Objective To study the spatial distribution of the incidence of pulmonary tuberculosis in Hubei Province and its influencing factors, so as to improve the theoretical basis for scientific development of tuberculosis prevention and control measures in the future. Methods The data of reported incidence of tuberculosis and related influencing factors in various counties and districts of Hubei Province in 2020 were collected. Global Moran's I index, hotspot analysis and geographically weighted regression (GWR) model analysis were used to calculate the spatial autocorrelation of the incidence of tuberculosis, and to analyze the influencing factors affecting the incidence rate of tuberculosis. Results There were obvious regional differences in the space distribution of the incidence rate of tuberculosis. Hot spot analysis showed positive spatial correlation and obvious clustering. The GWR model (AICc=784.251) in this study had higher AICc value compared to the ordinary least squares regression (OLS) model (AICc=804.2585). The GWR model showed that the increase in the proportion of the population aged 65 and above and the proportion of the ethnic minority population had a significant promoting effect on the increase of the incidence rate of tuberculosis, and there was significant spatial heterogeneity. The effect of PM_2.5 concentration on the incidence rate of pulmonary tuberculosis varied in different regions, and the degree of effect was also different. Conclusion The proportion of people aged 65 and above and the proportion of ethnic minorities may significantly influence the incidence of pulmonary tuberculosis. The effect of PM_2.5 concentration varies in different regions, so targeted measures should be formulated according to the situation in different regions.

The translocator protein (TSPO) positron emission tomography (PET) can noninvasively detect neuroinflammation associated with epileptogenesis and epilepsy. This study explored the role of the TSPO-targeting radioligand [¹⁸F]F-TFQC, an m-trifluoromethyl ER176 analog, in the PET neuroimaging of epileptic rats. Initially, [¹⁸F]F-TFQC was synthesized with a radiochemical yield of 8%-10% (EOS), a radiochemical purity of over 99%, and a specific activity of 38.21 ± 1.73 MBq/nmol (EOS). After determining that [¹⁸F]F-TFQC exhibited good biochemical properties, [¹⁸F]F-TFQC PET neuroimaging was performed in epileptic rats at multiple time points in various stages of disease progression. PET imaging showed specific [¹⁸F]F-TFQC uptake in the right hippocampus (KA-injected site, i.e., epileptogenic zone), which was most pronounced at 1 week (T/NT 1.63 ± 0.21) and 1 month (T/NT 1.66 ± 0.20). The PET results were further validated using autoradiography and pathological analysis. Thus, [¹⁸F]F-TFQC can reflect the TSPO levels and localize the epileptogenic zone, thereby offering the potential for monitoring neuroinflammation and guiding anti-inflammatory treatment in patients with epilepsy.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Phage therapy is one of the most important tools for the treatment of infections with multi-drug resistant bacteria. Such phages are usually isolated from hospital effluents, however, no systematic study on the distribution of phages in hospital effluents has been conducted so far. The aim of this study was to isolate the corresponding phages of common pathogenic bacteria isolated in the clinic as hosts, so as to assess the ecological distribution of phages in hospital wastewater and to provide a reference for the isolation and application of phages of drug-resistant bacteria in the clinic. A cross-sectional study design was used in this study. The 125 pathogenic bacteria (belonging to 16 different strains) isolated from the clinical microbiology laboratory of Qilu Hospital of Shandong University from May to June 2023 were selected as the target strains, and the phages corresponding to these strains were isolated and purified from the hospital wastewater by using the double-layer plate sandwich method. At the same time, the distribution of pathogenic bacteria in the same batch of wastewater was analyzed with the help of mNGS sequencing technology, so as to preliminarily investigate the abundance correspondence between pathogenic bacteria and phages in wastewater. The results showed that a total of 56 phage strains were isolated from 125 clinical pathogens as hosts, corresponding to six pathogens, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. All six pathogenic bacteria contained strains with different degrees of drug resistance, with a higher percentage of multi-drug resistant strains in A. baumannii, Escherichia coli and P. aeruginosa. The phage acquisition rates of these six pathogens were, in descending order, Escherichia coli (80%), Stenotrophomonas maltophilia (75%), Pseudomonas aeruginosa (70%), Klebsiella pneumoniae (66.67%), Acinetobacter baumannii (36.36%) and Staphylococcus aureus (12.5%). Preliminary mNGS sequencing results showed that the pathogenic bacteria with higher abundance in the batch of effluent were Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Klebsiella aerogenes, Klebsiella michiganensis and Pseudomonas aeruginosa. In conclusion, phages of most common clinical Gram-negative pathogens were isolated from hospital wastewater with high isolation rates; however, phages of Gram-positive pathogens were isolated at lower rates, and only phages corresponding to Staphylococcus aureus were isolated in this study. The corresponding mNGS sequencing results showed that the distribution of Gram-negative pathogens in sewage may had a positive correlation with the ecological distribution of phages.

