Occupational health technical service (OHTS) is one of the core contents in the technical support system of occupational disease prevention and control, and efficient management of OHTS institutions is necessary for improving the service ability. At present, OHTS institutions in China face several issues, such as uneven distribution in terms of quantity, function, unclear area coverage and roles and overlapping responsibilities among different types of institutions, and insufficient service capabilities with inconsistent service levels in some institutions. With the implementation of the national reform like the “separating permits from business license” and “delegate power, streamline administration and optimize government services"”policies, the management mode and operational approach of OHTS institutions have been profoundly changed. In light of this, five key recommendations are proposed to improve the management of OHTS institutions and enhance their management effectiveness, ensuring the sustainable development of national OHTS services. Firstly, it is necessary to clarify the relationship between national and provincial administrative levels in managing OHTS institutions to ensure their healthy and orderly development. Secondly, multiple measurements are taken to strengthen OHTS institutional capacity building to address regional disparities in technical capabilities and service quality. Thirdly, both technical capabilities and service quality should be focused on strengthening the supervision and management of OHTS institutions, preventing the decline of key conditions such as staffing, laboratories, equipment, and quality management after obtaining qualifications. Fourthly, “dual randomized- inspections and one open” and “internet+supervision” methods are used as basic tools for managing OHTS institutions operating across multiple provincial regions and enforcing cross-regional law. Fifthly, professional integrity of radiological health service institutions should be restored to effectively apply their technical advantages in their specialized fields.

[Objective] To evaluate the therapeutic effect of autologous platelet-rich plasma (PRP) for chronic endometritis (CE). [Methods] A retrospective analysis was conducted on 36 patients with CE who had failed antibiotic treatment. The clinical outcomes, pregnancy rates, and early miscarriage rates were assessed following PRP treatment. Meanwhile, the CE patients of receiving first/second-line Clinical drug treatment were used as the control experiment group. [Results] Among the 36 patients treated with PRP, the effective rate was 83.33%. The clinical pregnancy rate in the treatment group was higher than that in the control group [17-36(65.38%) vs 14/27(51.85%), P>0.05], and the early miscarriage rate was lower 2/17(11.76%) vs 2/14(14.29%), P>0.05]. [Conclusion] PRP therapy is effective for CE, with no antibiotic resistance or side effects, and can be widely promoted as a treatment option.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

OBJECTIVE To provide a reference for pharmaceutical care in patients with ulcerative colitis （UC） and ankylosing spondylitis （AS） who developed pustular psoriasis induced by infliximab. METHODS Clinical pharmacists participated in the pharmaceutical care process of a patient with UC and AS who developed pustular psoriasis after using infliximab. The clinical pharmacists determined， using Naranjo’s Scale， that the correlation between the patient’s pustular psoriasis and infliximab was “likely”. Regarding the patient’s development of pustular psoriasis after using infliximab， the clinical pharmacists recommended discontinuing infliximab and switching to Upadacitinib extended-release tablets. For the patient’s skin allergic reaction after using upadacitinib， the clinical pharmacists advised continuing the use of upadacitinib and closely monitoring any potential adverse reactions during the treatment period. RESULTS The clinicians adopted the clinical pharmacists’ recommendation. Following the treatment， the patient’s symptoms were significantly alleviated， and the patient was discharged with medication. The follow-up after discharge showed that the treatment was effective and well-tolerated. CONCLUSIONS The clinical pharmacists analyzed the causal relationship between infliximab and pustular psoriasis. Through pharmaceutical care measures such as dynamic monitoring of skin lesions， evaluation of treatment responses， and optimization of drug regimens， they assisted the physicians in formulating an individualized medication plan， ensuring the safety and efficacy of the patient’s medication use.

【Objective】 To explore the model of "One Core, Multiple Elements" emergency blood donation volunteer team (referred to as the Model) . 【Methods】 The Nanjing City Voluntary Blood Donation Joint Meeting serves as the core, with diverse entities including party committees, government departments, district governments, social organizations, enterprises, blood donors, etc. Following the principles of "emergency response in emergencies, wartime readiness, combining regular and wartime efforts," and adhering to the framework of the Model, the emergency blood donation volunteer team system in Nanjing was constructed. 【Results】 1) After the construction of the Model (2018—2022), the total number of emergency blood donation volunteers in Nanjing City increased by 191% compared to the pre-construction period (2013—2017), with an average annual blood donation of 20 929, showing significant differences (P<0.05). 2) After the construction of the Model, the number of emergency blood donation during the winter and summer increased by 206% and 185%, respectively, compared to the pre-construction period, demonstrating significant differences (P< 0.05) .3) Prior to the construction of the Model, Nanjing lacked a relatively stable emergency volunteer team. After the construction, Nanjing established a total of 5 relatively stable volunteer teams, with the district-level government and township personnel accounting for the highest proportion (52.96%), followed by medical personnel (23.95%), enterprise team (11.10%), State-owned Assets Supervision and Administration Commission team (7%), and Nanjing municipal government team (4.98%). 4) Following the Model, during the COVID-19 pandemic, Nanjing successfully initiated two Level Ⅱ blood emergency responses, with emergency blood donations reaching 23 041. 【Conclusion】 The Model can effectively ensure the blood supply in Nanjing region during emergencies.

