This paper focuses on extreme environments and systematically analyzes sleep disorders caused by multiple pathogenesis,including circadian rhythm disorder,yin-yang imbalance and qi-blood disorder under weightlessness,emotional depression due to environmental changes,abnormal diet and excretion,and six excesses pathogenic factors,in accordance with the theory of correspondence between nature and human.It proposes harmonizing yin and yang as the core therapeutic principle and guiding framework,with specific methods including calming rebellious qi-blood,regulating qi movement,harmonizing heart and kidney,and dredging and regulating blood vessels,thus forming the"one guiding principle and four specific methods"treatment strategy.Additionally,by integrating the modified application of classic formulas,a diagnostic and therapeutic approach targeting multi-dimensional pathogenesis is established.This study aims to promote the in-depth integration of Traditional Chinese Medicine(TCM)in extreme environmental medicine through TCM theories and innovative application of prescriptions,provide TCM-characterized solutions for health management of workers in extreme environments,and facilitate the transformation of extreme environmental medicine toward the modern medical model of"prevention-treatment integration".

Objective:To explore the impact of adolescent mental health status on smartphone addiction, and construct a predictive model for smartphone addiction based on the eXtreme Gradient Boosting(XGBoost) algorithm and multivariate Logistic regression.Methods:In April 2023, a cross-sectional survey was conducted among 14 666 adolescents.All participants were systematically evaluated using a self-developed general information questionnaire, the middle school student mental health scale(MSSMHS), the adolescents self-harm scale(ASHS), the interaction anxiousness scale(IAS), the mobile phone addiction index(MPAI), the middle school students shame scale(MSSS), the UCLA loneliness scale(UCLA-LS), the multidimensional peer victimization scale(MPVS), and the basic psychological needs scale(BPNS).R software version 4.3.2 was used for data analysis. Participants were randomly divided into training set and validation set at the ratio of 7∶3.The XGBoost model and multivariate logistic regression model were constructed to predict the risk of smartphone addiction, and a nomogram was plotted.Model performance was evaluated using the Hosmer-Lemeshow test, area under the curve(AUC), and accuracy(ACC).Results:(1) A total of 14 036 high school students were included in the study, with 5 069(36.1%) exhibited smartphone addiction.The training set comprised 9 826 students, with 3 549(36.1%) being smartphone addicts.The validation set included 4 210 students, with 1 520(36.1%) being smartphone addicts.(2) The XGBoost model identified shame-proneness and social anxiety as the two main predictors of smartphone addiction.(3) Multivariate Logistic regression analysis revealed that anxiety( B=0.328, OR(95% CI)=1.39(1.07-1.81), P=0.015), interpersonal sensitivity( B=0.311, OR(95% CI)=1.36(1.05-1.77), P=0.018), learning pressure( B=0.606, OR(95% CI)=1.83(1.46-2.31), P<0.001), mood swings( B=0.775, OR(95% CI)=2.17(1.70-2.78), P<0.001), social anxiety( B=0.024, OR(95% CI)=1.02(1.01-1.04), P<0.001), shame-proneness( B=0.049, OR(95% CI)=1.05(1.04-1.06), P<0.001), and peer victimization( B=0.037, OR(95% CI)=1.04(1.02-1.06), P<0.001) were significant predictors of smartphone addiction.(4) The ACC and AUC values of the XGBoost model were 0.890 and 0.929 in the training set, and 0.865 and 0.864 in the validation set, respectively.The multivariate Logistic regression model achieved ACC and AUC values of 0.870 and 0.854 in the training set, and 0.867 and 0.859 in the validation set, respectively. Conclusion:Anxiety, interpersonal sensitivity, learning pressure, mood swings, social anxiety, shame-proneness, and peer victimization are identified risk predictors of smartphone addiction in high school adolescents.