Phage therapy is one of the most important tools for the treatment of infections with multi-drug resistant bacteria. Such phages are usually isolated from hospital effluents, however, no systematic study on the distribution of phages in hospital effluents has been conducted so far. The aim of this study was to isolate the corresponding phages of common pathogenic bacteria isolated in the clinic as hosts, so as to assess the ecological distribution of phages in hospital wastewater and to provide a reference for the isolation and application of phages of drug-resistant bacteria in the clinic. A cross-sectional study design was used in this study. The 125 pathogenic bacteria (belonging to 16 different strains) isolated from the clinical microbiology laboratory of Qilu Hospital of Shandong University from May to June 2023 were selected as the target strains, and the phages corresponding to these strains were isolated and purified from the hospital wastewater by using the double-layer plate sandwich method. At the same time, the distribution of pathogenic bacteria in the same batch of wastewater was analyzed with the help of mNGS sequencing technology, so as to preliminarily investigate the abundance correspondence between pathogenic bacteria and phages in wastewater. The results showed that a total of 56 phage strains were isolated from 125 clinical pathogens as hosts, corresponding to six pathogens, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. All six pathogenic bacteria contained strains with different degrees of drug resistance, with a higher percentage of multi-drug resistant strains in A. baumannii, Escherichia coli and P. aeruginosa. The phage acquisition rates of these six pathogens were, in descending order, Escherichia coli (80%), Stenotrophomonas maltophilia (75%), Pseudomonas aeruginosa (70%), Klebsiella pneumoniae (66.67%), Acinetobacter baumannii (36.36%) and Staphylococcus aureus (12.5%). Preliminary mNGS sequencing results showed that the pathogenic bacteria with higher abundance in the batch of effluent were Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Klebsiella aerogenes, Klebsiella michiganensis and Pseudomonas aeruginosa. In conclusion, phages of most common clinical Gram-negative pathogens were isolated from hospital wastewater with high isolation rates; however, phages of Gram-positive pathogens were isolated at lower rates, and only phages corresponding to Staphylococcus aureus were isolated in this study. The corresponding mNGS sequencing results showed that the distribution of Gram-negative pathogens in sewage may had a positive correlation with the ecological distribution of phages.

Background::Adamantinomatous craniopharyngioma (ACP) is the commonest pediatric sellar tumor. No effective drug is available and interpatient heterogeneity is prominent. This study aimed to identify distinct molecular subgroups of ACP based on the multi-omics profiles, imaging findings, and histological features, in order to predict the response to anti-inflammatory treatment and immunotherapies.Methods::Totally 142 Chinese cases diagnosed with craniopharyngiomas were profiled, including 119 ACPs and 23 papillary craniopharyngiomas. Whole-exome sequencing (151 tumors, including recurrent ones), RNA sequencing (84 tumors), and DNA methylome profiling (95 tumors) were performed. Consensus clustering and non-negative matrix factorization were used for subgrouping, and Cox regression were utilized for prognostic evaluation, respectively.Results::Three distinct molecular subgroups were identified: WNT, ImA, and ImB. The WNT subgroup showed higher Wnt/β-catenin pathway activity, with a greater number of epithelial cells and more predominantly solid tumors. The ImA and ImB subgroups had activated inflammatory and interferon response pathways, with enhanced immune cell infiltration and more predominantly cystic tumors. Mitogen-activated protein kinases (MEK/MAPK) signaling was activated only in ImA samples, while IL-6 and epithelial-mesenchymal transition biomarkers were highly expressed in the ImB group, mostly consisting of children. The degree of astrogliosis was significantly elevated in the ImA group, with severe finger-like protrusions at the invasive front of the tumor. The molecular subgrouping was an independent prognostic factor, with the WNT group having longer event-free survival than ImB (Cox, P = 0.04). ImA/ImB cases were more likely to respond to immune checkpoint blockade (ICB) therapy than the WNT group ( P <0.01). In the preliminary screening of subtyping markers, CD38 was significantly downregulated in WNT compared with ImA and ImB ( P = 0.01). Conclusions::ACP comprises three molecular subtypes with distinct imaging and histological features. The prognosis of the WNT type is better than that of the ImB group, which is more likely to benefit from the ICB treatment.

