Objective To evaluate the effectiveness of schistosomiasis surveillance in Jiangsu Province during the stage moving from transmission control to transmission interruption, and to analyze the current risk and challenges, so as to provide the evidence for achieving the target of schistosomiasis elimination. Methods Schistosomiasis surveillance data were collected from Jiangsu Province from 2012 to 2024, and the endemic areas, Schistosoma japonicum infections in humans and livestock, Oncomelania hupensis snail distribution and implementation of integrated interventions were descriptively analyzed. In addition, the trends in areas with snails, seroprevalence of human S. japonicum infections and numbers of advanced schistosomiasis cases were assessed using a Joinpoint regression model. Results The endemic areas of schistosomiasis continued to shrink in Jiangsu Province from 2012 to 2024, with the number of schistosomiasis-eliminated counties (cities, districts) increasing from 53 (75.71%) to 63 (96.92%), and interruption of schistosomiasis transmission was achieved across the province. A total of 4 600 300 person-times were tested for serum antibodies against S. japonicum, with 28 719 person-times positive detected; and 616 500 person-times were tested S. japonicum infections among local residents in Jiangsu Province from 2012 to 2024, with only 3 egg-positives detected, and no egg-positives found since 2017. A total of 187 600 herd-times were tested for schistosomiasis in livestock, and no S. japonicum infections were found. O. hupensis snail survey was performed covering 1 018 408.97 hm², and a total of 35 556.35 hm² was found with snail-infested habitats, including 174.40 hm2 of emerging snail-infested habitats. A total of 1 102 800 O. hupensis snails were identified for S. japonicum infections, and no infections were found. The areas of snail-infested habitats appeared a tendency towards a rise in Jiangsu Province from 2019 to 2023 (APC = 23.67%, P < 0.05), and the actual areas of snail-infested habitats appeared a tendency towards a decline from 2012 to 2015 (APC = −22.77%, P < 0.05), and towards a rise from 2015 to 2023 (APC = 9.76%, P < 0.01). The seroprevalence of anti-S. japonicum antibodies appeared a tendency towards a decline among residents in Jiangsu Province from 2017 to 2023 (APC = −14.92%, P < 0.01). In addition, the number of newly diagnosed advanced schistosomiasis cases appeared a tendency towards a decline from 2012 to 2024 (APC = −12.02%, P < 0.01), and the numbers of advanced schistosomiasis patients requiring treatment showed a tendency towards a decline from 2012 to 2021 (APC = −10.56%, P < 0.01) and from 2021 to 2023 (APC = −20.06%, P < 0.01). Conclusions Great progresses had been achieved in schistosomiasis control in Jiangsu Province following transmission control, and transmission interruption had been achieved; however, there are still snail-infested habitats. High-intensity surveillance and integrated control are required to be maintained to advance the achievement of the target of schistosomiasis elimination in Jiangsu Province.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

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.

Purpose To assess the utility of echocardiographic parameters in predicting adverse cardiovascular in patients with connective tissue disease.Materials and Methods A retrospective analysis was conducted on the clinical and echocardiographic records of patients with connective tissue disease from the Affiliated Hospital of Inner Mongolia Medical University(June 1st,2020 to June 1st,2023)who had complete medical data and at least twelve months of follow-up.Variables were screened based on univariate analysis,combined with clinical expertise and XGBoost feature weight analysis;this information was used to construct a Cox proportional hazards regression model designed to predict composite endpoint events of adverse cardiovascular outcomes.Internal validation was performed using the Bootstrap resampling method,and the model's performance was evaluated.Results The study included 123 participants.The incidence of positive events reached 39.02%(48/123).Mitral valve early diastolic annular velocity(reflecting left heart function)(HR=0.79,P=0.041)and tricuspid annular plane systolic excursion(reflecting right heart function)(HR=0.92,P=0.044)emerged as significant predictors for adverse cardiovascular outcomes.Compared with the clinical model,the model combined with left heart function parameters showed significant improvements in both risk classification and absolute accuracy for short-term and medium-term adverse prognosis(NRI365=0.054,IDI365=0.060,NRI730=0.064,IDI730=0.079,all P<0.05)and optimized risk classification for long-term adverse prognosis(NRI1 095=0.256,P<0.05).In contrast,the model combined with right heart function parameters improved risk classification at all time points(NRI365=0.054,NRI730=0.000,NRI1 095=0.135,all P<0.05).Conclusion Mitral valve early diastolic annular velocity and tricuspid annular plane systolic excursion,which reflect cardiac function,are factors for predicting adverse cardiovascular outcomes among individuals diagnosed with connective tissue disease.Multi-parameter combined models incorporating echocardiographic variables can provide incremental predictive value compared with clinical models.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.

