Objective To elucidate the molecular mechanism of sirtuin-3 (SIRT3) in regulating mitochondrial biogenesis in human renal tubular epithelial cells. Methods Cells were stimulated with different concentrations of H₂O₂ and divided into four groups: control (NC), 50 μmol/L H₂O₂, 110 μmol/L H₂O₂ and 150 μmol/L H₂O₂. SIRT3 protein expression was then measured. SIRT3 was knocked down with siRNA, and cells were further assigned to five groups: control (NC), negative-control siRNA (NCsi), SIRT3-siRNA (siSIRT3), NCsi+H₂O₂, and siSIRT3+H₂O₂. After 24 h, cellular adenosine triphosphate (ATP) and mitochondrial superoxide anion (O₂•⁻) levels were determined, together with mitochondrial expression of SIRT3, peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), nuclear respiratory factor 1 (NRF1), mitochondrial transcription factor A (TFAM), superoxide dismutase 2 (SOD2), acetylated-SOD2 and adenosine monophosphate activated protein kinase α1 (AMPKα1). Results The 110 and 150 μmol/L H₂O₂ decreased SIRT3 protein (both P<0.05). ATP and mitochondrial O₂•⁻ did not differ between NC and NCsi groups (both P>0.05). Compared to the NCsi group, the siSIRT3 group exhibited elevated O₂•⁻ level, decreased SIRT3 protein and increased expression levels of SOD2 and acetylated SOD2 protein (all P<0.05). Compared to the NCsi group, the NCsi+H₂O₂ group exhibited decreased cellular ATP levels, elevated mitochondrial O₂•⁻ levels, and reduced protein expression levels of SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 (all P<0.05). Compared with the siSIRT3 group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 protein expression levels and a decrease in acetylated SOD2 protein expression levels (all P<0.05). Compared with the NCsi+H₂O₂ group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, AMPKα1, PGC-1α and NRF1, TFAM protein expression levels, and an increase in SOD2 and acetylated SOD2 protein expression levels (all P<0.05). Conclusions SIRT3 promotes mitochondrial biogenesis in tubular epithelial cells via the AMPK/PGC-1α/NRF1/TFAM axis, representing a key mechanism through which SIRT3 ameliorates oxidative stress-induced mitochondrial dysfunction.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Objective A scoping review was conducted on relevant studies regarding the use of non-invasive brain-computer interface(BCI)technology to promote the rehabilitation of upper limb function in stroke patients,aiming to provide new ideas and references for the rehabilitation nursing of stroke patients.Methods Relevant studies on non-invasive BCI in upper limb functional rehabilitation of stroke patients were searched through computer system including Chinese biomedical literature database,Wanfang database,CNKI,VIP database,Cochrane Library,PubMed,Embase and Web of Science.The search period was from the establishment of the database to December 6,2024,and the included literature was sorted and analyzed.Results A total of 23 articles were included,involving 1 235 stroke patients.Non-invasive brain-computer interface technology mainly includes brain-computer interface based on motion imagination combined with virtual reality technology,functional electrical stimulation and exoskeleton robot.The main evaluation indexes were Fugl-Meyer upper extremity partial scale,modified Barthel index,event related desynchronization intensity,upper limb motor function rating scale,etc.Non-invasive brain-computer interface technology can improve upper limb function,self-care ability and stimulation of cerebral cortex in stroke patients.Conclusion Non-invasive brain-computer interface technology is feasible and effective in upper limb functional rehabilitation training of stroke patients,but there are few relevant studies.In the future,a new era multidisciplinary rehabilitation model can be built,and scientific and practical evaluation indicators were formulated to promote rapid rehabilitation of stroke patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective To analyze the relationship between frailty and acute kidney injury(AKI)after hip fracture surgery in the elderly.Methods A total of 405 elderly patients who underwent hip fracture surgery in Jieyang People's Hospital from August 2021 to January 2023 were retrospectively analysed.According to the modified frailty index(mFI),they were divided into frail group(mFI≥0.27,n=112)and non-frail group(mFI<0.27,n=293).Postoperative AKI was defined according to the Kidney Disease:Improving Global Outcomes(KDIGO)criteria.After 1:1 propensity score matching(PSM),100 cases in each group were successfully matched.Univariable and multivariable logistic regression models,propensity score