Identification and validation of a novel Parkinson-Glioma feature gene signature in glioma and Parkinson's disease.

Introduction: The prognosis for glioma is generally poor, and the 5-year survival rate for patients with this disease has not shown significant improvement over the past few decades. Parkinson's disease (PD) is a prevalent movement disorder, ranking as the second most common neurodegenerative disease after Alzheimer's disease. Although Parkinson's disease and glioma are distinct diseases, they may share certain underlying biological pathways that contribute to their development. Objective: This study aims to investigate the involvement of genes associated with Parkinson's disease in the development and prognosis of glioma. Methods: We obtained datasets from the TCGA, CGGA, and GEO databases, which included RNA sequencing data and clinical information of glioma and Parkinson's patients. Eight machine learning algorithms were used to identify Parkinson-Glioma feature genes (PGFGs). PGFGs associated with glioma prognosis were identified through univariate Cox analysis. A risk signature was constructed based on PGFGs using Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) method. We subsequently validated its predictive ability using various methods, including ROC curves, calibration curves, KM survival analysis, C-index, DCA, independent prognostic analysis, and stratified analysis. To validate the reproducibility of the results, similar work was performed on three external test datasets. Additionally, a meta-analysis was employed to observe the heterogeneity and consistency of the signature across different datasets. We also compared the differences in genomic variations, functional enrichment, immune infiltration, and drug sensitivity analysis based on risk scores. This exploration aimed to uncover potential mechanisms of glioma occurrence and prognosis. Results: We identified 30 PGFGs, of which 25 were found to be significantly associated with glioma survival. The prognostic signature, consisting of 19 genes, demonstrated excellent predictive performance for 1-, 2-, and 3-year overall survival (OS) of glioma. The signature emerged as an independent prognostic factor for glioma overall survival (OS), surpassing the predictive performance of traditional clinical variables. Notably, we observed differences in the tumor microenvironment (TME), levels of immune cell infiltration, immune gene expression, and drug resistance analysis among distinct risk groups. These findings may have significant implications for the clinical treatment of glioma patients. Conclusion: The expression of genes related to Parkinson's disease is closely associated with the immune status and prognosis of glioma patients, potentially regulating glioma pathogenesis through multiple mechanisms. The interaction between genes associated with Parkinson's disease and the immune system during glioma development provides novel insights into the molecular mechanisms and targeted therapies for glioma.

PCSK9 aggravated carotid artery stenosis in ApoE-/- mice by promoting the expression of tissue factors in endothelial cells via the TLR4/NF-κB pathway.

Atherosclerosis, a chronic inflammatory disease, is the most relevant cause of carotid artery stenosis. Vascular endothelial cells (ECs) play a significant role in the development of atherosclerosis. In this chronic inflammatory environment, we aimed to investigate whether PCSK9 could mitigate atherosclerosis progression by reducing tissue factor expression in ECs via in vivo and in vitro assays. In vivo, we investigated the effect of PCSK9 inhibition on preventing atherosclerotic lesion formation in ApoE-/- mice fed a western diet. The results showed that inhibiting PCSK9 could significantly downregulate the protein expression of tissue factor (TF) in ECs to reduce the area of atherosclerotic plaques. In vitro, we incubated human umbilical vein endothelial cells (HUVECs) with lipopolysaccharide (LPS). We found that LPS-induced TF elevation was suppressed by a PCSK9 inhibitor at both the mRNA and protein levels and that the TLR4/NF-κB pathway was also suppressed by a PCSK9 inhibitor. With respect to plasma samples from patients with carotid artery stenosis, we also demonstrated that the expression of TF was positively correlated with that of PCSK9. Thus, in addition to regulating lipid metabolism, the regulation of endothelial cell TF expression through the TLR4/NF-κB pathway may be a potential mechanism of PCSK9 in promoting atherosclerotic carotid stenosis.

Flexible calorimetric flow sensor with unprecedented sensitivity and directional resolution for multiple flight parameter detection.

The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s-1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

FGF7 enhances the expression of ACE2 in human islet organoids aggravating SARS-CoV-2 infection.

