ObjectiveTo systematically compare the differential regulation of the maternal-fetal interface cell lineages and communication networks in the CBA/J×DBA/2 mouse model of recurrent pregnancy loss （RPL） by the two classic therapeutic methods-tonifying the kidney to stabilize the fetus and invigorating the spleen to stabilize the fetus （Shoutai Wan， Juyuan Jian）-of traditional Chinese medicine （TCM） at the single-cell resolution and clarify their modern scientific connotations. MethodsFemale non-pregnant CBA/J mice were caged with male BALB/c （blank group） and DBA/2 （modeling group） mice separately. Pregnant mice in the modeling group were randomly grouped as follows： high/low-dose Shoutai Wan， high/low-dose Juyuan Jian， model （RPL）， and positive control （dydrogesterone）， with 10 mice in each group. Starting from the day after the detection of the vaginal plug， mice were administrated with drugs or an equal volume of normal saline by gavage for 10 consecutive days. After the intervention， the following indicators were measured. ① Macroscopic evaluation： general conditions， uterine wet weight， embryo loss rate， four coagulation parameters ［prothrombin time （PT）， activated partial thromboplastin time （APTT）， fibrinogen （FIB）， and thrombin time （TT）］， and peripheral blood estradiol （E₂） and progesterone （Pg） levels. The decidua with embryos was stained with hematoxylin-eosin （HE） and evaluated by transmission electron microscopy （TEM）. The expression of B-cell lymphoma-2 （Bcl-2）， vascular endothelial growth factor （VEGF）， angiotensin Ⅱ （AngⅡ）， matrix metalloproteinase-2 （MMP-2）， interleukin-6 （IL-6）， leukemia inhibitory factor （LIF）， CXC chemokine ligand 12 （CXCL12）， and microtubule-associated protein 1 light chain 3 homolog （LC3）Ⅰ/Ⅱ was quantified by Western blot. ② Mechanism analysis at the single-cell level： The decidua with embryos from the blank， model， high-dose Shoutai Wan， and high-dose Juyuan Jian groups （6 mice per group， with 3 single-cell samples per group， totaling 24 mice） were analyzed by the BD Rhapsody™ platform， and the whole-cell atlas was drawn by uniform manifold approximation and projection （UMAP） dimensionality reduction clustering combined with the single-cell mouse cell atlas （scMCA）. The differentially expressed genes （DEGs） and cell interaction networks were analyzed via Gene Ontology （GO）， Kyoto Encyclopedia of Genes and Genomes （KEGG）， and CellChat， and the protein-protein interaction （PPI） map of subtype cells was constructed. The CytoTRACE pseudo-temporal analysis was performed to explore the developmental trajectories of core immune cells （natural killer cells， NK cells） from maternal and fetal sources. Results① Pathological and Western blot results indicated that compared with the blank group， the RPL group showed an increase in the embryo loss rate （P<0.01）， down-regulated expression of Bcl-2， LIF， MMP-2， and Vegf in the decidua with embryos （P<0.05）， up-regulated protein levels of CXCL-12， AngⅡ， and IL-6 （P<0.05）， blocked angiogenesis， apoptosis-inflammation imbalance， and coagulation dysfunction. Both prescriptions dose-dependently reduced the abortion rate and restored the angiogenesis-inflammation balance， and Shoutai pill showed superior performance in restoring the E₂ level to the Pg level （P<0.05）. ② Single-cell transcriptome analysis indicated that compared with the blank group， the RPL group showed differences in multiple key cell populations such as decidual cells， trophoblast cells， endothelial cells， erythroblasts， NK cells， and macrophages at the maternal-fetal interface. Immunity and angiogenesis were the key links in RPL. Compared with the RPL group， high-dose Shoutai Wan reversed the changes of NK cells in the embryonic layer （upregulating the mRNA levels of 17 genes and downregulating the mRNA levels of 29 genes） and macrophages （upregulating the mRNA levels of 117 genes and downregulating the mRNA levels of 53 genes） through the regulation of gene expression. High-dose Shoutai pill regulated the immune cells to affect unfolded proteins， cell adhesion， and programmed cell death， thereby promoting decidualization and angiogenesis and modulating embryo-membrane development. High-dose Juyuan Jian regulated the key subgroups of NK cells （up-regulating the mRNA levels of 9 genes and down-regulating the mRNA levels of 17 genes） and macrophages （up-regulating the mRNA levels of 110 genes and down-regulating the mRNA levels of 81 genes）， which affected decidual inflammation and apoptosis and intervened in glycolysis. ③ The pseudo-temporal analysis and communication network indicated that the communication frequency of the RPL group decreased. High-dose Shoutai Wan restored maternal-fetal tolerance through pathways such as NKG2D， CDH5， GDF， and FASLG. High-dose Juyuan Jian enhanced the IL-6/LIFR/JAK/signal transducer and activator of transcription 3 （STAT3） and desmosome/SEMA6/tumor necrosis factor-like weak inducer of apoptosis （TWEAK） signaling to improve endometrial receptivity. The RPL group showed an increased proportion of toxic dNK7， a decreased proportion of reparative dNK4， and blocked embryo fNK1. High-dose Shoutai Wan down-regulated dNK7 and up-regulated dNK4. High-dose Juyuan Jian inhibited the terminal differentiation of dNK7 and up-regulated LILRB1， thus restoring the balance of cytotoxicity and repair. ConclusionBoth the kidney-tonifying and spleen-invigorating methods are effective in treating RPL. NK and macrophages are the key immune cells in the interaction between the embryo and the membrane. The kidney-tonifying method （Shoutai Wan） has an advantage in regulating the phenotypes of unfolded protein， cell adhesion， and programmed cell death， and shows expression characteristics closer to the physiological state in the regulation of NKG2D and CDH5 signals. The spleen-invigorating method （Juyuan Jian） has an advantage in regulating epithelial-mesenchymal transition （EMT）， angiogenesis， and glycolysis and shows higher communication intensity in the IL-6 and LIFR pathways.

