Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

Objective:To explore the influencing factors of brain injury in children with neonatal asphyxia after resuscitation.Methods:The clinical data of 180 children with neonatal asphyxia from January 2017 to January 2024 in Shijiazhuang Maternal and Child Health Hospital were retrospectively analyzed, and all children were received resuscitation treatment. The children were divided into modeling group (126 cases) and validation group (54 cases) in a 7∶3 ratio. Among the children in modeling group, 51 children combined brain injury (brain injury subgroup), and 75 children did not combine brain injury (non-brain injury subgroup). The general data were recorded, and the continuous variables were determined by the receiver operating characteristic (ROC) curve to determine the optimal cut-off value. Multivariate Logistic regression analysis was used to analyze the independent risk factors of brain injury in children with neonatal asphyxia after resuscitation. The R language software "rms" package was used to construct a nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation. The nomogram model was internally verified by the calibration curve, and the prediction efficiency of the nomogram model was evaluated by the decision curve and ROC curve.Results:There was no statistical difference in general data between modeling group and validation group ( P>0.05). The gestation age<37 weeks proportion, severe asphyxia proportion, Ⅱ to Ⅲ grade amniotic fluid contamination proportion, intrauterine distress proportion and blood lactate in brain injury subgroup were significantly higher than those in non-brain injury subgroup: 60.78% (31/51) vs. 38.67% (29/75), 37.25% (19/51) vs. 17.33% (13/75), 27.45% (14/51) vs. 10.67% (8/75), 47.06% (24/51) vs. 26.67% (20/75) and (2.64 ± 0.61) mmol/L vs. (2.21 ± 0.56) mmol/L, and there were statistical differences ( P<0.05 or <0.01); there were no statistical differences in gender composition, birth weight, maternal age, maternal history of adverse pregnancy and childbirth, mode of delivery, parity, abnormal amniotic fluid volume, abnormal fetal position, abnormal umbilical cord, abnormal placenta, systolic blood pressure, diastolic blood pressure, body temperature and blood glucose between the two groups ( P>0.05). ROC curve analysis result showed that the optimal cutoff value of blood lactate was 2.59 mmol/L. Multivariate Logistic regression analysis result showed that the young gestation age, severe asphyxia, Ⅱ to Ⅲ grade amniotic fluid contamination, intrauterine distress and high blood lactate were independent risk factors of brain injury in children with neonatal asphyxia after resuscitation ( OR = 2.854, 3.428, 3.405, 3.427 and 7.844; 95% CI 1.166 to 6.983, 1.263 to 9.305, 1.076 to 10.768, 1.358 to 8.645 and 3.080 to 19.978; P<0.05 or <0.01). The gestation age, degree of asphyxia, amniotic fluid contamination, intrauterine distress and blood lactate were used as predictors to construct a nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation. The calibration curve analysis result showed that the calibration curve of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation tended towards the ideal curve ( C- index = 0.824, 95% CI 0.745 to 0.903). The decision curve analysis result showed that, when the risk threshold was greater than 0.18, the clinical net benefits provided by the nomogram model were higher than those of a single independent risk factor, and it could provide significant additional clinical net benefits in predicting the high risk of brain injury in children with neonatal asphyxia after resuscitation. ROC curve of internal validation analysis result that the curve (AUC) of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation was 0.824 (95% CI 0.744 to 0.903). ROC curve of external validation result showed that the AUC of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation was 0.838 (95% CI 0.714 to 0.962). Conclusions:The gestation age, degree of asphyxia, amniotic fluid contamination, intrauterine distress and blood lactate are independent risk factors for brain injury in children with neonatal asphyxia after resuscitation. The nomogram model constructed based on these factors has a high clinical benefit in predicting brain injury in children with neonatal asphyxia after resuscitation.

