ObjectiveTo investigate the disruptive effects of perinatal exposure to the environmental endocrine disruptor bisphenol AF (BPAF) on hepatic lipid metabolism in prepubertal (postnatal day 21, PND21) male offspring rats, and to provide scientific evidence for assessing the obesogenic effect of BPAF. MethodsSprague-Dawley (SD) rats aged 8 weeks were used in this study. Pregnant rats were divided into BPAF dose groups (2, 10, 50 mg·kg⁻¹) and a vehicle control group (corn oil), with 6 confirmed pregnant females per group. Gavage administration started from gestational day 0 and continued until the end of lactation. At PND21, one male offspring per litter was randomly selected. Serum concentrations of glucose (GLU), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), leptin (LEP), free fatty acid (FFA), as well as oxidative stress markers superoxide dismutase (SOD) and malondialdehyde (MDA), were measured. Pathological changes in liver and adipose tissues were evaluated, and the expression levels of genes related to hepatic lipid metabolism were measured. ResultsCompared to the vehicle control group, the 50 mg·kg⁻¹ group showed significantly increased serum LEP and MDA levels in male offspring (P<0.05), and significant upregulation of hepatic lipoprotein lipase (Lpl), fatty acid synthetase (Fas), and peroxisome proliferator-activated receptor γ (Pparg) gene expression (P<0.05). The 2 mg·kg⁻¹ group exhibited a significant increase in adipocyte length (P<0.05), while the 50 mg·kg⁻¹ group showed significant increases in both adipocyte area and length (P<0.05). No significant abnormalities were observed in liver histopathological examination. ConclusionPerinatal exposure to 50 mg·kg⁻¹ BPAF induced adipocyte hypertrophy, elevated leptin levels, upregulation of lipid synthesis gene expression, and enhanced oxidative stress in prepubertal male offspring, suggesting that BPAF may exert environmental obesogenic effects by disrupting lipid metabolism pathways.

Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective To investigate the correlation between gut microbiota characteristics and immunotherapy efficacy in patients with advanced microsatellite stable (MSS) advanced gastrointestinal tumors. Methods Thirty patients with advanced MSS gastrointestinal tumors, including fourteen cases of gastric cancer and sixteen cases of colorectal cancer, who were admitted from November 1, 2022, to July 31, 2025 were enrolled. All patients underwent gut microbiota testing and received corresponding interventions on the basis of the results, followed by treatment with antiangiogenic agents combined with immunotherapy. Some patients additionally received probiotics or fecal microbiota transplantation. The primary endpoints were disease control rate (DCR) and objective response rate (ORR). The secondary endpoints were progression-free survival (PFS) and overall survival (OS). Univariate and multivariate Cox regression analyses were used to assess potential prognostic factors. Results Among the thirty patients, no complete response was observed. Two cases of partial response (PR), twelve cases of stable disease, and sixteen cases of progressive disease were recorded. The ORR was 6.7%, and the DCR was 46.7%. The median PFS was 6.4 months, and the median OS was 8.3 months. Both PR patients were classified as having a medium risk of gut microbiota dysbiosis and exhibited a Bacteroides-dominated enterotype. Multivariate analysis indicated that tumor type, liver metastasis, and bone metastasis were potential prognostic factors for PFS and OS. Conclusion Patients with a medium risk of gut dysbiosis may exhibit a relatively favorable response to immunotherapy, suggesting that gut microbiota status could serve as a potential biomarker for predicting treatment efficacy in advanced MSS gastrointestinal tumors.

The development status of the key technologies of first-aid robotics was introduced in autonomous system,embo-died intelligence,digital twins,large artificial intelligence model and autonomous unmanned medical treatment.The present situation in first-aid robotics equipment was reviewed for first-aid diagnosis,treatment,assistance and transportation.The development trends of the key technology and equipment of first-aid robotics were analyzed.It was pointed out the involve-ment of big model-based embodied intelligence technology and digital twins technology in first aid might provide new pers-pectives for the application and advancement of specialized first-aid robotics.[Chinese Medical Equipment Journal,2025,46(3):96-114]

Objective:To explore the factors associated with the efficacy of high-frequency repetitive transcranial magnetic stimulation (rTMS) in the treatment of neuropathic pain (NP) following spinal cord injury (SCI).Methods:This was a retrospective study of 89 SCI survivors with NP receiving high-frequency rTMS. Those with a ≥30% reduction in their Numeric Rating Scales (NRS) scores after 2 weeks of treatment were termed Responders ( n=36), with the others classified as non-responders ( n=53). Demographic data (gender, education level, age), SCI characteristics (injury etiology, injury severity, neurological injury level, injury duration), NP characteristics (pain type, pain intensity, analgesic use), functional assessment (Modified Ashworth Scale score, Spinal Cord Independence Measure score, Modified Barthel Index score, American Spinal Injury Association motor/sensory score) were collected. Least absolute shrinkage and selection operator (LASSO) regression was used for variable selection, followed by binary logistic regression to identify factors associated with treatment efficacy. Results:Among the 89 patients, 36 (40.4%) were Responders to high-frequency rTMS. Binary logistic regression revealed that those with a cervical spinal cord injury and/or spasticity and women were more likely to respond to high-frequency rTMS.Conclusions:Female gender, cervical spinal cord injury, and spasticity are independent factors predicting rTMS efficacy in treating SCI, with spasticity demonstrating the strongest association.

Objective:To investigate the application of the conjugate gradient (CG) algorithm to treatment plan optimization for intensity-modulated brachytherapy (IMBT).Methods:The general Monte Carlo software TOPAS was utilized to simulate the 192Ir source of IMBT, and the unit dose contribution matrix was calculated. An objective function was established using the weighted least squares method and was solved using the CG algorithm to achieve optimized IMBT treatment plans. The optimization was validated using five clinical cervical cancer cases under modulation width 60°. The dose distributions of IMBT treatment plans under 45°, 60°, 90°, 120°, and 180° modulation widths were compared using the Wilcoxon test to determine the optimal IMBT treatment plan for cervical cancer treatment. Results:The CG algorithm successfully optimized IMBT treatment plans under modulation width 60° for five cases within 22.2 s on average. On the premise of sufficient target dose coverage, the average D2 cm 3 values of the bladder and rectum in IMBT treatment plans were 3.66 and 1.97 Gy, respectively, representing reductions of 0.54 and 0.69 Gy compared to traditional brachytherapy plans. For the five modulation widths, the D90% values of all IMBT treatment plans reached 6 Gy, without statistically significant differences ( P > 0.05). The average D2 cm 3 values of the bladder in IMBT treatment plans were significantly lower than those in the traditional brachytherapy plans( P<0.05), with modulation width 60° associated with the greatest reduction of 0.61 Gy. In contrast, the average D2 cm 3 values of the rectum under 45°, 60°, and 90° modulation widths decreased by 0.63, 0.54, and 0.45 Gy, respectively, compared to traditional plans, with statistically significant differences( P<0.05). Conclusions:The CG method enables rapid achievement of optimized IMBT treatment plans that meet clinical requirements, and modulation width 60° contributes to valid dosimetric optimization. This study can serve as a guide for the clinical implementation of IMBT.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.