Avian coccidiosis, an acute parasitic disease that mainly harms chicks, is widely prevalent across the world, which poses a serious threat to poultry industry. Because of the single prophylactic formulations, veterinary clinical treatment of coccidiosis mainly relies on chemically synthesized agents, polyether ionophores and Chinese herbal medicines. The introduction of novel anticoccidial drugs is slow for a long period of time, and there is an increasing problem of anticoccidial drug resistance following long-term use, which has become an urgent problem to be solved in poultry industry. This review summarizes the levels of anticoccidial drug resistance across China from 2018 to 2023, and analyzes the resistance to various anticoccidial agents in coccidia. It is indicated that the overall prevalence of anticoccidial drug resistance is high in coccidia, and development of novel anticoccidial agents and products with reduced antibiotics use and alternatives of antibiotics is of an urgent need.

OBJECTIVE To explore the efficacy and safety of different doses of bupivacaine liposome （referred to as “LB”） in posterior quadratus lumborum block （QLB） for postoperative analgesia in patients undergoing cesarean section （CS）. METHODS In prospective research method， a total of 168 patients undergoing CS admitted to Chongzhou Maternal and Child Health Hospital from June to December 2024 were randomly divided into LB1 group， LB2 group， and LB3 group （LB of 199， 133 and 67 mg， respectively） according to the random number sorting method， with 56 cases in each group. All patients underwent CS after combined spinal-epidural anesthesia， and received patient-controlled intravenous analgesia and bilateral posterior QLB with different doses of LB after the operation. Visual analogue scale score， Ramsay sedation score， the presence of postoperative block planes and muscle strength classification were observed in the three groups of patients at 6， 12， 24， 48 and 72 hours after the operation. The time of the first compression of the analgesic pump， the dosage of sufentanil and butorphanol within 72 hours after surgery， the number of compressions of the analgesic pump， the analgesic rescue rate， the time of initiating lactation， the score of neonatal behavioral neurological assessment （NBNA）， the time of postoperative exhaust， the indwelling time of urinary catheter， the length of hospital stay， and the total satisfaction at 72 hours after surgery were compared. The occurrence of adverse reactions within 72 hours after the operation was recorded. RESULTS The resting and motor pain scores， the dosage of sufentanil and butorphanol within 72 hours after surgery， the number of compressions of the analgesic pump， the analgesic rescue rate， and the time of initiating lactation at 6， 12， 24， 48 and 72 hours after surgery in the LB1 group and the LB2 group were significantly lower or shorter than those in the LB3 group（P＜0.05）. The proportion of postoperative block planes at 24， 48 and 72 hours after surgery， the time of the first compression of the analgesic pump and the total satisfaction in the LB1 group and the LB2 group were significantly higher or longer than those in the LB3 group（P＜0.05）. The proportion of patients with muscle strength≤grade 3 at 6 hours after surgery in the LB1 group was significantly higher than that in the LB2 and the LB3 groups （P＜0.05）. There were no statistically significant differences in the Ramsay sedation scores at each time point after surgery， NBNA scores， postoperative exhaust time， urinary catheter indwelling time， the length of hospital stay， as well as the occurrence of adverse reactions among the 3 groups （P＞0.05）. CONCLUSIONS Compared with 67 mg of LB， 199 mg and 133 mg of LB can improve the postoperative analgesic effect and total satisfaction of CS patients undergoing posterior QLB， reduce the use of postoperative analgesic drugs， and shorten the time to start lactation. Compared with 199 mg and 133 mg of LB， 67 mg of LB has a smaller impact on the motor function of CS patients. All three doses of LB had no significant effect on the neurobehavioral abilities of newborns, and demonstrated comparable sedative efficacy and safety.

