Objective To investigate the changes in the prevalence of Babesia microti infections, spleen morphology and proportions of splenic immune cells in BALB/c mice following intravenous and intraperitoneal injections, so as to provide insights into unraveling the immune regulatory mechanisms of Babesia infections. Methods Laboratory - maintained B. microti strains were prepared into whole blood samples with 10% prevalence of B. microti infection. A total of 75 BALB/c mice were randomly divided into three groups, including the normal control group, intravenous injection group, and intraperitoneal injection group, of 25 mice in each group. Mice in the intravenous and intraperitoneal injection groups were administered 100 μL of whole blood samples with 10% prevalence of B. microti infection, with the day of injection recorded as d0, and animals in the normal control group were given no treatments. Blood was sampled from mice in each group via the tail tip on d7, d14, d21, d28 and d35, and prepared into thin-film blood smears, and B. microti infection was observed in red blood cells. Five mice were randomly sampled from each group and sacrificed on d7, d14, d21, d28 and d35, and spleen was collected for measurement of spleen size and weight. In addition, splenic cells were isolated, and the proportions of CD3e⁺ T cells, CD45R⁺ B cells, CD49b⁺ nature killer (NK) cells, and F4/80⁺ macrophages were detected in CD45⁺ lymphocytes using flow cytometry. Results The prevalence of B. microti infection in the intravenous (22.80%) and intraperitoneal injection groups (44.82%) peaked on d7 (χ² = 8.141, P < 0.01) and then rapidly decreased, and no parasites were observed on d35. The longest mouse spleen length [(32.91 ± 2.20) mm] and width [(9.82 ± 0.43) mm], and the greatest weight [(0.78 ± 0.10) g] were found on d14 in the intravenous injection group, and the longest spleen length [(32.42 ± 3.21) mm] and width [(10.25 ± 0.73) mm], and the greatest weight [(0.73 ± 0.09) g] were seen in the intra-peritoneal injection group on d21, d7 and d14, respectively. There were significant differences among the intravenous injection group, intraperitoneal injection group and the normal control group in terms of spleen length (F = 10.310, P < 0.05), width (F = 9.824, P < 0.05), and weight (F = 10.672, P < 0.05) on d21, and the mouse spleen length, width and weight were all significantly greater in the intraperitoneal injection group than in the intravenous injection group (allP values < 0.05). The proportions of splenic CD3e⁺ T cells [(60.60 ± 6.20)% and (39.68 ± 7.62)%], CD45R⁺ B cells [(43.32 ± 2.08)% and (49.53 ± 4.90)%], CD49b⁺ NK cells [(6.88 ± 1.34)% and (7.71 ± 1.59)%], and F4/80⁺ macrophages [(2.21 ± 0.29)% and (3.80 ± 0.35)%] peaked on d14, d21, d21 and d14 in the intravenous and intraperitoneal injection groups, respectively. There were significant differences in the proportions of CD3e⁺ T cells (F = 16.730, P < 0.05) and F4/80⁺ macrophages (F = 15.941, P < 0.05) among the intravenous injection group, intraperitoneal injection group and normal control group on d14, and a higher proportion of CD3e⁺ T cells and a lower proportion of F4/80⁺ macrophages were detected in the intravenous injection group than in the intraperitoneal injection group (both P values < 0.01). There were significant differences among the intravenous injection group, intraperitoneal injection group and normal control group on d21 in terms of proportions of splenic CD3e⁺ T cells (F = 9.252, P < 0.05), CD45R⁺ B cells (F = 14.349, P < 0.05), CD49b⁺ NK cells (F = 13.436,P < 0.05), and F4/80⁺ macrophages (F = 8.180, P < 0.05), and a higher proportion of CD3e⁺ T cells and lower proportions of CD45R⁺ B cells and F4/80⁺ macrophages were detected in the intravenous injection group than in the intraperitoneal injection group (all P values < 0.01). In addition, there was a significant difference in the proportion of CD3e⁺ T cells among the intravenous injection group, intraperitoneal injection group and normal control group on d28 (F = 9.772,P < 0.05), and a lower proportion of CD3e⁺ T cells was found in the intravenous injection group than in the intraperitoneal injection group (P < 0.01). Conclusions Both intraperitoneal and intravenous routes are effective to induce B. microti infections in BALB/c mice, and the prevalence of B. microti infections is higher in BALB/c mice through the intraperitoneal route than through the intravenous route. Intraperitoneal and intravenous injections with B. microti cause diverse spleen morphologies and proportions of splenic immune cells in mice, indicating routes of B. microti infections cause different impacts on immune response mechanisms in mice.

Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.

Objective To investigate the changes in eosinophil counts and the activation of microglial cells in the brain tissues of mice at different stages of Angiostrongylus cantonensis infection, and to examine the role of microglia in regulating the progression of angiostrongyliasis and unravel the possible molecular mechanisms. Methods Fifty BALB/c mice were randomly divided into the control group and the 7-d, 14-d, 21-day and 25-d infection groups, of 10 mice in each group. All mice in infection groups were infected with 30 stage III A. cantonensis larvae by gavage, and animals in the control group was given an equal amount of physiological saline. Five mice were collected from each of infection groups on days 7, 14, 21 d and 25 d post-infection, and 5 mice were collected from the control group on the day of oral gavage. The general and focal functional impairment was scored using the Clark scoring method to assess the degree of mouse neurological impairment. Five mice from each of infection groups were sacrificed on days 7, 14, 21 d and 25 d post-infection, and 5 mice from the control group were sacrificed on the day of oral gavage. Mouse brain tissues were sampled, and the pathological changes of brain tissues were dynamically observed using hematoxylin and eosin (HE) staining. Immunofluorescence staining with eosinophilic cationic protein (ECP) and ionized calcium binding adaptor molecule 1 (Iba1) was used to assess the degree of eosinophil infiltration and the counts of microglial cells in mouse brain tissues in each group, and the morphological parameters of microglial cells (skeleton analysis and fractal analysis) were quantified by using Image J software to determine the morphological changes of microglial cells. In addition, the expression of M1 microglia markers Fcγ receptor III (Fcgr3), Fcγ receptor IIb (Fcgr2b) and CD86 antigen (Cd86), M2 microglia markers Arginase 1 (Arg1), macrophage mannose receptor C-type 1 (Mrc1), chitinase-like 3 (Chil3), and phagocytosis genes myeloid cell triggering receptor expressed on myeloid cells 2 (Trem2), CD68 antigen (Cd68), and apolipoprotein E (Apoe) was quantified using real-time quantitative reverse transcription PCR (RT-qPCR) assay in the mouse cerebral cortex of mice post-infection. Results A large number of A. cantonensis larvae were seen on the mouse meninges surface post-infection, and many neuronal nuclei were crumpled and deeply stained, with a large number of bleeding points in the meninges. The median Clark scores of mouse general functional impairment were 0 (interquartile range, 0), 0 (interquartile range, 0.5), 6 (interquartile range, 1.0), 14 (interquartile range, 8.5) points and 20 (interquartile range, 9.0) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.45, P < 0.01), and the median Clark scores of mouse focal functional impairment were 0 (interquartile range, 0), 2 (interquartile range, 2.5), 7 (interquartile range, 3.0), 18 (interquartile range, 5.0) points and 25 (interquartile range, 6.5) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.72, P < 0.01). The mean scores of mice general and focal functional impairment were all higher in the infection groups than in the control group (all P values < 0.05). Immunofluorescence staining showed a significant difference in the eosinophil counts in mouse brain tissues among the five groups (F = 40.05, P < 0.000 1), and the eosinophil counts were significantly higher in mouse brain tissues in the 14-d (3.08 ± 0.78) and 21-d infection groups (5.97 ± 1.37) than in the control group (1.00 ± 0.28) (both P values < 0.05). Semi-quantitative analysis of microglia immunofluorescence showed a significant difference in the counts of microglial cells among the five groups (F = 17.66, P < 0.000 1), and higher Iba1 levels were detected in mouse brain tissues in 14-d (5.75 ± 1.28), 21-d (6.23 ± 1.89) and 25-d infection groups (3.70 ± 1.30) than in the control group (1.00 ± 0.30) (all P values < 0.05). Skeleton and fractal analyses showed that the branch length [(162.04 ± 34.10) μm vs. (395.37 ± 64.11) μm; t = 5.566, P < 0.05] and fractal dimension of microglial cells (1.30 ± 0.01 vs. 1.41 ± 0.03; t = 5.266, P < 0.05) were reduced in mouse brain tissues in the 21-d infection group relative to the control group. In addition, there were significant differences among the 5 groups in terms of M1 and M2 microglia markers Fcgr3 (F = 48.34, P < 0.05), Fcgr2b (F = 55.46, P < 0.05), Cd86 (F = 24.44, P < 0.05), Arg1 (F = 31.18, P < 0.05), Mrc1 (F = 15.42, P < 0.05) and Chil3 (F = 24.41, P < 0.05), as well as phagocytosis markers Trem2 (F = 21.19, P < 0.05), Cd68 (F = 43.95, P < 0.05) and Apoe (F = 7.12, P < 0.05) in mice brain tissues. Conclusions A. cantonensis infections may induce severe pathological injuries in mouse brain tissues that are characterized by massive eosinophil infiltration and persistent activation of microglia cells, thereby resulting in progressive deterioration of neurological functions.

