Objective This study established a qualitative and quantitative detection method for 9 new synthetic cannabinoids in e-cigarette oil using liquid chromatography-high resolution mass spectrometry.Methods E-cigarette oil was extracted with methanol,concentrated by nitrogen blowing under a water bath at 60℃,and separated using an Acquity UPLC? HSS T3(100 mm×2.1 mm,1.8 μm)column.Gradient elution was performed with ammonium acetate buffer solution(20 mmol/L)containing 0.1%formic acid and acetonitrile as the mobile phase.Detection was carried out in the positive ion mode of the HESI ion source using DDA(FullScan+dd-MS2)mode.Quantification was performed using the external standard method based on precise precursor ion peak areas,while qualitative analysis relied on retention times and characteristic fragment ions.Results The results showed that the standard curves of all 9 synthetic cannabinoids in blank e-cigarette oil matrix exhibited good linearity with R2 values>0.999.The limits of detection ranged from 0.0001 to 0.01 μg/g,and the limits of quantification ranged from 0.0003 to 0.03 μg/g.Recovery rates at low,medium,and high spiking levels in blank e-cigarette oil matrix ranged from 75.7%to 115%,with relative deviations<8.5%.Conclusion This method features a short instrument detection time of only 10 min,relatively simple operation,low detection limits,high accuracy,and good precision,making it applicable for rapid screening and quantitative analysis of synthetic cannabinoids in e-cigarette oil.

The prevalence of periodontitis in China is as high as 74.2％,making it the leading cause of tooth loss in adults and severely impacting both oral and overall health.The treatment of periodontitis and periodontal tissue regeneration are global challenges of significant concern.GE Shaohua's group at School and Hospital of Stomatology,Shandong University has focused on the key scientific issue of"re-modeling the periodontal inflammatory microenvironment and optimizing tissue repair and regeneration".They have elucidated the mechanisms underlying the persistence of periodontitis,developed bioactive ma-terials to enhance stem cell regenerative properties,and constructed a series of guided tissue regeneration barrier membranes to promote periodontal tissue repair,leading to the establishment of a comprehensive technology system for the treatment of periodontitis.Specific achievements and progress include:(1)Elucidating the mechanism by which key periodontal pathogens evade antimicrobial autophagy,leading to inflammatory damage;developing intelligent antimicrobial hydrogels and nanosystems,and creating metal-polyphenol network microsphere capsules to reshape the periodontal inflammatory microenviron-ment;(2)Explaining the mechanisms by which nanomaterial structures and electroactive interfaces regu-late stem cell behavior,developing optimized nanostructures and electroactive biomaterials,thereby effec-tively enhancing the regenerative repair capabilities of stem cells;(3)Creating a series of biphasic heterogeneous barrier membranes,refining guided tissue regeneration and in situ tissue engineering techniques,stimulating the body's intrinsic repair potential,and synergistically promoting the structural regeneration and functional reconstruction of periodontal tissues.The research outcomes of the group have innovated the fundamental theories of periodontal tissue regeneration,broken through foreign technologi-cal barriers and patent blockades,established a cascade repair strategy for periodontal regeneration,and enhanced China's core competitiveness in the field of periodontal tissue regeneration.

