Health economics evidence plays an important role in linking clinical value evidence with health resource allocation decisions in the development of clinical practice guidelines. It can not only effectively balance clinical effectiveness and economic feasibility but also avoid forming "idealized" recommendations that are detached from the affordability of the healthcare system or the burden-bearing capacity of patients. To promote guideline developers to use health economics evidence more standardizedly and fully, this paper conducts an in-depth analysis of the current application status, existing challenges, access channels, and application processes of health economics evidence in current guidelines, and on this basis, puts forward considerations and suggestions for strengthening and standardizing the application of health economics evidence in China's clinical practice guidelines.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the effects of different doses of sufentanil on the pupillary dilation reflex (PDR) during induction of general anesthesia.Methods:In this randomized controlled study, 124 patients of either sex, aged 18-64 yr, with a body mass index of 18-30 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ, undergoing surgery with general anesthesia, were divided into 4 groups ( n=31 each) using a random number table method: control group (group C) and different doses of sufentanil groups (S1-S3 groups). Sufentanil 0.2, 0.4 and 0.6 μg/kg were intravenously injected in S1-S3 groups, respectively, and the equal volume of normal saline was injected instead in group C. Tetanic stimulation (50 mA, 50 Hz, 5 s) was applied at 5 min after injection of sufentanil. Pupil diameter was measured and the pupillary dilation value and dilation rate were calculated upon entering the operating room while awake, after loss of consciousness, 5 min after intravenous injection of sufentanil, and at maximal pupil diameter after tetanic stimulation. The presence or absence of PDR, PDR latency and PDR duration were also recorded. Results:The pupillary dilation values and dilation rates decreased progressively from group C through groups S1 to S3 ( P<0.05). Compared to group C, the disappearance rate of PDR was significantly increased, and the latency of PDR was prolonged in groups S2 and S3, and the duration of PDR was significantly shortened in groups S1-S3 ( P<0.05). Compared to group S1, the disappearance rate of PDR was significantly increased, and the latency of PDR was prolonged in S2 and S3 groups ( P<0.05). Conclusions:The inhibitory effect of sufentanil on the PDR during induction of general anesthesia is dose-dependent.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

This article reports a first case of combined infection with severe fever with thrombocytopenia syndrome(SFTS)and scrub typhus in Dalian City.The patient was admitted to the hospital due to recurrent fever for 7 days and loss of consciousness for 1 day.Pathogen metagenomic sequencing(mNGS),SFTSV quantitative PCR,and enzyme-linked immunosorbent assay(ELISA)IgM tests were performed,showing positive results for Orientia tsutsugamushi and SFTSV nucleic acids.Based on clinical manifestations and epidemiological history,the patient was diagnosed with combined infections.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective:To formulate the audit standards of Chinese patent medicine prescriptions, and provide reference for rational prescriptions of Chinese patent medicine.Methods:A three-level evidence system for prescription review of Chinese patent medicine was established according to the national regulatory documents, drug labels, relevant guidelines, and expert consensuses. The catalog of Chinese patent medicines in Army Medical Center of the People′s Liberation Army was integrated and classified, preliminary review criteria including indications, drug selection, usage and dosage, and combination drugs was established and submitted to clinical experts of traditional Chinese medicine for review and revision, and finally the prescription review standard was confirmed.Results:The Chinese patent medicine catalog of the Medical Center contained 218 drugs, which were divided into 23 kinds according to efficacy and 17 kinds according to dosage forms. The prescription review standards of Chinese patent medicine were as follows. (1) Indications: both traditional Chinese medicine and Western medicine diagnosis were required. (2) Drug selection: 37 kinds of Chinese patent medicines were marked as forbidden for pregnant women in the labels, and 16 kinds were not marked but contained forbidden ingredients; 4 kinds were marked with caution for patients with liver dysfunction, and 24 kinds were not marked but contained ingredients with caution; 2 kinds of Chinese patent medicines were marked with caution for patients with renal insufficiency, and 9 kinds were not marked but contained ingredients with caution. (3) Usage and dosage: the usage and dosage rules of Chinese patent medicines for children, the elderly and patients with liver and kidney dysfunction were formulated. (4) Combined medication: 5 and 21 kinds of Chinese patent medicines were marked as "highly toxic" and "toxic" in the labels, respectively, 11 kinds of Chinese patent medicines contained incompatible ingredients of "Shibafan" (eighteen antagonisms) and "Shijiuwei (nineteen incompatibilities), and a new review scale for repeated use of Chinese patent medicine was developed.Conclusions:Based on the existing evidence-based medicine, the evidence system of prescription review of Chinese patent medicine is established, the prescription review standards of Chinese patent medicine prescription based on the pharmaceutical interaction mode is formulated and constructed.