The angiotensin-converting enzyme 2 (ACE2) is a primary cell surface viral binding receptor for SARS-CoV-2, so finding new regulatory molecules to modulate ACE2 expression levels is a promising strategy against COVID-19. In the current study, we utilized islet organoids derived from human embryonic stem cells (hESCs), animal models and COVID-19 patients to discover that fibroblast growth factor 7 (FGF7) enhances ACE2 expression within the islets, facilitating SARS-CoV-2 infection and resulting in impaired insulin secretion. Using hESC-derived islet organoids, we demonstrated that FGF7 interacts with FGF receptor 2 (FGFR2) and FGFR1 to upregulate ACE2 expression predominantly in ß cells. This upregulation increases both insulin secretion and susceptibility of ß cells to SARS-CoV-2 infection. Inhibiting FGFR counteracts the FGF7-induced ACE2 upregulation, subsequently reducing viral infection and replication in the islets. Furthermore, retrospective clinical data revealed that diabetic patients with severe COVID-19 symptoms exhibited elevated serum FGF7 levels compared to those with mild symptoms. Finally, animal experiments indicated that SARS-CoV-2 infection increased pancreatic FGF7 levels, resulting in a reduction of insulin concentrations in situ. Taken together, our research offers a potential regulatory strategy for ACE2 by controlling FGF7, thereby protecting islets from SARS-CoV-2 infection and preventing the progression of diabetes in the context of COVID-19.

Architecture of integrated solid-state zinc-ion battery based on sodium alginate gelation.

How to construct a new electrode/electrolyte interface structure in solid-state batteries (SSBs), enhance interface stability, and improve the cycling performance of SSBs is a great challenge for the development of SSBs. Here, an all-in-one "interface-free" structure was developed. This interfacial structure constructs a full-interface hydrogen bonding network through the abundant hydrogen bond donors and acceptors in the cathode and electrolyte to enhance the interfacial stability and avoid interfacial failure during charging and discharging, and generates cathode-electrolyte interface (CEI) in-situ to effectively regulate zinc ion transport. Square cells assembled in this structure are stabilized for 100 cycles at a current density of 0.1 mA cm-2. This integrated electrode provides a new idea for the long stable cycle of SSBs.

Identification and clinical validation of the role of anoikis-related genes in diabetic foot.

This study aims to investigate the role of anoikis-related genes in diabetic foot (DF) by utilizing bioinformatics analysis to identify key genes associated with anoikis in DF. We selected the GEO datasets GSE7014, GSE80178 and GSE68183 for the extraction and analysis of differentially expressed anoikis-related genes (DE-ARGs). GO analysis and KEGG analysis indicated that DE-ARGs in DF were primarily enriched in apoptosis, positive regulation of MAPK cascade, anoikis, focal adhesion and the PI3K-Akt signalling pathway. Based on the LASSO and SVM-RFE algorithms, we identified six characteristic genes. ROC curve analysis revealed that these six characteristic genes had an area under the curve (AUC) greater than 0.7, indicating good diagnostic efficacy. Expression analysis in the validation set revealed downregulation of CALR in DF, consistent with the training set results. GSEA results demonstrated that CALR was mainly enriched in blood vessel morphogenesis, endothelial cell migration, ECM-receptor interaction and focal adhesion. The HPA database revealed that CALR was moderately enriched in endothelial cells, and CALR was found to interact with 63 protein-coding genes. Functional analysis with DAVID suggested that CALR and associated genes were enriched in the phagosome component. CALR shows promise as a potential marker for the development and treatment of DF.

Bayesian Optimization of Environmentally Sustainable Graphene Inks Produced by Wet Jet Milling.

