Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

OBJECTIVE: To observe the clinical efficacy of acupuncture combined with thunder-fire moxibustion in treating low back pain with cold-damp. METHODS: Seventy-two patients of low back pain with cold-damp were randomly divided into an observation group (36 cases, 1 case was eliminated) and a control group (36 cases, 1 case dropped out). The control group received acupuncture at Jizhong (GV6), Yaoyangguan (GV3), ashi points, bilateral Shenshu (BL23), Dachangshu (BL25), and Weizhong (BL40) for 30 min daily. The observation group was treated with thunder-fire moxibustion in addition to the same acupuncture regimen as the control group, once daily. Both groups were treated for 6 consecutive days followed by one rest day, for a total duration of 4 weeks. The visual analog scale (VAS) score, Oswestry disability index (ODI) score, Japanese Orthopedic Association (JOA) score, present pain intensity (PPI) score, and serum levels of β-endorphin (β-EP), 5-hydroxytryp tamin (5-HT), and substance P (SP) were compared before and after treatment, and the clinical efficacy was also compared between the two groups. RESULTS: Compared before treatment, the VAS scores, ODI scores, PPI scores, and serum levels of 5-HT and SP were decreased (P<0.01), while JOA scores and serum levels of β-EP were increased (P<0.01) in both groups after treatment. The observation group showed lower VAS, ODI, and PPI scores and serum levels of 5-HT and SP than those in the control group (P<0.05), as well as higher JOA score and serum level of β-EP (P<0.05). The total effective rate in the observation group was 94.3% (33/35), higher than 82.9% (29/35) in the control group (P<0.05). CONCLUSION Acupuncture combined with thunder-fire moxibustion could effectively alleviate pain and improve lumbar function in patients of low back pain with cold-damp, possibly by regulating β-EP, 5-HT, and SP levels.
Humans ; Moxibustion ; Low Back Pain/blood* ; Male ; Female ; Adult ; Middle Aged ; Acupuncture Therapy ; Acupuncture Points ; Treatment Outcome ; Combined Modality Therapy ; beta-Endorphin/blood* ; Young Adult ; Aged

Skin diseases significantly affect the quality of life of approximately 190 million individuals worldwide.The complexity and diversity of their clinical manifestations are the major challenges for traditional diagnostic approaches,and exploring novel diagnostic strategies has become an urgent priority.In recent years,deep learning(DL)technology has been increasingly applied in the intelligent recognition of skin diseases,demonstrating substantial potential.This study provides a systematic review of the research progress of DL in dermatological diagnosis from three major dimensions.First,at the data input level,it focuses on the characterization and preprocessing of multimodal data,including dermoscopic images,ultrasound images,and histopathological slides.Second,at the algorithmic model level,it explores ensemble learning frameworks,multimodal data fusion strategies,multicenter collaborative training approaches,and interpretable model construction.Finally,at the task recognition level,it evaluates the performance of DL models in benign skin disease screening,malignant skin lesion differentiation,and binary as well as multiclass classification tasks.By comprehensively reviewing advancements in DL-based skin disease diagnostic models from multiple perspectives,this paper aims to provide valuable insights for the further optimization and clinical translation of intelligent diagnostic systems.

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

Objective:To systematically integrate qualitative study on stroke patients' perception of recurrence risk, so as to providing evidence for optimizing stroke risk communication education and secondary prevention strategies.Methods:Qualitative studies related to the perception of recurrence risk in stroke patients were searched through computers on PubMed, Web of Science, Embase, CINAHL, Cochrane Library, Joanna Briggs Institute (JBI) Evidence-Based Health Care Centers Database, China National Knowledge Infrastructure, WanFang Data, VIP, and China Biomedical Medicine Database. The search period was from the establishment of the database to September 2022. The articles quality were evaluated using the quality evaluation criteria for qualitative research of the Australian JBI Evidence-Based Health Care Center (2020) . The results were integrated by Meta-synthesis.Results:A total of 7 articles were included, 37 research results were extracted, 9 new categories were summarized, and 3 integrated results were obtained, which were respectively the perceived characteristics of recurrence risk in stroke patients, the barriers to accurate perception of recurrence risk, and the ways to actively or negatively address recurrence risk.Conclusions:In clinical practice, it is necessary to carry out early dynamic assessment of recurrence risk perception among stroke patients, attach importance to and optimize communication and education on recurrence risk, improve comprehensive support mechanisms, so as to promote stroke patients to participate in and adhere to active risk management.

