To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

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.

Esophageal squamous cell carcinoma (ESCC) poses a significant global health challenge, necessitating early detection, timely diagnosis, and prompt treatment to improve patient outcomes. Endoscopic examination plays a pivotal role in this regard. However, despite the availability of various endoscopic techniques, certain limitations can result in missed or misdiagnosed ESCCs. Currently, artificial intelligence (AI)-assisted endoscopic diagnosis has made significant strides in addressing these limitations and improving the diagnosis of ESCC and precancerous lesions. In this review, we provide an overview of the current state of AI applications for endoscopic diagnosis of ESCC and precancerous lesions in aspects including lesion characterization, margin delineation, invasion depth estimation, and microvascular subtype classification. Furthermore, we offer insights into the future direction of this field, highlighting potential advancements that can lead to more accurate diagnoses and ultimately better prognoses for patients.
Humans ; Artificial Intelligence ; Esophageal Squamous Cell Carcinoma/diagnosis* ; Esophageal Neoplasms/diagnosis* ; Precancerous Conditions/diagnosis*

Extensive studies have identified potential adverse effects on semen quality of obesity, based on body mass index, but the association between body fat distribution, a more relevant indicator for obesity, and semen quality remains less clear. We conducted a longitudinal study of 4304 sperm donors from the Guangdong Provincial Human Sperm Bank (Guangzhou, China) during 2017-2021. A body composition analyzer was used to measure total and local body fat percentage for each participant. Generalized estimating equations were employed to assess the association between body fat percentage and sperm count, motility, and morphology. We estimated that each 10% increase in total body fat percentage (estimated change [95% confidence interval, 95% CI]) was significantly associated with a 0.18 × 10 6 (0.09 × 10 6 -0.27 × 10 6 ) ml and 12.21 × 10 6 (4.52 × 10 6 -19.91 × 10 6 ) reduction in semen volume and total sperm count, respectively. Categorical analyses and exposure-response curves showed that the association of body fat distribution with semen volume and total sperm count was stronger at higher body fat percentages. In addition, the association still held among normal weight and overweight participants. We observed similar associations for upper limb, trunk, and lower limb body fact distributions. In conclusion, we found that a higher body fat distribution was significantly associated with lower semen quality (especially semen volume) even in men with a normal weight. These findings provide useful clues in exploring body fat as a risk factor for semen quality decline and add to evidence for improving semen quality for those who are expected to conceive.
Humans ; Male ; Adult ; Semen Analysis ; China ; Body Fat Distribution ; Longitudinal Studies ; Sperm Count ; Sperm Motility ; Body Mass Index ; Tissue Donors ; Obesity/complications* ; Spermatozoa ; Young Adult ; Middle Aged ; East Asian People

OBJECTIVES: To evaluate the effectiveness of single-balloon and double-balloon enteroscopy in diagnosing pediatric small bowel diseases and assess the diagnostic efficacy of computed tomography enterography (CTE) for small bowel diseases using enteroscopy as the reference standard. METHODS: Clinical data from 576 children who underwent enteroscopy at Hunan Children's Hospital between January 2017 and December 2023 were retrospectively collected. The children were categorized based on enteroscopy type into the single-balloon enteroscopy (SBE) group (n=457) and double-balloon enteroscopy (DBE) group (n=119), and the clinical data were compared between the two groups. The sensitivity and specificity of CTE for diagnosing small bowel diseases were evaluated using enteroscopy results as the standard. RESULTS: Among the 576 children, small bowel lesions were detected by enteroscopy in 274 children (47.6%).There was no significant difference in lesion detection rates or complication rates between the SBE and DBE groups (P>0.05), but the DBE group had deeper insertion, longer procedure time, and higher complete small bowel examination rate (P<0.05). The complication rate during enteroscopy was 4.3% (25/576), with 18 cases (3.1%) of mild complications and 7 cases (1.2%) of severe complications, which improved with symptomatic treatment, surgical, or endoscopic intervention. Among the 412 children who underwent CTE, the sensitivity and specificity for diagnosing small bowel diseases were 44.4% and 71.3%, respectively. CONCLUSIONS SBE and DBE have similar diagnostic efficacy for pediatric small bowel diseases, but DBE is preferred for suspected deep small bowel lesions and comprehensive small bowel examination. Enteroscopy in children demonstrates relatively good overall safety. CTE demonstrates relatively low sensitivity but comparatively high specificity for diagnosing small bowel diseases.
Retrospective Studies ; Treatment Outcome ; Double-Balloon Enteroscopy/statistics & numerical data* ; Single-Balloon Enteroscopy/statistics & numerical data* ; Humans ; Male ; Female ; Child ; Operative Time ; Tomography, X-Ray Computed/statistics & numerical data* ; Sensitivity and Specificity ; Intestine, Small/surgery* ; Intestinal Diseases/surgery*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective: To investigate the protective effects and underlying mechanisms of sodium pyruvate (SP) on RBC storage lesions using an oxidative damage model. Methods: Six units of leukocyte-depleted suspended RBCs (discarded for non-infectious reasons within three days post-collection) were randomly assigned to four groups: negative control (NS), positive control (PS), experimental group 1 (SP1), and experimental group 2 (SP2). Oxidative stress was induced in the PS group by the addition of hydrogen peroxide (H O ), while SP1 and SP2 received SP supplementation at different concentrations (25 mM and 50 mM, respectively) in the presence of H O . After 1 hour of incubation, RBC morphology was assessed microscopically, and biochemical indicators including glutathione (GSH), malondialdehyde (MDA), methemoglobin (MetHb), adenosine triphosphate (ATP), and Na /K -ATPase activity were measured. Results: RBCs in the PS group exhibited pronounced morphological damage, including cell shrinkage and echinocyte formation, whereas both SP-treated groups showed significantly reduced structural injury. SP treatment led to elevated GSH levels and decreased concentrations of MDA and MetHb, suggesting attenuation of oxidative stress. Additionally, SP enhanced intracellular ATP levels and Na /K -ATPase activity, thereby contributing to membrane stability. Notably, the SP2 group (50 mM) demonstrated superior protective effects compared to SP1 (25 mM). Conclusion: Sodium pyruvate effectively attenuates oxidative storage lesions in RBCs, primarily through its antioxidant properties, energy metabolism supporting ability, and celluar membrane stabilizing function. These findings suggest SP as a promising additive for enhancing the quality and safety of stored RBCs.