Liquid phase exfoliation (LPE) of graphene is a potentially scalable method to produce conductive graphene inks for printed electronic applications. Among LPE methods, wet jet milling (WJM) is an emerging approach that uses high-speed, turbulent flow to exfoliate graphene nanoplatelets from graphite in a continuous flow manner. Unlike prior WJM work based on toxic, high-boiling-point solvents such as n-methyl-2-pyrollidone (NMP), this study uses the environmentally friendly solvent ethanol and the polymer stabilizer ethyl cellulose (EC). Bayesian optimization and iterative batch sampling are employed to guide the exploration of the experimental phase space (namely, concentrations of graphite and EC in ethanol) in order to identify the Pareto frontier that simultaneously optimizes three performance criteria (graphene yield, conversion rate, and film conductivity). This data-driven strategy identifies vastly different optimal WJM conditions compared to literature precedent, including an optimal loading of 15 wt% graphite in ethanol compared to 1 wt% graphite in NMP. These WJM conditions provide superlative graphene production rates of 3.2 g hr-1 with the resulting graphene nanoplatelets being suitable for screen-printed micro-supercapacitors. Finally, life cycle assessment reveals that ethanol-based WJM graphene exfoliation presents distinct environmental sustainability advantages for greenhouse gas emissions, fossil fuel consumption, and toxicity.

Highly Efficient Monolithic Perovskite/Perovskite/Silicon Triple-Junction Solar Cells.

Wide-bandgap metal halide perovskites have demonstrated promise in multijunction photovoltaic (PV) cells. However, photoinduced phase segregation and the resultant low open-circuit voltage (Voc) have greatly limited the PV performance of perovskite-based multijunction devices. Here, a alloying strategy is reported to achieve uniform distribution of triple cations and halides in wide-bandgap perovskites by doping Rb+ and Cl- with small ionic radii, which effectively suppresses halide phase segregation while promoting the homogenization of surface potential. Based on this strategy, a Voc of 1.33 V is obtained from single-junction perovskite solar cells, and a VOC approaching 3.0 V and a power conversion efficiency of 25.0% (obtained from reverse scan direction, certified efficiency: 24.19%) on an 1.04 cm2 photoactive area can be achieved in a perovskite/perovskite/c-Si triple-junction tandem cell, where the certification efficiency is by far the greatest performance of perovskite-based triple-junction tandem solar cells. This work overcomes the performance deadlock of perovskite-based triple-junction tandem cells by setting a materials-by-design paradigm.

Aneurysmal Subarachnoid Hemorrhage and Sex Differences: Analysis of Epidemiology, Outcomes, and Risk Factors.

BACKGROUND: The differences in outcomes after aneurysmal subarachnoid hemorrhage (aSAH) between the sexes have not been concretely determined. This study aimed to evaluate the differences in epidemiology, outcomes, and risk factors between male and female patients with aSAH. METHODS: We performed a multicenter, retrospective study of patients with aSAH from 2017 to 2020. We investigated the epidemiological differences between the two sexes. Propensity score matching (PSM) was used to compare short-term outcomes between the sexes. Binary logarithmic regression was performed to investigate the odds ratio (OR) for dependent survival in patients of different sexes. RESULTS: A total of 5,407 consecutive patients with aSAH were included in this study, and the female-to-male ratio was 1.8:1. The peak incidence of aSAH occurred in the 6th and 7th decades in males and females, respectively. There were more female patients with internal carotid artery or posterior communicating artery aneurysms (53.2%), and there were more male patients with anterior cerebral artery or anterior communicating artery aneurysms (43.2%). The incidence of multiple aneurysms was greater in female patients (21.5% vs. 14.2%, P < 0.001). There was no significant difference in outcomes before and after PSM at discharge. The dependent survival risk was related only to the clinical condition on admission in women. In addition, age > 50 years (OR 1.88, 95% confidence interval 1.17-3.02; P = 0.01) and hypertension (OR 1.81, 95% confidence interval 1.25-2.61; P = 0.002) were also risk factors for male patients. CONCLUSIONS: There were more female patients with aneurysms than male patients in this study. Most aneurysm locations were different between the two groups. There was no significant difference in discharge outcomes before and after PSM. The risk factors for dependent survival were different between female and male patients.

Risk Factors and Location of Intracranial Aneurysm Rupture in a Consecutive Chinese Han Population.

