ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Objective To analyze the ultrasonographic features of secondary squamous cell carcinoma of the thyroid(SSCC-T)and evaluate the diagnostic value of ultrasound.Methods A retrospective analysis was conducted on clinical and ultrasonographic data from 12 patients with pathologically confirmed SSCC-T treated at Beijing Friendship Hospital,Capital Medical University between January 2016 and January 2025.Evaluated parameters included lesion size,echogenicity,edge,vascularity,calcification,and cervical lymph node metastasis.Descriptive statistical analysis was performed to analyze the ultrasonographic features of SSCC-T,and Fisher's exact test was conducted to analyze the correlation between different ultrasound classifications and thyroid dysfunction.Results The 12 patients showed the following ultrasound classifications:nodular type(50.0%,6/12),diffuse type(33.3%,4/12),and mixed type(16.7%,2/12).All diffuse-type patients exhibited a characteristic cord-like hypoechoic pattern.Cervical lymph node metastasis was observed in all the patients,with 75.0%(9/12)showing lymph nodes >2 cm in maximum diameter.Thyroid dysfunction occurred in 66.7%(8/12)of patients,including 2 patients with dynamic shifts from hyperthyroidism to hypothyroidism.Diffuse and mixed types were associated with hypothyroidism(P=0.038).Conclusions SSCC-T demonstrates specific ultrasonographic features,particularly the cord-like hypoechoic pattern in the diffuse type.For patients with squamous cell carcinoma,regular ultrasound examinations of the thyroid and cervical lymph nodes combined with changes in thyroid function are conducive to the timely detection of thyroid metastasis of squamous cell carcinoma.
Humans ; Retrospective Studies ; Ultrasonography ; Carcinoma, Squamous Cell/diagnostic imaging* ; Thyroid Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Male ; Female ; Middle Aged ; Thyroid Gland/diagnostic imaging* ; Adult

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

ObjectiveThis study aims to identify cuproptosis-related gene biomarkers in Alzheimer's disease（AD） using bioinformatics and machine learning methods， validate them at the clinical specimen level， and predict potential traditional Chinese medicine（TCM）. MethodsDifferentially expressed genes in the AD group and normal group were obtained using the Gene Expression Omnibus （GEO） database， and intersections were taken with reported cuproptosis-related genes to obtain differentially expressed cuproptosis-related genes. Machine learning methods were applied to identify core differential genes of cuproptosis in AD. Peripheral blood's single nucleated cells from clinical AD patients were collected， and the relative gene expression was clinically verified by real-time polymerase chain reaction（Real-time PCR）. Potential TCM regulating cuproptosis for AD were predicted by COREMINE database. ResultsA total of 12 cuproptosis-related genes were obtained， mainly involved in pathways of tricarboxylic acid cycle， 2-oxocarboxylic acid metabolism， and carbon metabolism. Five core cuproptosis-related genes， dihydrolipoamide dehydrogenase （DLD）， glutaminase （GLS）， pyruvate dehydrogenase E1 subunit beta （PDHB）， full name nuclear factor （erythroid-derived 2）-related factor 2 （NFE2L2）， and dihydrolipoamide branched-chain transacylase E2 （DBT） were finally screened using four machine methods. Thirty cases each of normal and AD patients were collected clinically. Compared with those in the normal group， minimum mental state examination （MMSE） and Montreal cognitive assessment （MoCA） were significantly decreased in the AD group （P<0.01）， Homocysteine（Hcy）， interleukin（IL）-6， C-reactive protein（CRP） ， and β amyloid protein（Aβ） indexes were significantly increased （P<0.01）， and malondialdehyde（MDA） indexes were decreased （P<0.05）. Superoxide dismutase（SOD） levels were significantly decreased （P<0.01）. The mRNA relative expressions of NFE2L2 and DBT were up-regulated （P<0.05）， and those of DLD， GLS， and PDHB were significantly down-regulated （P<0.01）. The TCM regulating cuproptosis-related genes for the treatment of AD were mainly based on the four Qi such as warmth， calmness， and cold， and the five flavors including bitterness， sweetness， and pungency， and it was attributed to the meridians of the liver， spleen， stomach， and kidney， with the efficacy of tonifying Qi， activating blood， eliminating phlegm， and resoling dampness. ConclusionDLD， GLS， NFE2L2， PDHB， and DBT can be used as novel diagnostic molecular markers for AD cuproptosis-related genes， and the corresponding potential therapeutic TCM can provide new ideas for the treatment of AD by TCM.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective: To investigate the characteristics of malignant tumor incidence and mortality in cancer registration areas of Sichuan Province in 2021. Methods: Cancer registration data from 142 registries in Sichuan Province in 2021 were collected via the China Cancer Registry Platform. Crude incidence and crude mortality were calculated. The Chinese population-standardized incidence and world population-standardized incidence were standardized using the age structure of the standard population from the Fifth National Population Census in 2000 and Segi's world standard population. Descriptive analyses examined the distribution of rates by genders, urban/rural areas, and ages, and the ranking of leading cancer sites. Results: In 2021, there were 248 600 new malignant tumor cases reported in Sichuan Province, with a crude incidence of 296.37/100 000. The Chinese population-standardized incidence and world population-standardized incidence were 164.67/100 000 and 160.47/100 000, respectively. There were 158 673 malignant tumor deaths, with a crude mortality of 189.16/100 000. The Chinese population-standardized mortality and world population-standardized mortality were 92.47/100 000 and 92.00/100 000, respectively. The Chinese population-standardized incidence and mortality in males were higher than in females (179.56/100 000 vs. 151.62/100 000, 125.09/100 000 vs. 60.35/100 000). The Chinese population-standardized incidence and mortality in urban areas were higher than in rural areas (175.74/100 000 vs. 157.54/100 000, 93.63/100 000 vs. 91.82/100 000). Both the crude incidence and crude mortality increased with age. The top ten malignant tumors by crude incidence were lung cancer, colorectal cancer, liver cancer, breast cancer, esophageal cancer, gastric cancer, cervical cancer, prostate cancer, thyroid cancer, and corpus uteri cancer, accounting for 76.33% of all new cases. The top ten by crude mortality were lung cancer, liver cancer, esophageal cancer, colorectal cancer, gastric cancer, breast cancer, pancreatic cancer, cervical cancer, prostate cancer, and brain tumors, accounting for 82.39% of all cancer deaths. Conclusions In registration areas of Sichuan Province, the incidence and mortality of malignant tumors are relatively low. Key populations such as males, urban residents, and the elderly require focused prevention and control efforts. Comprehensive measures should be prioritized for malignant tumors including lung cancer, liver cancer, esophageal cancer, gastric cancer, colorectal cancer, and breast cancer.

