This research investigated the impact of Ganoderma lucidum polysaccharides(GLP) on hepatoblastoma HepG2 and Huh6 cell models, as well as KM mouse model with in situ transplanted tumors, so as to provide a theoretical basis for the clinical application of GLP. Cell viability was assessed through the CCK-8 assay, whereas cell proliferation was evaluated by using the BeyoClick~(TM)EdU-488 test. Cell apoptosis was visualized via Hochest 33258 staining, and autophagy was detected through Mrfp-GFP-LC3 dual fluorescence staining. An in situ tumor transplantation model was created by using HepG2 cells in mice, and mice were treated with normal saline and GLP of 100, 200, and 300 mg·kg~(-1) for tumor count calculation and size assessment. Hematoxylin-eosin(HE) staining was used to observe pathological changes in tumor tissue and vital organs(liver, kidney, lung, spleen, and heart). Western blot analysis was conducted to measure the protein expressions of tumor protein P53(P53), B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), cleaved-caspase-3, Beclin-1, autophagy related protein-5(Atg-5), microtubule-associated protein-light chain-3Ⅰ(LC3Ⅰ)/LC3Ⅱ, autophagy adapter protein 62(P62), protein kinase B(Akt), p-Akt, mammalian target of rapamycin(mTOR), and p-mTOR. The in vitro experiment revealed that compared with the control group, after GLP treatment, tumor cell viability decreased significantly; apoptosis rate increased in a dose-dependent manner, and autophagic flux was inhibited. The in vivo experiments showed that compared with the model group, mice treated with GLP exhibited significantly fewer and smaller tumors. Western blot results showed that compared with the control group or model group, levels of P53, Bax, cleaved-caspase-3, Beclin-1, Atg-5, and LC3-Ⅱ/LC3-Ⅰ were significantly increased after GLP treatment, and the levels of Bcl-2, P62, p-Akt/Akt, and p-mTOR/mTOR were significantly decreased. These outcomes suggest that GLP promotes apoptosis and autophagy in hepatoblastoma cells by regulating the Akt/mTOR pathway.
Animals ; Humans ; Autophagy/drug effects* ; Reishi/chemistry* ; Mice ; Apoptosis/drug effects* ; TOR Serine-Threonine Kinases/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Liver Neoplasms/genetics* ; Hepatoblastoma/genetics* ; Polysaccharides/pharmacology* ; Cell Line, Tumor ; Signal Transduction/drug effects* ; Male ; Cell Proliferation/drug effects* ; Hep G2 Cells

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Selenoproteins, as the active form of selenium, play an important role in various physiological and pathological processes, such as anti-oxidation, anti-tumor, immune response, metabolic regulation, reproduction and aging. Although the expression level of selenoproteins in adipose tissue is significantly influenced by dietary selenium intake, it is closely related to the homeostasis of adipose tissue. In this review, we summarized the role of selenoproteins in the physiological function of adipose tissue and the pathogenesis of obesity in recent years, in order to provide a rationale for developing potential therapeutic agents for the treatment of obesity and related metabolic diseases.
Selenoproteins/metabolism* ; Adipose Tissue/physiology* ; Obesity/metabolism* ; Humans ; Animals ; Selenium

Objective To understand the implementation status of"Diagnosis of Ascariasis"(WS/T 565-2017)and provide a scientific basis for promoting,revising,and improving the Standard.Methods Using the convenient sampling method,the investigation targeted professional and technical personnel at the provincial,city,county,and township levels engaged in parasitic disease prevention,control,or diagnosis and treatment in Anhui and Sichuan provinces.No less than 150 individuals were included in each province.The implementation survey of Diagnosis of Ascariasis(WS/T 565-2017)was conducted by the subjects completing a questionnaire by themselves.Results The response rate to the questionnaire was 91.90%(386/420).The awareness and utilization rates of the Standard were 81.87%and 49.22%,respectively and both increased with age(χ2 trend=7.977 and 19.016,respectively,P＜0.01).Respondents with college degrees(90.72%)had a higher awareness rate(χ2=8.619,P＜0.05).In terms of utilization rate,males(58.38%),those with college degrees(67.01%),staff members of provincial-level units(77.78%),and personnel in medical institutions(71.43%)had higher utilization rates(χ2=13.486,17.166,8.426,and 5.956,respectively,all P＜0.05).The survey indicated that 57.77%of the work units of respondents have conducted promotional activities,and 53.89%of the work units of respondents have sent personnel to participate in training.Moreover,this proportion tended to increase as the unit level decreased(χ2 trend=9.403 and 14.729,P＜0.01).The level of participation in publicity and training by medical institutions(89.29%)was significantly higher than that of disease control institutions(55.31%and 51.12%,respectively,χ2=12.290 and 15.225,P＜0.01).Furthermore,training participation is a crucial factor in enhancing awareness rates.A total of 368 respondents(95.34%)reported that their work units have conducted testing for ascariasis.Additionally,378 individuals(97.92%)believe that the Standard is"applicable"or"basically applicable,"while 369(95.60%)felt that no revisions were needed.Conclusions The results indicated that"Diagnosis of Ascariasis"(WS/T 565-2017)remains applicable to the diagnostic needs of ascariasis and it is recommended to strengthen its promotion and implementation.

