Whole-brain mapping of histaminergic projections in mouse brain.

Histamine is a conserved neuromodulator in mammalian brains and critically involved in many physiological functions. Understanding the precise structure of the histaminergic network is the cornerstone in elucidating its function. Herein, using histidine decarboxylase (HDC)-CreERT2 mice and genetic labeling strategies, we reconstructed a whole-brain three dimensional (3D) structure of histaminergic neurons and their outputs at 0.32 × 0.32 × 2 µm3 pixel resolution with a cutting-edge fluorescence microoptical sectioning tomography system. We quantified the fluorescence density of all brain areas and found that histaminergic fiber density varied significantly among brain regions. The density of histaminergic fiber was positively correlated with the amount of histamine release induced by optogenetic stimulation or physiological aversive stimulation. Lastly, we reconstructed a fine morphological structure of 60 histaminergic neurons via sparse labeling and uncovered the largely heterogeneous projection pattern of individual histaminergic neurons. Collectively, this study reveals an unprecedented whole-brain quantitative analysis of histaminergic projections at the mesoscopic level, providing a foundation for future functional histaminergic study.

Evolution and Antigenic Differentiation of Avian Influenza A(H7N9) Virus, China.

We characterized the evolution and molecular characteristics of avian influenza A(H7N9) viruses isolated in China during 2021-2023. We systematically analyzed the 10-year evolution of the hemagglutinin gene to determine the evolutionary branch. Our results showed recent antigenic drift, providing crucial clues for updating the H7N9 vaccine and disease prevention and control.

Lipomatous metaplasia prolongs repolarization and increases repolarization dispersion within post-infarct ventricular tachycardia circuit cites.

AIMS: Post-infarct myocardium contains viable corridors traversing scar or lipomatous metaplasia (LM). Ventricular tachycardia (VT) circuitry has been separately reported to associate with corridors that traverse LM and with repolarization heterogeneity. We examined the association of corridor activation recovery interval (ARI) and ARI dispersion with surrounding tissue type. METHODS AND RESULTS: The cohort included 33 post-infarct patients from the prospective Intra-Myocardial Fat Deposition and Ventricular Tachycardia in Cardiomyopathy (INFINITY) study. We co-registered scar and corridors from late gadolinium enhanced magnetic resonance, and LM from computed tomography with intracardiac electrogram locations. Activation recovery interval was calculated during sinus or ventricular pacing, as the time interval from the minimum derivative within the QRS to the maximum derivative within the T-wave on unipolar electrograms. Regional ARI dispersion was defined as the standard deviation (SD) of ARI per AHA segment (ARISD). Lipomatous metaplasia exhibited higher ARI than scar [325 (interquartile range 270-392) vs. 313 (255-374), P < 0.001]. Corridors critical to VT re-entry were more likely to traverse through or near LM and displayed prolonged ARI compared with non-critical corridors [355 (319-397) vs. 302 (279-333) ms, P < 0.001]. ARISD was more closely associated with LM than with scar (likelihood ratio χ2 50 vs. 12, and 4.2-unit vs. 0.9-unit increase in 0.01*Log(ARISD) per 1 cm2 increase per AHA segment). Additionally, LM and scar exhibited interaction (P < 0.001) in their association with ARISD. CONCLUSION: Lipomatous metaplasia is closely associated with prolonged local action potential duration of corridors and ARI dispersion, which may facilitate the propensity of VT circuit re-entry.

Efficacy and safety of entecavir for hepatitis B virus-associated glomerulonephritis with renal insufficiency.

BACKGROUND: HBV-GN is one of the most common secondary kidney diseases in China. Entecavir is a first-line antiviral therapy in patients with HBV-GN. OBJECTIVE: This retrospective study explored whether entecavir is effective and safe for the treatment of HBV-GN with renal insufficiency. METHODS: We screened patients diagnosed with HBV-GN in The Affiliated Hospital of Qingdao University who had elevated serum creatinine levels. Group 1 (30 patients) was given entecavir as antiviral treatment. Group 2 (28 patients) was treated with ARBs. Changes in renal function and the possible influencing factors were observed, with a mean follow-up duration of 36 months. RESULTS: At the end of follow-up, the elevation in the serum creatinine level and reduction in the eGFR were greater in group 1 than in group 2. The overall renal survival rate, using eGFR < 15 ml/min as the primary renal end point, was 96.7% in group 1 and 67.9% in group 2. Urine protein excretion was decreased in both groups. Treatment with entecavir and the remission of proteinuria were protective factors against renal function impairment, while a lower baseline eGFR was a risk factor for progression to ESRD. CONCLUSIONS: Entecavir slows the progression of renal function impairment in HBV-GN and exerts a significant renal protective effect.