Objective To investigate the association between butyrate metabolism-related genes(BMRGs)and the prognosis of lung adenocarcinoma(LUAD),construct a prognostic model,and evaluate its predictive value.Methods Differentially expressed BMRGs(BMR-DEGs)were screened from the TCGA-LUAD dataset.Cox and LASSO regression analyses were employed to establish a risk scoring model,stratifying patients into low-and high-risk groups.The model's performance was assessed using Kaplan-Meier(K-M)and receiver operating characteristic(ROC)curves,with external validation conducted using the GSE68465 dataset.In vitro experiments included RT-PCR and Western blotting to measure insulin-like growth factor binding protein 1(IGFBP1)expression.IGFBP1 was knocked down using siRNA,and its effects on cell proliferation,migration,and invasion were evaluated via CCK-8,colony formation,Transwell,and wound healing assays.Gene Set Enrichment Analysis(GSEA)was performed to explore IGFBP1-related regulatory mechanisms.Results We identified a total of 51 BMR-DEGs,primarily involved in biological processes such as cell proliferation,migration,and invasion,and associated with the PI3K-Akt and MAPK signaling pathways.The constructed 5-gene risk scoring model demonstrated that high-risk patients had significantly worse overall survival(OS)than low-risk patients(P＜0.05).IGFBP1 was highly expressed in LUAD tissues and correlated with poor prognosis.Knockdown of IGFBP1 significantly suppressed cancer cell proliferation,migration,and invasion(P＜0.05).GSEA revealed that IGFBP1 was linked to lipid metabolism-related pathways.Conclusion BMRGs are associated with LUAD prognosis,and the established risk scoring model exhibits strong predictive performance.High IGFBP1 expression correlates with unfavorable outcomes,and its knockdown inhibits cancer cell proliferation,migration,and invasion.

Objective The purpose of this study is to investigate the expression of histone lysine-specific demethylase 1 (KDM1A) and ubiquitin carboxyl-terminal hydrolase L3 (UCHL3) in thyroid cancer (TC) tissue and its relationship with clinical features and prognosis. Methods 94 TC patients diagnosed and treated at the Third Hospital of Heilongjiang Province from January 2017 to January 2019 were retrospectively selected as the study subjects. Immunohistochemistry was used to detect the expression of KDM1A and UCHL3 in tissues. Spearman correlation analysis was used to investigate the correlation between KDM1A and UCHL3. Kaplan-Meier survival curve was used to analyze the relationship between the levels of KDM1A and UCHL3 and the 5-year progression-free survival rate of TC patients. Multivariate COX regression model was used to analyze the prognostic factors of TC patients. Results The positive rates of KDM1A (68.09％) and UCHL3 (65.96％) in cancer tissues were higher than those in adjacent tissues(10.64％,8.51％),and the differences were statistically significant(x2=64.984,66.369,all P<0.001). The protein expression of KDM1A and UCHL3 was significant protein correlation (r=0.714,P<0.001). The positive rates of KDM1A (87.50％,90.91％) and UCHL3 (85.00％,87.88％) in TNM stage Ⅲ～Ⅳ and lymph node metastatic TC cancer tissues were higher than those in stage Ⅰ～Ⅱ(53.70％,53.85％)and non-lymph node metastatic(55.74％,54.10％) cancer tissues,and the differences were statistically significant(x2=9.985～12.191,all P<0.001). The 5-year progression-free survival rates of TC patients in the KDM1A positive and negative groups were 62.50％ (40/64) and 86.67％ (26/30),with significant differences,the 5-year progression-free survival rates of UCHL3 positive and negative patients were 58.06％ (36/62) and 90.63％ (29/32),with significant differences (Log-Rankx2=5.670,9.724,P=0.017,0.002). KDM1A positive,UCHL3 positive,TNM stage Ⅲ～Ⅳ,lymph node metastasis were risk factors affecting the prognosis of TC patients (Waldx2=1.315～1.697,all P<0.001). Conclusion KDM1A and UCHL3 are upregulated in TC,and played a pro-cancer role. They are new tumor markers for evaluating the prognosis of TC patients.

