Objective To investigate the gender differences and the effect of three factors(the angle of rotation, left/right,palm/back) on hand mental rotation. Methods 40 healthy adults (20 males and 20 females, age; 18～26 years) were enrolled in this study. By simulation of human hand as picture stimuli,participants were instructed to decide as quickly as possible whether the stimulus was a left or right hand. The accuracy rate and reaction time of the behavior task were quantified. Results ① the subjects' reaction speed was far slower at 180° than 0°(P＜0.01). ②On judgment of 0° back picture,females were faster than males(left back: males( 1033. 16 ±245.85) ms,females( 853.15 ± 142.79) ms,P=0.014; right back; males( 973.07 ±217.11) ms;,females (796.28 ±146.67 )ms, P = 0.016). And,the right hand was responded faster than left hand,with statistical significance (males; P = 0.028, females; P=0.038). ③The time of females in judging the 0° hand back ( left (853. 15 ± 142.79) ms,right (796. 27 ± 146. 67 ms) ) was shorter than palm(left ( 1002. 72 ± 227. 91) ms,right ( 986.06 ± 230. 03) ms), reached statistical significance ( both at P ＜ 0. 001). In contrast, males in judging the 180° pictures, the speed of reaction to back(left ( 1252. 70 ±269. 35) ms,right ( 1216. 68 ±293. 54 )ms) was slower than palm with statistical significance (left: P ＜ 0. 01, right: P = 0. 015). Conclusion The three factors (angle of rotation,left/right,and palm/back) all exert effect on the behavior of hand mental rotation. It really has gender difference on hand mental rotation. Females response faster than males.

ObjectiveTo investigate the effects of eyes-closed (EC) and eyes-open (EO) EEG field powers on the auditory P300 evoke potentials.MethodsThe EEG was recorded in 12 healthy male college students (20 ～24 years) respectively in their eyes-closed and eyes-open states,and then the auditory P300 paradigm was performed.Results① Alpha band was distributed at the posterior-occipital area,while Alpha-1 (7.5～9.5 Hz) field power were EC as (2.62 ±0.81 ) μV2 and EO as ( 1.80 ±0.56) μV2,with statistical significance (P ＜ 0.01 ) ; Alpha-2 ( 10 ～ 12 Hz) field power were EC as ( 8.55 ± 1.85 ) μV2 and EO as (4.95 ± 1.59 )μV2,also with statistical significance (P＜0.05).②In P300,the Common stimulus elicited clear component N1 (90ms)and P2 (180ms) in the ERPs after stimulus,while there were no significant differences between EC and EO states.Correspondingly,the rare stimulus elicited clear component N2 (207 ms) and P3 (313 ms) in the ERPs after stimulus on-set.Comparing the differences of field potentials of the rare stimulus between the two states,N2field potential in EC ( (0.01 ± 0.71 ) μV) was smaller than that in EO ( ( - 2.13 ± 0.80 ) μV ),with statistical significance (P ＜ 0.05 ) ; while P3 field potential in the EC ( ( 4.16 ± 1.08 ) μV ) was smaller than that in EO ( (4.78 ± 1.20) μV),but without statistical significance (P ＞ 0.05 ).ConclusionThe alpha field power is higher in eyes-closed than in eyes-open state,while performing the same auditory P300 paradigm,significant reduction of field potential in the N2 component are observed in eyes-closed than in eyes-open state.

