Stroke ranks as the third leading cause of death and the fourth leading cause of disability worldwide. Its high disability rate and prolonged recovery period not only severely impact patients' quality of life but also impose a significant burden on families and society. Primary prevention is the cornerstone of stroke control, as early intervention on risk factors can effectively reduce its incidence. Therefore, the development of predictive models for first-ever stroke risk holds substantial clinical value. In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. Second, there is a need to diversify data types and optimize model architectures to construct more comprehensive and precise predictive models. Lastly, particular attention should be given to the clinical validation of models in real-world settings. This not only enhances the robustness and generalizability of the models but also promotes physicians' understanding of predictive models, which is crucial for their application and dissemination.

Objective:To assess the prevalence of dentinal hypersensitivity (DH) and related factors in urban adults in China.Methods:The study was designed as an observational, cross-sectional epidemiological study carried out in adults aged 18-69 years old in seven cities (Beijing, Shanghai, Wuhan, Chengdu, Xi′an, Guangzhou, and Harbin) of China. The study was conducted from March 2021 to May 2023. Patients were required to complete a questionnaire regarding the subjects′ socio-economic factors, dietary behavior, oral health behavior and personal antecedent factors. DH was clinically diagnosed by judging whether the tooth cold air stimulation provoked DH or not, and recorded by investigator pain rating Schiff score. Compare the findings of six cities (Harbin excluded) with a similar study conducted in 2008.Results:In total, 11 622 subjects from seven cities in China participated the study. Fifty two point two percent (6 072/11 622) of subjects reported DH in questionnaire, 36.7% (4 266/11 622) of subjects reported experiencing DH in response to cold air stimulation for at least one study tooth. Risk factors including age, sex, city, toothbrush method and acid reflux showed marked associations with DH ( P<0.05). The prevalence of DH of urban residents in six cities (Harbin excluded) was 33.7% (3 335/9 882), higher than that in 2008 [29.7%(2 354/7 939)]. Conclusions:Overall, DH was common among urban adults in China and the prevalence increased in recent years. Better understanding of DH and its associated factors should be considered in its prevention and management by dental professionals.

Objective:To investigate alterations in brain functional connectivity (FC) in schizophrenia (SZ) model rats treated with Yudian decoction by using functional magnetic resonance imaging (fMRI).Methods:At 17th day of gestation in healthy SPF grade SD rats, a single intraperitoneal injection of methylazoxymethanol (MAM) (25 mg/kg) was used to induce abnormalities in monoamine neurotransmitters in pregnant female rats, thereby to establish a model of neural development abnormalities in the offspring. Four weeks old male offspring were selected as SZ model rats.Thirty SZ model rats were divided into model group, experimental group, and positive control group according to the body mass matching method, with 10 rats in each group. Additionally, 10 male offspring born to healthy female rats were selected as the blank control group.At 6 weeks of age, the rats in experimental group and positive control group were administered with Yudian decoction (1.54 g/kg) and risperidone (0.24 mg/kg) by gavage, respectively. The rats in blank control group and positive control group were administered with distilled water (6.7 mL/kg) by gavage.All the above interventions were conducted once a day for 14 consecutive days.The fMRI data were acquired from all samples using a 3.0 T MRI scanner. The bilateral hippocampus, bilateral prefrontal cortex, and bilateral striatum were designated as region of interest (ROI). FC comparisons between each pair of ROIs and whole-brain FC were conducted using two-sample t-test. Results:(1) Compared to the control group, the model group demonstrated enhanced whole-brain FC at the left cerebellar granular cell level (SIGMA: x=-2, y=-107, z=48) (cluster size=43, P<0.05, FWE adjusted under cluster-level). The experimental group exhibited increased whole-brain FC at the left cerebellar molecular layer (SIGMA: x=-5, y=-152, z=36) compared to the model group (cluster size=48, P<0.05, FWE adjusted under cluster-level). (2) Using the bilateral hippocampus as ROI, the positive control group exhibited enhanced FC at the deep layer of the superior colliculus (SIGMA: x=13, y=-77, z=27) compared to the model group (cluster size=88, P<0.05, FWE adjusted under cluster-level). The blank control group displayed decreased FC at the right granular insular cortex (SIGMA: x=43, y=19, z=9) compared to the model group (cluster size=125, P<0.05, FWE adjusted under cluster-level). Utilizing the bilateral prefrontal cortex as ROI, the experimental group showed reduced FC at the left cerebellar molecular layer (SIGMA: x=-14, y=-128, z=48) compared to the blank control group (cluster size=68, P<0.05 FWE adjusted under cluster-level). Conclusion:Schizophrenia is associated with abnormal whole-brain functional connectivity, notably characterized by enhanced functional connectivity in the hippocampal region.Yudian decoction demonstrates the capability to inhibit activity in the prefrontal cortex.