Objective:To explore the influencing factors of brain injury in children with neonatal asphyxia after resuscitation.Methods:The clinical data of 180 children with neonatal asphyxia from January 2017 to January 2024 in Shijiazhuang Maternal and Child Health Hospital were retrospectively analyzed, and all children were received resuscitation treatment. The children were divided into modeling group (126 cases) and validation group (54 cases) in a 7∶3 ratio. Among the children in modeling group, 51 children combined brain injury (brain injury subgroup), and 75 children did not combine brain injury (non-brain injury subgroup). The general data were recorded, and the continuous variables were determined by the receiver operating characteristic (ROC) curve to determine the optimal cut-off value. Multivariate Logistic regression analysis was used to analyze the independent risk factors of brain injury in children with neonatal asphyxia after resuscitation. The R language software "rms" package was used to construct a nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation. The nomogram model was internally verified by the calibration curve, and the prediction efficiency of the nomogram model was evaluated by the decision curve and ROC curve.Results:There was no statistical difference in general data between modeling group and validation group ( P>0.05). The gestation age<37 weeks proportion, severe asphyxia proportion, Ⅱ to Ⅲ grade amniotic fluid contamination proportion, intrauterine distress proportion and blood lactate in brain injury subgroup were significantly higher than those in non-brain injury subgroup: 60.78% (31/51) vs. 38.67% (29/75), 37.25% (19/51) vs. 17.33% (13/75), 27.45% (14/51) vs. 10.67% (8/75), 47.06% (24/51) vs. 26.67% (20/75) and (2.64 ± 0.61) mmol/L vs. (2.21 ± 0.56) mmol/L, and there were statistical differences ( P<0.05 or <0.01); there were no statistical differences in gender composition, birth weight, maternal age, maternal history of adverse pregnancy and childbirth, mode of delivery, parity, abnormal amniotic fluid volume, abnormal fetal position, abnormal umbilical cord, abnormal placenta, systolic blood pressure, diastolic blood pressure, body temperature and blood glucose between the two groups ( P>0.05). ROC curve analysis result showed that the optimal cutoff value of blood lactate was 2.59 mmol/L. Multivariate Logistic regression analysis result showed that the young gestation age, severe asphyxia, Ⅱ to Ⅲ grade amniotic fluid contamination, intrauterine distress and high blood lactate were independent risk factors of brain injury in children with neonatal asphyxia after resuscitation ( OR = 2.854, 3.428, 3.405, 3.427 and 7.844; 95% CI 1.166 to 6.983, 1.263 to 9.305, 1.076 to 10.768, 1.358 to 8.645 and 3.080 to 19.978; P<0.05 or <0.01). The gestation age, degree of asphyxia, amniotic fluid contamination, intrauterine distress and blood lactate were used as predictors to construct a nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation. The calibration curve analysis result showed that the calibration curve of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation tended towards the ideal curve ( C- index = 0.824, 95% CI 0.745 to 0.903). The decision curve analysis result showed that, when the risk threshold was greater than 0.18, the clinical net benefits provided by the nomogram model were higher than those of a single independent risk factor, and it could provide significant additional clinical net benefits in predicting the high risk of brain injury in children with neonatal asphyxia after resuscitation. ROC curve of internal validation analysis result that the curve (AUC) of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation was 0.824 (95% CI 0.744 to 0.903). ROC curve of external validation result showed that the AUC of the nomogram model for predicting brain injury in children with neonatal asphyxia after resuscitation was 0.838 (95% CI 0.714 to 0.962). Conclusions:The gestation age, degree of asphyxia, amniotic fluid contamination, intrauterine distress and blood lactate are independent risk factors for brain injury in children with neonatal asphyxia after resuscitation. The nomogram model constructed based on these factors has a high clinical benefit in predicting brain injury in children with neonatal asphyxia after resuscitation.

Objective To investigate the association between butyrate metabolism-related genes(BMRGs)and the prognosis of lung adenocarcinoma(LUAD),construct a prognostic model,and evaluate its predictive value.Methods Differentially expressed BMRGs(BMR-DEGs)were screened from the TCGA-LUAD dataset.Cox and LASSO regression analyses were employed to establish a risk scoring model,stratifying patients into low-and high-risk groups.The model's performance was assessed using Kaplan-Meier(K-M)and receiver operating characteristic(ROC)curves,with external validation conducted using the GSE68465 dataset.In vitro experiments included RT-PCR and Western blotting to measure insulin-like growth factor binding protein 1(IGFBP1)expression.IGFBP1 was knocked down using siRNA,and its effects on cell proliferation,migration,and invasion were evaluated via CCK-8,colony formation,Transwell,and wound healing assays.Gene Set Enrichment Analysis(GSEA)was performed to explore IGFBP1-related regulatory mechanisms.Results We identified a total of 51 BMR-DEGs,primarily involved in biological processes such as cell proliferation,migration,and invasion,and associated with the PI3K-Akt and MAPK signaling pathways.The constructed 5-gene risk scoring model demonstrated that high-risk patients had significantly worse overall survival(OS)than low-risk patients(P＜0.05).IGFBP1 was highly expressed in LUAD tissues and correlated with poor prognosis.Knockdown of IGFBP1 significantly suppressed cancer cell proliferation,migration,and invasion(P＜0.05).GSEA revealed that IGFBP1 was linked to lipid metabolism-related pathways.Conclusion BMRGs are associated with LUAD prognosis,and the established risk scoring model exhibits strong predictive performance.High IGFBP1 expression correlates with unfavorable outcomes,and its knockdown inhibits cancer cell proliferation,migration,and invasion.