BACKGROUND:The combination of traditional Chinese medicine syndrome and semen quality-related parameters can jointly predict the occurrence of abnormal increase in sperm DNA fragmentation index (DFI) and draw a column chart,which can significantly improve clinical practicality and application efficiency,provide a basis for comprehensive evaluation of semen quality in clinical practice,take active intervention measures to improve clinical outcomes,and formulate personalized medical plans.OBJECTIVE:To explore the prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters.METHODS:Retrospective analysis was made on 420 infertile patients who received traditional Chinese medicine syndrome diagnosis and sperm DNA fragment rate examination in the Department of Traditional Chinese Medicine Andrology,Nanxishan Hospital of Guangxi Zhuang Autonomous Region from July 2019 to July 2021.According to the Manual of Human Semen Examination and Treatment Laboratories (6th Edition),137 patients with sperm DFI>30％ were included in the group of abnormally high sperm DFI,and 283 patients with sperm DFI ≤ 30％ were taken as the control group.First,univariate analysis was used to screen the influencing factors of the abnormal increase of sperm DFI.Then,the best matching factor was selected by using the collinearity problem of LASSO correction factors.Then,it was included in the multifactor forward stepwise logistic regression to find out its independent influencing factors and draw a nomogram.Finally,the receiver operating characteristic curve,calibration curve,decision curve analysis and clinical impact curve were used to verify the differentiation and accuracy of the prediction model and its clinical application effectiveness.RESULTS AND CONCLUSION:(1) The results of the univariate analysis showed that age,body mass index,forward motion rate,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney sperm deficiency syndrome were the influencing factors for the abnormal increase of sperm DFI (P<0.05).(2) The best matching factors further screened by LASSO regression were age,body mass index,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney essence deficiency syndrome (P<0.05).(3) Multifactor forward stepwise Logistic regression showed that age,body mass index,sperm concentration,total sperm motility,damp heat downpour syndrome,and kidney yang deficiency syndrome were six independent factors that caused the abnormal increase in sperm DFI.(4) Receiver operating characteristic curve showed that the area under the curve of the model group was 0.760(0.713,0.806),and the area under the curve of the validation group was 0.745(0.714,0.776).It showed that the prediction model had good discrimination.(5) The average absolute error of the calibration curve was 0.040,and the Hosmer Lemeshow test (P>0.05),suggesting that there was no significant statistical difference between the probability of the abnormal increase in DFI of spermatozoa predicted by the model and the probability of the abnormal increase in DFI of spermatozoa actually occurred,which confirmed that the model had good accuracy.(6) Decision curve analysis and clinical impact curve showed that the model group and validation group had the maximum clinical net benefit when the threshold probability values were (0.08-0.84) and (0.09-0.78) respectively,and had good clinical application efficiency within the threshold probability range.(7) These findings conclude that age,body mass index,sperm concentration,total sperm viability,damp heat downpour syndrome and kidney yang deficiency syndrome are independent factors that cause the abnormal increase in sperm DFI.The nomogram of the clinical prediction model constructed by them has good clinical prediction value and clinical application efficiency,and can provide the basis for comprehensive clinical evaluation of semen quality and individualized medical service.

This study collected data on 9 cases of fatal head injuries caused by adjustable wrenches and analyzed 16 types of injury characteristics of head injuries caused by adjustable wrenches.The distinctive patterns of head injuries caused by adjustable wrenches were summarized.A four level scoring model and scoring criteria were constructed for head injuries caused by adjustable wrenches.From a morphological perspective,it provided a reference for the inference of injury-causing instruments in forensic practice.

Objective This study established a qualitative and quantitative detection method for 9 new synthetic cannabinoids in e-cigarette oil using liquid chromatography-high resolution mass spectrometry.Methods E-cigarette oil was extracted with methanol,concentrated by nitrogen blowing under a water bath at 60℃,and separated using an Acquity UPLC? HSS T3(100 mm×2.1 mm,1.8 μm)column.Gradient elution was performed with ammonium acetate buffer solution(20 mmol/L)containing 0.1%formic acid and acetonitrile as the mobile phase.Detection was carried out in the positive ion mode of the HESI ion source using DDA(FullScan+dd-MS2)mode.Quantification was performed using the external standard method based on precise precursor ion peak areas,while qualitative analysis relied on retention times and characteristic fragment ions.Results The results showed that the standard curves of all 9 synthetic cannabinoids in blank e-cigarette oil matrix exhibited good linearity with R2 values>0.999.The limits of detection ranged from 0.0001 to 0.01 μg/g,and the limits of quantification ranged from 0.0003 to 0.03 μg/g.Recovery rates at low,medium,and high spiking levels in blank e-cigarette oil matrix ranged from 75.7%to 115%,with relative deviations<8.5%.Conclusion This method features a short instrument detection time of only 10 min,relatively simple operation,low detection limits,high accuracy,and good precision,making it applicable for rapid screening and quantitative analysis of synthetic cannabinoids in e-cigarette oil.

