metabolism of the target plasticizers. While no positive correlations were found in parent compounds or their primary metabolites between paired infant hair and meconium, significant positive correlations were observed among secondary oxidative metabolites of DEHP and DINCH in hair and meconium, suggesting that the primary metabolites in meconium come from hydrolysis of plasticizers in the fetus but most of the oxidative metabolites come from maternal-fetal transmission. The parent compound/metabolite ratios in infant hair showed a decreasing trend across pregnancy, suggesting in utero accumulation and deposition of plasticizers. To the best of our knowledge, this study is the first to report in utero exposure to both parent compounds and metabolites of plasticizers by using paired infant hair and meconium as noninvasive biomonitoring matrices and provides novel insights into the fetal biotransformation and accumulation of plasticizers across pregnancy.

Discovery of 3-hydroxymethyl-azetidine derivatives as potent polymerase theta inhibitors.

Inhibition of the low fidelity DNA polymerase Theta (Polθ) is emerging as an attractive, synthetic-lethal antitumor strategy in BRCA-deficient tumors. Here we report the AI-enabled development of 3-hydroxymethyl-azetidine derivatives as a novel class of Polθ inhibitors featuring central scaffolding rings. Structure-based drug design first identified A7 as a lead compound, which was further optimized to the more potent derivative B3 and the metabolically stable deuterated compound C1. C1 exhibited significant antiproliferative properties in DNA repair-compromised cells and demonstrated favorable pharmacokinetics, showcasing that 3-hydroxymethyl-azetidine is an effective bio-isostere of pyrrolidin-3-ol and emphasizing the potential of AI in medicinal chemistry for precise molecular modifications.

Discovery of novel MAT2A inhibitors by an allosteric site-compatible fragment growing approach.

The methionine adenosyltransferase MAT2A catalyzes the synthesis ofthe methyl donor S-adenosylmethionine (SAM) and thereby regulates critical aspects of metabolism and transcription. Aberrant MAT2A function can lead to metabolic and transcriptional reprogramming of cancer cells, and MAT2A has been shown to promote survival of MTAP-deficient tumors, a genetic alteration that occurs in âˆ¼ 13 % of all tumors. Thus, MAT2A holds great promise as a novel anticancer target. Here, we report a novel series of MAT2A inhibitors generated by a fragment growing approach from AZ-28, a low-molecular weight MAT2A inhibitor with promising pre-clinical properties. X-ray co-crystal structure revealed that compound 7 fully occupies the allosteric pocket of MAT2A as a single molecule mimicking MAT2B. By introducing additional backbone interactions and rigidifying the requisite linker extensions, we generated compound 8, which exhibited single digit nanomolar enzymatic and sub-micromolar cellular inhibitory potency for MAT2A.

Predictors and clinical outcomes of permanent pacemaker implantation after transcatheter aortic valve implantation.

OBJECTIVE: This study aimed to identify the incidence, risk factors, and outcomes of permanent pacemaker (PPM) implantation after transcatheter aortic valve implantation (TAVI) procedures. METHODS: A retrospective analysis was conducted on 70 patients who underwent TAVI at the Department of Cardiology, Fujian Provincial Hospital, from January 2018 to March 2022. Based on whether a new PPM was implanted after TAVI, all patients were divided into two groups: NEW PPM and NO PPM. Baseline characteristics and clinical data were compared between the two groups. Univariate analysis was used to analyze different variables between the two groups. A binary logistic regression analysis was used to evaluate independent correlates for PPM implantation after TAVI. RESULTS: The mean age of the 70 patients was 73.1 ± 8.8 years. The incidence of PPM implantation was 17.1%. Patients with diabetes and chronic kidney disease were more likely to require PPM (50% vs. 20.7%, p = 0.042, 25% vs. 5.2%, p = 0.042). Our study did not identify any significant differences in the incidence of electrocardiographic conduction disturbances except for the previous right bundle branch block (RBBB) (NO PPM 6.9% vs. NEW PPM 33.3%, p < 0.05). We found that prosthesis size, implantation depth, procedural duration, and length of hospital and intensive care unit (ICU) stays were comparable between the two groups. The leading independent predictors of PPM implantation were previous RBBB (odds ratio 10.129, p = 0.034). CONCLUSION: The previous RBBB was the leading independent predictor of PPM implantation. New PPM was not associated with significantly new-onset left BBB, extended post-procedure hospitalization, ICU stay, or procedural duration.

Discovery of macrocyclic CDK2/4/6 inhibitors with improved potency and DMPK properties through a highly efficient macrocyclic drug design platform.

Cyclin-dependent kinases (CDKs) are critical cell cycle regulators that are often overexpressed in tumors, making them promising targets for anti-cancer therapies. Despite substantial advancements in optimizing the selectivity and drug-like properties of CDK inhibitors, safety of multi-target inhibitors remains a significant challenge. Macrocyclization is a promising drug discovery strategy to improve the pharmacological properties of existing compounds. Here we report the development of a macrocyclization platform that enabled the highly efficient discovery of a novel, macrocyclic CDK2/4/6 inhibitor from an acyclic precursor (NUV422). Using dihedral angle scan and structure-based, computer-aided drug design to select an optimal ring-closing site and linker length for the macrocycle, we identified compound 8 as a potent new CDK2/4/6 inhibitor with optimized cellular potency and safety profile compared to NUV422. Our platform leverages both experimentally-solved as well as generative chemistry-derived macrocyclic structures and can be deployed to streamline the design of macrocyclic new drugs from acyclic starting compounds, yielding macrocyclic compounds with enhanced potency and improved drug-like properties.

Detecting lies through others' eyes: Children use perceptual access cues to evaluate listeners' beliefs about informants' deception.

Children are often third-party observers of conversations between informants and receivers. Although 5- and 6-year-olds can identify and reject informants' false testimony, it remains unclear whether they expect others to do the same. Accurately assessing others' impressions of informants and their testimony in a conversational setting is essential for children's navigation of the social world. Using a novel second-order lie detection task, the current study examined whether 4- to 7-year-olds (N = 74; Mage = 69 months) take receivers' epistemic states into account when predicting whether a receiver would think an informant is truthful or deceptive. We pitted children's firsthand observations of reality against informants' false testimony while manipulating receivers' perceptual access to a sticker-hiding event. Results showed that when the receiver had perceptual access and was knowledgeable, children predicted that the receiver would think the informant is lying. Critically, when the receiver lacked perceptual access and was ignorant, children were significantly more likely to predict that the receiver would think the informant is telling the truth. Second-order theory of mind and executive function strengthened this effect. Findings are interpreted using a dual-process framework and provide new insights into children's understanding of others' selective trust and susceptibility to deception.

Geriatric nutrition risk index in the prediction of all-cause and cardiovascular mortality in older adults with hyperlipidemia: NHANES 1999-2018.

BACKGROUND: Malnutrition is linked to a higher risk of unfavorable outcomes in various illnesses. The present investigation explored the correlation between inadequate nutritional condition and outcomes in older individuals diagnosed with hyperlipidemia. METHODS: The geriatric nutritional risk index (GNRI) was used to evaluate the nutritional status. All patients were divided into two groups according to GNRI. A Kaplan-Meier analysis was used to assess the survival rates of different groups at risk of malnutrition. In addition, GNRI was used in COX proportional risk regression models to evaluate its predictive effect on both overall mortality and cardiovascular mortality among patients with hyperlipidemia. Furthermore, the study employed restricted cubic splines (RCS) to examine the nonlinear correlation between GNRI and mortality. RESULTS: The study included 4,532 elderly individuals diagnosed with hyperlipidemia. During a median follow-up duration of 139 months, a total of 1498 deaths from all causes and 410 deaths from cardiovascular causes occurred. The Kaplan-Meier analysis demonstrated significantly poorer survival among individuals at risk of malnutrition, as indicated by the GNRI. In the malnutrition risk group, the modified COX proportional hazards model revealed that a decrease in GNRI was associated with a higher risk of all-cause mortality (HR=1.686, 95% CI 1.212-2.347) and cardiovascular mortality (HR=3.041, 95% CI 1.797-5.147). Furthermore, the restricted cubic splines revealed a non-linear association between GNRI and both all-cause mortality and cardiovascular mortality (p-value for non-linearity = 0.0039, p-value for non-linearity=0.0386). CONCLUSIONS: In older patients with hyperlipidemia, lower levels of GNRI are associated with mortality. The GNRI could potentially be used to predict all-cause mortality and cardiovascular mortality.

Facial recognition for disease diagnosis using a deep learning convolutional neural network: a systematic review and meta-analysis.

BACKGROUND: With the rapid advancement of deep learning network technology, the application of facial recognition technology in the medical field has received increasing attention. OBJECTIVE: This study aims to systematically review the literature of the past decade on facial recognition technology based on deep learning networks in the diagnosis of rare dysmorphic diseases and facial paralysis, among other conditions, to determine the effectiveness and applicability of this technology in disease identification. METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for literature search and retrieved relevant literature from multiple databases, including PubMed, on 31 December 2023. The search keywords included deep learning convolutional neural networks, facial recognition, and disease recognition. A total of 208 articles on facial recognition technology based on deep learning networks in disease diagnosis over the past 10 years were screened, and 22 articles were selected for analysis. The meta-analysis was conducted using Stata 14.0 software. RESULTS: The study collected 22 articles with a total sample size of 57 539 cases, of which 43 301 were samples with various diseases. The meta-analysis results indicated that the accuracy of deep learning in facial recognition for disease diagnosis was 91.0% [95% CI (87.0%, 95.0%)]. CONCLUSION: The study results suggested that facial recognition technology based on deep learning networks has high accuracy in disease diagnosis, providing a reference for further development and application of this technology.

Deep-learning reconstruction of complex dynamical networks from incomplete data.