Objective:To conduct a survey of the current status of education service offered to professional master's students in clinical medicine in a grade-A tertiary hospital in Chongqing, China based on the SERVQUAL model, and to discuss the problems with education service as well as measures for improvement.Methods:Based on the SERVQUAL model, a questionnaire consisting of 30 items in 5 dimensions was designed. Each item was rated for an expected score and a perceived score. Medical professional master's students in a Chongqing grade-A tertiary hospital in the first half year of 2022 were surveyed for the expected and perceived quality of education service to calculate service quality (SQ). SPSS 26.0 was used for reliability and validity analyses and descriptive statistical analyses. The results were analyzed using a two-dimensional quadrant graph.Results:A total of 263 valid questionnaires were returned, with an effective response rate of 97.77%. For both the expectation scale and the perception scale, the Cronbach's α values were >0.8, and the Kaiser-Meyer-Olkin values were >0.7, indicating good reliability and validity. The mean expected value of education service quality was 4.28, the mean perceived value was 3.96, and the mean gap value was -0.32. The SQ scores for all the items were negative, except for "provide neat suits for work". The two-dimensional quadrant analysis showed that 6 items were located in quadrant III (low-expectation and low-perception area), and 7 items were located in quadrant IV (high-expectation and low-perception area).Conclusions:The evaluation scale based on the SERVQUAL model can effectively reflect problems in postgraduate education for medical master's students, helping develop strategies to improve the quality of education service.

In this study,the immunological characteristics of the PhoP protein were explored with a two-component system of Mycobacterium tuberculosis(Mtb).Bioinformatics was used to predict the B and T cell epitopes of the PhoP protein.A re-combinant expression plasmid was constructed by PCR analysis of the phoP sequence and cloning into the prokaryotic expres-sion vector pET-28a(+).Competent Escherichia coli BL21 cells were transformed with the recombinant plasmid and expres-sion was induced with IPTG.The recombinant PhoP protein was purified by affinity chromatography.Serum levels of PhoP-specific antibodies in Mtb-infected mice and tuberculosis(TB)patients were analyzed with an ELISA.BALB/c mice were im-munized with the PhoP recombinant protein by intramuscular injection.Sera of mice were collected and antibody titers were detected with an ELISA and specificity was assessed by West-ern blot analysis.Mouse splenocytes were isolated and the pro-portions of IFN-y-positive cells and cytokine levels were detec-ted with an ELISpot and ELISA,respectively.Bioinformatics i-dentified 24 B cell and 11 T cell epitopes of the PhoP protein.A prokaryotic recombinant vector of PhoP was successfully con-structed and the recombinant PhoP protein was obtained by purification.Specific antibody levels to PhoP in sera of Mtb in-fected mice and TB patients increased significantly,with preci-sion of 99.9％and 82.5％,and specificity of 100％,respectively.PhoP protein immunization successfully induced production of specific antibodies in mice.Stimulated by antigens in vitro,IL-2 and IFN-γ levels were significantly increased in the splenocytes of immunized mice.Immunization with the PhoP protein induce a humoral immune response and Thl-dominated cellular immu-nity,indicating that the PhoP protein was immunogenic with diagnostic efficacy for TB.These results lay a foundation to clari-fy the role of PhoP in Mtb infection and application for diagnosis and prevention of TB.

The objective of this study was to determine the frequency and resistance patterns of ESBL-producing E.coli in lambs with diarrhea in the Kashi area,Xinjiang.The findings may provide guidance for the prevention and control of clinical E.coli disease.We collected 385 samples of perianal feces from lambs with diarrhea in the Kashgar area.From these samples,we isolated 371 strains of E.coli.We then used the double-paper-sheet synergistic method to screen for ESBL-producing E.coli.Additionally,we conducted analyses to identify drug-resistance genes,analyze drug resistance,and study the phylo-typing of the screened strains.Of 371 E.coli strains,204 were identified as ESBL-producing strains.The prevalence rates of blaCTX-M,blaCTX-M-1G,blaCTX-M-9G,and bla TEM resistance genes was 67.65％,69.12％,30.39％,and 63.73％,respectively.All ESBL-pro-ducing strains were resistant to multiple drugs,with resistance rates ranging from 90.69％to 100％for eight specific drugs:ampicillin,cefotaxime,gentamicin,enrofloxacin,azithromy-cin,tetracycline,chloramphenicol,methotrexate,and amitrazine.The phylogenetic subgroups of the strains were distributed primarily in groups A and D.Among group A strains,41.11％exhibited resistance to ten drugs,whereas among group D strains,40％exhibited resistance to 11 drugs.ESBL-pro-ducing strains of Escherichia coli are the main pathogens cau-sing diarrhea in lambs in the Kashgar region;group A is the main group,and all groups are multi-drug resistant.