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)mutations are influenced by random and uncontrollable factors,and the risk of the next widespread epidemic remains.Dual-target drugs that synergistically act on two targets exhibit strong therapeutic effects and advantages against mutations.In this study,a novel computational workflow was developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main protease selected as the two target proteins.The drug-like molecules of our self-constructed 3D scaffold database were used as high-throughput molecular docking probes for feature extraction of two target protein pockets.A multi-layer perceptron(MLP)was employed to embed the binding affinities into a latent space as conditional vectors to control conditional distribution.Utilizing a conditional generative neural network,cG-SchNet,with 3D Euclidean group(E3)symmetries,the conditional probability distributions of molecular 3D structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated.The 1D probability,2D joint probability,and 2D cumulative probability distribution results indicate that the generated sets are significantly enhanced compared to the training set in the high binding affinity area.Among the 201 generated molecules,42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol,demonstrating structure diversity along with strong dual-target affinities,good absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties,and ease of synthesis.Dual-target drugs are rare and difficult to find,and our"high-throughput docking-multi-conditional generation"workflow offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.

The polymerase 1 and transcript release factor (PTRF)-cytoplasmic phospholipase A2 (cPLA2) phospholipid remodeling pathway facilitates tumor proliferation in glioma. Nevertheless, blockade of this pathway leads to the excessive activation of oncogenic receptors on the plasma membrane and subsequent drug resistance. Here, CD26/dipeptidyl peptidase 4 (DPP4) was identified through screening of CRISPR/Cas9 libraries. Suppressing PTRF-cPLA2 signaling resulted in the activation of the epidermal growth factor receptor (EGFR) pathway through phosphatidylcholine and lysophosphatidylcholine remodeling, which ultimately increased DPP4 transcription. In turn, DPP4 interacted with EGFR and prevented its ubiquitination. Linagliptin, a DPP4 inhibitor, facilitated the degradation of EGFR by blocking its interaction with DPP4. When combined with the cPLA2 inhibitor AACOCF3, it exhibited synergistic effects and led to a decrease in energy metabolism in glioblastoma cells. Subsequent in vivo investigations provided further evidence of a synergistic impact of linagliptin by augmenting the sensitivity of AACOCF3 and strengthening the efficacy of temozolomide. DPP4 serves as a novel target and establishes a constructive feedback loop with EGFR. Linagliptin is a potent inhibitor that promotes EGFR degradation by blocking the DPP4-EGFR interaction. This study presents innovative approaches for treating glioma by combining linagliptin with AACOCF3 and temozolomide.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations are influenced by random and uncontrollable factors, and the risk of the next widespread epidemic remains. Dual-target drugs that synergistically act on two targets exhibit strong therapeutic effects and advantages against mutations. In this study, a novel computational workflow was developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main protease selected as the two target proteins. The drug-like molecules of our self-constructed 3D scaffold database were used as high-throughput molecular docking probes for feature extraction of two target protein pockets. A multi-layer perceptron (MLP) was employed to embed the binding affinities into a latent space as conditional vectors to control conditional distribution. Utilizing a conditional generative neural network, cG-SchNet, with 3D Euclidean group (E3) symmetries, the conditional probability distributions of molecular 3D structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated. The 1D probability, 2D joint probability, and 2D cumulative probability distribution results indicate that the generated sets are significantly enhanced compared to the training set in the high binding affinity area. Among the 201 generated molecules, 42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol, demonstrating structure diversity along with strong dual-target affinities, good absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and ease of synthesis. Dual-target drugs are rare and difficult to find, and our "high-throughput docking-multi-conditional generation" workflow offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.