Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

The ICR(Institute of Cancer Research)mouse infection model was constructed to study the pathogenicity of Sal-monella Telelkebir serotype,and the pathogenic identification of mouse isolates was carried out.Observe the bacterial excretion cycle,evaluate the pathogenicity of Salmonella serotype to mice,and calculate the LD50 by the changes in clinical characteris-tics,histopathology and tissue bacterial load of infected mice;by flight mass spectrometry,biochemical identification,serotype identification,molecular typing and other experiments,compared with human isolates;virulence gene analysis was carried out by PCR experiment and whole genome sequencing.The LD50 of Salmonella Telelkebir is 2.67 × 108 CFU/mL;curling and fluffing may occur 0.5 h after infection;autopsy of dead mice showed that the small intestine was severely congested,with more bubbles and fluid accumulation,cecal necrosis,liver apical degeneration and necrosis,necrotic foci on the surface of the kidney and spleen atrophy;the bacterial load of spleen,kidney,lung,liver and jejunum in mice reached its peak at 3 days after infection,while that of heart at 6 days;the bacterial excretion time of the high-dose group exceeded 100 days;The level of CD3 in tissues increased with increasing dose,with inflammatory cell infiltration,myocardial capillary dilation and hyperemia,large area of vacuoles,degeneration and necrosis of hepatocytes,obvious enlargement of splenic sinus,blurred zoning,thickening of glomerular basement membrane,partial exfoliation of ciliated epithelium,atrophy and exfoliation of jejunal villi;PCR and whole genome sequencing revealed Salmonella-related virulence genes such as cdtB,plt A and pltB.This study was the first to successfully establish the ICR mouse model of Salmonella Telelkebir,demonstrating that this serotype of Salmonella has some pathogenicity.

This study aimed to investigate the role and mechanism of sappanone A (SA) in regulating renal ischemia-reperfusion injury (IRI) in rats. The animal experiment has been approved by the Ethics Committee of Suzhou Wujiang District Children's Hospital (approval number: 2022010). First, hematoxylin-eosin (H&E) staining was used to evaluate the effects of SA on IRI, and renal damage was scored. Serum creatinine (SCr), blood urea nitrogen (BUN) and cystatin C (Cystatin C) were analyzed. The effect of sappanone A on the apoptosis of renal tubular epithelial cells induced by IRI was analyzed by TUNEL staining. Protein expression levels of p-JNK/JNK, p-ERK/ERK, Bcl2, Bax and cleaved-caspase 3 in renal tissues were detected by Western blot. Finally, H&E staining, serological analysis, TUNEL staining and Western blot were used to determine whether JNK activator anisomycin could reverse the effect of SA on IRI in rats. The results showed SA significantly reduced the renal tubule injury caused by ischemia-reperfusion, and decreased the level of SCr, BUN and Cys C in serum. TUNEL staining showed that SA significantly reduced the apoptosis of renal tubular epithelial cells induced by IRI. Western blot analysis of kidney tissue showed that SA significantly promoted the expression of apoptosis inhibiting protein Bcl2 and inhibited the expression of apoptosis-promoting proteins Bax and cleaved-caspase 3. Further analysis elucidated that SA did not affect the phosphorylation of ERK but decreased the phosphorylation of JNK. Finally, H&E staining, serological analysis, TUNEL staining and Western blot confirmed that JNK activator anisomycin could reverse the alleviating effect of SA on IRI in rats. The above findings suggest that SA could alleviate IRI in rats by inhibiting JNK phosphorylation.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

AIM: To explore the application value of deep learning technology in automatic meibomian glands segmentation. METHODS:Infrared meibomian gland images were collected and 193 of them were picked out for establishing the database. The images were manually labeled by three clinicians. UNet++ network and automatic data expansion strategy were introduced to construct the automatic meibomian glands segmentation model. The feasibility and effectiveness of the proposed segmentation model were analyzed by precision, sensitivity, specificity, accuracy and intersection over union.RESULTS: Taking manual labeling as the gold standard, the presented method segment the glands effectively and steadily with accuracy, sensitivity and specificity of 94.31%, 82.15% and 96.13% respectively. On the average, only 0.11s was taken for glands segmentation of single image.CONCLUSIONS: In this paper, deep learning technology is introduced to realize automatic segmentation of meibomian glands, achieving high accuracy, good stability and efficiency. It would be quite useful for calculation of gland morphological parameters, the clinical diagnosis and screening of related diseases, improving the diagnostic efficiency.

OBJECTIVES: To investigate the incidence of extrauterine growth retardation (EUGR) and its risk factors in very preterm infants (VPIs) during hospitalization in China. METHODS: A prospective multicenter study was performed on the medical data of 2 514 VPIs who were hospitalized in the department of neonatology in 28 hospitals from 7 areas of China between September 2019 and December 2020. According to the presence or absence of EUGR based on the evaluation of body weight at the corrected gestational age of 36 weeks or at discharge, the VPIs were classified to two groups: EUGR group (n=1 189) and non-EUGR (n=1 325). The clinical features were compared between the two groups, and the incidence of EUGR and risk factors for EUGR were examined. RESULTS: The incidence of EUGR was 47.30% (1 189/2 514) evaluated by weight. The multivariate logistic regression analysis showed that higher weight growth velocity after regaining birth weight and higher cumulative calorie intake during the first week of hospitalization were protective factors against EUGR (P<0.05), while small-for-gestational-age birth, prolonged time to the initiation of total enteral feeding, prolonged cumulative fasting time, lower breast milk intake before starting human milk fortifiers, prolonged time to the initiation of full fortified feeding, and moderate-to-severe bronchopulmonary dysplasia were risk factors for EUGR (P<0.05). CONCLUSIONS It is crucial to reduce the incidence of EUGR by achieving total enteral feeding as early as possible, strengthening breastfeeding, increasing calorie intake in the first week after birth, improving the velocity of weight gain, and preventing moderate-severe bronchopulmonary dysplasia in VPIs.
Female ; Fetal Growth Retardation ; Gestational Age ; Hospitalization ; Humans ; Incidence ; Infant ; Infant, Newborn ; Infant, Premature ; Infant, Very Low Birth Weight ; Prospective Studies ; Risk Factors

Objective: This study assesses the prevalence of musculoskeletal (MSK) pain in patients attending primary care clinics in a medium-sized town in Malaysia and examines the interventions given for the symptoms and the level of the associated disabilities. Method: This investigation comprises a cross-sectional descriptive study of all patients visiting two primary care clinics aged 18 years and above. Patients presenting with joint pain answered a questionnaire assessing demographic data, disabilities (measured by the Stanford HAQ-DI), and treatment options. Results: Of 1,074 patients surveyed, 202 (18.8%) had MSK complaints. The mean age of those with MSK pain was 56.1 years. Incidence increased with age, reaching 78.8% of those over 48 years of age. The knee was the most common site of MSK pain (52.2%), with 20.3% requiring referral for specialist assessment. The median HAQ score was 0.375 and 89.6% of those surveyed had mild disability. Conclusion: MSK pain is a common problem among patients visiting primary care clinics. The most common site of MSK pain was the knee. On formal assessment, the majority of these patients exhibited mild disability. A significant proportion of patients still required specialist referral. This finding would suggest a need for further training on the management of MSK disease at the primary care level to avoid over-burdening the secondary care services.