Reconstructing complex networks and predicting the dynamics are particularly challenging in real-world applications because the available information and data are incomplete. We develop a unified collaborative deep-learning framework consisting of three modules: network inference, state estimation, and dynamical learning. The complete network structure is first inferred and the states of the unobserved nodes are estimated, based on which the dynamical learning module is activated to determine the dynamical evolution rules. An alternating parameter updating strategy is deployed to improve the inference and prediction accuracy. Our framework outperforms baseline methods for synthetic and empirical networks hosting a variety of dynamical processes. A reciprocity emerges between network inference and dynamical prediction: better inference of network structure improves the accuracy of dynamical prediction, and vice versa. We demonstrate the superior performance of our framework on an influenza dataset consisting of 37 US States and a PM2.5 dataset covering 184 cities in China.

Impact of excessive daytime sleepiness on attention impairment in obstructive sleep apnea: a cross-sectional observational study.

PURPOSE: This study aims to examine the relationship between excessive daytime sleepiness (EDS) and attention impairment in Chinese individuals with obstructive sleep apnea (OSA). METHODS: A total of 1996 OSA patients with an apnea-hypopnea index (AHI) of ≥ 5 events per hour were included in this study. EDS was measured using the Epworth Sleepiness Scale (ESS), while cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). RESULTS: OSA patients with EDS demonstrated higher body mass index (BMI), comorbidities of hypertension and diabetes, decreased N3 sleep, increased AHI and ODI, as well as lower minimum oxygen saturation. Despite no significant differences in total cognitive scores assessed by MMSE and MoCA, individuals with comorbid sleepiness exhibited more evident attention deficits in the subdomains of MoCA. Stratified analysis indicated that regardless of age, educational level was the primary factor influencing attention in the AHI < =20 group. In the AHI > 20 group, attention impairment in patients younger than 40 remained significantly associated with education level, whereas for individuals aged 40 and above, attention deficits were associated with education level, age, and daytime sleepiness. The interaction analysis indicated that OSA severity modulated the impact of sleepiness on attention in patients aged 40 and above. CONCLUSION: A significant correlation was observed between EDS and attention deficits in Chinese individuals diagnosed with OSA, with a particular emphasis on patients aged 40 and above. The severity of OSA modulates the impact of sleepiness on attention in patients aged 40 and above.

Outcomes of ankle arthrodesis in adult patients with ankle osteoarthritis in Kashin-Beck disease.

PURPOSE: We retrospectively evaluated the characteristics of these patients and the effectiveness of ankle arthrodesis in the treatment of ankle arthritis caused by Kashin-Beck disease (KBD). METHODS: A retrospective study of KBD patients with ankle osteoarthritis who underwent ankle arthrodesis between December 2012 and January 2022 was performed. A total of 46 patients were included. The general characteristics, clinical manifestations and imaging features of the patients were recorded and summarized. measured using the VAS score, and ankle function was assessed by the AOFAS ankle-hindfoot score. RESULTS: Multiple subchondral cystic changes were found in 42(91.3%) patients. The VAS scores for both resting and weight-bearing conditions were 6.28 ± 1.30 vs. 2.09 ± 1.12 (P < .001) and 6.87 ± 1.01 vs. 2.17 ± 0.98 (P < .001), respectively. The AOFAS scores were 59.17 ± 5.50 and 88.39 ± 1.42, respectively (P < .001). CONCLUSIONS: The subchondral multiple cystic transformation of the ankle KBD has a certain suggestive role.Arthrodesis is an effective method to reduce ankle pain and improve ankle function in KBD patients with ankle osteoarthritis.

Targeting Molecular Mechanisms of Obesity- and Type 2 Diabetes Mellitus-Induced Skeletal Muscle Atrophy with Nerve Growth Factor.

Skeletal muscle plays a critical role in metabolic diseases, such as obesity and type 2 diabetes mellitus (T2DM). Muscle atrophy, characterized by a decrease in muscle mass and function, occurs due to an imbalance between the rates of muscle protein synthesis and degradation. This study aimed to investigate the molecular mechanisms that lead to muscle atrophy in obese and T2DM mouse models. Additionally, the effect of nerve growth factor (NGF) on the protein synthesis and degradation pathways was examined. Male mice were divided into three groups: a control group that was fed a standard chow diet, and two experimental groups that were fed a Western diet. After 8 weeks, the diabetic group was injected with streptozotocin to induce T2DM. Each group was then further divided into NGF-treated or non-treated control group. In the gastrocnemius muscles of the Western diet group, increased expressions of myostatin, autophagy markers, and ubiquitin ligases were observed. Skeletal muscle tissue morphology indicated signs of muscle atrophy in both obese and diabetic mice. The NGF-treated group showed a prominent decrease in the protein levels of myostatin and autophagy markers. Furthermore, the NGF-treated group showed an increased Cyclin D1 level. Western diet-induced obesity and T2DM may be linked to muscle atrophy through upregulation of myostatin and subsequent increase in the ubiquitin and autophagy systems. Moreover, NGF treatment may improve muscle protein synthesis and cell cycling.