ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder affecting a substantial proportion of women of reproductive age. It is frequently associated with ovulatory dysfunction, infertility, and an increased risk of chronic metabolic diseases. A hallmark pathological feature of PCOS is the arrest of follicular development, closely linked to impaired intercellular communication between the oocyte and surrounding granulosa cells. Transzonal projections (TZPs) are specialized cytoplasmic extensions derived from granulosa cells that penetrate the zona pellucida to establish direct contact with the oocyte. These structures serve as essential conduits for the transfer of metabolites, signaling molecules (e.g., cAMP, cGMP), and regulatory factors (e.g., microRNAs, growth differentiation factors), thereby maintaining meiotic arrest, facilitating metabolic cooperation, and supporting gene expression regulation in the oocyte. The proper formation and maintenance of TZPs depend on the cytoskeletal integrity of granulosa cells and the regulated expression of key connexins, particularly CX37 and CX43. Recent studies have revealed that in PCOS, TZPs exhibit significant structural and functional abnormalities. Contributing factors—such as hyperandrogenism, insulin resistance, oxidative stress, chronic inflammation, and dysregulation of critical signaling pathways (including PI3K/Akt, Wnt/β‑catenin, and MAPK/ERK)—collectively impair TZP integrity and reduce their formation. This disruption in granulosa-oocyte communication compromises oocyte quality and contributes to follicular arrest and anovulation. This review provides a comprehensive overview of TZP biology, including their formation mechanisms, molecular composition, and stage-specific dynamics during folliculogenesis. We highlight the pathological alterations in TZPs observed in PCOS and elucidate how endocrine and metabolic disturbances—particularly androgen excess and hyperinsulinemia—downregulate CX43 expression and impair gap junction function, thereby exacerbating ovarian microenvironmental dysfunction. Furthermore, we explore emerging therapeutic strategies aimed at preserving or restoring TZP integrity. Anti-androgen therapies (e.g., spironolactone, flutamide), insulin sensitizers (e.g., metformin), and GLP-1 receptor agonists (e.g., liraglutide) have shown potential in modulating connexin expression and enhancing granulosa-oocyte communication. In addition, agents such as melatonin, AMPK activators, and GDF9/BMP15 analogs may promote TZP formation and improve oocyte competence. Advanced technologies, including ovarian organoid models and CRISPR-based gene editing, offer promising platforms for studying TZP regulation and developing targeted interventions. In summary, TZPs are indispensable for maintaining follicular homeostasis, and their disruption plays a pivotal role in the pathogenesis of PCOS-related folliculogenesis failure. Targeting TZP integrity represents a promising therapeutic avenue in PCOS management and warrants further mechanistic and translational investigation.

Sepsis is a condition characterized by organ dysfunction resulting from the systemic inflammatory response triggered by an infection. Excessive inflammation and immunosuppression are intertwined, and severe cases may even develop into multiple organ failure. Studies have shown that indoleamine 2,3-dioxygenase 1-mediated tryptophan metabolism is involved in the occurrence and development of sepsis, and elevated plasma kynurenine levels and Kyn/Trp ratios are early indicators of sepsis development. In this paper, we provide a comprehensive summary of the role of IDO1 in the acute inflammatory phase of sepsis, late immunosuppression, and organ damage. This includes its regulation of inflammatory state, immune cell function, blood pressure, and other aspects. Additionally, we analyze preclinical studies on targeted IDO1 drugs. An in-depth understanding and study of IDO may help to understand the pathogenesis and clinical significance of sepsis and multiple organ damage from a new perspective and provide new research ideas for exploring its prevention and treatment methods.