Objective:To explore the impact of adolescent mental health status on smartphone addiction, and construct a predictive model for smartphone addiction based on the eXtreme Gradient Boosting(XGBoost) algorithm and multivariate Logistic regression.Methods:In April 2023, a cross-sectional survey was conducted among 14 666 adolescents.All participants were systematically evaluated using a self-developed general information questionnaire, the middle school student mental health scale(MSSMHS), the adolescents self-harm scale(ASHS), the interaction anxiousness scale(IAS), the mobile phone addiction index(MPAI), the middle school students shame scale(MSSS), the UCLA loneliness scale(UCLA-LS), the multidimensional peer victimization scale(MPVS), and the basic psychological needs scale(BPNS).R software version 4.3.2 was used for data analysis. Participants were randomly divided into training set and validation set at the ratio of 7∶3.The XGBoost model and multivariate logistic regression model were constructed to predict the risk of smartphone addiction, and a nomogram was plotted.Model performance was evaluated using the Hosmer-Lemeshow test, area under the curve(AUC), and accuracy(ACC).Results:(1) A total of 14 036 high school students were included in the study, with 5 069(36.1%) exhibited smartphone addiction.The training set comprised 9 826 students, with 3 549(36.1%) being smartphone addicts.The validation set included 4 210 students, with 1 520(36.1%) being smartphone addicts.(2) The XGBoost model identified shame-proneness and social anxiety as the two main predictors of smartphone addiction.(3) Multivariate Logistic regression analysis revealed that anxiety( B=0.328, OR(95% CI)=1.39(1.07-1.81), P=0.015), interpersonal sensitivity( B=0.311, OR(95% CI)=1.36(1.05-1.77), P=0.018), learning pressure( B=0.606, OR(95% CI)=1.83(1.46-2.31), P<0.001), mood swings( B=0.775, OR(95% CI)=2.17(1.70-2.78), P<0.001), social anxiety( B=0.024, OR(95% CI)=1.02(1.01-1.04), P<0.001), shame-proneness( B=0.049, OR(95% CI)=1.05(1.04-1.06), P<0.001), and peer victimization( B=0.037, OR(95% CI)=1.04(1.02-1.06), P<0.001) were significant predictors of smartphone addiction.(4) The ACC and AUC values of the XGBoost model were 0.890 and 0.929 in the training set, and 0.865 and 0.864 in the validation set, respectively.The multivariate Logistic regression model achieved ACC and AUC values of 0.870 and 0.854 in the training set, and 0.867 and 0.859 in the validation set, respectively. Conclusion:Anxiety, interpersonal sensitivity, learning pressure, mood swings, social anxiety, shame-proneness, and peer victimization are identified risk predictors of smartphone addiction in high school adolescents.

At present, external treatment of traditional Chinese medicine (TCM) has been widely used in the treatment of intestinal obstruction, which is safe and effective. This study reported a case of recurrent intestinal obstruction after radiotherapy and chemotherapy for rectal cancer. After the implementation of external treatment of TCM on the basis of conventional western medicine treatment, the patient's condition improved significantly, and the patient was discharged smoothly. This case aimed to provide a reference for the diagnosis and treatment of this disease.