Objective:To search, evaluate and summarize the best evidence on falls prevention and management in the frail elderly to provide ideas and references for clinical practice.Methods:Evidences related to falls prevention and management in the frail elderly were systematically searched on BMJ Best Practice, UpToDate, Registered Nurses' Association of Ontario, National Guideline Clearinghouse, National Institute for Health and Clinical Excellence, Medlive, Joanna Briggs Institute (JBI) Evidence Based Health Care Center Database in Australia, Scottish Intercollegiate Guideline Network, Cochrane Library, CINAHL, PubMed, Web of Science, Embase, CNKI, Wanfang Database, VIP and China Biology Medicine disc. The search period was from the establishment of the database to March 1, 2023. Three researchers independently evaluated quality of the included literature, and extracted, integrated and graded the evidence.Results:A total of 24 literatures were included, including 13 systematic reviews, 4 expert consensus, 6 guidelines and 1 evidence summary. A total of 30 evidences were summarized from 5 aspects of frailty screening, assessment, disease and medication management, exercise management and nutrition management.Conclusions:This study summarizes the best evidence for fall prevention and management in the frail elderly. It is suggested that practitioners should formulate a management plan in accordance with the actual situation in combination with the application scenario and the situation of the elderly, so as to improve the intervention level and reduce the incidence of falls in the frail elderly.

【Objective】 To analyze the metagenomics and microbiology of voluntary blood donors in China, so as to assess the potential threats of emerging infectious diseases to the safety of blood transfusion. 【Methods】 12 300 plasma samples (10 mL each) collected by central blood stations in Chongqing, Liuzhou, Urumqi, Mianyang, Wuhan, Nanjing, Mudanjiang, and Dehong Prefecture area from 2012 to 2018 were subjected to total DNA extraction after ultracentrifugation (32 000 rpm/min, centrifugal radius 91.9 mm) in minipools of 160 donations. The metagenomic library was constructed, and deep sequencing was conducted by Illumina Hiseq 4 500. By comparing with reference sequences of bacteria, fungi, parasites and viruses, metagenomic data were analyzed, classification of microbes were identified, and potentially harmful pathogens were evaluated. 【Results】 A total of 632 GB clean data were obtained by deep sequencing, and the top three pathogens were Pseudomonas(0.561 1%), Burkholderia(0.468 7%) and Serratia(4.242 0%). Pathogens with potential threat which could be transmitted by blood transfusion or blood products were found, such as human parvovirus B19(0.126 6%), Leishmania spp(1.348 5%) and Toxoplasma gondii(0.615 8%). 【Conclusion】 Our study analyzed metagenomics of voluntary blood donors in parts of China and revealed pathogens that may cause potential harm to blood safety, which were helpful for targeted prevention and control of emerging infectious diseases.

The oral microbial community is widely regarded as a latent reservoir of antibiotic resistance genes. This study assessed the molecular epidemiology, susceptibility profile, and resistance mechanisms of 35 methicillin-resistant Staphylococcus epidermidis (MRSE) strains isolated from the dental plaque of a healthy human population. Broth microdilution minimum inhibitory concentrations (MICs) revealed that all the isolates were nonsusceptible to oxacillin and penicillin G. Most of them were also resistant to trimethoprim (65.7%) and erythromycin (54.3%). The resistance to multiple antibiotics was found to be largely due to the acquisition of plasmid-borne genes. The mecA and dfrA genes were found in all the isolates, mostly dfrG (80%), aacA-aphD (20%), aadD (28.6%), aphA3 (22.9%), msrA (5.7%), and the ermC gene (14.3%). Classical mutational mechanisms found in these isolates were mainly efflux pumps such as qacA (31.4%), qacC (25.7%), tetK (17.1%), and norA (8.6%). Multilocus sequence type analysis revealed that sequence type 59 (ST59) strains comprised 71.43% of the typed isolates, and the eBURST algorithm clustered STs into the clonal complex 2-II(CC2-II). The staphyloccoccal cassette chromosome mec (SCCmec) type results showed that 25 (71.43%) were assigned to type IV. Moreover, 88.66% of the isolates were found to harbor six or more biofilm-associated genes. The aap, atlE, embp, sdrF, and IS256 genes were detected in all 35 isolates. This research demonstrates that biofilm-positive multiple-antibiotic-resistant ST59-SCCmec IV S. epidermidis strains exist in the dental plaque of healthy people and may be a potential risk for the transmission of antibiotic resistance.
Anti-Bacterial Agents ; therapeutic use ; Dental Plaque ; microbiology ; Female ; Humans ; Methicillin ; Methicillin-Resistant Staphylococcus aureus ; isolation & purification ; Staphylococcal Infections ; diagnosis ; Staphylococcus epidermidis ; isolation & purification