Developmental dysplasia of the hip (DDH) is a developmental disease with abnormal position and morphology of the acetabulum and femoral head. DDH ranges from mild dysplasia to complete dislocation, including simple acetabular dysplasia, subluxation, and total dislocation. DDH is one of the most common hip diseases in children, and its onset begins in infancy. The anatomical structure of the hip joint is complex, and there are some practical problems in the large -scale clinical diagnosis and screening work, such as heavy workload, high misdiagnosis rate and missed diagnosis rate, and a long learning period of surgery. Artificial intelligence (AI) is an emerging technology science used to research and develop theories, methods, technologies and application systems that can simulate human intelligence. The main goal is to enable machines to complete complex tasks that require human intelligence. At present, artificial intelligence is mainly used in the diagnosis and treatment of DDH. Artificial intelligence combined with X-ray or ultrasound is used to diagnose and screen DDH, which avoids subjectivity to a certain extent and improves the accuracy of diagnosis and screening. In the preoperative planning of periacetabular osteotomy and total hip arthroplasty, it can more accurately track the position of the bone block and design the size of the prosthesis, which makes the surgical planning more accurate to a certain extent. Artificial intelligence technologies such as 3D navigation system, surgical robot and robotic arm are helpful to improve the accuracy and safety of surgery. Artificial intelligence has the characteristics of simplicity, speed, high repeatability and deep learning ability, which to a certain extent saves manpower, material resources and time costs for DDH diagnosis and treatment, facilitates medical workers to share DDH diagnosis and treatment experience and reduces the burden of patients, families, society and the country. The application of artificial intelligence in DDH diagnosis and treatment is becoming more and more extensive, but at present, artificial intelligence in DDH screening is still in its preliminary stage. There are few reports on artificial intelligence technology in DDH hip preservation treatment and other surgical methods, and there is insufficient research on artificial intelligence in DDH conservative treatment, postoperative complications and prognosis prediction. It is worth exploring new ideas by researchers. At present, the application of artificial intelligence in DDH still has certain limitations, including problems such as difficult to control the quality of image data, difficult to develop and promote technology, and lack of laws and regulations. Based on the literature database and relevant data sharing network, this paper reviews the application of artificial intelligence in the diagnosis and treatment of DDH at home and abroad in recent years, summarizes the current application status of artificial intelligence in the diagnosis and treatment of DDH, and provides new ideas for the future application of artificial intelligence in the diagnosis and treatment of DDH.

Objective To investigate the effects of zalcitabine(ddC),a mitochondrial DNA polymerase γ(POLG)inhibitor,on the migration,invasion,and to preliminarily explore mitochondrial biogenesis of human tri-ple-negative breast cancer MDA-MB-231 cells.Methods The effect of ddC on cell viability was detected using the MTT assay.The migration and invasion abilities of the cells were evaluated using the cell scratch and Transwell in-vasion assays.Cell apoptosis was determined using flow cytometry and a V-FITC/PI cell apoptosis detection kit.The protein expression of POLG,NADH dehydrogenase subunit Ⅰ(NADH1),NADH dehydrogenase subunit Ⅱ(NADH2),ATP synthase subunit 6(ATPase6),cytochrome c oxidase subunit Ⅰ(COX-1)and cytochrome c ox-idase subunit Ⅲ(COX-3)were determined using Western blot.The POLG mRNA level and mtDNA copy number were determined using qPCR.The mitochondrial content and ATP levels were determined using MitoTracker Green fluorescent probe staining and an ATP determination kit.MDA-MB-231 cells were transfected with pcDNA3.1-EG-FP-POLG plasmids to overexpress POLG.The inhibitory effects of ddC on cell migration and invasion were detected in POLG-overexpressed MDA-MB-231 cells.Results POLG expression was higher in MDA-MB-231 cells than in normal mammary epithelial cells(MCF-10A)(P＜0.01).ddC inhibited cell viability in a dose-dependent man-ner.ddC inhibited the migration(P＜0.01)and invasion(P＜0.01)of MDA-MB-231 cells;however,it dis-played no significant inhibitory effects on cell viability in normal mammary epithelial cells(MCF-10A)at the same concentration.ddC downregulated the protein(P＜0.01)and mRNA(P＜0.01)levels of POLG,reduced mtD-NA copy number(P＜0.01)and downregulated mtDNA-coded NADH1,NADH2,ATPase6,COX-1 and COX-3 protein expression(P＜0.01)in MDA-MB-231 cells.Furthermore ddC inhibited mitochondrial content(P＜0.01)and ATP(P＜0.01)levels in MDA-MB-231 cells.POLG overexpression increased the migration(P＜0.05)and invasion(P＜0.05)abilities of MDA-MB-231 cells,while ddC did not significantly inhibit the migra-tion and invasion abilities of MDA-MB-231 cells overexpressing POLG.Conclusion ddC downregulates POLG ex-pression in MDA-MB-231 cells and inhibits mitochondrial biogenesis and ATP levels,thereby inhibiting the migra-tion and invasion of MDA-MB-231 cells.