Objective To establish a rat model of acclimatization to motion sickness(MS)induced by rotational stimulation.Methods To determine the stimulation conditions of MS,SD rats were divided into a static control group(SCG)and a single rotation stimulation group(SRG)before being subjected to the motion sickness index(MSI)measurement,open-field experiment and Morris water maze experiment after rotational stimulation to verify the feasibility of MS being induced in rats.Morris water maze experiments were performed to find out whether rotational stimulation could be used to induce MS in rats.During experiments on acclimatization,the SD rats were divided into the control group(Ctrl),one day of rotational stimulation group(Day1),three days of continuous rotational stimulation group(Day3),and seven days of continuous rotational stimulation group(Day7)before the changes in the MSI and behavior of these rats were recorded so as to explore the relationship between continuous stimulation and MS acclimatization in rats.Results After rotational stimulation,the rats showed a significant increase in the number of fecal pellets(P<0.0001)and in the MSI(P<0.0001)compared with the SCG.In the open field experiment,the rats showed a significant decrease in the spontaneous activity time(AT)(P<0.0001),total spontaneous activity distance(TD)(P<0.001)and distance moved by the center point per second(DMCPS)(P<0.001).The time taken to climb onto the platform(latency to find the platform,LP)(P<0.0001)and the total distance to the platform(distance to the platform,DP)(P<0.001)were significantly increased during the Morris water maze experiment.Acclimatization experiments revealed a significant increase in MSI and in the number of fecal pellets in the Day1 and Day3 groups of rotational stimulation compared to the Ctrl group(P<0.0001).AT(P<0.01),TD(P<0.05)and DMCPS(P<0.01)were significantly decreased,while LP and DP were significantly increased(P<0.0001),but there was no statistically significant difference in indices compared with the Day7 group(P>0.05).Conclusion Sinusoidal stimulation can induce MS in rats,and twice-a-day,continuous rotational stimulation for seven days can lead to acclimatization.The rat MS model can be assessed via behavioral experiments.