OBJECTIVE: The aim of the present study was to retrospectively analyze and investigate the clinical data of 704 cases of ruptured intracranial aneurysms (RIAs) and unruptured intracranial aneurysms (UIAs). The risk factors predicting aneurysm rupture were explored from the perspective of the clinical characteristics of intracranial aneurysm (IA). METHODS: The clinical data of 704 patients with RIAs (494 patients) and UIAs (210 patients) admitted to the Department of Neurosurgery of Tianjin Medical University General Hospital and Tianjin Fifth Central Hospital between January 2016 and May 2022 were analyzed. A detailed analysis of sex, age, history, personal history, drug intake, and site of aneurysm occurrence was performed. Age was analyzed in segments and strata, and parameters with significant differences in the preliminary analysis results were analyzed by logistic regression to predict factors associated with the risk of aneurysm rupture. RESULTS: Among 494 patients with RIA (70.2%) and 210 patients with UIA (29.8%), the logistic regression showed that IA location appeared to be the most significant factor associated with RIA (OR, 95% CI: internal carotid artery (ICA), reference; anterior communicating artery,27.864,12.548-61.878; posterior communicating artery,12.408,6.658-23.124; anterior cerebral artery,5.804,2.333-14.440; middle cerebral artery,9.284,4.599-18.744; posterior circulation arteries, 4.224,2.011-8.871). Age was not a significant factor associated with RIA in the model and Hyperlipidemia (OR: 0.365; 95% CI: 0.171-0.779), Atherosclerosis (OR: 0.277; 95% CI: 0.172-0.446) and Multiple aneurysms (OR: 0.275; 95% CI: 0.177-0.425) patients were less likely to have RIA.IA location and age were the best predictors of RIA using the model. CONCLUSIONS: The present findings indicated that hyperlipidemia and atherosclerosis have a protective effect on aneurysm rupture, and different anatomical sites of IA may be risk factors for the occurrence of IA rupture. Among the anatomical sites of IA, the anterior communicating artery and posterior communicating artery have a higher fracture risk.

Risk factors of rupture and mortality for intracranial aneurysms associated with moyamoya disease: a multicenter retrospective study.

OBJECTIVE: The aim of this study was to analyze the risk factors for aSAH and subsequent death in patients with MMD. METHODS: Chinese Multi-Center Cerebral Aneurysm Database (CMAD) is a multicenter study registered in China. From 2016 to 2021, 181 patients with MMD in CMAD. Logistic regression analysis was used to identify risk factors for intracranial aneurysm rupture. Univariate and multivariate Cox regression were used to risk factors associated with ruptured intracranial aneurysm patients with MMD follow-up events (death). Cumulative survival was described using the Kaplan‒Meier technique. RESULTS: Of 11,686 IA patients, 181 (1.5%) had MMD. In the study, 158 patients with MMD were enrolled. There were 53 ruptured aneurysms and 105 unruptured aneurysms. In multivariate analysis, age (≥ 60 years OR 2.350 [1.008-5.478]), location (middle cerebral artery OR5.431 [1.347-21.889]; posterior circulation arteries OR 3.189 [1.110-9.163]) and aneurysm size (≥ 5 mm OR 2.855 [1.274-6.397], P = 0.011) were associated with intracranial aneurysm rupture in patients with MMD. In the 2-year follow-up time of aSAH patients, 44% (22/50) had favorable outcomes, 14% (7/50) had unfavorable outcomes and 42% (21/50) had death. Hypertension (HR 6.643 [1.620-27.244], P = 0.009) and Hunt-Hess grade (H&H grade IV HR 14.852 [3.151-70.011], P = 0.001; H&H grade V HR 17.697 [3.046-102.842], P = 0.001) were associated with increased mortality. In contrast, both ST (HR 0.168 [0.031-0.921], P = 0.04) and ET (HR 0.289 [0.087-0.957], P = 0.042) achieved good results. CONCLUSIONS: This study showed that the proportion of MMD in IA patients was approximately 1.5% (181/11686). For patients with cerebral ischemia on admission, revascularization may prevent the rupture of intracranial aneurysms. Age ≥ 60 years, location, and aneurysm size ≥ 5 mm were associated with IA rupture. Further analysis showed that being located in the middle cerebral artery was the most relevant risk factor for rupture. Patients with ruptured IA who underwent ST or ET had better clinical outcomes and survival than those who underwent CT; however, hypertension and poor initial Hunt-Hess grade were independent predictors of death.

