Objective: To investigate the effect of targeted silencing of DNA methyltransferase 3A(DNMT3A) on collagen deposition, proliferation and migration activity of mouse lung fibroblasts(PFs). Methods: In order to ensure the proliferation and migration activity of primary fibroblasts, the lung tissues of neonatal C57 suckling mice were taken, PFs were extracted after being sheared, and the morphology was observed and identified under the microscope. PFs cells were activated by 5 ng/ml TGF-β1for 24 h after cell attachment, and DNMT3A silencing model was constructed by small interfering RNA; The experiment was divided into control group, TGF-β1group, TGF-β1+ siRNA-NC group and TGF-β1+ siRNA-DNMT3A group. The protein expressions of DNMT3A, α-smooth muscle actin(α-SMA) and Collagen Ⅰ were detected by Western blot; Real time quantitative reverse transcription polymerase chain reaction(RT-qPCR) was used to detect the mRNA expression changes ofDNMT3A,α-SMAandCollagenⅠ. The proliferation ability of PFs was detected by CCK-8 and EdU staining; the migration ability of PFs was detected by scratch test and Transwell migration test. Results: Compared with the control group, TGF-β1induced the increase of DNMT3A in the activated PFs cell group(P<0.01), the protein and mRNA levels of fibrosis and proliferation related indicators α-SMA and Collagen Ⅰ also increased(allP<0.05), and the proliferation and migration ability of PFs increased(allP<0.000 1). Compared with the siRNA-NC group, the protein expression levels of DNMT3A(P<0.000 1) and related indicators α-SMA(P<0.01) and Collagen Ⅰ(P<0.01) significantly decreased in the DNMT3A silencing group by Western blot, and the mRNA levels ofDNMT3A,α-SMAandCollagenⅠby RT-qPCR also decreased(allP<0.001), and the proliferation(P<0.01) and migration ability(P<0.05) of PFs cells decreased compared with the control group. Conclusion Silencing DNMT3A can inhibit the deposition of collagen and the proliferation of PFs. DNMT3A can promote the proliferation and migration of PFs, and then promote the activation of PFs and the development of pulmonary fibrosis. This process may be regulated by DNA methylation modification.

The COVID-19 epidemic has spread to the whole world for three years and has had a serious impact on human life, health and economic activities. China's epidemic prevention and control has gone through the following stages: emergency unconventional stage, emergency normalization stage, and the transitional stage from the emergency normalization to the "Category B infectious disease treated as Category B" normalization, and achieved a major and decisive victory. The designated hospitals for prevention and control of COVID-19 epidemic in Tianjin has successfully completed its tasks in all stages of epidemic prevention and control, and has accumulated valuable experience. This article summarizes the experience of constructing a hospital infection prevention and control system during the "Category B infectious disease treated as Category A" period in designated hospital. The experience is summarized as the "Cluster" hospital infection prevention and control system, namely "three rings" outside, middle and inside, "three districts" of green, orange and red, "three things" before, during and after the event, "two-day pre-purification" and "two-director system", and "one zone" management. In emergency situations, we adopt a simplified version of the cluster hospital infection prevention and control system. In emergency situations, a simplified version of the "Cluster" hospital infection prevention and control system can be adopted. This system has the following characteristics: firstly, the system emphasizes the characteristics of "cluster" and the overall management of key measures to avoid any shortcomings. The second, it emphasizes the transformation of infection control concepts to maximize the safety of medical services through infection control. The third, it emphasizes the optimization of the process. The prevention and control measures should be comprehensive and focused, while also preventing excessive use. The measures emphasize the use of the least resources to achieve the best infection control effect. The fourth, it emphasizes the quality control work of infection control, pays attention to the importance of the process, and advocates the concept of "system slimming, process fattening". Fifthly, it emphasizes that the future development depends on artificial intelligence, in order to improve the quality and efficiency of prevention and control to the greatest extent. Sixth, hospitals need to strengthen continuous training and retraining. We utilize diverse training methods, including artificial intelligence, to ensure that infection control policies and procedures are simple. We have established an evaluation and feedback mechanism to ensure that medical personnel are in an emergency state at all times.