ObjectiveTo optimize the processing technology of honey bran-fried Rosae Laevigatae Fructus（h-RLF）， formulate relevant quality standards， and explore its improving effect and mechanism on mice with ulcerative colitis（UC） induced by dextran sodium sulfate（DSS）. MethodsTaking the content of polysaccharides and water-soluble extract as the indexes， L₉（3⁴） orthogonal test was used to optimize parameters of the amount of honey bran， frying time and frying temperature. The quality of 15 batches of h-RLF decoction pieces was evaluated according to the optimized process， and the inspection limit standard was preliminarily drawn up. Eighty SPF male Kunming mice were randomly divided into 8 groups， including the blank group， model group， mesalazine group（0.13 g·kg^-1）， RLF group（3.77 g·kg^-1）， bran-fried RLF group（3.77 g·kg^-1）， h-RLF low， medium and high dose groups（1.89， 3.77， 7.54 g·kg^-1）， with 10 mice in each group. The mice in the blank group were free to drink pure water， and the other groups were free to drink 3% DSS solution for 7 days to prepare UC mouse model. Each treatment group was given corresponding drugs by intragastric administration， and the blank and model groups were given equal volume of normal saline. The body weight of mice was recorded daily and the disease activity index（DAI） was calculated. After the administration， the colon tissues of mice were collected to observe the pathological changes by hematoxylin-eosin（HE） staining. The levels of tumor necrosis factor（TNF）-α， interleukin（IL）-1β， IL-6 and IL-10 in the colon of mice were detected by enzyme-linked immunosorbent assay（ELISA）. Western blot was used to detect the expression levels of phosphorylation nuclear transcription factor-κB p65（p-NF-κB p65）， Toll-like receptor 4（TLR4）， p-p38 mitogen-activated protein kinase（p-p38 MAPK）， p-extracellular signal-regulated kinase（p-ERK） and p-c-Jun N-terminal kinase（p-JNK） proteins in colon tissues. ResultsThe optimum processing technology of h-RLF was 20 g honey bran per 100 g RLF， and stir-frying at 200 ℃ for 8 min. The limit standard under the examination of h-RLF was preliminarily formulated as follows：the polysaccharide content should not be less than 25% based on anhydrous glucose（C₆H₁₂O₆）， the content of water-soluble extract should not be less than 38%， the moisture content should not be more than 12.0%， the total ash content should not be more than 5.0%， and the acid-insoluble ash content should not be more than 1.0%. The cluster heat map analysis showed that the quality of RLF from Huanggang， Hubei province was better. Animal experiments showed that compared with the blank group， the DAI score of the model group was significantly increased， the levels of TNF-α， IL-1β and IL-6 in the colon tissue were significantly increased， the IL-10 level was significantly decreased， the colonic mucosa was seriously damaged， accompanied by a large number of inflammatory cell infiltration， tissue congestion and a significant reduction in glands， and the expression levels of p-NF-κB p65， TLR4， p-p38 MAPK， p-ERK and p-JNK proteins were significantly increased（P<0.01）. Compared with the model group， each administration group could alleviate the symptoms of colonic ulcer， the structure of colonic crypt was basically intact， and the glands were arranged in an orderly manner. Among them， the high-dose group of h-RLF had a better effect， which could significantly reduce the DAI score and the levels of TNF-α， IL-1β and IL-6 in colon tissue（P<0.01）， and significantly increase the level of IL-10（P<0.01）， alleviate the colonic mucosal injury， and effectively inhibit the expression levels of p-NF-κB p65， TLR4， p-p38 MAPK， p-ERK and p-JNK proteins（P<0.01）. ConclusionThe key parameters of the processing technology of h-RLF are determined， and the optimized technology is stable and feasible. The established quality standard is simple and reliable， and can be used for the quality control. h-RLF can effectively alleviate DSS-induced UC， and its mechanism may be related to inhibiting the activation of NF-κB/TLR4/MAPK pathway.