Objective To explore the current status of H.pylori infection in the natural population of Sanya City,analyze its influencing factors,and provide a reference basis for the prevention and control of H.pylori infection.Methods A total of 677 residents from four districts of Sanya City were selected by overall stratified random sampling method,and were subjected to urea 14C breath test and questionnaire survey to calculate the positive rate of H.pylori in the natural population and analyze the influencing factors of H.pylori infection.Results A total of 606 residents were included,and the number of H.pylori positive detections was 261,with a positive detection rate of 38.5％.Among them,different ethnicity,marital status,smoking,eating vegetables and fruits,and literacy level were associated with H.pylori infection(P＜0.05);gender,age,BMI,alcohol consumption,drinking water source,betel quid chewing,and the number of cohabitants were not significantly associated with H.pylori infection(P＞0.05).Family infection was an independent risk factor for H.pylori infection in the natural population of Sanya City,and Li ethnicity,frequent consumption of fruits and vegetables,and college and higher education level were independent protective factors for H.pylori infection in the natural population of Sanya City.Conclusion The rate of H.pylori infection in the natural population of Sanya City is lower than the national average.Consuming more fruits and vegetables and improving the awareness of hygiene protection are conducive to the prevention of H.pylori infection;and the promotion of the family and related members with the same examination and treatment is important to avoid aggregation of infection within the family.

Myeloid neoplasms (MNs) belong to a group of hematological malignancies characterized by the abnormal biological functions of hematopoietic stem progenitor cells. The abnormal immune and hematopoietic microenvironment of patients with MN interact with malignant clonal hematopoietic stem cells, promoting the occurrence and development of their diseases. MN large granular lymphocyte proliferation (MN-LGLP) is a special and rare clinical phenomenon in this type of disease. Currently, research on this disease in domestic and international cohorts is limited. This study analyzes the clinical and laboratory characteristics of this type of patient and explores the impact of LGLP on the clinical characteristics and survival of patients with MN. Patients with MN-LGLP are prone to neutropenia and splenomegaly. The presence of LGLP is not a risk factor affecting the survival of patients with MN-LGLP. STAG, ASXL1, and TET2 are the most common accompanying gene mutations in MN-LGLP, and patients with MN-LGLP and STAG2 mutations have poor prognoses.

Objective The MMV-Net,a deep learning framework based on mammogram multiple views,was constructed to evaluate the classification performance of the model for benign and malignant masses.Methods A retrospective analysis was conduc-ted on a dataset of 1 585 breast X-ray images from Harbin Medical University Cancer Hospital from 2018 to 2020,including 806 be-nign cases and 779 malignant cases.The dataset was divided into the training set(n=1268)and the test set(n=317)according to an 8∶2 ratios,and the training set was stratified according to the 5-fold cross validation.The integrated DDSM dataset and INBreast dataset were used as external test sets(n=1645)to evaluate the model performance.Each case in the input layer contained 4 views.The MMV-Net model was constructed by removing the last two layers of the ResNet22 network structure and adding an average poo-ling layer as the feature extraction layer,as well as fully connection layer and softmax activation function as the decision layers.Bayes-ian hyperparameter optimization was used.The performance of MMV-Net,MFA Net,and ensemble inception V4 models in AUC val-ues,accuracy,precision,recall and F1 scores were compared.Results The AUC values of MMV-Net model for distinguishing benign and malignant masses on the test set were 0.913,0.882 for MFA-Net,and 0.865 for inception V4.The accuracy and precision evalu-ation metrics of the MMV-Net model were also higher than the other two models.Conclusion The deep learning MMV-Net model based on multiple views of mammogram is helpful for the classification of benign and malignant breast masses.