Objective:To systematically evaluate the relationship between maternal arsenic exposure and neonatal mortality (NM) and infant mortality (IM).Methods:Literature searches were conducted through PubMed, Web of Science, Embase, Cochrane Library, CNKI database, Wanfang Data Knowledge Service Platform, VIP Chinese Journal Service Platform, and the Chinese Biomedical Literature Database to include case-control, cohort, and cross-sectional studies on the relationship between maternal arsenic exposure and NM, IM published domestically and internationally. The search period was from database establishment to June 4, 2023. Data analysis was conducted using Stata MP 16.0 software, and heterogeneity tests were performed using I2 statistics and Q-test. Fixed effect model (no significant heterogeneity, I2≤50%, P≥0.100) or random effect model (significant heterogeneity, I2 > 50%, P < 0.100) was selected according to heterogeneity among study results for meta-analysis. The OR value (95% CI) was used as the effect value, and subgroup analysis was performed based on different exposure index, arsenic exposure levels in drinking water and study types. At the same time, the dose-response relationship between maternal arsenic exposure and NM, IM was analyzed using generalized least square method. Results:Finally, 9 English literature articles (including 3 053 women and 74 172 maternal and infant pairs) were included, including 6 articles on NM outcomes and 8 articles on IM outcomes. After heterogeneity testing, there was significant heterogeneity in NM ( I2 = 75.20%, P = 0.001) and IM ( I2 = 62.50%, P = 0.009) among all studies. Random effect model was used for meta-analysis, and the combined OR values (95% CI) of NM and IM were 1.38 (1.11 - 1.73) and 1.51 (1.21 - 1.89), respectively. According to the exposure index grouping, in the NM outcome, all studies used drinking water arsenic as the exposure index, and the combined OR value (95% CI) of drinking water arsenic was 1.38 (1.11 - 1.73). In the IM outcome, the combined OR values (95% CI) for urinary arsenic and drinking water arsenic were 3.42 (1.38 - 8.47) and 1.44 (1.16 - 1.79), respectively. According to the grouping of arsenic exposure levels in drinking water, the combined OR values (95% CI) for high and low exposure levels ( > 50 and > 10 - 50 μg/L) in NM and IM outcomes were 1.18 (0.97 - 1.44), 1.54 (1.41 - 1.67), and 1.22 (1.03 - 1.43), 1.55 (1.18 - 2.03), respectively. According to the study types grouping, the combined OR values (95% CI) for retrospective, prospective, and cross-sectional studies in NM and IM outcomes were 1.54 (1.41 - 1.67), 1.11 (0.96 - 1.28), 1.90 (1.01 - 3.55), and 1.55 (1.18 - 2.03), 2.01 (0.82 - 4.94), 1.58 (0.87 - 2.88), respectively. The dose-response relationship analysis showed that the dose-response relationship between maternal arsenic exposure and IM exhibited a non-linear trend (χ 2 = 5.75, P = 0.017). Conclusion:Maternal arsenic exposure is correlated with NM and IM, and there is a non-linear dose-response relationship with IM.

Objective To investigate the effect of growth hormone(GH)pretreatment on the improvement of eu-ploid and pregnancy outcome.Methods A prospective analysis was conducted on 134 patients undergoing preim-plantation genetic testing for aneuploidy(PGT-A),among whom 30 patients were self-controlled and 104 patients were inter-group controlled.According to whether GH was added,the patients were divided into GH pretreatment group and GH non-pretreatment group.GH pretreatment included subcutaneous injection of GH 2U/day for 4-6 weeks before the start of gonadotropin(Gn),and the dose was doubled on the day of Gn until the trigger day.GH non-pretreatment meant no GH treatment,GH pretreatment was given when the previous PGT-A cycle failed within one year when the PGT-A was performed again,forming the self-control group.The basic situation,blastocyst situa-tion and pregnancy outcome were compared between the groups by inter-group and self-control.Results No matter in the group control or self-controlled group,the endometrial thickness on the day of HCG,ovarian sensitivity index(OSI),number of oocytes obtained,MII oocytes,2PN number,2PN fertilization rate,available oocyte rate,num-ber of biopsy blastocysts,number of euploid blastocysts,euploid blastocyst rate,and at least one euploid rate sig-nificantly increased after GH pretreatment,with statistically significant differences(P＜0.05).The total amount of Gn,Gn days,number of mosaic blastocysts,and mosaic blastocyst rate were not significantly changed after GH pretreatment,with no statistically significant differences.The implantation rate and clinical pregnancy rate in-creased after GH pretreatment,but with no statistically significant differences.Conclusion GH pretreatment can significantly improve the number and rate of euploid embryos in patients undergoing PGT-A,and has a tendency to improve pregnancy outcome.