Objective:To establish and validate the prediction model for bone marrow metastasis (BMM) in malignant tumors by screening out laboratory multiparameters.Methods:This case-control study collected 444 cases of malignant tumor patients who were hospitalized in the First Hospital of Jilin University from March 2018 to March 2024, including 243 cases for model establishment set and 201 cases for model validation set. The model establishment set was divided into BMM positive group (81 cases) and BMM negative group (162 cases), and the model validation set was divided into positive group (67 cases) and a negative group (134 cases). We collected patients′ clinical information such as gender, age, clinical diagnosis, and results of 47 laboratory tests including routine blood analysis, coagulation, liver function, tumor markers, potassium, sodium, chloride, and calcium ion tests, bone marrow morphology, and bone marrow biopsy. BMM was taken as the outcome event, differencial variables were analyzed using inter group comparisons, the correlation among parameters was analyzed using Pearson correlation analysis, the risk factors for BMM were analyzed using multivariate conditional logistic regression analysis, to establish logistic model, followed by efficiency evaluation on BMM predictive model using receiver operating characteristic (ROC) curves.Results:In the model establishment set, Pearson correlation analysis of 28 parameters that differed between the BMM positive and negative groups revealed that the correlation coefficients of 17 parameters, including mean platelet volume (MPV), hematocrit (HCT), hemoglobin (HGB), and prothrombin time (PT), were no more than 0.6 ( P<0.05). Further multivariate conditional logistic regression analysis demonstrated that MPV, HGB, HCT, PT, red cell distribution width (RDW), platelet count (PLT), alkaline phosphatase (ALP), chloride (Cl -), and mean erythrocyte hemoglobin concentration (MCHC) were the risk factors of BMM occurence in malignancy [MPV ( OR=9.929, 95% CI 2.688-71.335), HCT ( OR=8.232, 95% CI 6.223-9.841), HGB ( OR=4.300, 95% CI 1.947-16.577), PT ( OR=3.738, 95% CI 1.359-11.666), RDW ( OR=1.995, 95% CI 1.275-3.807), ALP ( OR=1.025, 95% CI 1.012-1.045), PLT ( OR=1.014, 95% CI 1.002-1.031), MCHC ( OR=0.724, 95% CI 0.523-0.880) and Cl -( OR=0.703, 95% CI 0.472-0.967)]. In the model establishment set, combiation of risk factors provided an AUC of 0.943 (95% CI 0.898-0.987, P<0.001), a sensitivity of 86.3%, and a specificity of 89.2% for BMM prediction. In the model validation set, the AUC was 0.924 (95% CI 0.854-0.960, P<0.001), with a sensitivity and specificity of 86.7% and 83.8%, respectively. Conclusion:This study built and validated a multiple-parameter model for BMM, which may facilitate the timely detection of BMM and provide reference for decision making of bone marrow aspiration.

Objective:To explore the performance of the attention-multiple instance learning (MIL) framework, an attention fusion network-based MIL, in the automated diagnosis of chronic gastritis with multiple indicators.Methods:A total of 1 015 biopsy cases of gastritis diagnosed in Fudan University Cancer Hospital, Shanghai, China and 115 biopsy cases of gastritis diagnosed in Shanghai Pudong Hospital, Shanghai, China were collected from January 1st to December 31st in 2018. All pathological sections were digitally converted into whole slide imaging (WSI). The WSI label was based on the corresponding pathological report, including "activity" "atrophy" and "intestinal metaplasia". The WSI were divided into a training set, a single test set, a mixed test set and an independent test set. The accuracy of automated diagnosis for the Attention-MIL model was validated in three test sets.Results:The area under receive-operator curve (AUC) values of Attention-MIL model in single test sets of 240 WSI were: activity 0.98, atrophy 0.89, and intestinal metaplasia 0.98; the average accuracy of the three indicators was 94.2%. The AUC values in mixed test sets of 117 WSI were: activity 0.95, atrophy 0.86, and intestinal metaplasia 0.94; the average accuracy of the three indicators was 88.3%. The AUC values in independent test sets of 115 WSI were: activity 0.93, atrophy 0.84, and intestinal metaplasia 0.90; the average accuracy of the three indicators was 85.5%.Conclusions:To assist in pathological diagnosis of chronic gastritis, the diagnostic accuracy of Attention-MIL model is very close to that of pathologists. Thus, it is suitable for practical application of artificial intelligence technology.

Bone homeostasis is a relative balance between bone formation and resorption. Signal transducer and activator of transcription 3 (STAT3), which is closely related to bone homeostasis, takes part in multiple intracellular and extracellular signal pathways. STAT3 participates in the process of osteoblast differentiation regulated by several factors. It can also maintain bone homeostasis by regulating the recruitment, differentiation and activation of osteoclasts. In addition, STAT3 is involved in the interaction between osteoblasts and osteoclasts. Patients with STAT3 mutations can have several inherited bone metabolism diseases. Furthermore, STAT3 plays a critical role in load-driven bone remodeling. Mechanical stimulation promotes osteoblast differentiation and bone formation through activating or enhancing STAT3 expression during bone remodeling process. This review summarizes the participation of STAT3 in maintaining bone homeostasis together with its possible mechanisms and discusses the connection between STAT3 and mechanical stimulation in bone remodeling, so as to provide a potential pharmacological target for the treatment of bone diseases.