Platelets are small, anucleated cells generated by cytoplasmic fragmentation and shedding from mature megakaryocytes. Upon vascular stimulation or injury, platelets become activated and adhere to exposed vascular endothelial cells, ultimately forming thrombi to promote blood coagulation and wound healing. In recent years, increasing evidence from in-depth studies on platelet function has revealed that autophagy plays a crucial role in platelet production and functional performance. Autophagy is an intracellular process of material recycling and reuse, involving autophagosome formation, cargo degradation, and nutrient recycling, which facilitates the maintenance of homeostasis and defense against pathogen infection. Numerous studies have demonstrated that autophagy participates in the regulation of platelet production, activation, and aggregation, and is closely implicated in the pathogenesis of platelet dysfunction-related diseases such as immune thrombocytopenia. Additionally, platelet-rich plasma therapy, by modulating the autophagic process, has shown great potential in treating osteoarthritis and promoting diabetic foot wound healing. This review thoroughly explores the potential roles of autophagy in regulating platelet production and function, as well as in platelet-related diseases. Future research should focus on the molecular mechanisms of platelet autophagy, investigate its dynamic changes under different disease conditions, and explore how autophagy modulation can improve platelet function and treat related diseases. This will provide a theoretical foundation for developing novel therapeutic strategies and is expected to bring breakthroughs in the treatment of platelet-related diseases.

Objective To evaluate the test-retest reliability of the ballistic push-up(BPU)test and establish predictive models for upper-limb strength and explosive power in young males.Methods A total of 71 male college students performed assessments of upper-limb bench press 1 repetition maximum(1RM)strength,bench press explosive power,and two BPU tests with a 48-hour interval.BPU test data were recorded using a three-dimensional(3D)force platform and motion capture system to calculate concentric metrics such as peak force(PF)and mean velocity(MV).The intraclass correlation coefficient(ICC)was used to examine the retest reliability of the BPU test.The Pearson correlation coefficient was used to evaluate the correlation of the BPU metrics with upper-limb strength and explosive power.Predictive models for upper-limb strength and explosive power were created using stepwise regression analysis.Results BPU metrics showed a good test-retest reliability(ICC=0.764-0.935).PF and MV,along with body weight(BW),were effective predictors of bench press 1RM in young males:bench press 1RM=0.129PF-16.772[R2=0.790,standard error of the estimate(SEE)=8.17 kg];bench press 1RM=1.511BW+87.15 MV-110.136(R2=0.767,SEE=8.60 kg).PF and BW were also predictors of bench press explosive power:bench press explosive power=2.755BW+0.287PF-17.351(R2=0.620,SEE=46.1 W).Conclusions The BPU test demonstrates a good test-retest reliability,and PF and MV from the BPU test can be used to predict upper-limb strength and explosive power in young males.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective To develop a risk prediction model for ischemic stroke in symptomatic intracranial atherosclerotic stenosis(ICAS)patients based on high-resolution magnetic resonance imaging(HR-MRI)and arterial spin labeling(ASL)imaging.Methods A total of 142 patients were included and divided into acute ischemic stroke(AIS)and transient ischemic attack(TIA)groups based on stroke occurrence.Clinical risk factors,plaque characteristics,and arterial transit artifact(ATA)presence on ASL images were compared between the two groups.Multivariate logistic regression analysis was performed,incorporating clinical risk factors,plaque characteristics,and double post labeling delay(PLD)ATA presence.The predictive value of different models was compared using receiver operating characteristic(ROC)curve and DeLong tests.Results Hypertension,positive lumen remodeling,plaque enhance-ment rate,1.5 s-ATA presence,and 2.5 s-ATA presence were independent risk factors for AIS(P＜0.05).The combination of HR-MRI and ASL imaging predicted AIS most effectively[area under the curve(AUC)=0.908;95％ confidence interval(CI)0.862-0.954].No significant difference was found between the prediction performances of HR-MRI and ASL(95％CI-0.041-0.082,Z=0.659,P=0.509).Conclusion ASL is more convenient than HR-MRI for predicting ischemic stroke in ICAS patients.A model combining plaque characteristics and ATA presence effectively predicts AIS occurrence.

