Peripheral neurotoxicity represents one of the most severe dose-limiting adverse reactions associated with oxaliplatin， with genetic polymorphisms playing a significant role in oxaliplatin-induced peripheral neuropathy （OIPN）. OIPN can be categorized as acute or chronic based on onset timing. The former presents clinically as sensory abnormalities or even motor disorders， while the latter presents clinically as limb sensory disorders that persist， numbness or pain in the hands and feet. The transporter genes OCT2， OCTN2， and NHE1 may be implicated in OIPN； drug-metabolizing enzyme gene GSTP1 Ile105Val， DPYD rs1801265， voltage-gated sodium channel （NaV） gene SCN4A rs2302237， SCN9A rs6746030， SCN10A rs12632942， and other associated genes such as HLA-G rs1610696， rs371194629 and CCNH rs2230641， rs3093816 are associated with severe OIPN. Conversely， DNA repair-related gene XRCC1 rs23885， NaV gene SCN9A rs3750904， rs12478318 and rs6754031 are associated with reduced OIPN risk. In the future， the genetic research findings on OIPN can be translated into clinical applications， ultimately achieving individualized precision medicine for patients.

ObjectiveTo characterize the quality differences among different germplasm and introduced varieties of Bupleurum scorzonerifolium roots（BSR）， and explore the underlying molecular mechanisms， providing a basis for high-quality production and quality control. MethodsWild BSR from Yulin（YLW） served as the quality reference， we conducted comparative analysis among YLW， locally domesticated wild germplasm in Yulin（YLC3）， Daqing germplasm introduced and cultivated in Yulin（YLDQC3）， and locally cultivated germplasm in Daqing（DQC3）. A combination of traditional pharmacognostic methods and modern multi-omics analyses was employed， including macroscopic traits（appearance， odor）， microscopic features（proportions of cork， phloem， xylem）， cell wall component contents（hemicellulose， cellulose， lignin）， carbohydrate contents（starch， water-soluble polysaccharides）， marker compound contents（ethanol-soluble extracts， total saponins， liposoluble extracts， and saikosaponins A， B₂， C， D）， metabolomics， and transcriptomics， in order to systematically characterize quality differences and investigate molecular mechanisms among these samples. ResultsMacroscopically， Yulin-produced BSR（YLW， YLC3， YLDQC3） exhibited significantly greater weight， length， and upper and middle diameters than Daqing-produced BSR（DQC3）. Odor-wise， YLW and YLC3 had a a fragrance taste， YLDQC3 had a rancid oil odor， and DQC3 had a sweet and fragrant taste. Microscopically， Yulin germplasm（YLW， YLC3） and Daqing germplasm（YLDQC3， DQC3） shared similar structural features， respectively. However， Yulin germplasm showed significantly higher proportions of cork and phloem， as well as stronger xylem vessel staining intensity compared to Daqing germplasm. Regarding various component contents， Yulin germplasm contained significantly higher levels of ethanol-soluble extracts， total saponins， and saikosaponins A， B₂， C， D， while Daqing germplasm had significantly higher levels of hemicellulose， starch， and liposoluble extracts. After introduction to Yulin， the Daqing germplasm（YLDQC3） showed increased starch， water-soluble polysaccharides and liposoluble extracts contents， decreased cell wall component content， but no significant difference in other component contents. Metabolomics revealed that saponins and terpenes accumulated significantly in Yulin germplasm， while alcohols and aldehydes accumulated predominantly in Daqing germplasm. Transcriptomics indicated similar gene expression patterns within the same germplasm but specificity between different germplasms. Integrative metabolomic-transcriptomic analysis identified 145 potential key genes associated with the saikosaponin biosynthesis pathway， including one acetyl-coenzyme A（CoA） acetyltransferase gene（ACAT）， one 3-hydroxy-3-methylglutaryl-coenzyme A synthase gene（HMGS）， two hydroxymethylglutaryl-CoA（HMG-CoA） reductase genes（HMG）， one phosphomevalonate kinase gene（PMK）， one 1-deoxy-D-xylose-5-phosphate synthase gene（CLA）， one hydroxymethylbuten-1-aldol synthase gene（HDR）， two farnesyl pyrophosphate synthase genes（FPPS）， one squalene synthase gene（SQS）， one β-amyrin synthase gene（BAS）， 102 cytochrome P450（CYP450） gene family members， and 32 uridine diphosphate-glucuronosyltransferase（UGT） gene family members. ConclusionAmong the three cultivated types， YLC3 most closely resembles YLW in appearance， microscopic features， contents of major bioactive constituents， metabolomic and transcriptomic profiles. Yulin germplasm exhibits superior saponin synthesis capability compared to Daqing germplasm， and Yulin region is more suitable for the growth of B. scorzonerifolium. Based on these findings， it is recommended that artificial cultivation in northern Shaanxi and similar regions utilize the local Yulin germplasm source cultivated for at least three years.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