Radiogenomics, an extension of radiomics, explores the relationship between imaging features and underlying gene expression patterns. This field is instrumental in providing reliable imaging surrogates, thus potentially representing an alternative to genetic testing. The rapidly growing area of radiogenomics that utilizes ultrasound (US) imaging seeks to elucidate the connections between US image characteristics and genomic data. In this review, the authors outline the radiogenomics workflow and summarize the applications of US-based radiogenomics. These include the prediction of gene variations, molecular subtypes, and other biological characteristics, as well as the exploration of the relationships between US phenotypes and cancer gene profiles. Although the field faces various challenges, US-based radiogenomics offers promising prospects and avenues for future research.

Radiogenomics, an extension of radiomics, explores the relationship between imaging features and underlying gene expression patterns. This field is instrumental in providing reliable imaging surrogates, thus potentially representing an alternative to genetic testing. The rapidly growing area of radiogenomics that utilizes ultrasound (US) imaging seeks to elucidate the connections between US image characteristics and genomic data. In this review, the authors outline the radiogenomics workflow and summarize the applications of US-based radiogenomics. These include the prediction of gene variations, molecular subtypes, and other biological characteristics, as well as the exploration of the relationships between US phenotypes and cancer gene profiles. Although the field faces various challenges, US-based radiogenomics offers promising prospects and avenues for future research.

Radiogenomics, an extension of radiomics, explores the relationship between imaging features and underlying gene expression patterns. This field is instrumental in providing reliable imaging surrogates, thus potentially representing an alternative to genetic testing. The rapidly growing area of radiogenomics that utilizes ultrasound (US) imaging seeks to elucidate the connections between US image characteristics and genomic data. In this review, the authors outline the radiogenomics workflow and summarize the applications of US-based radiogenomics. These include the prediction of gene variations, molecular subtypes, and other biological characteristics, as well as the exploration of the relationships between US phenotypes and cancer gene profiles. Although the field faces various challenges, US-based radiogenomics offers promising prospects and avenues for future research.

BACKGROUND:In recent years,artificial intelligence has gradually emerged and has been applied in various fields such as spinal cord nerve injury and repair,which has a positive impact on clinical treatment. OBJECTIVE:To study the application progress of artificial intelligence in the diagnosis,treatment,and rehabilitation of spinal cord nerve injury and repair,clarify the research hotspots and shortcomings in this field,and provide suggestions for future research work. METHODS:Relevant literature on artificial intelligence in the field of spinal cord nerve injury and repair was retrieved on the Web of Science core collection database until 2023.CiteSpace 6.1.R6 and VOSviewer 1.6.19 software was used to perform general literature analysis,co-citation of literature,co-citation of journals,double image overlay of journals,keyword clustering,and other visual analysis on the literature data. RESULTS AND CONCLUSION:(1)A total of 1 713 articles were selected,and the annual publication volume in this field showed a fluctuating upward trend,with the United States taking the lead,and Kadone and Hideki being the authors with the highest publication volume.ARCH PHYS MED REHAB was the journal with the highest number of citations.(2)Keyword co-occurrence and cluster analysis showed that after removing keywords similar to the search terms,the main keywords were divided into three main clusters:Exoskeleton and exercise rehabilitation(the largest core hotspot);machine learning and neural plasticity;robotics and rehabilitation training.(3)Keyword burst analysis showed that deep learning and artificial intelligence had become burst terms in the past five years.(4)The results of in-depth analysis of co cited and highly cited literature showed that the hotspots of artificial intelligence in the field of spinal cord nerve injury and repair were mainly focused on powered exoskeletons,gaits,electrical nerve stimulation,intracortical brain-computer interface(IBCI),robots,and polymer biomaterials,and neural stem cell.(5)The research on artificial intelligence in the field of spinal cord nerve injury and repair has shown an upward trend in recent years.The focus of this field had gradually shifted from single treatment methods such as exoskeletons and electrical stimulation to intelligent,precise,and personalized directions.(6)There were some limitations in this field,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(such as privacy,research transparency,and clinical reliability).Future research should address the issue of data collection,requiring large sample,high-quality clinical datasets to establish effective artificial intelligence models.At the same time,the research on genomics and other mechanisms in this field is very weak.In the future,various machine learning technologies such as brain chips can be used,and gene editing therapy,single-cell spatial transcriptome and other methods can be used to study the basic mechanisms of regeneration-related gene upregulation and axon growth structural protein production.

