OBJECTIVE To explore and establish a full-cycle management model for drug traceability codes that aligns with national policy requirements and the practical needs of healthcare institutions， thereby enhancing the refinement of drug management and the level of medication safety. METHODS A tripartite strategy integrating “hardware deployment， system transformation， and process re-engineering” was adopted. This involved the introduction of intelligent identification devices （personal digital assistant， high-definition industrial reader）， the modification of the hospital information system interface， and the re-engineering of workflows （drug warehousing， dispensing and distribution， drug withdrawal， uploading to the insurance platform） to achieve comprehensive， informatized collection and association of drug traceability codes throughout all stages. RESULTS A full-cycle management model for drug traceability codes was successfully established， realizing the goals of making drugs “traceable to their source， trackable in their distribution， and accountable in their responsibility”. The patient waiting time for medication dispensing before and after the implementation was [3.08（1.67，5.58）] min and [3.28（1.77，5.98）] min， respectively. Among them， the patient waiting time under the pre-preparation mode was [3.60（2.13，6.35）] min and [3.50（2.03，6.30）] min， respectively； the patient waiting time under the real-time mode was [2.05（0.83，4.03）] min and [2.78（1.18，5.38）] min， respectively； the number of dispensing errors was 3， 0， respectively； the staffing of relevant positions had not been increased. CONCLUSIONS The drug traceability code management model constructed from a full-cycle perspective effectively meets national policy requirements. It provides data support for refined hospital management and offers solid technical and procedural safeguards for ensuring patient medication safety and strengthening medical insurance fund supervision， demonstrating practical value.

Objective In order to understand the current resistance status of Aedes albopictus(Ae. albopictus) adult population to commonly used insecticides and the resistance dynamics development in Zhejiang Province and provide a theoretical basis for the scientific and rational use of hygienic insecticides. Methods Resistance determination was carried out using the diagnostic dose method(GB/T 26347-2010)recommended by WHO in the adult mosquito contact cylinder method to monitor the resistance of Ae. albopictus field populations in 11 cities and districts in Zhejiang Province in 2024. Results The monitoring result showed that adult Ae. albopictus in 11 areas were resistant or suspected resistant populations to both cis-cypermethrin and permethrin; suspected and resistant populations to the organophosphate insecticide malathion were as high as 81.82%; while suspected resistance to the carbamate insecticide residual carbofuran accounted for 45.45%, and the rest of the monitoring sites were sensitive to it. Conclusions The result suggest that the generalized resistance of Ae. albopictus populations to pyrethroids and organophosphorus insecticides in the field in Zhejiang Province needs to be highly emphasized. In future mosquito vector and mosquito-borne disease control, insecticides should be selected based on the resistance monitoring information, while following scientific guidelines for insecticide use.

Objective:To evaluate the safety and efficacy of accelerator-based boron neutron capture therapy (AB-BNCT) in the treatment of recurrent and refractory malignant tumors.Methods:The data of 14 patients admitted to Xiamen Humanity Hospital from September 2022 to April 2023 were prospectively collected, including 7 patients with primary brain malignancies and 7 patients with locally recurrent inoperable head and neck malignancies. All patients received intravenous infusion of boron drug (NBB-001, p-dihydroxyborylphe nylalanine, a patented freeze-dried formulation) at a total nominal dosage of 500 mg/kg (11 patients) or 750 mg/kg (3 patients), and were irradiated with neutrons (operating with NeuPex system). Adverse events after treatment were recorded and assessed. The primary efficacy endpoint was the 90 d objective response rate (ORR), while the secondary endpoints included progression-free survival (PFS) and complete response rate (CRR). Data were compiled and analyzed by SAS 9.4 software. The rate and 95% CI were calculated using Clopper-Pearson method. Results:The median dose delivered to 80% of the target volume (D 80%) was 16.80 GyE (range: 8.93-23.79 GyE). The most common adverse reactions were hyperamylasemia, alopecia, and hyperprolactinemia. Five patients experienced 8 cases of grade 3 or above adverse events, including 1 case of grade 4 acute kidney injury and 7 cases of grade 3 adverse events. All adverse events were recovered after observation or treatment. At 90 d after treatment, the ORR of all patients was 9/14 (64%, 95% CI: 35%-87%), disease control rate (DCR) was 10/14 (71%, 95% CI: 42%-92%), CRR was 2/14 (14%, 95% CI: 2%-42%); and the best overall response during the entire course included an ORR of 10/14 (71% ,95% CI: 42%-92%), DCR of 13/14 (93%, 95% CI: 66%-100%), and CRR of 3/14 (21% ,95% CI: 5%-51%). The 1-year survival rate for head and neck malignancies was 71.4%, and the 2-year survival rate was 42.8%. The 1-year survival rate for recurrent brain malignancies was 42.8%. Conclusion:AB-BNCT demonstrates favorable safety and promising efficacy in treating primary brain malignancies and recurrent/refractory head and neck malignancies, representing a potential therapeutic option.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective:To evaluate the safety and efficacy of accelerator-based boron neutron capture therapy (AB-BNCT) in the treatment of recurrent and refractory malignant tumors.Methods:The data of 14 patients admitted to Xiamen Humanity Hospital from September 2022 to April 2023 were prospectively collected, including 7 patients with primary brain malignancies and 7 patients with locally recurrent inoperable head and neck malignancies. All patients received intravenous infusion of boron drug (NBB-001, p-dihydroxyborylphe nylalanine, a patented freeze-dried formulation) at a total nominal dosage of 500 mg/kg (11 patients) or 750 mg/kg (3 patients), and were irradiated with neutrons (operating with NeuPex system). Adverse events after treatment were recorded and assessed. The primary efficacy endpoint was the 90 d objective response rate (ORR), while the secondary endpoints included progression-free survival (PFS) and complete response rate (CRR). Data were compiled and analyzed by SAS 9.4 software. The rate and 95% CI were calculated using Clopper-Pearson method. Results:The median dose delivered to 80% of the target volume (D 80%) was 16.80 GyE (range: 8.93-23.79 GyE). The most common adverse reactions were hyperamylasemia, alopecia, and hyperprolactinemia. Five patients experienced 8 cases of grade 3 or above adverse events, including 1 case of grade 4 acute kidney injury and 7 cases of grade 3 adverse events. All adverse events were recovered after observation or treatment. At 90 d after treatment, the ORR of all patients was 9/14 (64%, 95% CI: 35%-87%), disease control rate (DCR) was 10/14 (71%, 95% CI: 42%-92%), CRR was 2/14 (14%, 95% CI: 2%-42%); and the best overall response during the entire course included an ORR of 10/14 (71% ,95% CI: 42%-92%), DCR of 13/14 (93%, 95% CI: 66%-100%), and CRR of 3/14 (21% ,95% CI: 5%-51%). The 1-year survival rate for head and neck malignancies was 71.4%, and the 2-year survival rate was 42.8%. The 1-year survival rate for recurrent brain malignancies was 42.8%. Conclusion:AB-BNCT demonstrates favorable safety and promising efficacy in treating primary brain malignancies and recurrent/refractory head and neck malignancies, representing a potential therapeutic option.