Predictive value of glycemic gap and stress glycemia ratio among critically ill patients with acute kidney injury: a retrospective analysis of the MIMIC-III database.

BACKGROUND AND AIMS: Acute hyperglycemia has been identified as a risk factor for acute kidney injury occurrence and mortality in various diseases. The aim of the current study was to investigate the relationship between stress-induced hyperglycemia and adverse outcomes in critically ill patients with AKI. METHODS: We extracted clinical data from Multiparameter Intelligent Monitoring in Intensive Care III version 1.4. Blood glucose and glycosylated hemoglobin during the first 24 h of ICU admission were used to calculate glycemic gap and stress hyperglycemia ratio (SHR). The outcomes included ICU mortality and need for renal replacement therapy. The association of the glycemic gap and SHR with outcomes were determined via logistic regression model and receiver-operating curves. The subgroup analysis of patients with and without diabetes was performed separately. RESULTS: Higher glycemic gap and SHR were observed in patients who had increased need of RRT, higher mortality rates and longer ICU stay. Multivariate analysis demonstrated that higher glycemic gap (OR 1.01, 95%CI 1.00-1.02, P = 0.015), as well as SHR (OR 1.32; 95%CI 1.07-1.64, P = 0.009), were independently associated with ICU mortality after adjusting for potential covariates. In subgroup analysis, the association of glycemic gap and SHR were only significant in the non-diabetic population as for the outcome of ICU mortality (OR 2.25, 95%CI 1.64-3.08, P < 0.001 and OR 1.99; 95%CI 1.46-2.72, P < 0.001, respectively). CONCLUSIONS: The glycemic gap and SHR might serve as a potential prognostic indicator of ICU mortality in critically ill patients with AKI, especially in the non-diabetic population.

Prediction of hyperkalemia in ESRD patients by identification of multiple leads and multiple features on ECG.

BACKGROUND: Patients with end-stage renal disease (ESRD) especially those undergoing dialysis have a high prevalence of hyperkalemia, which must be detected and treated immediately. But the initial symptoms of hyperkalemia are insidious, and traditional laboratory serum potassium concentration testing takes time. Therefore, rapid and real-time measurement of serum potassium is urgently needed. In this study, different machine learning methods were used to make rapid predictions of different degrees of hyperkalemia by analyzing the ECG. METHODS: A total of 1024 datasets of ECG and serum potassium concentrations were analyzed from December 2020 to December 2021. The data were scaled into training and test sets. Different machine learning models (LR, SVM, CNN, XGB, Adaboost) were built for dichotomous prediction of hyperkalemia by analyzing 48 features of chest leads V2-V5. The performance of the models was also evaluated and compared using sensitivity, specificity, accuracy, accuracy, F1 score and AUC. RESULTS: We constructed different machine models to predict hyperkalemia using LR and four other common machine-learning methods. The AUCs of the different models ranged from 0.740 (0.661, 0.810) to 0.931 (0.912,0.953) when different serum potassium concentrations were used as the diagnostic threshold for hyperkalemia, respectively. As the diagnostic threshold of hyperkalemia was raised, the sensitivity, specificity, accuracy and precision of the model decreased to various degrees. And AUC also performed less well than when predicting mild hyperkalemia. CONCLUSION: Noninvasive and rapid prediction of hyperkalemia can be achieved by analyzing specific waveforms on the ECG by machine learning methods. But overall, XGB had a higher AUC in mild hyperkalemia, but SVM performed better in predicting more severe hyperkalemia.

Novel Reassortant Avian Influenza A(H5N6) Virus, China, 2021.

Although reports of human infection with influenza A(H5N6) increased in 2021, reports of similar H5N6 virus infection in poultry are few. We detected 10 avian influenza A(H5N6) clade 2.3.4.4b viruses in poultry from 4 provinces in China. The viruses showed strong immune-escape capacity and complex genetic reassortment, suggesting further transmission risk.