Objective:To establish the reference intervals (RIs) of systemic immune inflammatory index (SII), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR) and monocyte to lymphocyte ratio (MLR) in healthy pregnant women in Henan province, China.Methods:A retrospective analysis was conducted on the data of the healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from August 2016 to February 2019. A total of 4 016 healthy pregnant women were selected for establishing RIs. Data from healthy adult control group were derived from the healthy adult cohort in Henan established earlier by our team, and the Propensity Score Matching analysis was used and 3 595 healthy adult women and 3 595 healthy pregnant women to compare the indicators between the two groups. The RIs of the above indicators were established using the indirect method with a 95% confidence interval. The Tukey Rule was used to identify and remove outliers. The RIs were stratified and grouped based on the differences in each indicator during the pregnancy: SII: 3 929 cases, including 712 in the first trimester, 1 947 in the second trimester, and 1, 270 in the third trimester; PLR: 3 927 cases, no grouping; NLR: 3 925 cases, including 712 in the first trimester and 3 213 in the second and third trimesters; LMR: 3 925 cases, including 723 in the first trimester, 1 942 in the second trimester, and 1 260 in the third trimester; MLR: 3 904 cases, including 721 in the first trimester, 1 928 in the second trimester, and 1 255 in the third trimester. After the RIs were established, another 396 healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from February to April 2019 were selected for the validation of the RIs.Results:SII, NLR, LMR, MLR, and PLR differ significantly between healthy adult women and healthy pregnant women. There were significant differences in SII, LMR, and MLR among the three trimesters ( P<0.05). NLR in the first trimester was significantly lower than that in the second and third trimesters ( P<0.05), while there was no significant difference between the second and third trimester ( P=0.124). PLR only showed significant differences between the second and third trimester ( P<0.05), while no significant differences were found among the other groups. Based on the above results, the stratified RIs of each index in healthy pregnant population were established and verified. SII: first trimester (341-1 426)×10 9/L, second trimester (437-1 680)×10 9/L, third trimester (379-1 580)×10 9/L; PLR: 73-215; NLR: first trimester 1.78-5.60, second and third trimester 2.21-6.74; LMR: first trimester 2.20-6.61, second trimester 1.85-5.42, third trimester 1.63-4.82; MLR: first trimester 0.14-0.42, second trimester 0.17-0.49, third trimester 0.18-0.55. The rejection rate of 396 cases was less than 10%. Conclusions:The RIs of SII, NLR, LMR, MLR and PLR for healthy pregnant women in Hernan province of China were established and validated, and4 could be used in clinical practice.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To establish the reference intervals (RIs) of systemic immune inflammatory index (SII), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR) and monocyte to lymphocyte ratio (MLR) in healthy pregnant women in Henan province, China.Methods:A retrospective analysis was conducted on the data of the healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from August 2016 to February 2019. A total of 4 016 healthy pregnant women were selected for establishing RIs. Data from healthy adult control group were derived from the healthy adult cohort in Henan established earlier by our team, and the Propensity Score Matching analysis was used and 3 595 healthy adult women and 3 595 healthy pregnant women to compare the indicators between the two groups. The RIs of the above indicators were established using the indirect method with a 95% confidence interval. The Tukey Rule was used to identify and remove outliers. The RIs were stratified and grouped based on the differences in each indicator during the pregnancy: SII: 3 929 cases, including 712 in the first trimester, 1 947 in the second trimester, and 1, 270 in the third trimester; PLR: 3 927 cases, no grouping; NLR: 3 925 cases, including 712 in the first trimester and 3 213 in the second and third trimesters; LMR: 3 925 cases, including 723 in the first trimester, 1 942 in the second trimester, and 1 260 in the third trimester; MLR: 3 904 cases, including 721 in the first trimester, 1 928 in the second trimester, and 1 255 in the third trimester. After the RIs were established, another 396 healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from February to April 2019 were selected for the validation of the RIs.Results:SII, NLR, LMR, MLR, and PLR differ significantly between healthy adult women and healthy pregnant women. There were significant differences in SII, LMR, and MLR among the three trimesters ( P<0.05). NLR in the first trimester was significantly lower than that in the second and third trimesters ( P<0.05), while there was no significant difference between the second and third trimester ( P=0.124). PLR only showed significant differences between the second and third trimester ( P<0.05), while no significant differences were found among the other groups. Based on the above results, the stratified RIs of each index in healthy pregnant population were established and verified. SII: first trimester (341-1 426)×10 9/L, second trimester (437-1 680)×10 9/L, third trimester (379-1 580)×10 9/L; PLR: 73-215; NLR: first trimester 1.78-5.60, second and third trimester 2.21-6.74; LMR: first trimester 2.20-6.61, second trimester 1.85-5.42, third trimester 1.63-4.82; MLR: first trimester 0.14-0.42, second trimester 0.17-0.49, third trimester 0.18-0.55. The rejection rate of 396 cases was less than 10%. Conclusions:The RIs of SII, NLR, LMR, MLR and PLR for healthy pregnant women in Hernan province of China were established and validated, and4 could be used in clinical practice.

With accelerated aging process of the population, femoral intertrochanteric fractures have gradually become another major social health problem in China. Internal fixation is still the gold standard treatment for the fractures. Fracture reduction is the first step of the treatment and also the first element that affects the treatment efficacy. It is still controversial in clinical practice how to evaluate the quality of fracture reduction during internal fixation of the fractures. This article systematically expounds and analyzes the 7 systems of judging criteria for the reduction of intertrochanteric fractures from the aspects of fracture alignment, fracture apposition, difference in judgment criteria, and difference in imaging methods, in order to provide a reference for reaching consensus and improving curative effects.

OBJECTIVE: According to the digital image features of corneal opacity, a multi classification model of support vector machine (SVM) was established to explore the objective quantification method of corneal opacity. METHODS: The cornea digital images of dead pigs were collected, part of the color features and texture features were extracted according to the previous experience, and the SVM multi classification model was established. The test results of the model were evaluated by precision, sensitivity and RESULTS: In the classification of corneal opacity, the highest CONCLUSIONS The SVM multi classification model can classify the degree of corneal opacity.
Animals ; Corneal Opacity ; Support Vector Machine ; Swine