A Versatile Hydrogel with Antibacterial and Sequential Drug-Releasing Capability for the Programmable Healing of Infectious Keratitis.

Hydrogels have attracted tremendous attention as favorable corneal substitutes for treating severe infectious keratitis (IK). However, current hydrogel-based corneal substitutes were majorly designed to promote the single stage of corneal regeneration, which falls short in meeting the clinical management needs of severe IK including the multiple phases of corneal wound healing. Herein, we introduce a versatile hybrid hydrogel (SQPV) composed of silk fibroin and chitosan, which exhibits spatiotemporal properties for drug release. The SQPV is fabricated by incorporating verteporfin-loaded poly(lactic-co-glycolic)-polyethylene glycol-o-nitrobenzene micelles into a hydrogel network, which is formed from methacrylate silk fibroin and glycidyl methacrylate functionalized quaternized chitosan containing polydeoxyribonucleotide. This double network approach results in a material with exceptional anti-inflammatory, antibacterial, and proliferative stimulation and tissue remodeling regulation capabilities. Furthermore, SQPV showcases mechanical strength and transparency akin to those of native cornea. Extensive in vitro and in vivo studies validate SQPV's ability to effectively eliminate residual bacteria, mitigate inflammation, foster regeneration of corneal epithelium and stroma, prevent corneal scarring, and ultimately expedite wound healing. In summary, the SF/CS-based hybrid hydrogel may represent a promising substitute for comprehensive corneal repair and regeneration in severe IK.

Fully neuroendoscopic resection of cerebellopontine angle tumors through a retrosigmoid approach: a retrospective single-center study.

The objective of this study is to preliminarily investigate the surgical safety, efficacy, techniques, and clinical value of fully neuroendoscopic surgery for the resection of cerebellopontine angle (CPA) tumors via a retrosigmoid approach. The clinical data of 47 cerebellopontine angle area (CPA) tumors that were treated by full neuroendoscopic surgery from June 2014 to June 2023 were retrospectively analyzed. The efficacy and advantages of the surgical techniques were evaluated based on indicators such as duration of the surgery, neuroendoscopic techniques, intraoperative integrity of nerves and blood vessels, extent of tumor resection, outcomes or postoperative symptoms, and incidence of complications. The 47 cases of cerebellopontine angle tumors include 34 cases of epidermoid cysts, 7 cases of vestibular schwannomas, and 6 cases of meningiomas. All patients underwent fully neuroendoscopic surgery. Twenty tumors were removed using the one-surgeon two-hands technique, and 27 tumors were removed using the two-surgeons four-hands technique. The anatomical integrity of the affected cranial nerves was preserved in all 47 cases. None of the patients suffered a postoperative hemorrhage, cerebrospinal fluid leak, and aseptic or septic meningitis, or died. The rate of total tumor resection was 72.3% (34/47), and the symptom improvement rate was 89.4% (42/47). All patients were followed up for 2 to 12 months, and none died nor showed any signs of tumor recurrence. By analyzing 47 fully neuroendoscopic resections of CPA tumors using the posterior sigmoid sinus approach in our center, we believe that such method allows complete, safe, and effective resection of CPA tumors and is thereby worthy of clinical promotion.

Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning.

A bottleneck in high-throughput nanomaterials discovery is the pace at which new materials can be structurally characterized. Although current machine learning (ML) methods show promise for the automated processing of electron diffraction patterns (DPs), they fail in high-throughput experiments where DPs are collected from crystals with random orientations. Inspired by the human decision-making process, a framework for automated crystal system classification from DPs with arbitrary orientations was developed. A convolutional neural network was trained using evidential deep learning, and the predictive uncertainties were quantified and leveraged to fuse multiview predictions. Using vector map representations of DPs, the framework achieves a testing accuracy of 0.94 in the examples considered, is robust to noise, and retains remarkable accuracy using experimental data. This work highlights the ability of ML to be used to accelerate experimental high-throughput materials data analytics.