Comparison of epicardial adipose tissue volume quantification between ECG-gated cardiac and non-ECG-gated chest computed tomography scans.

BACKGROUND: This study investigated accuracy and consistency of epicardial adipose tissue (EAT) quantification in non-ECG-gated chest computed tomography (CT) scans. METHODS: EAT volume was semi-automatically quantified using a standard Hounsfield unit threshold (- 190, - 30) in three independent cohorts: (1) Cohort 1 (N = 49): paired 120 kVp ECG-gated cardiac non-contrast CT (NCCT) and 120 kVp non-ECG-gated chest NCCT; (2) Cohort 2 (N = 34): paired 120 kVp cardiac NCCT and 100 kVp non-ECG-gated chest NCCT; (3) Cohort 3 (N = 32): paired non-ECG-gated chest NCCT and chest contrast-enhanced CT (CECT) datasets (including arterial phase and venous phase). Images were reconstructed with the slice thicknesses of 1.25 mm and 5 mm in the chest CT datasets, and 3 mm in the cardiac NCCT datasets. RESULTS: In Cohort 1, the chest NCCT-1.25 mm EAT volume was similar to the cardiac NCCT EAT volume, while chest NCCT-5 mm underestimated the EAT volume by 7.5%. In Cohort 2, 100 kVp chest NCCT-1.25 mm were 13.2% larger than 120 kVp cardiac NCCT EAT volumes. In Cohort 3, the chest arterial CECT and venous CECT dataset underestimated EAT volumes by ~ 28% and ~ 18%, relative to chest NCCT datasets. All chest CT-derived EAT volumes were similarly associated with significant coronary atherosclerosis with cardiac CT counterparts. CONCLUSION: The 120 kVp non-ECG-gated chest NCCT-1.25 mm images produced EAT volumes comparable to cardiac NCCT. Chest CT EAT volumes derived from consistent imaging settings are excellent alternatives to the cardiac NCCT to investigate their association with coronary artery disease.

Prognostic significance of albumin to alkaline phosphatase ratio in critically ill patients with acute kidney injury.

OBJECTIVE: No epidemiological evidence has investigated the effect of albumin to alkaline phosphatase ratio (AAPR) on the prognosis among critically ill patients with acute kidney injury (AKI). We aimed to explore the prognostic value of AAPR in these patients. METHODS: We extracted all clinical data from MIMIC III. ROC curve analysis was used to evaluate the discrimination of AAPR for predicting in-hospital mortality. A generalized additive model was applied to identify a nonlinear association between AAPR and in-hospital mortality. The Cox proportional hazards models were used to determine the association between AAPR and in-hospital and 30-day mortality. RESULTS: A total of 6894 eligible subjects were enrolled in this study. The relationship between AAPR and in-hospital mortality was nonlinear. Multivariate analysis demonstrated that lower AAPR (AAPR < 0.35) was an independent predictor of in-hospital and 30-day mortality after adjusting for potential confounders (HR 1.74, 95% CI 1.72-2.20, P < 0.001; HR 1.89, 95% CI 1.66-2.14, P < 0.001, respectively). CONCLUSIONS: AAPR may serve as a potential prognostic biomarker in critically ill patients with AKI and lower AAPR was associated with increased risk of in-hospital and 30-day mortality among these patients.

Malnutrition screening and acute kidney injury in hospitalised patients: a retrospective study over a 5-year period from China.

Malnutrition and acute kidney injury (AKI) are common complications in hospitalised patients, and both increase mortality; however, the relationship between them is unknown. This is a retrospective propensity score matching study enrolling 46 549 inpatients, aimed to investigate the association between Nutritional Risk Screening 2002 (NRS-2002) and AKI and to assess the ability of NRS-2002 and AKI in predicting prognosis. In total, 37 190 (80 %) and 9359 (20 %) patients had NRS-2002 scores <3 and ≥3, respectively. Patients with NRS-2002 scores ≥3 had longer lengths of stay (12·6 (sd 7·8) v. 10·4 (sd 6·2) d, P < 0·05), higher mortality rates (9·6 v. 2·5 %, P < 0·05) and higher incidence of AKI (28 v. 16 %, P < 0·05) than patients with normal nutritional status. The NRS-2002 showed a strong association with AKI, that is, the risk of AKI changed in parallel with the score of the NRS-2002. In short- and long-term survival, patients with a lower NRS-2002 score or who did not have AKI achieved a significantly lower risk of mortality than those with a high NRS-2002 score or AKI. Univariate Cox regression analyses indicated that both the NRS-2002 and AKI were strongly related to long-term survival (AUC 0·79 and 0·71) and that the combination of the two showed better accuracy (AUC 0·80) than the individual variables. In conclusion, malnutrition can increase the risk of AKI and both AKI and malnutrition can worsen the prognosis that the undernourished patients who develop AKI yield far worse prognosis than patients with normal nutritional status.