AIM: To investigate the protective effect and mechanism of Danlou tablet on retinal ischemia-reperfusion injury(RIRI)in mice.METHODS: A total of 40 ApoE-/- mice were fed with high fat diet for 6 wk, and the RIRI model was established by anterior chamber infusion of pressurized saline. The mice were divided into control group(normal saline for 8 wk), RIRI model group(normal saline for 8 wk), and low-, medium-, and high-dose Danlou tablets groups [1, 2, and 4 g/(kg·d), respectively, for 8 wk]. The morphological changes of retina were observed by hematoxylin-eosin(HE)staining, retinal cell apoptosis was detected by terminal-deoxynucleoitidyl transferase mediated Nick-End Labeling(TUNEL)staining. The Western-blot assay was used to detect the expression of retinal tissue sample Kelch-like ech-associated protein 1(Keap1), nuclear factor E2 related factor 2(Nrf2), heme oxygenase 1(HO-1), and superoxide dismutase(Sod2)proteins.RESULTS: Compared with the control group, the mouse retina was atrophic with thinning thickness and increasing cell apoptosis, down-regulation of Sod2 protein expression, and up-regulation of Keap1 protein expression in the RIRI model group(all P<0.01). Compared with the RIRI model group, the retinal thickness increased in the medium- and high-dose of Danlou tablets groups(all P<0.01), and the cell apoptosis of retina decreased in the low-, medium- and high-dose of Danlou tablets groups(all P<0.05). There were no significant differences in the expression of Keap1 and HO-1 proteins of mouse retina tissue in the low-dose of Danlou tablets group(P>0.05). The expression of Sod2, Nrf2 and HO-1 proteins up regulated, and the expression of Keap1 protein down regulated in the medium- and high-dose of Danlou tablets groups(all P<0.05).CONCLUSION: Danlou tablet can alleviate RIRI-induced atrophy and thinning of retina and retinal cell apoptosis by regulating Keap1-Nrf2/HO-1 signal pathway and reducing oxidative stress.

Objective:To investigate the status of medical care seeking delay and diagnosis delay of pulmonary tuberculosis (PTB) patients in Tongzhou District and Changping District of Beijing, analyze the related factors and put forward suggestions for early detection and scientific management of PTB patients.Methods:A retrospective epidemiological survey was conducted to collect the incidence data of PTB registered in Tongzhou and Changping from January 1 to December 31, 2021 by using the Chinese Tuberculosis Information Management System, and telephone interview were used for information supplement. Multivariate logistic regression model and decision tree model were used to analyze the influencing factors of medical care seeking delay and diagnosis delay of PTB patients.Results:In 2021, the medical care seeking delay time M( Q1, Q3) in the PTB patients in Tongzhou and Changping was 11 (5, 26) days, with a delay rate of 41.71%. Results from multivariate logistic regression model analysis revealed that factors influencing the medical care seeking delay included regular health check-up ( OR=0.033, 95% CI: 0.008-0.147), coughing for less than 2 weeks or showing any symptom of PTB before medical care seeking ( OR=0.378, 95% CI: 0.215-0.665), showing other symptoms before medical care seeking( OR=2.791, 95% CI: 1.710-4.555), no work or school in medical care seeking ( OR=2.990, 95% CI: 1.419-6.298). The diagnosis delay time M( Q1, Q3) in the PTB patients was 8 (0, 18) days, with a delay rate of 35.20%. Multivariate logistic regression model analysis revealed that the factors influencing the diagnosis delay of PTB included being diagnosed at a specialized tuberculosis hospital ( OR=0.426, 95% CI: 0.236-0.767) or a tuberculosis prevention and control institution ( OR=1.843, 95% CI: 1.061-3.202) and being traced as a source of infection ( OR=2.632, 95% CI: 1.062-6.521). The overall performance of the multivariate logistic regression model was comparable to that of the decision tree model, with the decision tree model exhibiting higher sensitivity but lower specificity. Conclusions:The medical care seeking delay rate and diagnosis delay rate of tuberculosis in Tongzhou and Changping were at low levels in 2021. However, it is still necessary to strengthen the health education and active screening, improve the public awareness of PTB prevention and control, and further improve the level of medical services and medical access to reduce the medical care seeking delay and diagnosis delay of PTB patients.