Objective To evaluate the test-retest reliability of the ballistic push-up(BPU)test and establish predictive models for upper-limb strength and explosive power in young males.Methods A total of 71 male college students performed assessments of upper-limb bench press 1 repetition maximum(1RM)strength,bench press explosive power,and two BPU tests with a 48-hour interval.BPU test data were recorded using a three-dimensional(3D)force platform and motion capture system to calculate concentric metrics such as peak force(PF)and mean velocity(MV).The intraclass correlation coefficient(ICC)was used to examine the retest reliability of the BPU test.The Pearson correlation coefficient was used to evaluate the correlation of the BPU metrics with upper-limb strength and explosive power.Predictive models for upper-limb strength and explosive power were created using stepwise regression analysis.Results BPU metrics showed a good test-retest reliability(ICC=0.764-0.935).PF and MV,along with body weight(BW),were effective predictors of bench press 1RM in young males:bench press 1RM=0.129PF-16.772[R2=0.790,standard error of the estimate(SEE)=8.17 kg];bench press 1RM=1.511BW+87.15 MV-110.136(R2=0.767,SEE=8.60 kg).PF and BW were also predictors of bench press explosive power:bench press explosive power=2.755BW+0.287PF-17.351(R2=0.620,SEE=46.1 W).Conclusions The BPU test demonstrates a good test-retest reliability,and PF and MV from the BPU test can be used to predict upper-limb strength and explosive power in young males.

Objective To develop a risk prediction model for ischemic stroke in symptomatic intracranial atherosclerotic stenosis(ICAS)patients based on high-resolution magnetic resonance imaging(HR-MRI)and arterial spin labeling(ASL)imaging.Methods A total of 142 patients were included and divided into acute ischemic stroke(AIS)and transient ischemic attack(TIA)groups based on stroke occurrence.Clinical risk factors,plaque characteristics,and arterial transit artifact(ATA)presence on ASL images were compared between the two groups.Multivariate logistic regression analysis was performed,incorporating clinical risk factors,plaque characteristics,and double post labeling delay(PLD)ATA presence.The predictive value of different models was compared using receiver operating characteristic(ROC)curve and DeLong tests.Results Hypertension,positive lumen remodeling,plaque enhance-ment rate,1.5 s-ATA presence,and 2.5 s-ATA presence were independent risk factors for AIS(P＜0.05).The combination of HR-MRI and ASL imaging predicted AIS most effectively[area under the curve(AUC)=0.908;95％ confidence interval(CI)0.862-0.954].No significant difference was found between the prediction performances of HR-MRI and ASL(95％CI-0.041-0.082,Z=0.659,P=0.509).Conclusion ASL is more convenient than HR-MRI for predicting ischemic stroke in ICAS patients.A model combining plaque characteristics and ATA presence effectively predicts AIS occurrence.

The advancement of surgical techniques enables effective treatment for many patients with oral and maxillofacial tumors.How-ever,post-surgery problems such as chewing,swallowing and speech difficulty may arise due to the defects in speech organs and inade-quate compensatory function of tissue flap repair.Speech disorders,in particular,isolate patients by making it difficult for them to com-municate with others,not only impact their quality of life but also potentially lead to psychological problems and social interaction disor-ders.Although the decline in life quality and other related issues caused by speech dysfunction due to surgery and radiotherapy or chemo-therapy have been widely recognized,there is currently no standardized and universally applicable assessment method and standardized re-habilitation treatment management guideline or consensus for speech disorders following oral and maxillofacial tumor surgery at home and abroad.Based on previous clinical practice,combined with the characteristics of speech disorders in patients after oral and maxillofacial tumor surgery,the clinical experience of the experts in maxillofacial tumor surgery and rehabilitation and the relevant domestic and foreign literature,relevant experts organized discussions and modifications,reach a consensus on core content such as the assessment of speech disorders and the implementation plan for early rehabilitation treatment management,providing a reference for clinical practice,in order to improve patients'speech-related life quality and enhance the assessment and rehabilitation treatment techniques for speech disorders after oral and maxillofacial tumor surgery.

Objective:To summarize the clinical characteristics of autoimmune glial fibrillary acidic protein astrocytopathy(GFAP-A),in order to improve the understanding of the disease among clinical physicians.Methods:A retrospective analysis was conducted on the clinical manifestations,imaging examination,laboratory examination of a patient with GFAP-A who was admitted to the First People's Hospital of Yunnan Province and diagnosed on May 11,2023.Results:A female patient with GFAP-A,aged 67 years,presented with meningoencephalomyelitis.The head MRI showed abnormalities,with extensive lesions in the bilateral basal ganglia,pons,and lateral paraventricular white matter areas,and enhancement of the lateral ventricular ependyma and pia mater.Long segment spinal cord abnormal signals were observed,and cerebrospinal fluid anti GFAP antibodies were positive.After hormone treatment,the prognosis was good,and there was no recurrence during follow-up.Conclusion:The main clinical manifestations of GFAP-A are acute or subacute onset meningitis and/or encephalitis,myelitis and meningitis.Detection of autoimmune antibodies in ce-rebrospinal fluid can provide a clear diagnosis,and timely treatment can improve prognosis.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.