Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding developed a strategy for platelet and plasma infusion management in critically ill children based on systematic reviews and consensus meetings of international multidisciplinary experts. One good practice statement and six expert consensus statements were proposed for plasma and platelet transfusions in critically ill children following severe trauma, traumatic brain injury, and/or intracranial hemorrhage. This article introduces the specific methods and basis for the formation of recommendations in this part of the guide.

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 To explore the pathological features of bronchiolar adenoma(BA)and its specific high-resolution computed tomography(HRCT)signs,and to differentiate BA from minimally invasive adenocarcinoma(MIA)using a non-invasive preoperative method.Methods A total of 80 patients with BA and 130 patients with MIA were retrospectively selected,and the clinical information and HRCT features were compared.All cases were divided into development set and test set at a 7︰3 ratio.Logistic regression analysis was used to screen the independent predictors of MIA and construct a model.Results There were significant differences in age,lobe distribution,density,vacuole sign,tumor-related vessels number(TVN),and distance to pleura(DTP)between BA and MIA patients(P<0.05).Age,density,TVN,DTP and long diameter were identified as independent predictors of MIA.A model was constructed,with area under the curve(AUC)of 0.887 and 0.884 in the development and test sets,respectively.Conclusion The model based on HRCT morphological features of BA and MIA demonstrates superior diagnostic performance compared to individual CT morphological features.

Objective:To systematically evaluate the current status and methodological quality of guideline and consensus in ovarian stimulation for in vitro fertilization (IVF), and to provide reference for the development of future guidelines and research. Methods:A systematic search was conducted in databases including PubMed, Embase, CNKI, Wanfang, Sinomed and relevant guideline websites from inceptions to October 2024. Data were extracted from the literature that met the inclusion criteria, and methodological quality was assessed using the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) tool. Descriptive analysis was performed with results presented in visual data charts.Results:A total of 23 studies were included, with 8 guidelines and 15 consensus. Totally 21 (91.3%) studies focused on the selection of ovarian stimulation protocols, with the majority concentrating on protocols for patients undergoing IVF treatment for the first cycle, and 12 (52.2%) studies focused on the selection of gonadotropin starting dosage. In terms of methodology, the average standardized scores in the 6 assessment domains of the AGREE Ⅱ tool were as follows: scope and purpose (85.1%), stakeholder involvement (66.6%), rigour of development (36.5%), clarity of presentation (70.1%), applicability (36.4%), and editorial independence (46.2%).Conclusion:Current recommendations in ovarian stimulation for IVF exhibit inconsistencies, and the methodological quality varies, which partially hinders the translation of evidence into clinical practice. Future research should further focus on the selection of ovarian stimulation protocols and gonadotropin starting dosage, promoting the update and refinement of guidelines and consensus to guide the precise treatment of ovarian stimulation.