Objective: To investigate the incidence and trends of liver, lung, breast, colorectal and gastric cancers in Nanning City from 2018 to 2022. Methods: Data of new cases of liver, lung, breast, colorectal and gastric cancers in Nanning City from 2018 to 2022 were collected through the big data platform of the Nanning Health Propaganda and Information Center's Hospitalization System. The incidence rates were calculated and standardized using the data of the seventh national population census in 2020. The age, gender, and urban-rural distribution of the five malignant tumor cases were descriptively analyzed. The trends in incidence of the five malignant tumors were analyzed using annual percent change (APC). Results: From 2018 to 2022, the crude and standardized incidence rates of liver cancer in Nanning City were 24.46/105 and 26.39/105, respectively, showing upward trends (APC=15.122% and 13.111%, both P<0.05). The crude and standardized incidence rates of lung cancer were 23.42/105 and 25.83/105, respectively, showing upward trends (APC=13.714% and 10.056%, both P<0.05). The crude and standardized incidence rates of breast cancer were 19.13/105 and 20.29/105, respectively, with no significant trends (APC=-5.129% and -5.164%, both P>0.05). The crude incidence rate of colorectal cancer was 18.81/105, showing an upward trend (APC=8.164%, P<0.05), while the standardized incidence rate was 20.64/105, with no significant trend (APC=5.044%, P>0.05). The crude incidence rate of gastric cancer was 7.27/105, showing an upward trend (APC=5.984%, P<0.05), while the standardized incidence rate was 7.98/105, with no significant trend (APC=3.304%, P>0.05). The age of onset peak for liver cancer was 65 to <70 years, for lung cancer was 75 to <80 years, for breast cancer was 55 to <60 years, for colorectal cancer was 80 to <85 years, and for gastric cancer was 75 to <80 years. The standardized incidence rates of liver, lung, colorectal and gastric cancers were higher in males than in females (all P<0.05). The standardized incidence rates of liver, lung and gastric cancers were higher in rural areas than in urban areas, while the standardized incidence rates of breast and colorectal cancers were lower in rural areas (all P<0.05). Conclusions The incidence rates of liver, lung, colorectal and gastric cancers in Nanning City showed upward trends from 2018 to 2022, while the incidence rate of breast cancer remained stable. The standardized incidence rates of liver, lung, colorectal and gastric cancers were higher in males, and the standardized incidences of liver, lung and gastric cancers were higher in rural areas.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

ObjectiveTo explore the data standard system of electronic medical records in the field of rehabilitation, focusing on the terminology and coding standards, data structure, and key content categories of rehabilitation electronic medical records. MethodsBased on the Administrative Norms for the Application of Electronic Medical Records issued by the National Health Commission of China, the electronic medical record standard architecture issued by the International Organization for Standardization and Health Level Seven (HL7), the framework of the World Health Organization Family of International Classifications (WHO-FICs), Basic Architecture and Data Standards of Electronic Medical Records, Basic Data Set of Electronic Medical Records, and Specifications for Sharing Documents of Electronic Medical Records, the study constructed and organized the data structure, content, and data standards of rehabilitation electronic medical records. ResultsThe data structure of rehabilitation electronic medical records should strictly follow the structure of electronic medical records, including four levels (clinical document, document section, data set and data element) and four major content areas (basic information, diagnostic information, intervention information and cost information). Rehabilitation electronic medical records further integrated information related to rehabilitation needs and characteristics, emphasizing rehabilitation treatment, into clinical information. By fully applying the WHO-FICs reference classifications, rehabilitation electronic medical records could establish a standardized framework, diagnostic criteria, functional description tools, coding tools and terminology index tools for the coding, indexing, functional description, and analysis and interpretation of diseases and health problems. The study elaborated on the data structure and content categories of rehabilitation electronic medical records in four major categories, refined the granularity of reporting rehabilitation content in electronic medical records, and provided detailed data reporting guidance for rehabilitation electronic medical records. ConclusionThe standardization of rehabilitation electronic medical records is significant for improving the quality of rehabilitation medical services and promoting the rehabilitation process of patients. The development of rehabilitation electronic medical records must be based on the national and international standards. Under the general electronic medical records data structure and standards, a rehabilitation electronic medical records data system should be constructed which incorporates core data such as disease diagnosis, functional description and assessment, and rehabilitation interventions. The standardized rehabilitation electronic medical records scheme constructed in this study can support the improvement of standardization of rehabilitation electronic medical records data information.