A unified consensus statement on medication-related osteonecrosis of the jaw (MRONJ) has not yet been established among the Asian member countries or regions of the Asian Federation of Osteoporosis Societies (AFOS). This study aimed to develop a consensus on MRONJ in patients with osteoporosis across these countries and regions. In this study, the term “Asia-Pacific” refers specifically to the Asian member countries and regions of AFOS. A structured survey consisting of nine MRONJ-related questions was distributed across 10 countries and regions to assess the level of agreement and summarize regional perspectives. In addition, a manual literature review and voting were conducted to evaluate the current evidence on MRONJ. The key aspects of MRONJ, including definition, staging, diagnosis, pathogenesis, risk factors, management, and prevention, were generally consistent among the AFOS countries and regions. The annual incidence and incidence rate of MRONJ associated with low-dose antiresorptive therapy in patients with osteoporosis ranged from 0.025% to 0.136% and 21 to 283 cases per 100,000 person-years, respectively. However, evidence regarding the benefits of drug discontinuation before dental surgery, such as tooth extraction, remains insufficient. Large-scale, multinational studies across AFOS countries and regions are warranted to determine the incidence of MRONJ better and evaluate the impact of antiresorptive drug discontinuation before dental procedures. These findings may contribute to the devel opment of effective evidence-based strategies for preventing MRONJ in patients with osteoporosis.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Background: In acute and chronic renal inflammatory diseases, the activation of inflammatory cells is involved in the defect of erythropoietin (EPO) production. Ras guanine nucleotide-releasing protein-4 (RasGRP4) promotes renal inflammatory injury in type 2 diabetes mellitus (T2DM). Our study aimed to investigate the role and mechanism of RasGRP4 in the production of renal EPO in diabetes. Methods: The degree of tissue injury was observed by pathological staining. Inflammatory cell infiltration was analyzed by immunohistochemical staining. Serum EPO levels were detected by enzyme-linked immunosorbent assay, and EPO production and renal interstitial fibrosis were analyzed by immunofluorescence. Quantitative real-time polymerase chain reaction and Western blotting were used to detect the expression of key inflammatory factors and the activation of signaling pathways. In vitro, the interaction between peripheral blood mononuclear cells (PBMCs) and C3H10T1/2 cells was investigated via cell coculture experiments. Results: RasGRP4 decreased the expression of hypoxia-inducible factor 2-alpha (HIF2A) via the ubiquitination–proteasome degradation pathway and promoted myofibroblastic transformation by activating critical inflammatory pathways, consequently reducing the production of EPO in T2DM mice. Conclusion RasGRP4 participates in the production of renal EPO in diabetic mice by affecting the secretion of proinflammatory cytokines in PBMCs, degrading HIF2A, and promoting the myofibroblastic transformation of C3H10T1/2 cells.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To evaluate the effectiveness for the construction of the "mosquito-free village" in Jinzishan Village, Fuling District, Chongqing Municipality, so as to provide references for improving mosquito control practices in hilly and mountainous rural areas. Methods: The "mosquito-free village" initiative in Fuling District was launched in April 2023. Mosquito density monitoring was conducted annually from April to October. Larval mosquito density was monitored using the path method and scoop-catch method, and adult mosquito density was monitored using human-baited landing catch. One hundred and fifty-two villagers were randomly conducted before the "mosquito-free village" construction (April 2023) and one hundred and sixty-seven villagers were randomly conducted after the construction (November 2024). Knowledge awareness rate and correct behavioral practices regarding mosquito control among villagers were assessed. The satisfaction among villagers were evaluated in November 2024. The effectiveness of the initiative was evaluated based on mosquito density data, health education outcomes from 2023 to 2024, and satisfaction. Results: The average larval mosquitoes path index in Jinshanzi Village decreased from 1.50 spots/km in 2023 to 0.07 spots/km in 2024 (P<0.05). The average sampling spoon index of larval mosquitoes decreased from 3.43% in 2023 to 0 in 2024. The average landing rate index of adult mosquitoes decreased from 3.90 mosquitoes/(person·time) in 2023 to 0.38 mosquitoes/(person·time) in 2024 (P<0.05). The awareness rate of mosquito control knowledge and the formation rate of correct behaviors among villagers increased from 59.87% and 57.24% in 2023 to 92.22% and 90.42% in 2024, respectively (both P<0.05). In 2024, the satisfaction of villagers was 92.81%. Conclusion The mosquito density, health education effectiveness, and satisfaction of villagers in Jinzishan Village have all met the evaluation criteria for a "mosquito-free village", providing a replicable model for promotion in hilly and mountainous rural areas.