The survival and outcome of older patients with primary aneurysmal subarachnoid haemorrhage: a 2-year follow-up, multi-centre, observational study.

BACKGROUND AND PURPOSE: The management of older aneurysmal subarachnoid haemorrhage (aSAH) cases is a clinical challenge. This study aimed to analyse the survival and functional outcomes in older aSAH patients (age ≥ 70 years) to provide evidence for making treatment decisions for such patients. METHODS: We performed a 2-year follow-up analysis of the Chinese Multi-Centre Cerebral Aneurysm Database for older patients suffering from aSAH from 2017 to 2020. A survival analysis was used to investigate the mean survival and hazard ratios for death. Binary logarithmic regression was performed to investigate the odds ratio for independent survival and dependent survival. RESULTS: A total of 1,136 consecutive older patients with aSAH were assessed in this study, and 944 patients (83.1%) were followed up. The overall mean survival was 37.79 ± 1.04 months. A total of 380 (40.25%) patients died within 2 years after aSAH. In survival analysis, the predictors of mortality were older age, intracerebral haemorrhage (ICH) history, Hunt-Hess (H-H) grade, World Federation of Neurosurgical Societies (WFNS) grade and operative treatment decreased the risk of mortality compared to conservative treatment. In binary logarithmic regression, the predictors of dependent survival were hypertension, diabetes, WFNS grade. CONCLUSIONS: The risk for 2-year mortality after aSAH increases markedly with older age, ICH history, H-H grade and WFNS grade. Risk factors for 2-year dependent survival were associated with hypertension, diabetes and WFNS grade in older patients with aSAH. Operative treatment markedly decreased mortality but did not significantly decrease the morbidity of dependent survival compared to conservative treatment.

Association between composite lifestyle factors and cardiometabolic multimorbidity in Chongqing, China: A cross-sectional exploratory study in people over 45 years and older.

Introduction: Modifiable lifestyle factors are considered key to the control of cardiometabolic diseases. This study aimed to explore the association between multiple lifestyle factors and cardiometabolic multimorbidity. Methods: A total of 14,968 participants were included in this cross-sectional exploratory study (mean age 54.33 years, range 45-91; 49.6% male). Pearson's Chi-square test, logistic regression, and latent class analysis were employed. Results: We found that men with 4-5 high-risk lifestyle factors had a 2.54-fold higher risk (95% CI: 1.60-4.04) of developing multimorbidity compared to males with zero high-risk lifestyle factors. In an analysis of dietary behavior, we found that in women compared to men, over-eating (OR = 1.94, P < 0.001) and intra-meal water drinking (OR = 2.15, P < 0.001) were more likely to contribute to the development of cardiometabolic multimorbidity. In an analysis of taste preferences, men may be more sensitive to the effect of taste preferences and cardiometabolic multimorbidity risk, particularly for smoky (OR = 1.71, P < 0.001), hot (OR = 1.62, P < 0.001), and spicy (OR = 1.38, P < 0.001) tastes. Furthermore, "smoking and physical activity" and "physical activity and alcohol consumption" were men's most common high-risk lifestyle patterns. "Physical activity and dietary intake" were women's most common high-risk lifestyle patterns. A total of four common high-risk dietary behavior patterns were found in both males and females. Conclusions: This research reveals that the likelihood of cardiometabolic multimorbidity increases as high-risk lifestyle factors accumulate. Taste preferences and unhealthy dietary behaviors were found to be associated with an increased risk of developing cardiometabolic multimorbidity and this association differed between genders. Several common lifestyle and dietary behavior patterns suggest that patients with cardiometabolic multimorbidity may achieve better health outcomes if those with certain high-risk lifestyle patterns are identified and managed.