Background::Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) can profoundly affect the mental health of the people living with HIV (PLWH), with higher rates of anxiety, depression, and sleep disturbances. The disparities in neuropsychological problems evaluated by physicians and self-assessed by patients are still unknown.Methods::A total of 5000 PLWH and 500 physicians from 167 hospitals were enrolled in this cross-sectional study from September 2022 to February 2023. 4-Item Patient Health Questionnaire (PHQ-4) was used for the evaluation of depressive issues and anxiety issues by PLWH. Each physician assessed 10 PLWH under their care for the presence of depressive or anxiety issues. The primary outcomes of this study are the concordance rates on the depressive issues and anxiety issues evaluation between physicians and PLWH. The Cohen’s kappa test was used to assess the agreement between physicians and PLWH.Results::The concordance rate for the evaluation of depressive issues is 73.84% (95% confidence interval [CI]: 72.60-75.04%), and it is significantly different from the expected rate of 80% ( P <0.001). Similarly, the concordance rate for the evaluation of anxiety issues is 71.74% (95% CI: 70.47-72.97%), which is significantly different from the expected rate of 80% as per the null hypothesis ( P <0.001). The overestimation rate by physicians on depressive issues is 12.20% (95% CI: 11.32-13.14%), and for anxiety issues is 12.76% (95% CI: 11.86-13.71%). The mismatch rate for depressive issues is 26.16% (95% CI: 24.96-27.40%), and for anxiety issues is 28.26% (95% CI: 27.02-29.53%). The underestimation rate by physicians on depressive issues is 13.96% (95% CI: 13.03-14.95%), and for anxiety issues is 15.50% (95% CI: 14.52-16.53%). For the treatment regiments, PLWH sustained on innovative treatment regimen (IR) related to a lower prevalence of depressive issues (odds ratio [OR] = 0.71, 95% CI: 0.59-0.87, P = 0.003) and a lower prevalence of anxiety issues (OR = 0.63, 95% CI: 0.52-0.76, P <0.001). PLWH switch from conventional treatment regimen (CR) to IR also related to a lower prevalence of depressive issues (OR = 0.79, 95% CI: 0.64-0.98) and a lower prevalence of anxiety issues (OR = 0.81, 95% CI: 0.67-0.99). Conclusion::Nearly one in three PLWH had their condition misjudged by their physicians. The findings underscore the need for improved communication and standardized assessment protocols in the care of PLWH, especially during the acute phase of HIV infection.

Objective To establish a high-performance liquid chromatography tandem mass spectrometry(HPLC-MS/MS)method for determining the plasma concentration of olverembatinib in leukemia patients,apply it to clinical drug monitoring,and provide reliable basis for rational drug use in clinical practice.Methods Ponatinib-d8 was used as an internal standard,and methanol was used to precipitate plasma proteins and extract olverembatinib.The chromatographic column was Welch Ultimate XB-C18 cloumn(50 mmx4.6 mm,5 μm),with a column temperature of 60 ℃.The mobile phase consisted of an aqueous solution(containing 0.1％formic acid+2 mmol/L ammonium acetate)-methanol solution(containing 0.1％formic acid),with a flow rate of 0.8 mL/min and gradient elution.Electrospray positive ion mode was used,with multiple reaction monitoring scanning.The quantitative ion pair of olverembatinib was m/z 533.3→260.1,the qualitative ion pair was m/z 533.3→433.3,and the internal standard ion pair was m/z 541.1 →260.2.The plasma samples of 40 leukemia patients taking olverembatinib were monitored and analyzed for concentration,and IBM SPSS Statistics 27.0 and OriginPro 2021 softwares were used for statistical analysis of the results.Results The linear range of olverembatinib was 1-250 ng/mL(r=0.998 0),the lower limit of quantification was 1 ng/mL,the extraction recovery rate was 100.28％～101.27％,the intra-day precision RSD was 1.15％～3.87％,and the inter-day precision RSD was 2.32％～3.68％.Conclusion This method is easy to operate,highly specific and sensitive,and can be used to determine the blood concentration of olverembatinib in leukemia patients.

Spinal cord injury (SCI) is a highly disabling condition, often requiring lifelong management of its complications. Due to the lengthy rehabilitation process and significant economic burden, home rehabilitation has become the primary mode of recovery for patients with SCI. Effective home rehabilitation is crucial for promoting functional recovery and improving the quality of life in patients with SCI. The application of digital health offers great potential to enhance the quality of home rehabilitation for patients with SCI. This paper reviews the necessity, common forms, application effects, shortcomings, and future prospects of digital health in the home rehabilitation of patients with SCI. The goal is to improve the feasibility, practicality, and safety of digital health applications in home rehabilitation, thereby enhancing the overall rehabilitation level and quality of life for patients with SCI.

Purpose/Significance To construct a named entity corpus of traditional Chinese medicine(TCM)ancient records,and to improve the recognition accuracy and applicability of the general domain named entity recognition(NER)model in the field of TCM ancient records.Method/Process Annotation standards for entities in TCM ancient records are formulated,and 2 384 Xin'an medical records are annotated.A RoBERTa-BiLSTM-CRF model is developed,and word vectors with semantic features are generated using the RoBERTa pre-trained language model.The BiLSTM-CRF model is used to learn the global semantic features of sequences and decode and output the optimal label sequence.Dictionary and rule features are incorporated to enhance the model's capability to recognize entity boundaries and categories.Result/Conclusion The model shows a good recognition effect on the named entity corpus of Xin'an medical cases.Integration of domain terminology dictionaries and rule-based features improves the overall Fl score to 72.8％.