Objective To observe the impact of age and menstrual status on semi-quantitative parameters of breast dynamic enhanced MRI(DCE-MRI)in healthy adult women.Methods A total of 283 adult females who underwent MR examinations due to suspected breast mass or breast discomfort but no breast tumor was detected after 1 year's clinical follow-up were retrospectively collected.Meanwhile,49 healthy adult female subjects in the menstrual period(menstruating subgroup)were prospectively recruited.All the above 332 subjects were divided into low age group(n=107),middle age group(n=114)and high age group(n=111)according to age,while into postmenopausal group(n=112)and premenopausal group(n=220,including 49 in menstruating subgroup,77 in proliferating subgroup and 94 in secreting subgroup).DCE-MRI semi-quantitative parameters,including maximum enhancement rate(ERmax)and maximum slope of increasing(Slopemax)were compared among different groups and subgroups,and the variations were observed.Results Significant differences of ERmax and Slopemax were found between high and low age groups(both P＜0.05),while no significant difference of ERmax and Slopemax was found between middle and low age group,nor between middle and high age group(all P＞0.05).Both ERmax and Slopemax in postmenopausal group were lower than those in premenopausal group(both P＜0.05),while no significant difference of DCE-MRI semi-quantitative parameters was found among different menstrual cycle subgroups(all P＞0.05).The coefficient of variance(CV)of normal breast ERmax in low,middle and high age groups was 56.20％,44.02％and 50.97％,respectively,of Slopemax was 54.74％,81.78％and 76.93％,respectively.CV of normal breast ERmax was 50.12％and 46.02％in postmenopausal and premenopausal groups,respectively,while CV of Slopemax was 72.84％and 62.04％,respectively.Among different subgroups,CV of ERmax and Slopemax in proliferative period were both the largest(61.39％,82.54％),which in menstrual period were both the smallest(33.99％,42.33％).Conclusion Semi-quantitative parameters of breast DCE-MRI were different among healthy women of different age and menstrual status,and the individual variations were large.

Objective:To explore the value of machine-learning models based on magnetic resonance imaging(MRI)radiomics features for the preoperative prediction of the blood supply in pituitary neuroendocrine tumors.Methods:A retrospective analysis was performed on the clinical and imaging data of 136 patients with pathologically confirmed pituitary neuroendocrine tumors(diameter>10 mm)from April 2013 to April 2023 at Yi Jishan Hospital of Wannan Medical College.Based on the intraoperative findings,the patients were assigned into richly vascularized(n=50)and normally vascularized(n=86)groups.All patients were allocated randomly in a 7:3 ratio into a training(n=96)or a validation group(n=40).Three machine-learning algorithms,multivariate Logistic regression(LR),random forest(RF),and support vec-tor machine(SVM),were used to establish radiomics prediction models.Receiver operating characteristic(ROC)curves were plotted to eval-uate the diagnostic performance of the models;decision curve analysis(DCA)was used to assess the net clinical benefit of the models.Res-ults:The clinical model achieved areas under the ROC curve(AUC)of 0.74 and 0.82 in the training and validation groups,respectively.The radiomics models using T1-weighted imaging(WI),T2WI,T1WI-enhanced,and combined sequences achieved AUCs of 0.80,0.84,0.82,and 0.84 in the training group and 0.82,0.80,0.85,and 0.83 in the validation group,respectively.The LR,RF,and SVM models had AUCs of 0.85,0.87,and 0.84 in the training group and 0.85,0.85,and 0.83 in the validation group,respectively.All radiomics models demonstrated great-er diagnostic efficacy than the clinical model.DCA indicated that the LR,SVM,and combined-sequence models achieved good net clinical be-nefits;the LR model showed the best results.Conclusions:Machine-learning models based on MRI radiomics exhibit high predictive value,surpassing the clinical judgment of radiologists based on MRI images alone,and offer a favorable net clinical benefit.

Objective:To analyze the changes in the management methods of large medical equipment in China, evaluate the equity of large medical equipment allocation planning from the 13th Five-Year Plan to the 14th Five-Year Plan.Methods:The literature research was used to sort out the characteristics and changes of the management of large medical equipment in China. The database was established to quantitatively analyze the existing number of large medical equipment at the end of the 13th Five-Year Plan and the planned number of large medical equipment at the end of the 14th Five-Year Plan, and then the fairness evaluation was carried out based on the Lorenz curve and Gini coefficient.Results:Since the 1980s, the management measures of large-scale medical equipment in China have been introduced and updated iteratively to meet the needs of social development and medical services. In addition to conventional radiotherapy equipment, the number of large medical equipment per million population in China at the end of the 14th Five-Year Plan at least doubled compared with the end of the 13th Five-Year Plan, among which the heavy ion radiotherapy system and the laparoscopic surgery system increased by more than two times. Lorenz curve analysis showed that the fairness of large medical equipment based on population distribution at the end of the 14th Five-Year Plan was better than that at the end of the 13th Five-Year Plan, especially for heavy ion proton radiotherapy system, high-end radiotherapy equipment and PET/MR. The Gini coefficient of large medical equipment planning based on population distribution during the 14th Five-Year Plan was generally smaller than that of the 13th Five-Year Plan. Except for the heavy ion proton radiotherapy system and PET/MR in North China, the Gini coefficient of the planned number of all kinds of equipment in the six regions of the country during the 14th Five-Year Plan was less than 0.4 based on population distribution, which was in a relatively fair state.Conclusions:The management of large medical equipment in China keeps pace with the times and constantly adapts to the new development stage of health care. The fairness of large medical equipment allocation planning based on population distribution in six regions of China has been steadily improved, and it is suggested that the fairness based on population distribution and the clinical application of existing equipment should be taken into account in the allocation planning.