Layer-specific strain in patients with heart failure using cardiovascular magnetic resonance: not all layers are the same.

BACKGROUND: Global longitudinal strain (GLS), most commonly measured at the endocardium, has been shown to be superior to left ventricular (LV) ejection fraction (LVEF) for the identification of systolic dysfunction and prediction of outcomes in heart failure (HF). We hypothesized that strains measured at different myocardial layers (endocardium = ENDO, epicardium = EPI, average = AVE) will have distinct diagnostic and predictive performance for patients with HF. METHODS: Layer-specific GLS, layer-specific global circumferential strain (GCS) and global radial strain (GRS) were evaluated by cardiovascular magnetic resonance imaging (CMR) feature tracking in the Alberta HEART study. A total of 453 subjects consisted of healthy controls (controls, n = 77), at-risk for HF (at-risk, n = 143), HF with preserved ejection fraction (HFpEF, n = 87), HF with mid-range ejection fraction (HFmrEF, n = 88) and HF with reduced ejection fraction (HFrEF, n = 58). For outcomes analysis, CMR-derived imaging parameters were adjusted with a base model that included age and N-terminal prohormone of b-type natriuretic peptide (NT-proBNP) to test their independent association with 5-year all-cause mortality. RESULTS: GLS_EPI distinguished all groups with preserved LVEF (controls - 16.5 ± 2.4% vs. at-risk - 15.5 ± 2.7% vs. HFpEF - 14.1 ± 3.0%, p < 0.001) while GLS_ENDO and all GCS (all layers) were similar among these groups. GRS was reduced in HFpEF (41.1 ± 13.8% versus 48.9 ± 10.7% in controls, p < 0.001) and the difference between GLS_EPI and GLS_ENDO were significantly larger in HFpEF as compared to controls. Within the preserved LVEF groups, reduced GRS and GLS_EPI were significantly associated with increased LV mass (LVM) and LVM/LV end-diastolic volume EDV (concentricity). In multivariable analysis, only GLS_AVE and GRS predicted 5-year all-cause mortality (all ps < 0.05), with the strongest association with 5-year all-cause mortality by Akaike Information Criterion analysis and significant incremental value for outcomes prediction beyond LVEF or GLS_ENDO by the likelihood ratio test. CONCLUSION: Global strains measured on endocardium, epicardium or averaged across the wall thickness are not equivalent for the identification of systolic dysfunction or outcomes prediction in HF. The endocardium-specific strains were shown to have poorest all-around performance. GLS_AVE and GRS were the only CMR parameters to be significantly associated with 5-year all-cause mortality in multivariable analysis. GLS_EPI and GRS, as well as the difference in endocardial and epicardial strains, were sensitive to systolic dysfunction among HF patients with normal LVEF (> 55%), in whom lower strains were associated with increased concentricity.

Acute kidney injury after nephrectomy: a new nomogram to predict postoperative renal function.