Knee osteoarthritis (KOA) is a prevalent degenerative joint disease characterized by synovial inflammation, cartilage loss. Often manifesting as joint pain and limited mobility, it severely affects the quality of life of patients. Traditional treatment methods such as pharmacological injections and surgical interventions primarily aim to alleviate symptoms but have limited effects on cartilage repair. Human umbilical cord mesenchymal stem cells (hUC-MSCs), due to their anti-inflammatory and chondrogenic capabilities, is considered a new hope for the treatment of KOA. This article synthesizes the latest research findings from both domestic and international sources to discuss the theoretical basis for the clinical application of hUC-MSCs in treating KOA, clinical study design, and efficacy evaluation. It also addresses the challenges in the clinical application of hUC-MSCs and explores future directions, in the hope of providing feasible theoretical support for the treatment of KOA with hUC-MSCs.

[Objective] To explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×10¹²/L, Hb 10⁶ g/L, HCT 30.40%, PLT 115.00×10⁹/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×10¹²/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×10⁹/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.

Objective The purpose of this study is to investigate the expression of histone lysine-specific demethylase 1 (KDM1A) and ubiquitin carboxyl-terminal hydrolase L3 (UCHL3) in thyroid cancer (TC) tissue and its relationship with clinical features and prognosis. Methods 94 TC patients diagnosed and treated at the Third Hospital of Heilongjiang Province from January 2017 to January 2019 were retrospectively selected as the study subjects. Immunohistochemistry was used to detect the expression of KDM1A and UCHL3 in tissues. Spearman correlation analysis was used to investigate the correlation between KDM1A and UCHL3. Kaplan-Meier survival curve was used to analyze the relationship between the levels of KDM1A and UCHL3 and the 5-year progression-free survival rate of TC patients. Multivariate COX regression model was used to analyze the prognostic factors of TC patients. Results The positive rates of KDM1A (68.09％) and UCHL3 (65.96％) in cancer tissues were higher than those in adjacent tissues(10.64％,8.51％),and the differences were statistically significant(x2=64.984,66.369,all P<0.001). The protein expression of KDM1A and UCHL3 was significant protein correlation (r=0.714,P<0.001). The positive rates of KDM1A (87.50％,90.91％) and UCHL3 (85.00％,87.88％) in TNM stage Ⅲ～Ⅳ and lymph node metastatic TC cancer tissues were higher than those in stage Ⅰ～Ⅱ(53.70％,53.85％)and non-lymph node metastatic(55.74％,54.10％) cancer tissues,and the differences were statistically significant(x2=9.985～12.191,all P<0.001). The 5-year progression-free survival rates of TC patients in the KDM1A positive and negative groups were 62.50％ (40/64) and 86.67％ (26/30),with significant differences,the 5-year progression-free survival rates of UCHL3 positive and negative patients were 58.06％ (36/62) and 90.63％ (29/32),with significant differences (Log-Rankx2=5.670,9.724,P=0.017,0.002). KDM1A positive,UCHL3 positive,TNM stage Ⅲ～Ⅳ,lymph node metastasis were risk factors affecting the prognosis of TC patients (Waldx2=1.315～1.697,all P<0.001). Conclusion KDM1A and UCHL3 are upregulated in TC,and played a pro-cancer role. They are new tumor markers for evaluating the prognosis of TC patients.

Circulating tumor cells (CTCs) have the ability to sow tumors and can be found in the peripheral blood of patients with precancerous lesions and healthy people. However, CTCs are not currently screened in the donors blood. A large number of allogeneic blood transfusions occurred worldwide each year, and allogeneic blood transfusions expose recipients to the risk of transmission and affect tumors associated with donor CTCs. Although leukocyte filtration can not completely remove tumor cells in the blood, it can effectively reduce the number of white blood cells in the blood and reduce their proliferation ability. Blood irradiation can effectively destroy the DNA of CTCs in the blood, and inhibit the occurrence and metastasis of tumors caused by the infusion of allogeneic blood containing CTCs. Therefore, we should pay attention to the potential risk of CTCs on clinical transfusion, and strengthen the preclinical treatment of blood to avoid donor-related tumor infection in blood recipients due to clinical transfusion.