Objective To investigate the factors that influence ocular surface biology and visual acuity in individuals with diabetic dry eye(DDE)and analyze how these factors contribute to changes in visual quality.Methods Based on the disease duration,fasting blood glucose(FBG),and glycated hemoglobin(HbA1c)levels of patients with type 2 diabe-tes mellitus(T2DM),the DDE patients were divided into different groups.Logistic regression analysis was used to identify influencing factors related to ocular surface biology and visual quality in each group of DDE patients.Tear film stability was evaluated based on the tear film rupture time(BUT),Schirmer I test(SIt),and ocular surface disease index(OSDI).Lip-iview? Surface interferometers were used to measure tear film lipid layer thickness(LLT),meibomian gland loss rate(MGP),meibomian gland opening number(MGYLS),and meibomian gland secretion score(MGYSS).Wavefront aber-rometry was used to measure corneal wavefront aberration values at 4 mm and 6 mm pupil diameters.Ocular response ana-lyzer(ORA)was adopted to analyze corneal hysteresis(CH)and corneal resistance factor(CRF).Moreover,ELISA ex-periment to evaluate the trend of changes in inflammatory factors in tears.Results Logistic regression analysis revealed that T2DM duration,smoking history,FBG,HbA1c,total cholesterol(TC),triglycerides(TG),OSDI score,LLT,BUT,SIt,MGP,MGYLS,MGYSS,total higher-order aberrations,spherical aberration,coma aberration,trefoil aberration,tumor necrosis factor-α,interleukin-6,matrix metalloproteinase-9,receptor for advanced glycation end products,and insu-lin were all influencing factors for the risk of DDE(all P＜0.05).As the T2DM course prolonged and FBG or HbA1 c levels rose,tear film-related indicators(LLT,BUT,and SIt)and meibomian gland-related indicators(MGYLS and MGYSS)inpa-tients gradually decreased,while OSDI scores and MGP gradually increased(all P＜0.05).As the T2DM course prolonged and FBG or HbA1c levels rose,the total higher-order aberrations,spherical aberration,coma aberration,and trefoil aber-ration in DDE patients under 4 mm and 6 mm pupil diameters gradually increased;Meanwhile,best corrected visual acuity,corneal hysteresis,and corneal resistance factor gradually decreased;The contents of tumor necrosis factor-α,interleukin-6,matrix metalloproteinase-9,receptor for advanced glycation end products,and insulin in tears all gradually increased,while mucin-5AC gradually decreased(all P＜0.05).Conclusion With the prolongation of T2DM duration and the in-crease of FBG or HbA1c,the ocular surface inflammatory response in DDE patients gradually worsens,corneal biological function decreases,and visual quality deteriorates.Timely systemic and local interventions are of great significance for im-proving dry eye symptoms and visual quality in DDE patients.

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

This study aims to establish BHK-21 stable cell lines expressing APN from four species(human,pig,dog,and cat),the APN fragments were amplified from pEGFP-C1-APN plasmids of the four species stored in the laboratory to generate the recombinant plasmids pcDNA4.0-APN.Af-ter the recombinant plasmids were transfected into BHK-21 cells,the stable BHK-21 cell lines ex-pressing the APNs were selected by two rounds of limited dilution.The constructed BHK-21 cell lines were identified by indirect immunofluorescence assay(IFA),and their susceptibility to PD-CoV and TGEV was tested for these four cell lines.Virus infection experiments revealed that PD-CoV infected cells expressing human,pig,and dog APNs,while it did not infect cells expressing cat APN.Simultaneously,TGEV infected cells expressing pig,dog,and cat APNs,but did not infect cells expressing human APN.The results suggest that the risk of cross-species infection for different coronaviruses and the established cell line can be used effectively to evaluate the virus in-fection.The findings also revealed that PDCoV has the potential risk of cross-species infection of human and dog,and TGEV has the potential risk of cross-species infection of dog and cat.These results provide a basis for the prevention and control strategy of coronaviruses.

Objective:To construct and validate a predictive model for postoperative pulmonary complications (PPCs) in patients undergoing robot-assisted laparoscopic urological surgery.Methods:This retrospective study included the medical records of 932 patients who underwent robot-assisted laparoscopic urological surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to February 2022. The patients were divided into a training group ( n=559) and a validation group ( n=373) at a 6∶4 ratio. Logistic regression analysis was used to determine the independent risk factors for PPCs, and a nomogram prediction model was constructed based on these factors. The performance of the model was evaluated using the receiver operating characteristic curve and calibration curve, and the clinical benefit was assessed using the clinical decision curve analysis. Results:The independent risk factors for PPCs included advanced age (>60 yr), smoking history, respiratory tract infection within 1 month, preoperative low SpO 2 (<96%), and prolonged length of postoperative hospital stay ( P<0.05), and the body mass index (18.5-<28.0 kg/m 2) was a protective factor. The nomogram prediction model developed based on the aforementioned 6 influencing factors had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.76-0.86) in training group and 0.80 (95% confidence interval 0.75-0.86) in validation group. The calibration curve indicated a good consistency between the predicted and actual occurrence curves, and the clinical decision curve analysis showed good accuracy and net benefit of the prediction model. Conclusions:The predictive model for PPCs is successfully constructed based on age, low body mass index, smoking history, history of respiratory tract infection within 1 month, preoperative low SpO 2 and prolonged length of postoperative hospital stay and has good predictive performance in patients undergoing robot-assisted laparoscopic urological surgery.