Objective To observe the value of dual-energy CT(DECT)radiomics combined with clinical and CT features for predicting differentiation degree of gastric adenocarcinoma(GAC).Methods Totally 254 patients with GAC were prospectively analyzed and divided into high-grade group(low differentiation GAC,n=88)and low-grade group(middle-high differentiation GAC,n=166)according to pathological results.The patients were also divided into training set(n=203,including 70 high-grade and 133 low-grade GAC)and verification set(n=51,including 18 high-grade and 33 low-grade GAC)at the ratio of 8∶2.Radiomics features were extracted and screened based on venous phase single-level(40,70,100 and 140 keV)DECT,and a multi-energy radiomics model was constructed to predict GAC classification.Univariate analysis and multivariate logistic regression were used to analyze clinical and CT features as well as DECT parameters in training set to construct a clinic-CT model.Then a combined model was constructed through combining clinic-CT model with radiomics model.The predictive efficacy of the models were evaluated,and the calibration degree of the combined model was assessed.Results The area under the curve(AUC)of clinic-CT model,multi-energy radiomics model and combined model was 0.74,0.75 and 0.78 in training set,and 0.73,0.77 and 0.78 in verification set,respectively.Except for AUC of combined model was higher than that of clinic-CT model in training set(P＜0.05),no significant difference of AUC was found among models in training set nor verification set(all P＞0.05).The calibration degree of combined model was good in both training set and verification set(both P＞0.05).Conclusion DECT radiomics combined with clinical and CT features could effectively predict differentiation degree of GAC.

Objective To observe the value of spectral CT parameters for evaluating T staging of advanced gastric cancer(AGC).Methods Totally 155 AGC patients were collected and divided into T2 stage(n=40)and T3/4a stage(n=115)according to postoperative pathology.CT values,water concentration(WC)and iodine concentration(IC)of AGC lesions on 40-140 keV arteriovenous phase single energy level images were measured,and the standardized IC(nIC)and spectral curve slopes k1 and k2 were calculated.Clinical variables and spectral quantitative parameters were compared between groups,and receiver operating characteristic curve was plotted,the area under the curve(AUC)was calculated to evaluate the value of each parameter and model for identifying T2 and T3/4a stage AGC.Results Tumor thickness,proportion of low differentiation degree,CT100kev,CT140kev,and WC values in T3/4a group were all significantly higher than those in T2 group(all P＜0.05).CT140keV of AGC lesions on venous phase images presented the highest discrimination efficacy among single parameters,with AUC of 0.782.AUC of clinical-arterial phase-venous phase model was 0.848,higher than that of clinical model and arterial phase model alone(both P＜0.05)but not significantly different compared with AUC of venous phase model(P＞0.05).Conclusion Spectral CT quantitative parameters,especially venous phase parameters could be used to effectively identify T stage of AGC.Multi-parameter combined models had higher diagnostic value.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To assess the quality of low-keV monoenergetic images using deep learning image reconstruction (DLIR) algorithm combined with dual energy CT (DECT) in gastric cancer and to compare them with images from the conventional adaptive statistical iterative reconstruction (ASiR-V) algorithm.Methods:In this cross-sectional study, DECT images of 31 gastric cancer patients in the First Affiliated Hospital of Zhengzhou University were prospectively collected from September 2022 to March 2023. The 55 keV monoenergy images were reconstructed using the DLIR algorithm at low-, medium-, and high-intensity levels (DLIR-L, DLIR-M, and DLIR-H) based on arterial phase and venous phase images, respectively. The 70 keV 40% mixing coefficient (ASiR-V40%) images were reconstructed using the ASiR-V algorithm. In the objective evaluation of images, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for both lesions and muscle were calculated across four sets of reconstructed images. In the subjective evaluation of images, scores were assigned to the overall image quality, lesion visibility, and diagnostic confidence for each set of reconstructed images. Comparisons of SNR and CNR between the 4 groups were made by One-way repeated-measures ANOVA or Friedman′s test. Comparisons of scores were made by Friedman′s test. The P value of pairwise comparison was adjusted using Bonferroni correction methods. Results:In the objective evaluations, CNR lesion, SNR lesion and SNR muscle were highest on the 55 keV DLIR-H images in the arterial and venous phases, and showed a gradually increasing trend on the 70 keV ASiR-V40%, 55 keV DLIR-L, DLIR-M, DLIR-H images ( P<0.05). In subjective evaluations, compared to the 70 keV ASiR-V40% images, overall image quality scores were numerically higher for the 55 keV DLIR-H ( P>0.05), similar or slightly worse for the 55 keV DLIR-M, and significantly lower for the 55 keV DLIR-L ( P<0.05). The lesion visibility and diagnostic confidence on the 55 keV DLIR reconstruction images were higher in both arterial and venous phases than 70 keV ASiR-V40% images ( P<0.05). Conclusions:Compared to the conventional 70 keV ASiR-V40% images, the 55 keV DLIR-H images had higher lesion contrast and diagnostic confidence with lower image noise. The 55 keV DLIR-M images had comparable overall image quality to 70 keV ASiR-V40% images, but the former had higher lesion contrast and diagnostic confidence. The 55 keV DLIR-L was unable to improve image quality to the level of 70 keV ASiR-V40%.

