A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

ObjectiveTo investigate the effects of different concentrations of Shaoyaotang-containing serum on lipopolysaccharide （LPS）-induced inflammation of human colorectal adenocarcinoma （Caco-2） cells by inhibiting apoptosis via activating the tumor necrosis factor （TNF） receptor superfamily member 6 （Fas）/Fas ligand （FasL） pathway. MethodsCaco-2 cells were allocated into blank， model （LPS， 10 mg·L^-1）， Shaoyaotang-containing serum （5%， 10%， 15%， 20%）， and Fas inhibitor （KR-33493， 20 mmol·L^-1） groups. Except the blank group， the other groups were stimulated with 10 mg·L^-1 LPS for 24 h for the modeling of inflammation. After successful modeling， the blank， Fas inhibitor， and model groups were treated with blank serum， and the Shaoyaotang-containing serum groups were treated with the serum samples at corresponding concentrations for 24 h. The Fas inhibitor group was subjected to KR-33493 pretreatment for 1 h. Cell proliferation and viability were examined by the cell-counting kit-8 （CCK-8） method. The levels of interleukin （IL）-6， IL-1β， and TNF-α were measured by enzyme-linked immunosorbent assay. Apoptosis was detected by flow cytometry. The protein and mRNA levels of Fas， FasL， cysteinyl aspartate-specific proteinase （Caspase）-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsCompared with the blank group， the model group presented a decrease in cell survival rate （P<0.01）. Compared with that in the model group， the cell survival rate showed no significant change in the 5% Shaoyaotang-containing serum group but increased in the 10%， 15%， and 20% Shaoyaotang-containing serum groups （P<0.01）. Since there was no statistical difference between the 5% Shaoyaotang-containing serum group and the model group， 10%， 15%， and 20% Shaoyaotang-containing sera were selected for the follow-up study. Compared with the blank group， the model group showed risen levels of IL-6， IL-1β， and TNF-α （P<0.01）， an increased apoptosis rate （P<0.01）， up-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.01）， and down-regulated protein and mRNA levels of Bcl-2 （P<0.01）. Compared with the model group， the Fas inhibitor group and the 10%， 15%， and 20% Shaoyaotang-containing serum groups showed declined levels of IL-6， IL-1β， and TNF-α （P<0.01）， decreased apoptosis rates （P<0.01）， down-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of Bcl-2 （P<0.05， P<0.01）. In addition， the 15% and 20% Shaoyaotang-containing serum groups had lower levels of IL-6， IL-1β， and TNF-α （P<0.05， P<0.01）， lower apoptosis rates （P<0.05， P<0.01）， lower protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and higher protein and mRNA levels of Bcl-2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can reduce the content of inflammatory factors in Caco-2 cells， down-regulate the protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax， and up-regulate the protein and mRNA levels of Bcl-2 under the intervention of LPS by regulating the Fas/FasL pathway and inhibiting the apoptosis of intestinal epithelial cells in ulcerative colitis.