Twelve compounds were isolated from the ethyl acetate fraction of the 80% aqueous ethanol extract of the roots and stems of Dalbergia rimosa Roxb. by silica gel, MCI, Sephadex LH-20 column chromatography, and semi-preparative HPLC. Their structures were identified by spectral analysis such as UV, IR, MS, 1D/2D NMR and by comparison with literature information as dalbergiquinol A (1), dalbergiquinol B (2), R-(-)-3′-hydroxy-2,4,5-trimethoxydalbergiquinol (3), neokhriol A (4), mucronulatol (5), (3R)-7,2′,3′-trihydroxy-4′-methoxy-isoflavane (6), isomucronulatol (7), (3S)-violanone (8), 3′-O-methylviolanone (9), eryvarin M (10), (±)-α,3,4,2′,4′-pentahydroxydihydrochalcone (11) and (-)-butin (12). Compound 1 and 2 are new compounds, and compounds 3-12 were isolated from this plant for the first time. Compounds 1, 2, 4, 6, 8, 11, 12 showed good scavenging effect on DPPH free radical.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Mitophagy, a highly precise form of autophagy, plays a pivotal role in maintaining cellular homeostasis by selectively targeting and eliminating damaged mitochondria through a process known as mitophagy. Within this tightly regulated mechanism, dysfunctional mitochondria are specifically delivered to lysosomes for degradation. Disruptions in mitophagy have been implicated in a diverse range of pathological conditions, spanning diseases of the nervous system, cardiovascular system, cancer, aging, and metabolic syndrome. The elucidation of mitophagy’s impact on cardiovascular disorders, liver diseases, metabolic syndromes, immune dysfunctions, inflammatory conditions, and cancer has significantly advanced our understanding of the complex pathogenesis underlying these conditions. These studies have shed light on the intricate connections between dysfunctional mitophagy and disease progression. Among the disorders associated with mitochondrial dysfunction, insulin resistance (IR) stands out as a prominent condition linked to metabolic disorders. IR is characterized by a diminished response to normal levels of insulin, necessitating higher insulin levels to trigger a typical physiological reaction. Hyperinsulinemia and metabolic disturbances often coexist with IR, primarily due to defects in insulin signal transduction. Oxidative stress, stemming from mitochondrial dysfunction, exerts dual effects in the context of IR. Initially, it disrupts insulin signaling pathways and subtly contributes to the development of IR. Additionally, by inducing mitochondrial damage and autophagy, oxidative stress indirectly impedes insulin signaling pathways. Consequently, mitophagy acts as a protective mechanism, encapsulating damaged or dysfunctional mitochondria through the autophagy-lysosome pathway. This efficient process eliminates excessive oxidative stress reactive. The intricate interplay between mitochondrial function, oxidative stress, mitophagy, and IR represents a captivating field of investigation in the realm of metabolic disorders. By unraveling the underlying complexities and comprehending the intricate relationships between these intertwined processes, researchers strive toward uncovering novel therapeutic strategies. With a particular focus on mitochondrial quality control and the maintenance of redox homeostasis, these interventions hold tremendous potential in mitigating IR and enhancing overall metabolic health. Emerging evidence from a myriad of studies has shed light on the active involvement of mitophagy in the pathogenesis of metabolic disorders. Notably, interventions such as exercise, drug therapies, and natural products have been documented to induce mitophagy, thereby exerting beneficial effects on metabolic health through the activation of diverse signaling pathways. Several pivotal signaling molecules, including AMPK, PINK1/Parkin, BNIP3/Nix, and FUNDC1, have been identified as key regulators of mitophagy and have been implicated in the favorable outcomes observed in metabolic disorders. Of particular interest is the unique role of PINK1/Parkin in mitophagy compared to other proteins involved in this process. PINK1/Parkin exerts influence on mitophagy through the ubiquitination of outer mitochondrial membrane proteins. Conversely, BNIP3/Nix and FUNDC1 modulate mitophagy through their interaction with LC3, while also displaying certain interrelationships with each other. In this comprehensive review, our objective is to investigate the intricate interplay between mitophagy and IR, elucidating the relevant signaling pathways and exploring the treatment strategies that have garnered attention in recent years. By assimilating and integrating these findings, we aim to establish a comprehensive understanding of the multifaceted roles and intricate mechanisms by which mitophagy influences IR. This endeavor, in turn, seeks to provide novel insights and serve as a catalyst for further research in the pursuit of innovative treatments targeting IR.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

AIM To study the extraction process,enzymatic properties and practical application of glucuronic hydrolase in Scutellaria baicalensis stems and leaves(sbsl GUS).METHODS With granularity,water consumption,extraction time and extraction frequency as influencing factors,enzymatic activity as an evaluation index,the extraction process was optimized by orthogonal test on the basis of single factor test.The relationship between substrate(baicalin)concentration and enzymolysis rate,after which Vmax and Km were calculated,the effects of pH value,temperature and metal ion on enzymatic activity were investigated,pH stability and heat stability were evaluated.sbsl GUS was adotped in the enzymolysis of baicalin to prepare baicalein,then the effects of pH value,temperature,reaction time,initial substrate concentration and enzyme addition on transfer rate were investigated.RESULTS The optimal extraction process was determined to be 40 mesh for granularity,10 times for water consumption,15 min for extraction time,and 3 times for extraction frequency.The enzymolysis accorded with the kinetics of enzymatic reaction,Km was 0.006 3 mol/L,Vmax was 70.42 μmol/h,the strongest enzymatic activity was found at the pH value of 6.0,temperature of 45℃and metal ion of 100 mmol/L Cu2+,sbsl GUS demonstrated good stability at the ranges of 4.0-7.0 for pH value and 4-30℃for temperature.The optimal preparation process was determined to be 6.0 for pH value,45℃for temperature,more than 12 h for reaction time,67.2 mmol/L for initial substrate concentration,and 1 mL/0.269 mmol baicalin for enzyme addition,the transfer rate was 97.83%.CONCLUSION sbsl GUS enzymolysis exhibits high efficiency and mild condition,which can provide a simple preparation method for obtaining baicalein,and expand the application path of Scutellaria baicalensis stems and leaves.

Objective To analyze the atrioventricular synchronization rate after implantation of Micra AV leadless pacemaker,and the impact of postoperative programming optimization on atrioventricular synchronization rate.Methods A prospective cohort study was conducted to select patients with complete atrioventricular block who underwent Micra AV leadless pacemaker implantation at Beijing Anzhen Hospital from August 2022 to June 2023.Programming optimization were performed at 1 week,1 month,and 3 months postoperatively,and atrioventricular synchronization rate,electrical parameters,and echocardiography were recorded.Results A total of 68 patients with complete atrioventricular block implanted with Micra AV were selected,with an average age of(68.2±9.7)years,including 47 males(69.1％).All patients were successfully implanted with Micra AV,and there were no serious postoperative complications;The average threshold,sense,and impedance parameters were stable during 1 week,1 month,and 3 months after the procedure;There was no significant difference in the EF value of postoperative echocardiography(P=0.162);The average atrioventricular synchronization rates at 1 week,1 month,and 3 months postoperatively were(75.2％vs.83.8％vs.91.6％,P=0.001).Conclusions As an mechanical atrial sensing,Micra AV requires personalized adjustment of relevant parameters;Postoperative follow-up programming optimization plays an important role in the atrioventricular synchronization and comfort level in patients with complete atrioventricular block after implantation of Micra AV leadless pacemaker.