Background/Aims: Four-week treatment of linvencorvir (RO7049389) was generally safe and well tolerated, and showed anti-viral activity in chronic hepatitis B (CHB) patients. This study evaluated the efficacy, safety, and pharmacokinetics of 48-week treatment with linvencorvir plus standard of care (SoC) in CHB patients. Methods: This was a multicentre, non-randomized, non-controlled, open-label phase 2 study enrolling three cohorts: nucleos(t)ide analogue (NUC)-suppressed patients received linvencorvir plus NUC (Cohort A, n=32); treatment-naïve patients received linvencorvir plus NUC without (Cohort B, n=10) or with (Cohort C, n=30) pegylated interferon-α (Peg-IFN-α). Treatment duration was 48 weeks, followed by NUC alone for 24 weeks. Results: 68 patients completed the study. No patient achieved functional cure (sustained HBsAg loss and unquantifiable HBV DNA). By Week 48, 89% of treatment-naïve patients (10/10 Cohort B; 24/28 Cohort C) reached unquantifiable HBV DNA. Unquantifiable HBV RNA was achieved in 92% of patients with quantifiable baseline HBV RNA (14/15 Cohort A, 8/8 Cohort B, 22/25 Cohort C) at Week 48 along with partially sustained HBV RNA responses in treatment-naïve patients during follow-up period. Pronounced reductions in HBeAg and HBcrAg were observed in treatment-naïve patients, while HBsAg decline was only observed in Cohort C. Most adverse events were grade 1–2, and no linvencorvir-related serious adverse events were reported. Conclusions 48-week linvencorvir plus SoC was generally safe and well tolerated, and resulted in potent HBV DNA and RNA suppression. However, 48-week linvencorvir plus NUC with or without Peg-IFN did not result in the achievement of functional cure in any patient.

Objective: To investigate the epidemiological characteristics of foodborne disease outbreaks in Shaoxing City, Zhejiang Province, from 2012 to 2022, so as to provide the evidence for improving the foodborne disease control strategy. Methods: Foodborne disease outbreaks in Shaoxing City from 2012 to 2022 were collected from National Foodborne Disease Outbreak Monitoring System in China, including populations, places of outbreak, pathogenic factors and suspected foods. The temporal distribution, regional distribution, distribution of outbreak places and pathogenic factors of foodborne disease outbreaks were descriptively analyzed. Results: A total of 89 foodborne disease outbreaks were reported in Shaoxing City from 2012 to 2022, covering totally 699 patients, with an average annual attack rate of 6.35%. The outbreak peaked during the period between June and October (73 outbreaks, 82.02%), and family was the predominant place of outbreak (41 outbreaks, 46.07%). There were 83 outbreaks with known pathogenic factors, including 51 outbreaks caused by microbial factors, with Vibrio parahaemolyticus, Salmonella and norovirus as predominant pathogens, and 29 outbreaks caused by fungi and their toxins, which were all poisonous mushrooms poisoning, resulting in 2 deaths. In addition, there were 3 outbreaks caused by chemical factors. Conclusions The outbreak of foodborne diseases predominantly occurred in summer and autumn in Shaoxing City from 2012 to 2022. Family was the predominant place of outbreak, and toxic mushroom poisoning was the most lethal pathogenic factor.

Objection To investigate the value of CT based radiomics in predicting progression of early acute pancreatitis (AP). Methods:From November 2013 to February 2021, 109 patients diagnosed with AP according to the new revised Atlanta classification in Yijishan Hospital of Wannan Medical College were retrospectively analyzed. The patients were divided into progressive group (40 cases) and non-progressive group (69 cases) according to the follow-up results. All patients underwent plain and enhanced abdominal CT scan within a week of onset. The patients were divided into training set (77 cases, including 28 cases in progressive group and 49 cases in non-progressive group) and validation set (32 cases, including 12 cases in progressive group and 20 cases in non-progressive group) in a ratio of 7∶3 using a computer completely random method. Manual region of interest mapping was performed on all levels of pancreas on the plain scan, arterial phase, venous phase and delayed phase CT images, then performed 3D fusion. AK software was used to extract texture features. The minimum redundancy maximum relevance and minimum absolute shrinkage and selection operator regression analysis were used to select features and establish radiomics labels of the plain scan, arterial phase, venous phase, delayed phase and combining the 4 sequences. The multiple logistic regression analysis was used to establish the clinical model by combining clinical features and CT features, and the comprehensive model was established by combining clinical features, CT features and imaging radiomics label. The receiver operating characteristic (ROC) curve was used to evaluate the efficacy of each model in predicting early AP progression and the decision curve analysis (DCA) was used to evaluate the clinical application value of each model.Results:In the training set, logistic regression results showed that edge was an independent predictor (OR=0.16, P=0.033). The clinical model was established using edge and serum calcium level, and its areas under the ROC curve (AUC) in the training set and validation set were 0.69 and 0.70, respectively. Totally 14, 11, 13, 13 and 9 optimal texture features were extracted from the plain scan, arterial phase, venous phase, delayed phase and combined sequence images, respectively. The delay phase image radiomics label had relatively better predictive performance in training set and validation set, and the AUC were both 0.85. The comprehensive model was established based on the delayed phase image radiomics label (OR=2.22, P<0.001) and edge (OR=0.02, P=0.042), and the AUC in the training set and validation set was 0.90 and 0.86, respectively. DCA showed that both the comprehensive model and the delayed phase radiomics label had better benefits. Conclusions:CT radiomics model has high value for predicting progression of AP, and its clinical benefits exhibited superior performance of clinical model.