BACKGROUND: We aimed to develop a nomogram based on preprocedural features for early prediction of acute kidney injury (AKI) and to assess the prognosis in patients after radical and partial nephrectomy. METHODS: The study included a development cohort of 1111 patients who were treated between June 2012 and June 2017 and an additional validation cohort of 356 patients who were treated between July 2017 and June 2018. Stepwise regression and logistic regression analyses were used to evaluate the association between predictors and AKI. Incorporating all independent predictors, a nomogram for postoperative AKI was developed and externally validated. Patients were followed up for 5 years to assess renal function, acute kidney disease (AKD), chronic kidney disease (CKD), hospital readmission and mortality were key prognosis we focused on. RESULTS: After multivariate logistic regression, radical nephrectomy (odds ratio (OR) = 3.57, p < 0.001), aspirin (OR = 1.79, p = 0.008), systolic blood pressure (OR = 1.41, p = 0.004), triglyceride (OR = 1.26, p = 0.024), and alkaline phosphatase (OR = 1.75, p = 0.034) were independent risk factors for postoperative AKI, while albumin (OR = 0.72, p = 0.031) was a protective factor for postoperative AKI. Patients with a higher estimated glomerular filtration rate (eGFR) (60-90 ml/min/1.73 m2, OR = 0.41, p = 0.004; ≥ 90 ml/min/1.73 m2, OR = 0.37, p < 0.001) were less prone to AKI than those with a lower eGFR (< 15 ml/min/1.73 m2). These predictors were all included in the final nomogram. The area under the receiver operating characteristics curve for the model were 0.77 (p < 0.001) in the development cohort and 0.72 (p < 0.001) in the validation cohort. The incidence of AKD and CKD were 27.12 and 18.64% in AKI group, which were much higher than those in no AKI group (p < 0.001). CONCLUSIONS: The nomogram had excellent predictive ability and might have significant clinical implications for the early detection of AKI in patients undergoing nephrectomy.

A precise and accurate acupoint location obtained on the face using consistency matrix pointwise fusion method.

OBJECTIVE: To develop a more precise and accurate method, and identified a procedure to measure whether an acupoint had been correctly located. METHODS: On the face, we used an acupoint location from different acupuncture experts and obtained the most precise and accurate values of acupoint location based on the consistency information fusion algorithm, through a virtual simulation of the facial orientation coordinate system. RESULTS: Because of inconsistencies in each acupuncture expert's original data, the system error the general weight calculation. First, we corrected each expert of acupoint location system error itself, to obtain a rational quantification for each expert of acupuncture and moxibustion acupoint location consistent support degree, to obtain pointwise variable precision fusion results, to put every expert's acupuncture acupoint location fusion error enhanced to pointwise variable precision. Then, we more effectively used the measured characteristics of different acupuncture expert's acupoint location, to improve the measurement information utilization efficiency and acupuncture acupoint location precision and accuracy. CONCLUSION: Based on using the consistency matrix pointwise fusion method on the acupuncture experts' acupoint location values, each expert's acupoint location information could be calculated, and the most precise and accurate values of each expert's acupoint location could be obtained.

Using dynamic spatio-temporal graph pooling network for identifying autism spectrum disorders in spontaneous functional infrared spectral sequence signals.

BACKGROUND: Autism classification work on fNIRS data using dynamic graph networks. Explore the impact of the dynamic connection relationship between brain channels on ASD, and compare the brain channel connection diagrams of ASD and TD to explore potential factors that influence the development of autism. METHOD: Using dynamic graph construction to mine the dynamic relationships of fNIRS data, obtain spatio-temporal correlations through dynamic feature extraction, and improve the information extraction capabilities of the network through spatio-temporal graph pooling to achieve classification of ASD. RESULT: A classification effect with an accuracy of 97.2% was achieved using a short sequence of 1.75s. The results showed that the dynamic connections of channel 5 and 19, channel 12 and 25, and channel 7 and 34 have a greater impact on the classification of autism. Comparison with previously used method(s): Compared with previous deep learning models, our model achieves efficient classification using short-term fNIRS data of 1.75s, and analyzes the impact of dynamic connections on classification through dynamic graphs. CONCLUSION: Using Dynamic Spatio-Temporal Graph Pooled Neural Networks (DSTGPN), dynamic connectivity between brain channels was found to have an impact on the classification of autism. By modeling the brain channel relationship maps of ASD and TD, hyperlink clusters were found to exist on the brain channel connections of ASD.

The associated factors for physical activity-related injuries among first-year university students in southern China from a biopsychosocial perspective.