Objective:To construct a classification management model of medical equipment in public hospitals based on association rules algorithm,and to analyze its application effect in hospital equipment management.Methods:Equipment classification management was performed based on Apriori algorithm(association rule analysis)and K-means algorithm(equipment abnormal information mining)in the association rules algorithm,the classification management model of medical equipment in public hospitals was constructed to mine the abnormal characteristics of equipment status.A total of 244 medical devices in clinical use in Beijing Huilongguan Hospital from 2022 to 2023 were selected.According to the application of the classification management model of medical equipment in public hospitals based on the association rule algorithm,the equipment use period from January to December 2022 was set before the application of the association rule algorithm model,and the equipment use period from January to December 2023 was set to the time after the application of the association rule algorithm model.The scores of equipment classification management,the failure rate of different types of equipment and equipment efficiency score before and after the application of association rule algorithm model were compared.Results:After the application of association rule algorithm model,the average scores of warehousing management,use management,maintenance management and scrap management were(89.65±4.65)points,(90.25±4.36)points,(87.69±3.12)points and(90.36±3.39)points,respectively,which were higher than before the application,the difference was statistically significant(t=17.866,14.671,18.128,19.479,P<0.05).After the application of association rule algorithm model,the number of medical image diagnostic and auxiliary equipment,health monitoring equipment,rehabilitation equipment and intervention and treatment equipment that failed was 2,3,2,and 3,and the failure rates were 3.33%,4.69%,2.86%and 6.00%,respectively,which were lower than those before the application,the difference was statistically significant(x2=5.925,6.117,7.937,5.316,P<0.05).After the application of association rule algorithm model,the average scores of overall utilization efficiency,quality stability efficiency and accurate diagnosis and treatment efficiency of the equipment were(96.39±3.69)points,(94.23±3.06)points and(95.47±4.36)points,respectively,which were higher than those before the application,and the difference was statistically significant(t=16.762,17.919,11.769,P<0.05).Conclusion:The application of the classification management model of medical equipment in public hospitals based on association rules algorithm can realize the classification management of medical equipment in hospitals,improve the operating efficiency and management level of equipment,and reduce the equipment failure rate.

Objective:To establish a prediction model for symptomatic radiation pneumonitis (SRP) after radiotherapy for thoracic cancer based on a longitudinal cohort and dose interval variations.Methods:Clinical data of 587 patients who received thoracic radiotherapy in Department of Radiotherapy of Yunnan Cancer Hospital from July 2022 to June 2023 were retrospectively analyzed. The National Cancer Institute common terminology criteria for adverse events (CTCAE) version 5.0 was used to grade radiation pneumonitis, and clinical factors, traditional independent dosimetric characteristics and dose interval variation characteristics were collected. Features used to predict the occurrence of SRP were screened using genetic algorithms and analyzed the correlation between the selected features and SRP occurrence. Predictive models for SRP occurrence were established using the selected features and evaluated, and the optimal predictive model was visualized using a column chart.Results:The incidence of SRP was 35.94%. Five clinical factors, seven independent dosimetric features and six dose interval variation features were screened out by genetic algorithms to effectively predict the occurrence of SRP. The area under ROC curve (AUC) of clinical factors combined with traditional independent dosimetric factors and dose interval variation factors was 76%. The AUC of clinical factors combined with traditional independent dosimetric factors and that of clinical factors combined with dose interval variation factors was 69% and 67%, respectively. The addition of the characteristics of dose interval variation factors significantly improved the effectiveness of the prediction model.Conclusions:The supplement of the characteristics of dose interval variation factors can significantly improve the performance of the SRP prediction model for thoracic tumors after radiotherapy. The SRP prediction model based on dose interval variations can effectively predict the occurrence of SRP.