Objective:To investigate the predictive value of STAF (score for the targeting of atrial fibrillation) score for paroxysmal atrial fibrillation (PAF) in patients with recurrent acute ischemic stroke.Methods:Consecutive patients with recurrent acute ischemic stroke hospitalized in the Department of Neurology, Huizhou Municipal Central Hospital from January 2014 to January 2020 were enrolled retrospectively. All patients were divided into a sinus rhythm (SR) group and a PAF group. PAF was defined as no PAF during the last stroke hospitalization or after discharge, and PAF was found by routine ECG, ambulatory ECG or long-term ECG monitoring after this recurrent acute ischemic stroke. Multivariate logistic regression analysis was used to evaluate the independent related factors of PAF in patients with recurrent acute ischemic stroke. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of STAF for PAF in patients with recurrent acute ischemic stroke. Results:A total of 234 patients with recurrent acute ischemic stroke were enrolled, including 174 males (74.4%), aged 67.15±10.63 years, and 199 (85.0%) in the SR group and 35 (15.0%) in the PAF group. Univariate analysis showed that the proportion of patients in age >62 years old (94.3% vs. 63.8%; χ2=12.777, P<0.001) and left atrial enlargement (54.3% vs. 11.1%; χ2=40.379, P<0.001) of the PAF group was significantly higher than those of the SR group. Multivariate logistic regression analysis showed that age (odd ratio [ OR] 1.071, 95% confidence interval [ CI] 1.028-1.114; P=0.001) or age >62 years ( OR 17.512, 95% CI 2.881-106.453; P=0.002), left atrial enlargement ( OR 17.511, 95% CI 6.298-48.687; P<0.001), absence of vascular etiology ( OR 8.562, 95% CI 2.534-28.923; P=0.001), STAF score ( OR 2.715, 95% CI 1.969-3.744; P<0.001) and STAF score ≥5 ( OR 12.714, 95% CI 5.636-28.681; P<0.001) were independently associated with PAF. ROC curve analysis showed that the area under the curve of STAF for predicting PAF in patients with recurrent acute ischemic stroke was 0.848 (95% CI 0.779-0.917), and the sensitivity and specificity of STAF ≥5 for predicting PAF were 58.1% and 89.4%, respectively; the area under the curve for predicting PAF in patients with recurrent ischemic stroke of undetermined cause was 0.809 (95% CI 0.663-0.956), and the sensitivity and specificity of STAF ≥5 for predicting PAF were 53.8% and 91.3%, respectively. Conclusions:PAF is likely to exist in patients with recurrent acute ischemic stroke and aged >62 years, left atrial enlargement and absence of vascular etiology. STAF has medium predictive value for PAF in patients with recurrent acute ischemic stroke, but the sensitivity is not high.

Cinnamomum migao plants often face different degrees of drought in karst habitats, which can lead to plants’ death, especially in the seedling stage. Widespread of arbuscular mycorrhizal (AM) fungi in karst soils have the potential to address this drought, which is a threat to C. migao seedlings. We inoculated C. migao seedlings with spores from Glomus lamellosum and Glomus etunicatum, two AM fungi widely distributed in karst soils, to observe seedling growth response after simulated drought. Our results showed that 40 g of G. lamellosum and G. etunicatum significantly promoted the growth of C. migao seedlings, 120 days after inoculation. Following a 15-day drought treatment, root colonization of the seedlings with G. lamellosum or G. etunicatum had lower the accumulation of malondialdehyde (MDA) and increased the accumulation of enzymes and osmotic substances in the seedlings. The relative water content in different organs (roots, stems, and leaves) of the drought-stressed seedlings was higher in plants with G. lamellosum or G. etunicatum than in plants without AM fungi colonization. Our results showed that inoculation with AM fungi was an effective means to improve the drought resistance of C. migao seedlings.