Objective: To analyze changes in tuberculosis infection among junior high school students before and after tuberculosis exposure, so as to provide a reference for improving school tuberculosis prevention and control measures and policy formulation. Methods: Retrospectively collect data on a tuberculosis outbreak that occurred in a grade of a junior high school in Chongqing in 2025, including tuberculosis screening records of students in this grade upon their enrollment in 2022 (1 156 students) and after two tuberculosis outbreaks in 2023 (206 students) and 2025 (171 students). The Wilcoxon signed rank test for paired design was used to compare the induration diameters of the subjects, and the Chi square test was adopted to analyze the rate of tuberculosis infection among students. Results: In the tuberculosis outbreak in 2023, the rate of tuberculosis infection among close contacts ( 11.84 %) and the rate of tuberculosis infection among freshrman at school enrollment (12.89%) showed no statistically significant difference ( χ 2=0.25, P >0.05). The rate of tuberculosis infection of close contacts in the 2025 tuberculosis outbreak (55.56%) was higher than that in the 2023 outbreak (11.84%) ( χ 2=30.42, P <0.01). Among the 106 students included in the cohort analysis, the median induration diameter was 3.50 (1.50, 7.50) mm in 2023 and 8.75 (4.25, 11.50) mm in 2025, with a statistically significant difference ( Z=-5.76, P <0.01). There was no statistically significant difference between the infection rate in 2022 (16.98%) and that in 2023 (10.38%) ( χ 2=1.96, P =0.16). The infection rate in 2025 (43.40%) was higher than those in 2022 and 2023 ( χ 2=17.55, 29.39, both P <0.017). The seroconversion rate of students in the same class in 2025 ( 58.00 %) was higher than that of students in different classes (16.07%), with a statistically significant difference ( χ 2=20.19, P <0.01). All 72 individuals with latent tuberculosis infections identified during the pandemic in 2023 and 2025 refused to undergo prophylactic treatment. Conclusions The lack of preventive treatment may be the underlying cause of the successive outbreaks during the epidemic. Early detection of infection sources and standardized outbreak management are crucial to controlling the spread of the epidemic.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

A pyrene-phenol-based fluorescent probe PyP which showed typical intramolecular charge transfer(ICT)and monomer-excimer activities was synthesized by using pyrene carboxaldehyde hydrazone and 4-tert-butyl-2,6-diformylphenol as the raw materials.The effects of solvents on PyP were studied,and the results showed that the color of protic polar solvents(Ethanol,N,N-dimethylformamide,methanol and H2O)were successfully identified.Based on the solvent polarity-regulated PyP monomer-excimer switching,the rapid and highly sensitive ratiometric probe,"Turn-off"and"Turn-on"multimodal probes were established for detection of trace water content in organic solvents(Dimethyl sulfoxide,N,N-dimethylformamide,ethanol and methanol),with detection limits(3σ/k)of 0.0021％,0.046％,0.062％and 0.024％.The method was successfully used to detect water content in dimethyl sulfoxide,N,N-dimethy lformamide,ethanol and methanol commercial organic solvents,with recoveries ranging from 97.2％to 108.0％.The developed method showed good accuracy and stability,and had good application prospect.

Introducing fingerprint level 3 features(especially sweat pores)in fingerprint recognition can significantly improve the value of fingerprints.However,conventional fingerprint visualization methods suffer from issues such as poor stability and reproducibility,insufficient resolution,and feature masking in detecting level 3 features.Electrospun membrane has unique advantages in latent fingerprint(LFP)detection due to its excellent adsorption performance and high specific surface area,and thus its application potential in LFP visualization urgently need to be explored.A novel pore visualization method based on core-shell structured PAN-Flu/PVP composite nanofibrous membrane was proposed in this work.Specifically,the PAN-Flu/PVP composite nanofibrous membrane was prepared via coaxial electrospinning technology,with polyacrylonitrile(PAN)loaded with fluorescein(Flu)as the core and polyvinylpyrrolidone(PVP)as the shell.The experimental results showed that the prepared PAN Flu/PVP composite nanofibrous membrane had a porous structure and excellent adsorption performance.Based on the water solubility of the outer shell PVP and the water induced fluorescence enhancement effect of the core Flu,high-resolution visualization of sweat pores could be achieved within 2 s.The optimization experiment showed that the best quality of sweat latent fingerprints was obtained when the Flu content was 4 mg/mL,the spinning time was 1 h,and the sweating time was 2 min.Through repeated fingerprinting and live fingerprint comparison experiment,the strong stability and high reproducibility of the as-produced membrane in displaying fingerprint sweat pores were finally verified.In summary,the development method could quickly,stably and accurately extract the spatial distribution and activity level of fingerprint sweat pores,which was of great significance for improving the utilization and value of fingerprints.

Water-soluble silver nanoclusters(DHLA-AgNCs)with red fluorescence emission were synthesized using silver nitrate(AgNO3)as silver source,dihydrolipoic acid(DHLA)as ligand and sodium borohydride(NaBH4)as reducing agent by one-pot method.Based on the selective quenching of DHLA-AgNCs by tetracycline(TC),a rapid and selective fluorescence analysis method for detection of TC was constructed by monitoring the fluorescence intensity change at 650 nm.Under the optimal detection conditions,the fluorescence quenching efficiency of DHLA-AgNCs showed good linear relationship with concentration of TC within the range of 10.0-120.0 μmol/L,and the limit of detection(LOD)was 0.39 μmol/L.This method was successfully applied to detection of TC in milk samples,with spiked recoveries ranging from 99.5%to 102.5%,and relative standard deviations(RSDs)less than 5%.This method had the advantages of simplicity,rapidity,strong specificity and low cost,and thus provided a simple and feasible strategy for selective detection of TC.

OBJECTIVE: To investigate the gene carrier rate and genotype distribution characteristics of thalassemia in the population of Kunming, and compare the differences of red blood cell (RBC) parameters between β⁺ heterozygous carriers, β⁰ heterozygous carriers and healthy population, as well as between different sexes of adults aged 18-45 years. METHODS: A retrospective analysis of 3 195 cases of thalassemia gene screened in the First Affiliated Hospital of Kunming Medical University from April 1, 2020 to March 31, 2022 was performed to detect 21 mutations of β-globin genes which was common in Chinese people using fluorescence PCR melting curve method. Patients with single heterozygous carrying β-thalassemia gene were divided into β⁺ heterozygote group and β⁰ heterozygote group, while the control group consisted of 219 healthy individuals. Four indices, including RBC, hemoglobin (Hb), mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) were collected from all β heterozygous carriers and 219 healthy people, and compared between β⁺ heterozygote group, β⁰ heterozygote group and control group, as well as between β⁺ heterozygous carriers, β⁰ heterozygous carriers and healthy population of different sexes aged 18-45 years. RESULTS: There were 688 cases confirmed thalassemia gene carriers, accounting for 21.53%. Among them, 322 cases were found to have β-globin gene mutations, including 145 cases of β⁺ heterozygote, 151 cases of β⁰ heterozygote, and 14 cases of β⁺ homozygotes as well as β⁺ and β⁰ dual heterozygotes. Additionally, 12 cases were found to have simultaneous mutation or deletion of β-globin and α-globin. The carrier rate of CD26 G>A mutation in β⁺ thalassemia was the highest, accounting for 57.9%, while in β⁰ thalassemia CD17 A>T was the highest, accounting for 46.4%. The erythrocyte parameters of 296 β heterozygous mutation carriers were compared with the normal reference interval, and it was found that 218 cases with RBC value greater than the highest value of reference interval, while 105, 281, and 269 cases with Hb, MCV, and MCH value less than the lowest value of reference interval, respectively. There were significant differences in the 4 erythrocyte parameters between β⁺ heterozygotes, β⁰ heterozygotes and healthy individuals (all P < 0.001), and further comparison between different sexes also showed significant differences (all P < 0.001). CONCLUSIONS The carrier rates of thalassemia gene and β-thalassemia heterozygote are both at high level in Kunming, and there are significant differences in the erythrocyte parameters between β⁺ heterozygous carriers, β⁰ heterozygous carriers and healthy individuals. When genetic counseling, it is necessary to inform and strengthen screening among adults of marriageable age to prevent birth of children with severe thalassemia.
Humans ; beta-Thalassemia/blood* ; Adult ; Heterozygote ; Male ; Female ; beta-Globins/genetics* ; Retrospective Studies ; Middle Aged ; Mutation ; Adolescent ; Genotype ; Erythrocytes ; Erythrocyte Indices ; Young Adult ; China ; Genetic Testing ; Asian People/genetics*

[This corrects the article DOI: 10.11909/j.issn.1671-5411.2017.08.005.].