Objective:To explore the clinical application value of artificial intelligence（AI）-assisted training in enhancing the accuracy of nuchal translucency（NT）identification，standardization of measurement，and diagnostic efficacy for abnormalities among ultrasound residents.Methods:A retrospective collection of 300 standard fetal NT ultrasound images was conducted at the Center for Medical Ultrasound，Suzhou Hospital Affiliated of Nanjing Medical University from January 2018 to June 2024. The AI model performed NT measurements and diagnoses once. Four sonographers of different seniority levels（including two resident physicians）independently conducted NT measurements and diagnoses twice. Prior to the experiment，the middle-age and resident sonographers had uniformly completed traditional theory training. Following the first independent measurements，the two resident sonographers received additional AI-assisted training，after which all 4 sonographers performed the second independent measurements. A fetal medicine expert evaluated blindly all the results and compared the differences in NT recognition accuracy，measurement standard rate and diagnosis accuracy between the middle-age sonographer（traditional training only）and two resident sonographers（traditional + AI-assisted training）.Results:For the middle-aged sonographer who only received traditional lecture-based training，the accuracy of NT recognition，standardization rate of measurement，or diagnostic accuracy were not significantly improved befroe and after the training，and the diffrence was not statistically significant（ χ2=0.189，1.887，0.326；all P>0.05）. In contrast，the second-year resident（Resident 2）and first-year resident（Resident 1），who received both traditional lecture-based training and AI training，demonstrated some improvements in the accuracy of NT measurement site recognition，though the differences were not statistically significant（ χ2=1.301，2.418；all P>0.05）. However，both residents did significant improvements in the standardization rate of NT measurement（ χ2=25.768，17.035；all P<0.05）. In terms of diagnostic accuracy，Resident 1 did significant improvement（ χ2=10.180， P<0.05），while Resident 2 also did some improvement，though the difference was not statistically significant（ χ2=2.573， P>0.05）. Conclusions:The AI-assisted training system enhances the ability of ultrasound resident sonographers to recognize，measure，and diagnose NT，providing a novel and efficient training model for standardized residency training in ultrasound specialties.

Objective To explore the feasibility of prototype of flexible ultrasound array transducer for measuring intravascular diameter and blood flow velocity.Methods A prototype of flexible ultrasonic array transducer composed of a surface mount flexible ultrasonic array transducer(referred to as the transducer)and acquisition system was designed and fabricated.Doppler body model and vascular simulation control system was used to simulate human blood.Mindray M7 color multi-functional ultrasound diagnostic instrument(abbreviated as M7)and the prototype were adopted to detect pulse wave excitation mode,spectral morphology,echo signal time interval,blood flow velocity,etc.Taken the results of M7 as standards,the effectiveness of the prototype was evaluated.Then the inner diameter and flow velocity of left common carotid artery,left brachial artery and left radial artery of 20 healthy controls(HC)were measured respectively using M7 and the prototype,and the consistency of measurement results were analyzed to evaluate the accuracy of the prototype.The safety of the prototype was evaluated according to subjectively scoring the comfort level of HC applying the transducer and whether there was skin discomfort,injury,etc.after removing the transducer.Results The collected blood flow spectrum of the above vascular simulation control system acquire with the prototype were clear,and the spectral morphology,flow velocity,as well as echo signal time interval were basically consistent with those of M7.The consistency of the inner diameter of left common carotid artery,left brachial artery and left radial artery measured by the prototype and M7 in 20 HC were all very strong(ICC=0.919-0.992),while of flow velocities were moderate or very strong(ICC=0.524-0.831).The subjective score of comfort level of application of transducer was 3(2,3),and no skin discomfort occurred.Conclusion Flexible ultrasound array transducer technology could be used to measure intravascular diameter and blood flow velocity.

Objective To explore the feasibility of prototype of flexible ultrasound array transducer for measuring intravascular diameter and blood flow velocity.Methods A prototype of flexible ultrasonic array transducer composed of a surface mount flexible ultrasonic array transducer(referred to as the transducer)and acquisition system was designed and fabricated.Doppler body model and vascular simulation control system was used to simulate human blood.Mindray M7 color multi-functional ultrasound diagnostic instrument(abbreviated as M7)and the prototype were adopted to detect pulse wave excitation mode,spectral morphology,echo signal time interval,blood flow velocity,etc.Taken the results of M7 as standards,the effectiveness of the prototype was evaluated.Then the inner diameter and flow velocity of left common carotid artery,left brachial artery and left radial artery of 20 healthy controls(HC)were measured respectively using M7 and the prototype,and the consistency of measurement results were analyzed to evaluate the accuracy of the prototype.The safety of the prototype was evaluated according to subjectively scoring the comfort level of HC applying the transducer and whether there was skin discomfort,injury,etc.after removing the transducer.Results The collected blood flow spectrum of the above vascular simulation control system acquire with the prototype were clear,and the spectral morphology,flow velocity,as well as echo signal time interval were basically consistent with those of M7.The consistency of the inner diameter of left common carotid artery,left brachial artery and left radial artery measured by the prototype and M7 in 20 HC were all very strong(ICC=0.919-0.992),while of flow velocities were moderate or very strong(ICC=0.524-0.831).The subjective score of comfort level of application of transducer was 3(2,3),and no skin discomfort occurred.Conclusion Flexible ultrasound array transducer technology could be used to measure intravascular diameter and blood flow velocity.

Objective:To explore the clinical application value of artificial intelligence（AI）-assisted training in enhancing the accuracy of nuchal translucency（NT）identification，standardization of measurement，and diagnostic efficacy for abnormalities among ultrasound residents.Methods:A retrospective collection of 300 standard fetal NT ultrasound images was conducted at the Center for Medical Ultrasound，Suzhou Hospital Affiliated of Nanjing Medical University from January 2018 to June 2024. The AI model performed NT measurements and diagnoses once. Four sonographers of different seniority levels（including two resident physicians）independently conducted NT measurements and diagnoses twice. Prior to the experiment，the middle-age and resident sonographers had uniformly completed traditional theory training. Following the first independent measurements，the two resident sonographers received additional AI-assisted training，after which all 4 sonographers performed the second independent measurements. A fetal medicine expert evaluated blindly all the results and compared the differences in NT recognition accuracy，measurement standard rate and diagnosis accuracy between the middle-age sonographer（traditional training only）and two resident sonographers（traditional + AI-assisted training）.Results:For the middle-aged sonographer who only received traditional lecture-based training，the accuracy of NT recognition，standardization rate of measurement，or diagnostic accuracy were not significantly improved befroe and after the training，and the diffrence was not statistically significant（ χ2=0.189，1.887，0.326；all P>0.05）. In contrast，the second-year resident（Resident 2）and first-year resident（Resident 1），who received both traditional lecture-based training and AI training，demonstrated some improvements in the accuracy of NT measurement site recognition，though the differences were not statistically significant（ χ2=1.301，2.418；all P>0.05）. However，both residents did significant improvements in the standardization rate of NT measurement（ χ2=25.768，17.035；all P<0.05）. In terms of diagnostic accuracy，Resident 1 did significant improvement（ χ2=10.180， P<0.05），while Resident 2 also did some improvement，though the difference was not statistically significant（ χ2=2.573， P>0.05）. Conclusions:The AI-assisted training system enhances the ability of ultrasound resident sonographers to recognize，measure，and diagnose NT，providing a novel and efficient training model for standardized residency training in ultrasound specialties.

Objective:To investigate the etiological characteristics of hand, foot and mouth disease (HFMD) and the VP1 gene evolution of coxsackievirus A6 (CVA6) in Qingdao from 2020 to 2022.Methods:Total enterovirus (EV), enterovirus 71 (EV71), coxsackievirus A16 (CVA16), CVA6 and coxsackievirus A10 (CVA10) were detected by fluorescent RT-PCR in throat swab samples from HFMD patients in Qingdao from 2020 to 2022. The full-length sequence amplification of VP1 gene and gene sequence determination of CVA6 isolates were performed, and the phylogenetic and molecular characteristics were analyzed by MEGA-X software.Results:The overall positive rate of enteroviruses in 1 645 samples collected during 2020-2021 was 80.73%(1 328/1 645). The proportions of EV71, CVA16, CVA6, CVA10 and other enteroviruses were 0.08%(1/1 328), 19.65%(261/1 328), 68.15%(905/1 328), 0.98%(13/1 328) and 11.14%(148/1 328), respectively. Children under 5 years old accounted for 75.68% (1 245/1 645) of all cases and 100% (2/2) of severe cases. A phylogenetic tree was constructed based on the VP1 region sequences of 45 CVA6 strains showing all strains belonging to the D3a subtype. There were 10 non-synonymous mutations of amino acids in the VP1 protein by gene evolution analysis.Conclusions:CVA6 D3a subtype is the main epidemic strain causing HFMD in Qingdao from 2020 to 2022, especially in children under 5 years old.

Multiple sclerosis (MS) is a neuroinflammatory demyelinating disease, mediated by pathogenic T helper 17 (Th17) cells. However, the therapeutic effect is accompanied by the fluctuation of the proportion and function of Th17 cells, which prompted us to find the key regulator of Th17 differentiation in MS. Here, we demonstrated that the triggering receptor expressed on myeloid cells 2 (TREM-2), a modulator of pattern recognition receptors on innate immune cells, was highly expressed on pathogenic CD4-positive T lymphocyte (CD4⁺ T) cells in both patients with MS and experimental autoimmune encephalomyelitis (EAE) mouse models. Conditional knockout of Trem-2 in CD4⁺ T cells significantly alleviated the disease activity and reduced Th17 cell infiltration, activation, differentiation, and inflammatory cytokine production and secretion in EAE mice. Furthermore, with Trem-2 knockout in vivo experiments and in vitro inhibitor assays, the TREM-2/zeta-chain associated protein kinase 70 (ZAP70)/signal transducer and activator of transcription 3 (STAT3) signal axis was essential for Th17 activation and differentiation in EAE progression. In conclusion, TREM-2 is a key regulator of pathogenic Th17 in EAE mice, and this sheds new light on the potential of this therapeutic target for MS.
Animals ; Humans ; Mice ; CD4-Positive T-Lymphocytes/pathology* ; Cell Differentiation ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Mice, Inbred C57BL ; Multiple Sclerosis ; Th1 Cells/pathology*

Objective:To develop an expert consensus on safety management of inpatients with Alzheimer's disease (AD) (referred to as the " Consensus") and standardize safety management strategies for AD inpatients. Methods:The evidence on safety management of AD inpatients was searched, evaluated, and summarized, with a search period from database establishment to July 31, 2023. This study conducted methodological quality evaluation and evidence extraction on the included article to form a consensus draft. A total of 24 experts from 15 hospitals across the country were selected for two rounds of Delphi expert consultation to analyze, revise, and improve their opinions, forming the final draft of the Consensus. Results:The positive coefficients for both rounds of expert consultation were 100.00% (24/24). In the second round of consultation, the expert judgment basis coefficient was 0.925, familiarity level was 0.846, authority coefficient was 0.886, Kendall harmony coefficient was 0.044 ( P<0.01). The Consensus elaborated on five common safety problems (loss, falling, aspiration/choking, self-injury/other injury, and medication errors in AD inpatients) from three aspects (assessment, identification of risk factors, and nursing strategies) . Conclusions:The Consensus is scientific and practical to a certain extent, providing guidance and reference for the safety management practice of AD inpatients.

Objective:To form an expert consensus on plasma exchange nursing for severe autoimmune encephalitis ( " Consensus" for short) and standardize the practice of plasma exchange nursing for severe autoimmune encephalitis. Methods:After reviewing and summarizing the literature related to plasma exchange of severe autoimmune encephalitis, the relevant nursing evidence was extracted and the draft of Consensus was formed. From September to October 2023, a total of 20 experts were selected to conduct two rounds of expert letter consultation, and then the expert results were analyzed, sort outed and modified to form the final draft of the Consensus. Results:The expert positive coefficient was 100.00% (20/20), the expert judgment basis coefficient was 0.89, the expert familiarity coefficient was 0.85, the expert authority coefficient was 0.87, and the Kendall harmony coefficient was 0.15-0.22 ( P<0.05). The final Consensus included plasma exchange quality control management, preparation and evaluation before plasma exchange, setting and monitoring during plasma exchange, and evaluation and maintenance after plasma exchange. Conclusions:This Consensus is practical and can provide guidance for clinical nursing practice and quality control of plasma exchange in severe autoimmune encephalitis.

Objective Examining the expansion pattern and spatial distribution equilibrium of TCM staff in TCM-style hospitals between 2010 and 2021 in China,as well as projecting the shift in the overall staff's trend from 2022 to 2025,will serve as a guide for maximizing the distribution of TCM human resources.Methods The trend of the total number of employees from 2022 to 2025 was predicted using a combination of the ARIMA forecasting model,the GM (1,1) gray forecasting model,and the exponential smoothing model.Spatial autocorrelation analysis was utilized to determine the balance of resource allocation. Results TCM practitioners (assistant),TCM pharmacists (bachelor),and trainee TCM physicians in TCM-type hospitals in China had average annual growth rates of 8.11％,3.95％,and 1.35％,respectively,between 2010 and 2021.In terms of spatial distribution,in 2021,the high-high concentration of TCM practitioners (assistant) per 10000 population was concentrated in the East,TCM practitioners (sergeants) were concentrated in Tianjin and Heilongjiang Province,and trainee TCM practitioners were concentrated in the southwestern region.In terms of temporal changes,the compared to the"13th Five-Year Plan",the average yearly growth rate of TCM personnel in TCM hospitals during the"14th Five-Year Plan"period was comparatively slower.Conclusion There is a spatial clustering of the same qualities and an unequal overall growth tendency of TCM personnel in TCM hospitals in China.However,the spatial clustering trend of TCM workers over time is not consistent.

Objective Examining the expansion pattern and spatial distribution equilibrium of TCM staff in TCM-style hospitals between 2010 and 2021 in China,as well as projecting the shift in the overall staff's trend from 2022 to 2025,will serve as a guide for maximizing the distribution of TCM human resources.Methods The trend of the total number of employees from 2022 to 2025 was predicted using a combination of the ARIMA forecasting model,the GM (1,1) gray forecasting model,and the exponential smoothing model.Spatial autocorrelation analysis was utilized to determine the balance of resource allocation. Results TCM practitioners (assistant),TCM pharmacists (bachelor),and trainee TCM physicians in TCM-type hospitals in China had average annual growth rates of 8.11％,3.95％,and 1.35％,respectively,between 2010 and 2021.In terms of spatial distribution,in 2021,the high-high concentration of TCM practitioners (assistant) per 10000 population was concentrated in the East,TCM practitioners (sergeants) were concentrated in Tianjin and Heilongjiang Province,and trainee TCM practitioners were concentrated in the southwestern region.In terms of temporal changes,the compared to the"13th Five-Year Plan",the average yearly growth rate of TCM personnel in TCM hospitals during the"14th Five-Year Plan"period was comparatively slower.Conclusion There is a spatial clustering of the same qualities and an unequal overall growth tendency of TCM personnel in TCM hospitals in China.However,the spatial clustering trend of TCM workers over time is not consistent.