Background and Aims:Chronic skin ulcers are a significant disease affecting patients'daily lives and psychological well-being.Abnormalities in the cells and extracellular matrix within the tissue may disrupt the balance of the microenvironment,hindering the normal skin repair process and leading to delayed healing of the ulcer.There is currently a lack of research on the mechanisms underlying the development of chronic ulcers and their diagnostic biomarkers.Single-cell sequencing,a newly developed high-throughput sequencing method in recent years,uses gene sequencing at the single-cell resolution to precisely reveal disease mechanisms and has been applied in various diseases.This study used single-cell transcriptome sequencing(scRNA-Seq)to investigate the cellular heterogeneity in chronic skin ulcer tissue to elucidate the potential molecular mechanisms behind delayed healing and provide new insights for clinical treatment.Methods:The scRNA-Seq technology was used to compare the differences in cell subpopulations and gene expression between chronic ulcer tissue and normal skin tissue.Single cells were sorted using a microfluidic platform,and cDNA libraries were constructed for subsequent differential gene analysis and functional enrichment analysis.Results:scRNA-Seq analysis revealed significant immune-metabolic remodeling features in chronic ulcer tissue:the number of B cells,monocytes,and macrophages in ulcer tissue increased by 2.1 to 3.5 times compared to the normal tissue control.This was accompanied by widespread activation of collagen synthesis genes(COL1A1/COL3A1)and synergistic suppression of immune regulators(e.g.,granzyme family GZMA/GZMB/H).Cross-cell subpopulation functional network analysis showed that hypoxia response mediated by the HIF-1 signaling pathway and PI3K/Akt pathway abnormalities formed a positive feedback loop,exacerbating the imbalance in the secretion of inflammatory factors(CXCL3/8,TGFBI)and compensatory upregulation of mitochondrial oxidative phosphorylation.Conclusion:Chronic skin ulcers exhibit significant differences in cellular heterogeneity and gene expression,suggesting that chronic ulcers are not simply tissue defects but a complex pathological process dominated by chronic inflammation and immune dysregulation.The coordinated dysregulation of multiple cell subpopulations in the ulcer microenvironment,along with persistent inflammatory responses and metabolic abnormalities,is interconnected through the HIF-1/TNF/MAPK pathway network.Downregulation of granzyme gene family members and abnormal histone modifications may contribute to immune clearance defects,providing a theoretical basis for developing novel therapies targeting epigenetic regulation or mitochondrial function.

Blonanserin,a second-generation atypical antipsychotic agent,acts as an antagonist for dopamine D2,D3,and serotonin 5-HT2A receptors.Clinical studies have demonstrated that blonanserin is non-inferior to other antipsychotics,such as haloperidol and risperidone,in alleviating the symptoms of schizophrenia.Moreover,it exhib-its beneficial effects on cognitive symptoms and social functioning,with a favorable safety profile,making it one of the key treatment options for schizophrenia.With extensive clinical experience accumulated in China,this expert consensus aims to provide psychiatrists with updated and localized guidance on the optimal use of blonan-serin.Based on a systematic review of the latest evidence-particularly studies in Chinese population,this paper pres-ents the updated Chinese expert recommendations for the clinical use of blonanserin in 2024.

Objective:To carry out a systematic review of the development, introduction or validation of drug literacy assessment tools for adults at home and abroad, and to summarize and analyze the characteristics of the assessment tools.Methods:The research framework of the scoping review was used to systematically search 8 Chinese and English databases, such as China National Knowledge Infrastructure, China Biology Medicine disc, PubMed, Web of Science, and Embase. The search period was from database establishment to October 31, 2023. Studies on adult drug literacy assessment tools were screened and included, tool characteristics were extracted and analyzed, and ultimately the extracts were standardized for reporting.Results:A total of 31 articles that met the criteria were included, of which 26 were on the development and validation of assessment tools, three were on the localization and application of assessment tools, and two were on the revision of assessment tools, covering 33 assessment tools.Conclusions:It is needed to recognize the importance of drug literacy assessment, actively explore the diversity of drug literacy assessment tools, clarify the limitations of existing drug literacy assessment tools, further improve the reliability and validity of existing tools, continue to develop and introduce assessment tools suitable for China's national conditions, so as to increase the accuracy of drug literacy assessment.