ObjectiveTo investigate the effects of different concentrations of Shaoyaotang-containing serum on lipopolysaccharide （LPS）-induced inflammation of human colorectal adenocarcinoma （Caco-2） cells by inhibiting apoptosis via activating the tumor necrosis factor （TNF） receptor superfamily member 6 （Fas）/Fas ligand （FasL） pathway. MethodsCaco-2 cells were allocated into blank， model （LPS， 10 mg·L^-1）， Shaoyaotang-containing serum （5%， 10%， 15%， 20%）， and Fas inhibitor （KR-33493， 20 mmol·L^-1） groups. Except the blank group， the other groups were stimulated with 10 mg·L^-1 LPS for 24 h for the modeling of inflammation. After successful modeling， the blank， Fas inhibitor， and model groups were treated with blank serum， and the Shaoyaotang-containing serum groups were treated with the serum samples at corresponding concentrations for 24 h. The Fas inhibitor group was subjected to KR-33493 pretreatment for 1 h. Cell proliferation and viability were examined by the cell-counting kit-8 （CCK-8） method. The levels of interleukin （IL）-6， IL-1β， and TNF-α were measured by enzyme-linked immunosorbent assay. Apoptosis was detected by flow cytometry. The protein and mRNA levels of Fas， FasL， cysteinyl aspartate-specific proteinase （Caspase）-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsCompared with the blank group， the model group presented a decrease in cell survival rate （P<0.01）. Compared with that in the model group， the cell survival rate showed no significant change in the 5% Shaoyaotang-containing serum group but increased in the 10%， 15%， and 20% Shaoyaotang-containing serum groups （P<0.01）. Since there was no statistical difference between the 5% Shaoyaotang-containing serum group and the model group， 10%， 15%， and 20% Shaoyaotang-containing sera were selected for the follow-up study. Compared with the blank group， the model group showed risen levels of IL-6， IL-1β， and TNF-α （P<0.01）， an increased apoptosis rate （P<0.01）， up-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.01）， and down-regulated protein and mRNA levels of Bcl-2 （P<0.01）. Compared with the model group， the Fas inhibitor group and the 10%， 15%， and 20% Shaoyaotang-containing serum groups showed declined levels of IL-6， IL-1β， and TNF-α （P<0.01）， decreased apoptosis rates （P<0.01）， down-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of Bcl-2 （P<0.05， P<0.01）. In addition， the 15% and 20% Shaoyaotang-containing serum groups had lower levels of IL-6， IL-1β， and TNF-α （P<0.05， P<0.01）， lower apoptosis rates （P<0.05， P<0.01）， lower protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and higher protein and mRNA levels of Bcl-2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can reduce the content of inflammatory factors in Caco-2 cells， down-regulate the protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax， and up-regulate the protein and mRNA levels of Bcl-2 under the intervention of LPS by regulating the Fas/FasL pathway and inhibiting the apoptosis of intestinal epithelial cells in ulcerative colitis.

To investigate the correlation between vitamin D nutritional status and insulin resistance in pubertal adolescents.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

BACKGROUND:Human periodontal ligament stem cells are potential functional cells for periodontal tissue engineering.However,long-term in vitro culture may lead to reduced stemness and replicative senescence of periodontal ligament stem cells,which may impair the therapeutic effect of human periodontal ligament stem cells. OBJECTIVE:To investigate the effect of oxymatrine on the stemness maintenance and osteogenic differentiation of periodontal ligament stem cells in vitro,and to explore the potential mechanism. METHODS:Periodontal ligament stem cells were isolated from human periodontal ligament tissues by tissue explant enzyme digestion and cultured.The surface markers of mesenchymal cells were identified by flow cytometry.Periodontal ligament stem cells were incubated with 0,2.5,5,and 10 μg/mL oxymatrine.The effect of oxymatrine on the proliferation activity of periodontal ligament stem cells was detected by CCK8 assay.The appropriate drug concentration for subsequent experiments was screened.Western blot assay was used to detect the expression of stem cell non-specific proteins SOX2 and OCT4 in periodontal ligament stem cells.qRT-PCR and western blot assay were used to detect the expression levels of related osteogenic genes and proteins in periodontal ligament stem cells. RESULTS AND CONCLUSION:(1)The results of CCK8 assay showed that 2.5 μg/mL oxymatrine significantly enhanced the proliferative activity of periodontal stem cells,and the subsequent experiment selected 2.5 μg/mL oxymatrine to intervene.(2)Compared with the blank control group,the protein expression level of SOX2,a stem marker of periodontal ligament stem cells in the oxymatrine group did not change significantly(P>0.05),and the expression of OCT4 was significantly up-regulated(P<0.05).(3)Compared with the osteogenic induction group,the osteogenic genes ALP,RUNX2 mRNA expression and their osteogenic associated protein ALP protein expression of periodontal ligament stem cells were significantly down-regulated in the oxymatrine+osteogenic induction group(P<0.05).(4)The oxymatrine up-regulated the expression of stemness markers of periodontal ligament stem cells and inhibited the bone differentiation of periodontal ligament stem cells,and the results of high-throughput sequencing showed that it may be associated with WNT2,WNT16,COMP,and BMP6.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.