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

Objective:To identify the CDYL-interacting proteins in murine testis and investigate the mechanism of CDYL in-volved in spermatogenesis.Methods:CDYL-interacting partners in testis were identified using co-immunoprecipitation coupled with liquid chromatography-tandem mass spectrometry(LC-MS/MS).Expression pattern of CDYL-interacting protein MYH9 was analyzed through immunohistochemistry(IHC),confocal immunofluorescence(IF)and Western blot(WB)in mouse testicular cells.The effect of the Cdyl conditional knockout(CdylcKO)in spermatogenic cell on Myh9 expression was quantified via RT-qPCR,WB and IF imaging in both spermatids and spermatozoa from cauda epididymides.Results:Direct interaction between MYH9 and CDYL was confirmed in murine testis.During spermiogenesis,MYH9 exhibited co-localization with CDYL at the manchette structure,and binding to F-ACTIN,the component of manchette.In cauda epididymal spermatozoa,MYH9 signal concentrated on acrosomal region and con-tinuously distributed along the tail length.Conditional deletion of Cdyl in spermatogenic cell resulted in the transcriptional downregula-tion of Myh9.In spermatids,CdylcKO led to reduced but retained MYH9 localization to the disorganized manchette structure.In sperma-tozoa from CdylcKO mice,abnormalities of MYH9 localization were observed,including attenuation of acrosomal signal and/or partial vanishment/enhancement of tail signal.Conclusion:In murine spermatids,MYH9 protein is localized to the manchette structure,with its expression and subcellular distribution is affected by CDYL protein.CDYL-MYH9 interaction is essential for the spermiogenesis.

Objective:To explore the current status of back patting and sputum drainage nursing performed by nurses in the Neurological Intensive Care Unit (NICU) and their design requirements for a nursing robot, providing a reference for the design of nursing robots for back patting and sputum drainage.Methods:This descriptive qualitative study employed a purposive sampling method. From January to February 2024, semi-structured interviews were conducted with 15 nurses from the NICU of Xuanwu Hospital, Capital Medical University. Data were analyzed using Colaizzi 7-step analysis method.Results:A total of three major issues were identified regarding the current practice of back patting and sputum drainage nursing by NICU nurses: heavy workload and time-consuming; difficulties in patient positioning and maintenance; deficiencies in nursing care. The design requirements for a back patting and sputum drainage nursing robot were categorized into two main themes with 10 sub-themes: functional requirements (turning function, supporting function, intelligent recognition function, abnormality detection with alarm or pause feature, and evaluation of post-percussion effectiveness) ; design requirements (basic functional design, support component design, percussion component design, coordination between support and percussion functions, and overall structural design) .Conclusions:Understanding the design requirements of NICU nurses for a back patting and sputum drainage nursing robot provides valuable insights for developing a safe, scientific, reasonable, and effective robotic system.