Objective:To systematically evaluate the relationship between maternal arsenic exposure and neonatal mortality (NM) and infant mortality (IM).Methods:Literature searches were conducted through PubMed, Web of Science, Embase, Cochrane Library, CNKI database, Wanfang Data Knowledge Service Platform, VIP Chinese Journal Service Platform, and the Chinese Biomedical Literature Database to include case-control, cohort, and cross-sectional studies on the relationship between maternal arsenic exposure and NM, IM published domestically and internationally. The search period was from database establishment to June 4, 2023. Data analysis was conducted using Stata MP 16.0 software, and heterogeneity tests were performed using I2 statistics and Q-test. Fixed effect model (no significant heterogeneity, I2≤50%, P≥0.100) or random effect model (significant heterogeneity, I2 > 50%, P < 0.100) was selected according to heterogeneity among study results for meta-analysis. The OR value (95% CI) was used as the effect value, and subgroup analysis was performed based on different exposure index, arsenic exposure levels in drinking water and study types. At the same time, the dose-response relationship between maternal arsenic exposure and NM, IM was analyzed using generalized least square method. Results:Finally, 9 English literature articles (including 3 053 women and 74 172 maternal and infant pairs) were included, including 6 articles on NM outcomes and 8 articles on IM outcomes. After heterogeneity testing, there was significant heterogeneity in NM ( I2 = 75.20%, P = 0.001) and IM ( I2 = 62.50%, P = 0.009) among all studies. Random effect model was used for meta-analysis, and the combined OR values (95% CI) of NM and IM were 1.38 (1.11 - 1.73) and 1.51 (1.21 - 1.89), respectively. According to the exposure index grouping, in the NM outcome, all studies used drinking water arsenic as the exposure index, and the combined OR value (95% CI) of drinking water arsenic was 1.38 (1.11 - 1.73). In the IM outcome, the combined OR values (95% CI) for urinary arsenic and drinking water arsenic were 3.42 (1.38 - 8.47) and 1.44 (1.16 - 1.79), respectively. According to the grouping of arsenic exposure levels in drinking water, the combined OR values (95% CI) for high and low exposure levels ( > 50 and > 10 - 50 μg/L) in NM and IM outcomes were 1.18 (0.97 - 1.44), 1.54 (1.41 - 1.67), and 1.22 (1.03 - 1.43), 1.55 (1.18 - 2.03), respectively. According to the study types grouping, the combined OR values (95% CI) for retrospective, prospective, and cross-sectional studies in NM and IM outcomes were 1.54 (1.41 - 1.67), 1.11 (0.96 - 1.28), 1.90 (1.01 - 3.55), and 1.55 (1.18 - 2.03), 2.01 (0.82 - 4.94), 1.58 (0.87 - 2.88), respectively. The dose-response relationship analysis showed that the dose-response relationship between maternal arsenic exposure and IM exhibited a non-linear trend (χ 2 = 5.75, P = 0.017). Conclusion:Maternal arsenic exposure is correlated with NM and IM, and there is a non-linear dose-response relationship with IM.

Developing new therapeutic agents for cancer immunotherapy is highly demanding due to the low response ratio of PD-1/PD-L1 blockade in cancer patients. Here, we discovered that the novel immune checkpoint VISTA is highly expressed on a variety of tumor-infiltrating immune cells, especially myeloid derived suppressor cells (MDSCs) and CD8⁺ T cells. Then, peptide C1 with binding affinity to VISTA was developed by phage displayed bio-panning technique, and its mutant peptide VS3 was obtained by molecular docking based mutation. Peptide VS3 could bind VISTA with high affinity and block its interaction with ligand PSGL-1 under acidic condition, and elicit anti-tumor activity in vivo. The peptide DVS3-Pal was further designed by d-amino acid substitution and fatty acid modification, which exhibited strong proteolytic stability and significant anti-tumor activity through enhancing CD8⁺ T cell function and decreasing MDSCs infiltration. This is the first study to develop peptides to block VISTA/PSGL-1 interaction, which could act as promising candidates for cancer immunotherapy.