Objective To investigate the effect of long non-coding RNA(lncRNA)macrophage migration inhibitory factor antisense RNA1(MIF-AS1)on the malignant biological behavior of prostate cancer(PC)cells by regulating the miR-423-5p/pyrroline-5-carboxylic acid reductase 1(PYCR1)axis.Methods PC3 cells were cultured in vitro to knock down the expression of MIF-AS1 or down-regulate the expression of miR-423-5p.The expression of MIF-AS1,miR-423-5p and PYCR1 mRNA in tumor tissues and adjacent tissues and cells of PC patients were detected.The cell proliferation,apoptosis,migration,and invasion were detected and the expression of PYCR1 protein was detected by Western blot.The relationships between miR-423-5p,IF-AS1 and PYCR1 were verified.Results The MIF-AS1 and PYCR1 mRNA were observed to be highly expressed in the tumor tissues,while miR-423-5p was lowly expressed.Silenced MIF-AS1 inhibited the proliferation,migration and invasion of PC3 cells and up-regulated miR-423-5p induced cell apoptosis(P＜0.05).Inhibition of miR-423-5p expression reversed the inhibitory effect of silencing MIF-AS1 on malignant behavior of PC3 cells(P＜0.05).miR-423-5p was correlated with MIF-AS1 and PYCR1 by targeted regulation.Conclusion Silencing MIF-AS1 may inhibit the expression of PYCR1 by up-regulating miR-423-5p,thereby inhibiting the malignant behavior of PC cells.

Objective To evaluate the safety and efficacy of CT-guided needle puncture biopsy of pancreatic lesions through gastrointestinal space.Methods Data of 96 patients with single pancreatic lesion who underwent CT-guided needle puncture biopsy through gastrointestinal space were retrospectively analyzed,and the success rate of puncture biopsy was recorded.The diagnostic efficacy of biopsy pathology was evaluated based on surgical pathology and follow-up results,and the relative complications were observed.Results Puncture biopsy was successfully completed in all 96 cases(96/96,100%).The sensitivity of biopsy pathology diagnosis was 97.75%(87/89),with specificity of 100%(7/7),positive predictive value of 100%(87/87),negative predictive value of 77.78%(7/9)and accuracy of 97.92%(94/96).Complications were noticed in 6 cases,including small amount of peripancreatic effusion in 3 cases,small amount of abdominal effusion in 1 case and intermittent fever in 2 cases,which were all improved.No other complication occurred.Conclusion CT-guided needle puncture biopsy of pancreatic lesions through gastrointestinal space was safe and effective.

Objective To observe the value of CT radiomics-based nomogram for predicting difference of Lauren types of gastric cancers between endoscopic biopsy and postoperative pathology.Methods Totally 126 patients with gastric cancer diagnosed by surgical pathology were retrospectively analyzed.The patients were divided into concordant group(n=77)and inconsistent group(n=49)according to the concordance between endoscopic biopsy and postoperative pathology results or not,also divided into training set and validation set at the ratio of 2∶1.Clinical predictors were screened,then a clinical prediction model was constructed.Radiomics features were extracted based on venous-phase CT images and screened using L1 regularization.Radiomics models were constructed using 3 machine learning(ML)algorithms,i.e.decision trees,random forests and logistic regression.The nomogram based on clinical and the best ML radiomics model was constructed,and the efficacy and clinical utility of the above models and nomogram for predicting inconsistency of Lauren types of gastric cancers between endoscopic biopsy and postoperative pathology were evaluated.Results Patients'age,platelet count,and arterial-phase CT values of tumors were all independent predictors of inconsistency between endoscopic biopsy and postoperative pathology of Lauren types of gastric cancer.CT radiomics model using random forests algorithm showed better predictive efficacy among 3 ML models,with the area under the curve(AUC)of 0.835 in training set and 0.724 in validation set,respectively.The AUC of clinical model,radiomics model and the nomogram in training set was 0.764,0.835 and 0.884,while was 0.760,0.724 and 0.841 in validation set,respectively.In both training set and validation set,the nomogram showed a good fit and considerable clinical utility.Conclusion CT radiomics-based nomogram had potential clinical application value for predicting inconsistency of Lauren types of gastric cancers between endoscopic biopsy and postoperative pathology.