adjustment,PSM,inverse probability of treatment weighting(IPTW),standardized mortality ratio weighting(SMRW),pairwise algorithm(PA)weighting,and overlap weighting(OW)methods were used to analyze the relationship between frailty and postoperative AKI.Stratified analyses were performed according to age(≥80 or<80 years),gender,whether angiotensin-converting enzyme inhibitors(ACEI)/angiotensin Ⅱreceptor antagonists(ARB)were used,and whether intraoperative hypotension occurred.Results After PSM,there were no significant differences between the two groups in age,sex,surgical type,ACEI/ARB,blood urea nitrogen,serum creatinine,intraoperative blood loss,and intraoperative hypotension[standardized mean difference(SMD)<0.1].In both the original cohort and the matched cohort,the incidence of AKI was higher in frail group than in non-frail group(25.9%vs.8.9%,P<0.001;28.0%vs.11.0%,P=0.002).Analysis of the risk of postoperative AKI in elderly hip fracture patients in frail group found that compared with the non-frail group,in the univariate logistic regression model the odds ratio(OR)and a 95%confidence interval(CI)for the frail group was 3.59(2.00-6.43),P<0.001,and in the multivariable logistic regression model,the OR(95%CI)for frail group was 3.04(1.55-5.95),P=0.001.After adjustment for propensity score,the OR(95%CI)for frail group was 2.85(1.52-5.34),P=0.001,and the OR(95%CI)for frail group after PSM was 3.15(1.47-6.75),P=0.003.After IPTW,SMRW,PA weighting,and OW,the OR(95%CI)for frail group were 2.48(1.37-4.50),2.43(1.41-4.19),2.63(1.25-5.54),and 2.69(1.07-6.78),respectively,with P<0.05.The interaction tests were not statistically significant for age,sex,use of ACEI/ARB,and intraoperative hypotension(P>0.05).Conclusion In elderly patients with hip fractures,preoperative frailty may be a risk factor for postoperative AKI.

Objective This study aimed to provide an effective scientific basis for prevention and control of cockroaches on aircrafts by identifying cockroach-carried pathogens,and assess the insecticidal efficacy of gel bait mediated cockroach control on aircrafts,to provide technical guidance for aircraft disinsection.Methods Cassette-trapping was used to trap cockroaches,and the carried pathogens were detected using bacterial cultivation techniques.The gel bait mediated killing rate was calculated after 1,7,and 30 d by field application of gel bait.Results A total of 411 cockroaches were captured,and all were identified as Blattella germanica.26 strains of pathogenic bacteria were isolated from the trapped cockroaches.The killing rates of cockroaches were 58.8％-96.3％with 1-30 day application of gel bait.Statistically significant differences were observed in cockroach killing rates on different days(χ2=58.95,P<0.01).Conclusions B.germanica carry a large variety of pathogenic bacteria and opportunistic pathogens and are thus important infectious disease carriers.Gel bait agents have proven to be very effective against cockroaches on aircrafts.

Objective To investigate the density,species composition,and seasonal prevalence of domestic rodents in different habitats within Lanzhou garrisons,providing basic information for rodent prevention and control.Methods A total of 12 monitoring sites were sampled across urban,suburban,and rural residential areas from 2014 to 2022.Rodent density was monitored using the night-trapping method in the middle of odd-numbered months.Results From 2014 to 2022,346 domestic rodents were captured using 122 035 effective traps,with an average domestic rodent density of 0.28％.The highest domestic rodent density was 0.63％in 2016,and the lowest was 0.07％in 2020,showing significant differences across years,with an overall trend of initially decreasing and then increasing(χ2=136.555,P<0.001).The dominant species was Rattus norvegicus,accounting for 83.24％of the total rodents captured.Rattus norvegicus accounted for a relatively high proportion across different years,with a statistically significant difference in species composition(χ2=20.931,P<0.05).Rodent densities and species composition also varied significantly among the monitored habitats(P<0.001),with the highest densities observed in rural residential areas and the lowest in urban areas.Seasonal variation in rodent densities showed a bimodal pattern,with smaller peaks in January or March and a larger peak in July.Conclusions Domestic rodent density in Lanzhou garrisons has shown an upward trend in the past few years.Rodent control measures should focus on barracks in rural residential areas,with targeted interventions to reduce the risk of rodent-borne diseases.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.