Objective: To explore the association between Vitamin A, E and mycoplasma pneumoniae pneumonia in children. Methods: 153 children with mycoplasma pneumoniae pneumonia and 653 health children were selected as cases and controls, respectively. Propensity score matching (PSM) analysis were conducted to reducing confounding bias between groups. Blood samples were collected to test serum levels of vitamin A and E using high performance liquid chromatography (HPLC). Logistic regression was implemented to determine odds ratios (OR) and 95% confidence intervals (CI) for evaluating the association of mycoplasma pneumoniae pneumonia with the serum levels of Vitamin A and E. Results: After propensity score matching, the study cohort included 153 cases with mycoplasma pneumoniae pneumonia and 306 health children as controls. Before matching, with age and gender adjusted, logistic regression analysis indicated that higher serum levels of Vitamin A and E led to a lower risk of mycoplasma pneumoniae pneumonia (OR=0.075, 95% CI: 0.007-0.815; OR=0.854, 95% CI: 0.792-0.986). After matching, higher serum level of Vitamin E had a significantly lower risk of mycoplasma pneumoniae pneumonia (OR=0.877, 95% CI: 0.810-0.950). Conclusions The serum levels of Vitamin A didn't have a statistically significant association with mycoplasma pneumoniae pneumonia. However, we observed an obvious association between Vitamin E and mycoplasma pneumoniae pneumonia. Hence Vitamin E clinical monitoring and supplementation are vital for preventing and treating mycoplasma pneumoniae pneumonia.

Objective:To investigate the difference of vitamin A and E levels in children with different respiratory diseases at different ages.Methods:A total of 671 children in Hunan Children's Hospital from July 2017 to October 2019 were selected as the disease group, including 197 cases of pneumonia, 152 cases of recurrent respiratory tract infection, 91 cases of asthma, 88 cases of cough variant asthma and 143 cases of Mycoplasma pneumoniae pneumonia; At the same time, 245 healthy children were selected as the normal group. The serum vitamin A and vitamin E levels of the two groups were detected by high performance liquid chromatography (HPLC).Results:⑴ The vitamin A level [(0.31±0.09)mg/L] of the disease group was lower than the normal group [(0.35±0.25)mg/L], and the vitamin E level [(8.92±2.57)mg/L] was lower than the normal group [(9.62±2.79)mg/L], with statistically significant difference ( P<0.05); ⑵ The level of vitamin A in the disease group at the age of >1-3 years [(0.32±0.09)mg/L] was lower than that in the normal group of the same age group [(0.35±0.08)mg/L]; the level of vitamin A in the disease group at the age of >3-6 years old [(0.30±0.08)mg/L] was lower than that of the same age group [(0.32±0.07)mg/L], with statistically significant difference ( P<0.05); ⑶ The vitamin E level of the disease group at >1-3 years old [(9.23±2.56)mg/L], >3-6 [(8.02±1.86)mg/L] and >6-14 years old [(8.02±1.82)mg/L] were lower than that of the same age normal group [(9.76±2.81)mg/L, (9.67±2.87)mg/L, (9.19±2.58)mg/L], with statistically significant difference ( P<0.05); ⑷ There were significant differences in vitamin A levels among different age in disease group ( P<0.05). Among them, the children with high risk of subclinical deficiency accounted for the largest proportion (45.78%) in the 6-month-1-year-old group, and the proportion of children with normal vitamin A levels in other age groups was the largest; ⑸ There are significant differences in vitamin E levels in different age groups in the disease group ( P<0.05), the levels in the normal range accounts for the largest proportion of all ages; ⑹ The levels of vitamin A and vitamin E in mycoplasma pneumoniae infection group were increased compared with in recurrent respiratory infection group , asthma group, and cough variant asthma group, and the difference was statistically significant ( P<0.05). Compared with the pneumonia group, the level of vitamin E increased in the recurrent respiratory infection group, and the difference was statistically significant ( P<0.05); The vitamin E levels in the cough variant asthma group were reduced compared with the repeated respiratory infection group, asthma group and pneumonia group ( P<0.05). Conclusions:The Vitamin A and E levels of children suffering from respiratory diseases are lower than those of normal children. The Vitamin A and E levels of different respiratory diseases and different age groups are different. Vitamin A and E supplementation may be significantly targeted according to different ages and different respiratory diseases in clinical practice.

OBJECTIVE: Identifying Atrial Ventricular Hypertrophy Electrocardiogram (AVH ECG)and diagnosing the classification of theirs automatically. METHODS: The ECG data used in this experiment was collected from the First Affiliated Hospital of China Medical University. CNN are combined with conventional methods and a 10 layers of one dimensional CNN are created in this experiment to extract the features of ECG signals automatically and achieve the function of classifying. ROC, sensitivity and F1-score are used here to evaluate the effects of the model. RESULTS: In the experiment of identifying AVH ECG, the AUC of test dataset is 0.991, while in the experiment of classifying AVH ECG, the maximal F1-score can reach 0.992. CONCLUSIONS The CNN model created in this experiment can achieve the auxiliary diagnosis of AVH ECG.
China ; Electrocardiography ; Heart Atria/pathology* ; Humans ; Hypertrophy ; Neural Networks, Computer