Objective To analyze the technical movement characteristics of female table tennis play-ers with shoulder impingement syndrome when hitting a forehand topspin loop ball,in order to explore the reasons for shoulder impingement syndrome.Methods Thirteen female table tennis athletes with shoulder impingement syndrome were recruited for the shoulder impingement group(age 20.31±2.56 years,height 165.69±4.00 cm,weight 56.62±6.00 kg)and 13 healthy female table tennis athletes(age 21.54±2.78 years,height 165.54±4.45 cm,weight 60.08±8.02 kg)were selected for the healthy group.Kinematic and electromyographic data of the upper limbs were collected during six tri-als of forehand topspin strokes using a three-dimensional motion capture system and a wireless surface electromyographic system.The data were then averaged and compared between the groups.Results The shoulder impingement group had a greater shoulder flexion angular velocity at the end of the forward swing compared to the healthy group(t=-3.689,P=0.001).In addition,the shoulder impingement group showed significantly smaller trunk torsion angular amplitude(t=2.614,P=0.015)and average an-gular velocity of trunk torsion(t=3.958,P=0.001).Furthermore,the peak activation level of the anteri-or serratus muscle was smaller in the shoulder impingement group compared to the healthy group(t=2.363,P=0.027).Finally,the deactivation duration of both the triceps brachii and brachioradialis mus-cles was shorter in the shoulder impingement group compared to the latter(t=3.705,P=0.002;t=3.29,P=0.004).Conclusion Female table tennis players with shoulder impingement syndrome exhibit the fol-lowing characteristics in their forehand topspin:1)insufficient trunk rotation and premature deactiva-tion of the brachioradialis muscle,which lead to excessive loading on the shoulder during flexion;2)inadequate activation of the serratus anterior muscle,resulting in compromised scapular stability;3)premature deactivation of the triceps brachii muscle,which negatively affects the control of eccentric contraction velocity at the shoulder joint.

BACKGROUND:The sports medicine community has widely called for the use of machine learning technology to efficiently process the huge and complicated sports data resources,and construct intelligent sports injury prediction models,enabling accurate early warning of sports injuries.It is of great significance to comprehensively summarize and review such research results so as to grasp the direction of early warning model improvement and to guide the construction of sports injury prediction models in China. OBJECTIVE:To systematically review and analyze relevant research on sports injury prediction models based on machine learning technology,thereby providing references for the development of sports injury prediction models in China. METHODS:Literature search was conducted on CNKI,Web of Science and EBSCO databases,which mainly searched for literature related to machine learning techniques and sports injuries.Finally,61 articles related to sports injury prediction models were included for analysis. RESULTS AND CONCLUSION:(1)In terms of external risk feature indicators,there is a lack of competition scenario indicators,and the inclusion of related feature indicators needs to be further improved to further enrich the dimensions of the dataset for model training.In addition,the inclusion feature weighting methods of the sports injury prediction model are mainly based on filtering methods and the use of embedding and wrapping weighting methods needs to be strengthened in order to enhance the analysis of the interaction effects of multiple risk factors.(2)In terms of model body training,supervised learning algorithms become the mainstream choice.Such algorithms have higher requirements for the completeness of sample labeling information,and the application scenarios are easily limited.Therefore,the application of unsupervised and semi-supervised algorithms can be increased in the later stage.(3)In terms of model performance evaluation and optimization,the current studies mainly adopt two verification methods:HoldOut crossover and k-crossover.The range of AUC values is(0.76±0.12),the range of sensitivity is(75.92±11.03)%,the range of specificity is(0.03±4.54)%,the range of F1 score is(80.60±10.63)%,the range of accuracy is(69.96±13.10)%,and the range of precision is(70±14.71)%.Data augmentation and feature optimization are the most common model optimization operations.The accuracy and precision of the current sports injury prediction model are about 70%,and the early warning effect is good.However,the model optimization operation is relatively single,and data augmentation methods are often used to improve model performance.Further adjustments to the model algorithm and hyperparameters are needed to further improve model performance.(4)In terms of model feature extraction,most of the internal risk profile indicators included are mainly based on anthropometrics,training load,years of training,and injury history,but there is a lack of sports recovery and physical function indicators.