Objective To investigate the risk factors for ligamentum flavum hypertrophy(LFH)and its correlation with clinical symptoms in patients with degenerative lumbar spinal stenosis(DLSS).Methods The clinical and imaging data of 79 patients with DLSS were collected.Patients were divided into four groups based on LFH severity.Quantitative parameters,including lumbar lordosis(LL),sacral slope(SS),facet tropism,facet joint effusion,intervertebral height index,dural sac cross-sectional area(CSA),epidural fat area,and fat infiltration rate(FIR)of the paraspinal muscle were measured on imaging.One-way analysis of variance was used to compare the differences in these parameters among groups.Multiple linear regression analysis was performed to identify the risk fac-tors for LFH,and the correlation between LFH severity and clinical manifestations was analyzed.Results The results of one-way analy-sis of variance showed that there were statistically significant differences among the four groups of patients in terms of sex,body mass index(BMI),LL,epidural fat area and FIR of the multifidus(MF).Multiple linear regression analysis identified that BMI,LL,and epidural fat area as independent risk factors for LFH.Correlation analysis indicated a weak positive association between LFH and dis-ease duration(r=-0.231,P=0.041).Conclusion In DLSS patients,LFH is weakly correlated with disease duration,while BMI,LL,and epidural fat area are risk factors for LFH.

Objective To investigate the risk factors for ligamentum flavum hypertrophy(LFH)and its correlation with clinical symptoms in patients with degenerative lumbar spinal stenosis(DLSS).Methods The clinical and imaging data of 79 patients with DLSS were collected.Patients were divided into four groups based on LFH severity.Quantitative parameters,including lumbar lordosis(LL),sacral slope(SS),facet tropism,facet joint effusion,intervertebral height index,dural sac cross-sectional area(CSA),epidural fat area,and fat infiltration rate(FIR)of the paraspinal muscle were measured on imaging.One-way analysis of variance was used to compare the differences in these parameters among groups.Multiple linear regression analysis was performed to identify the risk fac-tors for LFH,and the correlation between LFH severity and clinical manifestations was analyzed.Results The results of one-way analy-sis of variance showed that there were statistically significant differences among the four groups of patients in terms of sex,body mass index(BMI),LL,epidural fat area and FIR of the multifidus(MF).Multiple linear regression analysis identified that BMI,LL,and epidural fat area as independent risk factors for LFH.Correlation analysis indicated a weak positive association between LFH and dis-ease duration(r=-0.231,P=0.041).Conclusion In DLSS patients,LFH is weakly correlated with disease duration,while BMI,LL,and epidural fat area are risk factors for LFH.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Objective:To explore the feasibility of adjusting the thyroid stimulating hormone (TSH) cut-off values for screening congenital hypothyroidism (CH) in newborns according to the seasons, and to establish a TSH screening cut-off value that is suitable for the actual situation in Quanzhou City.Methods:A total of 355 868 newborns who underwent CH screening at the Neonatal Disease Screening Center in Quanzhou in Fujian Province from January 1, 2018 to December 31, 2021 were included in the study. Heel blood samples were collected and made dried blood spots. TSH levels in the heel blood of newborns were measured using genetic screening processor (GSP). The TSH cut-off values for CH screening were established using the percentile method and the receiver operating characteristic (ROC) curve method, and were adjusted based on seasonal factors. The screening efficiency was then compared with the current TSH cut-off value (9.00 mU/L).Results:According to the percentile method, the 99th percentile TSH levels in newborn heel blood in spring, summer, autumn, and winter were 9.47, 9.01, 9.41, and 10.43 mU/L, respectively. Using these values as cut-off values, the initial screening positive rates in spring, summer, autumn, and winter were 1.00% (848/84 652), 1.04% (913/87 524), 1.00% (951/94 875), 1.00% (889/88 817) [1.27% (1 077/84 652), 1.05% (916/87 524), 1.23% (1 171/94 875), 2.01% (1 787/88 817) according to the current TSH cut-off value]. However, except for summer, there were 7, 6, and 17 cases of missed screening in spring, autumn, and winter, respectively. The cut-off values of TSH for the four seasons obtained by the ROC curve method were 9.01, 9.02, 9.01, and 9.01 mU/L, respectively. The initial screening positive rates in spring, autumn, and winter were consistent with the current cut-off values, at 1.27% (1 074/84 652), 1.23% (1 167/94 875), 2.01% (1 781/88 817), respectively, while in summer, it was 0.99% (866/87 524) [1.05% (916/87 524) according to the current TSH cut-off value], and the positive detection rates in all four seasons were 100.00%.Conclusions:It is not advisable to adjust the TSH cut-off value for CH screening according to seasons in Quanzhou City. Using the current TSH cut-off value of 9.00 mU/L for CH screening in Quanzhou City can effectively ensure the quality of screening.