Objective: To analyze the occupational health literacy (OHL) level and its influencing factors among key populations in the tertiary industry in Lu'an City, Anhui Province, so as to provide a basis for developing targeted health interventions and improving regional occupational health policies. Methods: A stratified cluster random sampling method was employed to select five categories of key populations from the tertiary industry in Lu'an City as study subjects from August to September 2024. Data on gender, age, education level, and OHL were collected through the National OHL Monitoring Questionnaire for Key Populations. The OHL levels were analyzed, and influencing factors of OHL levels among key populations were analyzed using a multivariable logistic regression model. Results: A total of 1 243 individuals were surveyed, comprising 700 (56.32%) males and 543 (43.68%) females. The median age was 42.00 (interquartile range, 17.00) years. There were 609 individuals with OHL, and the OHL level was 48.99%. The OHL levels in fundamental knowledge of occupational health protection, healthy work styles and behaviors, knowledge of occupational health laws, and basic skills for occupational health protection were 84.71%, 60.34%, 43.93%, and 37.09%, respectively. Multivariable logistic regression analysis showed that educational level (primary school and below, OR=0.149, 95%CI: 0.064-0.344; junior high school, OR=0.340, 95%CI: 0.184-0.629; high school, OR=0.408, 95%CI: 0.230-0.723), average monthly personal income (3 000-<5 000 yuan, OR=1.655, 95%CI: 1.092-2.508; 5 000-<7 000 yuan, OR=2.195, 95%CI: 1.302-3.699; ≥7 000 yuan, OR=2.062, 95%CI: 1.016-4.183), employer nature (private enterprises, OR=2.992, 95%CI: 1.569-5.443), and industry category (education, OR=3.423, 95%CI: 1.407-8.327; courier / food delivery services, OR=0.459, 95%CI: 0.268-0.787; healthcare, OR=7.539, 95%CI: 3.255-17.461) were statistically associated with the OHL level among key population. Conclusion The OHL level among key population in the tertiary industry of Lu'an City can be further enhanced, with educational level, average monthly personal income, employer nature, and industry category identified as the primary influencing factors.

The dried mature peel of Citrus reticulata, a plant in the Rutaceae family and its cultivated varieties, is a commonly used Chinese medicinal material known as Chenpi(Citri Reticulatae Pericarpium). It is rich in nutritional components and medicinal value, with pharmacological effects including relieving cough and eliminating phlegm, strengthening the spleen and drying dampness, protecting the liver and benefiting the stomach, tonifying Qi, and calming the mind. Huanglongbing(HLB), also known as Citrus Huanglongbing, is a destructive disease in citrus production that seriously threatens the development of the citrus industry. HLB causes symptoms such as the inability of Rutaceae plants to produce mature fruit, gradual weakening of the tree, and eventual death, posing a significant threat to the yield and quality of Chenpi. Due to the uneven distribution of the HLB pathogen in infected plants, accurate detection of the pathogen requires the collection of a large number of plant samples. Current sample pretreatment methods, such as traditional extraction methods and commercial extraction kits, are time-consuming and involve multiple steps, which significantly increase the difficulty and workload of HLB diagnosis and have become a bottleneck in HLB detection. In this study, a rapid high-throughput detection method combining alkali lysis and TaqMan qPCR was developed. This method allows the pretreatment of multiple samples within 5 min, and the entire detection process can be completed within 45 min, with a detection limit of 6.67 fg·μL~(-1). The alkali lysis method and commercial kits were used for parallel detection of field-collected citrus samples, and the results showed no significant difference. The sample pretreatment method established in this study is characterized by low cost, simplicity, and high efficiency. Combined with TaqMan qPCR, it can provide technical support for early and on-site diagnosis of HLB. This method is of great significance for disease prevention and control in the citrus industry and is expected to help improve the yield and quality of citrus medicinal materials.
Citrus/microbiology* ; Plant Diseases/microbiology* ; Rhizobiaceae/physiology* ; High-Throughput Screening Assays/methods* ; Liberibacter/physiology*

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires