Our acupuncture-moxibustion(Acu-Moxi)field has entered an era of digital and intelligent transformation,yet systematic and in-depth development remains limited.This article aims to provide an overview and reflection on the digital and intelligent progress of Acu-Moxi in China,offering systematic insights for the comprehensive development of this field.Through a retrieval from CNKI,VIP,and Wanfang databases,along with a discussion of relevant policies,case studies,achievements,and updates,the study evaluated the current advancements in the digitization and intelligence of Acu-Moxi,also discussing the current advantages and challenges.Findings revealed an overall upward trend in publications related to digital-intelligent technologies in Acu-Moxi,key forms including robotics,acupuncture point digitization,smart acupuncture devices,and clinical decision-making models,highlighting the empowering potential of digital intelligence across the discipline.Recently,publications of the Acu-Moxi digitization has decreased sharply,and the number of Acu-Moxi research about digital and intelligent transformation has increased.In conclusion,the field has undergone a transition from comprehensive digital accumulation to increasing intelligence,moving toward integrated digital-intelligent development.However,the internal development of digital and intelligent Acu-Moxi remains uneven.To achieve a harmonious intelligent Acu-Moxi ecosystem,it is crucial to leverage opportunities of discipline and times for systematic and balanced improvement.

OBJECTIVE To investigate the current status of monitoring indicators related to the"Perioperative In-fection Control"in medical institutions above the secondary level in Guizhou Province,and to delve into the imple-mentation of key measures for infection prevention and control during the perioperative period for patients under-going surgical operations.METHODS Based on the"Implementation Plan for the'Perioperative Infection Control'Initiative in Guizhou Province",a"Case Investigation Form on Key Measures for Infection Prevention and Control During the Perioperative Period for Patients Undergoing Surgical Operation"was developed.A total of 138 medi-cal institutions participated in the case investigation,and a total of 2 128 cases were investigated.RESULTS The overall monitoring indicators for the"Perioperative Infection Control"initiative in the 138 medical institutions a-bove the secondary level in Guizhou Province were at a relatively low level.The skin cleansing compliance rate was 80.32％,the hair removal compliance rate was 16.43％,the prophylactic antibacterial drug administration rate within 0.5-1 hour before surgery was 55.94％and the antibacterial drug discontinuation rate within 24 hours after prophylactic medication for type Ⅰ incision surgeries was 56.48％.The hair removal compliance rate was higher in tertiary medical institutions(19.21％)than in secondary medical institutions(14.34％)(P=0.039).The distri-bution of the four monitoring indicators varied in clinical departments and surgery types,with statistically signifi-cant differences(P＜0.05).The preferred method for surgical site skin cleansing in medical institutions across the province was local wiping,primarily with clean water(57.21％).The primary method for hair removal was razors(68.82％),and hair removal on the day of surgery was most common(61.75％).CONCLUSIONS Conduc-ting a survey on the current status of"Perioperative Infection Control"initiative monitoring indicators in medi-cal institutions in Guizhou Province helps to understand the implementation of key measures for perioperative in-fection prevention and control and set intervention targets,thus providing references for establishing a dynam-ic monitoring indicator change mechanism.

OBJECTIVE To investigate the current status of monitoring indicators related to the"Perioperative In-fection Control"in medical institutions above the secondary level in Guizhou Province,and to delve into the imple-mentation of key measures for infection prevention and control during the perioperative period for patients under-going surgical operations.METHODS Based on the"Implementation Plan for the'Perioperative Infection Control'Initiative in Guizhou Province",a"Case Investigation Form on Key Measures for Infection Prevention and Control During the Perioperative Period for Patients Undergoing Surgical Operation"was developed.A total of 138 medi-cal institutions participated in the case investigation,and a total of 2 128 cases were investigated.RESULTS The overall monitoring indicators for the"Perioperative Infection Control"initiative in the 138 medical institutions a-bove the secondary level in Guizhou Province were at a relatively low level.The skin cleansing compliance rate was 80.32％,the hair removal compliance rate was 16.43％,the prophylactic antibacterial drug administration rate within 0.5-1 hour before surgery was 55.94％and the antibacterial drug discontinuation rate within 24 hours after prophylactic medication for type Ⅰ incision surgeries was 56.48％.The hair removal compliance rate was higher in tertiary medical institutions(19.21％)than in secondary medical institutions(14.34％)(P=0.039).The distri-bution of the four monitoring indicators varied in clinical departments and surgery types,with statistically signifi-cant differences(P＜0.05).The preferred method for surgical site skin cleansing in medical institutions across the province was local wiping,primarily with clean water(57.21％).The primary method for hair removal was razors(68.82％),and hair removal on the day of surgery was most common(61.75％).CONCLUSIONS Conduc-ting a survey on the current status of"Perioperative Infection Control"initiative monitoring indicators in medi-cal institutions in Guizhou Province helps to understand the implementation of key measures for perioperative in-fection prevention and control and set intervention targets,thus providing references for establishing a dynam-ic monitoring indicator change mechanism.

Although the COVID-19 pandemic has subsided, the risk of the outbreak of new emerging infectious diseases remained constantly present. As such an outbreak can have devastating consequences to the society and economy, development of warning strategies before it takes place is a critical and urgent research task. However, there are currently no validated methods that are both effective and practically feasible for giving pre-outbreak alerts. As such, timely identification and rapid response after an outbreak takes place is still a feasible and effective method for responding to new emerging infectious diseases. The speed and efficiency of the response are largely contingent upon preparedness during the inter-epidemic periods. This paper aims to outline our thinking about the framework for infectious disease early warning and propose some recommendations. Implementation of such a strategy in practice necessitates the establishment of pilot initiatives to test the early warning system according to our proposed principles. These pilots may use severe influenza or hypothetical outbreak scenarios as examples, define warning signals, develop the mechanisms for epidemiological investigation, reporting and response so as to conduct feasibility assessments.

Although the COVID-19 pandemic has subsided, the risk of the outbreak of new emerging infectious diseases remained constantly present. As such an outbreak can have devastating consequences to the society and economy, development of warning strategies before it takes place is a critical and urgent research task. However, there are currently no validated methods that are both effective and practically feasible for giving pre-outbreak alerts. As such, timely identification and rapid response after an outbreak takes place is still a feasible and effective method for responding to new emerging infectious diseases. The speed and efficiency of the response are largely contingent upon preparedness during the inter-epidemic periods. This paper aims to outline our thinking about the framework for infectious disease early warning and propose some recommendations. Implementation of such a strategy in practice necessitates the establishment of pilot initiatives to test the early warning system according to our proposed principles. These pilots may use severe influenza or hypothetical outbreak scenarios as examples, define warning signals, develop the mechanisms for epidemiological investigation, reporting and response so as to conduct feasibility assessments.

Abstract In April 2021, type Ⅰ vaccine-derived poliovirus (VDPV) was detected from two fecal samples of a male infant with acute flaccid paralysis (AFP) in Zhejiang Province when he was admitted to the Children's Hospital Affiliated to Fudan University in Shanghai, with 12 and 14 nucleotide mutations in the VP1 region, respectively. The case had a history of immunization with three doses of poliovirus vaccines, and grade Ⅲ proximal muscle strength and grade Ⅱ distal muscle strength of the right lower limb. After symptomatic treatment, the activity of the right lower limb and the muscle strength was significantly restored, thus he was discharged. VDPV was not detected from subsequent (the 8th to 12th) fecal samples of the case and fecal samples of close contacts. No similar cases were found in medical institutions in the county, surrounding areas, neighboring villages or towns. Since the case did not exhibit clinical symptoms of poliomyelitis caused by VDPV, poliomyelitis was excluded, and the case was diagnosed with hemophilia type A based on the epidemiological investigation, laboratory tests, and the history of poliomyelitis vaccination. This event involved cross-provincial (municipal) cooperation and was responsed promptly, preventing further spread of the virus. It suggested that the sensitivity of the AFP case surveillance system should be maintained, environmental monitoring methods should be increased, and the poliomyelitis vaccination should be promoted to prevent the spread of the virus.

BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing important semantic information. A Transformer encoder was used for cross-modal semantic learning. By introducing manifold similarity constraints, balance constraints, and a linear classification network constraint, the algorithm enhanced the discriminability of the hash codes. Experimental results demonstrated that the MSACH algorithm improved the mean average precision (MAP) by 11.8% and 12.8% on two datasets compared to traditional methods. The algorithm exhibits outstanding performance in enhancing retrieval accuracy and handling large-scale medical data, showing promising potential for practical applications.
Algorithms ; Semantics ; Humans ; Ultrasonography ; Information Storage and Retrieval/methods* ; Image Processing, Computer-Assisted/methods*

Online hashing methods are receiving increasing attention in cross modal medical image retrieval research. However, existing online methods often lack the learning ability to maintain semantic correlation between new and existing data. To this end, we proposed online semantic similarity cross-modal hashing (OSCMH) learning framework to incrementally learn compact binary hash codes of medical stream data. Within it, a sparse representation of existing data based on online anchor datasets was designed to avoid semantic forgetting of the data and adaptively update hash codes, which effectively maintained semantic correlation between existing and arriving data and reduced information loss as well as improved training efficiency. Besides, an online discrete optimization method was proposed to solve the binary optimization problem of hash code by incrementally updating hash function and optimizing hash code on medical stream data. Compared with existing online or offline hashing methods, the proposed algorithm achieved average retrieval accuracy improvements of 12.5% and 14.3% on two datasets, respectively, effectively enhancing the retrieval efficiency in the field of medical images.
Semantics ; Humans ; Algorithms ; Information Storage and Retrieval/methods* ; Diagnostic Imaging ; Image Processing, Computer-Assisted/methods*