Ketogenic Diet Combined with Moderate Aerobic Exercise Training Ameliorates White Adipose Tissue Mass, Serum Biomarkers, and Hepatic Lipid Metabolism in High-Fat Diet-Induced Obese Mice.

Obesity is a serious public health issue worldwide. Growing evidence demonstrates the efficacy of the ketogenic diet (KD) for weight loss, but there may be some adverse side effects such as dyslipidemia and hepatic steatosis. Aerobic exercise is a widely recognized approach for improving these metabolic markers. Here we explored the combined impacts of KD and moderate aerobic exercise for an 8-week intervention on body weight and fat loss, serum biomarkers, and hepatic lipid metabolism in a mouse model of high-fat diet-induced obesity. Both KD and KD combined with exercise significantly reduced body weight and fat mass. No significant adverse effects of KD were observed in serum biomarkers or hepatic lipid storage, except for an increase in circulating triglyceride level. However, aerobic exercise lowered serum triglyceride levels, and further ameliorated serum parameters, and hepatic steatosis in KD-fed mice. Moreover, gene and protein expression analysis indicated that KD combined with exercise was associated with increased expression of lipolysis-related genes and protein levels, and reduced expression of lipogenic genes relative to KD without exercise. Overall, our findings for mice indicate that further work on humans might reveal that KD combined with moderate aerobic exercise could be a promising therapeutic strategy for obesity.

Identification of RNA N6-methyladenosine regulation in epilepsy: Significance of the cell death mode, glycometabolism, and drug reactivity.

Epilepsy, a functional disease caused by abnormal discharge of neurons, has attracted the attention of neurologists due to its complex characteristics. N6-methyladenosine (m6A) is a reversible mRNA modification that plays essential role in various biological processes. Nevertheless, no previous study has systematically evaluated the role of m6A regulators in epilepsy. Here, using gene expression screening in the Gene Expression Omnibus GSE143272, we identified seven significant m6A regulator genes in epileptic and non-epileptic patients. The random forest (RF) model was applied to the screening, and seven m6A regulators (HNRNPC, WATP, RBM15, YTHDC1, YTHDC2, CBLL1, and RBMX) were selected as the candidate genes for predicting the risk of epilepsy. A nomogram model was then established based on the seven-candidate m6A regulators. Decision curve analysis preliminarily showed that patients with epilepsy could benefit from the nomogram model. The consensus clustering method was performed to divide patients with epilepsy into two m6A patterns (clusterA and clusterB) based on the selected significant m6A regulators. Principal component analysis algorithms were constructed to calculate the m6A score for each sample to quantify the m6A patterns. Patients in clusterB had higher m6A scores than those in clusterA. Furthermore, the patients in each cluster had unique immune cell components and different cell death patterns. Meanwhile, based on the M6A classification, a correlation between epilepsy and glucose metabolism was laterally verified. In conclusion, the m6A regulation pattern plays a vital role in the pathogenesis of epilepsy. The research on m6A regulatory factors will play a key role in guiding the immune-related treatment, drug selection, and identification of metabolism conditions and mechanisms of epilepsy in the future.

Uncertainty-aware mixed-variable machine learning for materials design.

Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods. Bayesian optimization (BO) employs uncertainty-aware machine learning models to select promising designs to evaluate, hence reducing the cost. However, BO with mixed numerical and categorical variables, which is of particular interest in materials design, has not been well studied. In this work, we survey frequentist and Bayesian approaches to uncertainty quantification of machine learning with mixed variables. We then conduct a systematic comparative study of their performances in BO using a popular representative model from each group, the random forest-based Lolo model (frequentist) and the latent variable Gaussian process model (Bayesian). We examine the efficacy of the two models in the optimization of mathematical functions, as well as properties of structural and functional materials, where we observe performance differences as related to problem dimensionality and complexity. By investigating the machine learning models' predictive and uncertainty estimation capabilities, we provide interpretations of the observed performance differences. Our results provide practical guidance on choosing between frequentist and Bayesian uncertainty-aware machine learning models for mixed-variable BO in materials design.