Objective:To explore the value of an integrated modeling approach combining radiomics, dosiomics, and clinical factors in the prediction of the locoregional recurrence (LRR) risk after radiotherapy for patients with locoregionally advanced hypopharyngeal squamous cell carcinoma (HPSCC), in order to provide supplementary clinical evidence and decision-making basis for personalized treatment for this rare disease characterized by low incidence and poor prognosis.Methods:The clinical images and pathological data were retrospectively enrolled from 76 HPSCC patients treated at the Peking University Cancer Hospital from October 2011 to July 2020. The planning gross tumor volumes (PGTVs) were taken as the volumes of interest (VOIs). A total of 1 316 radiomic and dosiomic features were extracted from the planning CT and dose distribution images. After stability testing, feature dimensionality reduction was achieved using least absolute shrinkage and selection operator (LASSO) regression and principal component analysis (PCA), with radiomic principal components (RPCs) and dosiomic principal components (DPCs) obtained, respectively. Using various combinations of RPCs, DPCs, and clinical variables as predictors, multivariate Cox regression models were developed after 5-fold cross-validation 100 times. The model performance was evaluated based on the Akaike information criterion (AIC) and concordance index (C-index).Results:Using two RPCs and three DPCs selected, dosiomics and radiomic Cox proportional hazards models were constructed, with C-index values of 0.781 and 0.778 and AIC values of 94.44 and 92.27, respectively. The result indicated that one RPC and three DPCs showed significant associations in Cox regression ( P < 0.05). Other prediction models were established by integrating the clinical data of patients with radiomic features, dosiomic features, or both. The prediction result demonstrated that compared to models based on individual factors or dual components, the multi-omics model yielded the highest prediction accuracy (C-index: 0.823, AIC: 84.94). Conclusions:Integrated models that combine radiomic features, dosiomic features, and clinical factors demonstrate great potential for enhancing the accuracy of LRR risk prediction. These models are expected to provide decision-making support for devising personalized treatment strategies and ultimately improve the prognosis of HPSCC patients.

Objective:To systematically evaluate the current status and methodological quality of guideline and consensus in ovarian stimulation for in vitro fertilization (IVF), and to provide reference for the development of future guidelines and research. Methods:A systematic search was conducted in databases including PubMed, Embase, CNKI, Wanfang, Sinomed and relevant guideline websites from inceptions to October 2024. Data were extracted from the literature that met the inclusion criteria, and methodological quality was assessed using the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) tool. Descriptive analysis was performed with results presented in visual data charts.Results:A total of 23 studies were included, with 8 guidelines and 15 consensus. Totally 21 (91.3%) studies focused on the selection of ovarian stimulation protocols, with the majority concentrating on protocols for patients undergoing IVF treatment for the first cycle, and 12 (52.2%) studies focused on the selection of gonadotropin starting dosage. In terms of methodology, the average standardized scores in the 6 assessment domains of the AGREE Ⅱ tool were as follows: scope and purpose (85.1%), stakeholder involvement (66.6%), rigour of development (36.5%), clarity of presentation (70.1%), applicability (36.4%), and editorial independence (46.2%).Conclusion:Current recommendations in ovarian stimulation for IVF exhibit inconsistencies, and the methodological quality varies, which partially hinders the translation of evidence into clinical practice. Future research should further focus on the selection of ovarian stimulation protocols and gonadotropin starting dosage, promoting the update and refinement of guidelines and consensus to guide the precise treatment of ovarian stimulation.