Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

BackgroundWith the exacerbation of population aging， the number of elderly patients with mental disorders has increased significantly. The high prevalence of pulmonary infection in the aging population has largely contributed to the increased medical burdens and mortality rate， so preventing pulmonary infection in elderly patients with mental disorders has become a critical challenge in clinical practice. www.crd.york.ac.uk/PROSPERO注册号：CRD42024553735 ObjectiveTo investigate the prevalence and influencing factors of pulmonary infection in elderly patients with mental disorders， so as to provide references for preventing the occurrence of pulmonary infection in this population. MethodsOn July 1， 2024， computer searches of CNKI， China Biomedical Literature Database （CBM）， Wanfang， PubMed， Web of Science， Embase， Cochrane Library and Ovid were conducted from the inception of each database to June 2024. Two researchers independently conducted literature screening， data extraction and quality assessment. Meta-analysis was performed using Stata 16.0. ResultsA total of 17 literature （14 in Chinese， 3 in English） involving 75 724 elderly patients with mental disorders were included. Meta analysis revealed that the incidence rate of pulmonary infection in elderly patients with mental disorders was 20.8% （95% CI： 0.154~0.263）. Subgroup analysis indicated that the incidence rates of pulmonary infection among patients with dementia， schizophrenia， depression and unspecified mental disorders were 21.9% （95% CI： 0.182~0.256）， 20.6% （95% CI： 0.129~0.283）， 18.4% （95% CI： 0.136~0.232） and 5.2% （95% CI： 0.430~0.062）， respectively. In terms of influencing factors， the following were identified as risk factors for pulmonary infection in elderly patients with mental disorders： comorbid diabetes mellitus （OR=1.29， 95% CI： 1.24~1.34）， prolonged bed rest （OR=2.41， 95% CI： 2.10~2.76）， dysphagia （OR=1.76， 95% CI： 1.53~2.03）， smoking history （OR=6.27， 95% CI： 5.97~6.59）， irrational use of antibiotics （OR=2.10， 95% CI： 1.79~2.45）， hypoalbuminemia （OR=1.57， 95% CI： 1.35~1.83）， duration of illness （OR=2.05， 95% CI： 1.79~2.36）， age （OR=9.04， 95% CI： 8.44~9.68）， length of hospital stay （OR=2.68， 95% CI： 1.65~4.34）， use of proton pump inhibitors （OR=1.10， 95% CI： 1.06~1.14）， history of chronic lung disease （OR=1.50， 95% CI： 1.43~1.57）， poor oral hygiene （OR=3.66， 95% CI： 1.01~13.23）， comorbid tumors （OR=3.12， 95% CI： 2.18~4.48）， more than two somatic complications （OR=4.01， 95% CI： 1.08~14.86）， invasive procedures （OR=3.31， 95% CI： 1.81~6.04） and disorders of consciousness （OR=5.57， 95% CI： 2.18~14.24）. ConclusionElderly patients with mental disorders suffer a relatively high prevalence rate of pulmonary infection， and its prevalence rate varies among different types of mental disorders， with the highest rate being observed in patients with dementia. The factors contributing to the development of pulmonary infection are found to include age， duration of illness， smoking history， comorbid somatic complications， dysphagia， disorders of consciousness， hypoalbuminemia， prolonged bed rest， oral hygiene status， irrational use of antibiotics， use of proton pump inhibitor， length of hospital stay and invasive procedures. ［www.crd.york.ac.uk/PROSPERO number： CRD42024553735］

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: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

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.

ObjectiveTo investigate the effects of Xixintang （XXT）-medicated serum on the amyloid β-protein （Aβ）_25-35-induced polarization of BV-2 microglial cells by a cell experiment and uncover the potential mechanisms of this formula in the prevention and treatment of Alzheimer's disease （AD）， thus providing scientific evidence for the clinical application of XXT. MethodsBV-2 microglial cells were subcultured. The optimal concentrations of XXT-medicated serum and Aβ_25-35 were determined via the cell-counting kit-8 （CCK-8） assay. The cell experiment was carried out with the following groups： blank control， model （Aβ_25-35 at 40 μmol·L^-1）， XXT-medicated serum （Aβ_25-35 at 40 μmol·L^-1 + 10% XXT-medicated serum）， and blank serum （Aβ_25-35 at 40 μmol·L^-1 + 10% blank serum）. After 24 hours of cell incubation， immunofluorescence was used to detect the expression of ionized calcium-binding adaptor molecule 1 （IBA1）， CD16/32， and CD206. Real-time PCR was performed to measure the mRNA levels of CD206， CD163， inducible nitric oxide synthase （iNOS）， and arginase 1 （Arg-1）. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the levels of nerve growth factor （NGF）， iNOS， and Arg-1. The nitric oxide （NO） concentration was determined via the nitrate reductase method. ResultsCompared with the blank control group， the model group showed increased expression of IBA1 and CD16/32 （P<0.01）， decreased expression of CD206 （P<0.05）， upregulation in the mRNA level （P<0.01） and content （P<0.05） of iNOS， downregulation in the mRNA levels of CD206， CD163， and Arg-1 （P<0.05， P<0.01）， lowered levels of Arg-1 and NGF （P<0.05）， and an elevation in the NO level （P<0.05）. Compared with the model group， the XXT-medicated serum group exhibited reduced expression of IBA1 and CD16/32 （P<0.05， P<0.01） and increased expression of CD206 （P<0.01）. Both the content and mRNA level of iNOS were downregulated （P<0.05， P<0.01）， while the mRNA levels of CD206， CD163， and Arg-1 were upregulated （P<0.01） in the XXT-medicated serum group. In addition， the XXT-medicated serum group showed elevated levels of Arg-1 and NGF （P<0.05） and a lowered level of NO （P<0.05）. The blank serum group showed no statistically significant differences in the measured parameters compared with the model group. ConclusionThe XXT-medicated serum can inhibit the polarization toward the M1 phenotype and promote the polarization toward the M2 phenotype， exerting anti-inflammatory and neurotrophic effects.

GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.