The construction of an information system for equipment budget management in public hospitals is an important measure to strengthen comprehensive budget management, serving as an important foundation for promoting the development of clinical disciplines and enhancing operational management. Since September 2023, a tertiary public hospital had explored the construction of equipment budget management informatization. This practice had established a supporting budget management information system, which included an equipment demand reserve library and a general use product library, linked performance evaluation indicators, implemented visualizing real-time project progress, and strengthened data governance. A series of measures had been taken to move management to equipment demand research, expand the time window for departments to fill in budget requirements, simplify the department application process, and achieve a closed-loop management of the entire chain of department equipment demand research, budget approval, and execution, ensuring the rationality and accuracy of the budget. By the end of 2024, the budget management information system had covered 87 departments and included 30 000 sets of equipment applications, providing detailed data support and critical management references for demand departments, equipment management departments, and hospital decision-makers, while improving the quality and efficiency of in-hospital equipment management. This practice could provide references for other public hospitals in China to optimize their equipment budget management.

Objective Piperazine derivatives are a group of emerging psychoactive substances with excitatory and hallucinogenic effects on the central nervous system.This study established a high-performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)screening method for the detection of 40 piperazine compounds in urine.Methods A 200 μL urine sample(spiked with an internal standard at 1 ng/mL)was subjected to liquid-liquid extraction with ethyl acetate.After nitrogen evaporation,the residue was redissolved in 200 μL methanol and injected for analysis.Separation was performed on a Waters Acquity UPLC? HSS T3 column(100 mm × 2.1 mm,1.8 μm).The mobile phase consisted of(A)20 mmol/L ammonium acetate buffer containing 0.1％formic acid and 5％acetonitrile,and(B)acetonitrile.Gradient elution was applied,and detection was carried out in multiple reaction monitoring(MRM)mode.Quantification was achieved using an internal standard calibration curve.Results The 40 piperazine substances demonstrated good linearity within the range of 1-50 ng/mL,with correlation coefficients of 0.995-0.998.The extraction recovery ranged from 51.51％to 104.1％.Intra-day precision was below 5％,while inter-day precision ranged from 1.61％to 10.17％.Accuracy was between-7.84％and 8.77％.The limits of detection were 0.2-1 ng/mL,and the limit of quantification was 1 ng/mL.Conclusion The proposed method requires only a small sample volume,exhibits high sensitivity,selectivity,and stability,and offers short run times.It is suitable for the qualitative and quantitative determination of piperazine derivatives in urine in forensic toxicology practice.

Purpose To assess the utility of echocardiographic parameters in predicting adverse cardiovascular in patients with connective tissue disease.Materials and Methods A retrospective analysis was conducted on the clinical and echocardiographic records of patients with connective tissue disease from the Affiliated Hospital of Inner Mongolia Medical University(June 1st,2020 to June 1st,2023)who had complete medical data and at least twelve months of follow-up.Variables were screened based on univariate analysis,combined with clinical expertise and XGBoost feature weight analysis;this information was used to construct a Cox proportional hazards regression model designed to predict composite endpoint events of adverse cardiovascular outcomes.Internal validation was performed using the Bootstrap resampling method,and the model's performance was evaluated.Results The study included 123 participants.The incidence of positive events reached 39.02%(48/123).Mitral valve early diastolic annular velocity(reflecting left heart function)(HR=0.79,P=0.041)and tricuspid annular plane systolic excursion(reflecting right heart function)(HR=0.92,P=0.044)emerged as significant predictors for adverse cardiovascular outcomes.Compared with the clinical model,the model combined with left heart function parameters showed significant improvements in both risk classification and absolute accuracy for short-term and medium-term adverse prognosis(NRI365=0.054,IDI365=0.060,NRI730=0.064,IDI730=0.079,all P<0.05)and optimized risk classification for long-term adverse prognosis(NRI1 095=0.256,P<0.05).In contrast,the model combined with right heart function parameters improved risk classification at all time points(NRI365=0.054,NRI730=0.000,NRI1 095=0.135,all P<0.05).Conclusion Mitral valve early diastolic annular velocity and tricuspid annular plane systolic excursion,which reflect cardiac function,are factors for predicting adverse cardiovascular outcomes among individuals diagnosed with connective tissue disease.Multi-parameter combined models incorporating echocardiographic variables can provide incremental predictive value compared with clinical models.