Background: Understanding the diverse factors influencing physical activity-related injuries is crucial for developing effective interventions that enable individuals to participate in physical activity (PA) while minimizing injury risk. Currently, research evidence on the multiple factors associated with PA-related injuries is inadequate. This study aimed to examine the associations between PA-related injuries and various biological, psychological, and social factors among first-year university students in China. Methods: We recruited first-year university students from Shantou University in Guangdong Province, China, to participate in our study. Data collection employed a structured self-administered questionnaire, gathering information on PA-related injuries, as well as relevant biological, psychological, and social factors. Binary logistic regression, using a stepwise modeling approach, was employed for the data analysis. Results: Among 1,051 first-year university students, 28.16% reported having experienced PA-related injuries in the past year. Most of the injuries reported were minor, with the knee or lower leg being the most frequently injured part of the body. Improper posture, environmental conditions, and excessive physical load were the leading causes of PA-related injuries. Multiple logistic regression analysis revealed that female students (OR = 0.67, 95% CI: 0.47-0.94, p = 0.022) had reduced odds of PA-related injuries. Conversely, high neuroticism (OR = 1.61, 95% CI: 1.07-2.41, p = 0.022), being a member of a sports team (OR = 2.09, 95% CI: 1.34-3.27, p < 0.001), PA on the wet ground (OR = 1.73, 95% CI: 1.18-2.54, p = 0.005) increased the odds of PA-related injuries. Conclusion: Our findings underscore the intricate interplay of various factors contributing to PA-related injuries. Identifying high-risk individuals based on physiological and psychological characteristics, coupled with targeted interventions addressing modifiable risk factors, is crucial for effective prevention.

Noninvasive Visualization of the Atrioventricular Conduction System Using Cardiac Computed Tomography.

Importance: Noninvasive localization of the compact atrioventricular node and the proximal specialized conduction system (AVCS) would enhance planning for transcatheter aortic valve and complex or congenital heart disease surgical procedures. Objective: To test the hypothesis that preprocedure contrast-enhanced cardiac computed tomography (CECT) can accurately localize the AVCS by identification of the fat that insulates the conductive myocardium. Design, Setting, and Participants: This was a prospective cohort study that took place at an academic tertiary care center. Included in the study were patients with CECT acquired less than 1 month before atrial fibrillation ablation and electroanatomic localization of the His electrogram signal on electroanatomic mapping (EAM) between January 2022 and January 2023. Exposures: Preprocedure CECT. Main Outcomes and Measures: The distance from the His electrogram signal to the fat segmentation encompassing the AVCS on CECT, after registration of the images to EAM. Results: Among 20 patients (mean [SD] age, 66 [10] years; 15 male [75%]) in the cohort, the mean (SD) attenuation of the AVCS fat segmentation was 2.9 (21.5) Hounsfield units. The mean (SD) distance from the His electrogram to the closest AVCS fat voxel was 3.3 (1.6) mm. Conclusions and Relevance: Results of this cohort study suggest that CECT could accurately localize the fatty tissue that insulates the AVCS from surrounding atrial and ventricular myocardium and may enhance the efficacy and safety of procedures targeting the conduction system and structures in its proximity.

Facile synthesis of MoS2@red phosphorus heterojunction for synergistically photodynamic and photothermal therapy of renal cell carcinoma.

The therapy of the clear cell renal cell carcinoma (ccRCC) is crucial for the human healthcare due to its easy metastasis and recurrence, as well as resistance to radiotherapy and chemotherapy. In this work, we propose the synthesis of MoS2@red phosphorus (MoS2@RP) heterojunction to induce synergistic photodynamic and photothermal therapy (PDT/PTT) of ccRCC. The MoS2@RP heterojunction exhibits enhanced spectra absorption in the NIR range and produce local heat-increasing under the NIR laser irradiation compared with pure MoS2 and RP. The high photocatalytic activity of the MoS2@RP heterojunction contributes to effective transferring of the photo-excited electrons from the RP to MoS2, which promotes the production of various types of radical oxygen species (ROS) to kill the ccRCC cells. After the NIR irradiation, the MoS2@RP can effectively induce the apoptosis in the ccRCC cells through localized hyperthermia and the generation of ROS, while exhibiting low cytotoxicity towards normal kidney cells. In comparison to MoS2, the MoS2@RP heterojunction shows an approximate increase of 22 % in the lethality rate of the ccRCC cells and no significant change in toxicity towards normal cells. Furthermore, the PDT/PTT treatment using the MoS2@RP heterojunction effectively eradicates a substantial number of deep-tissue ccRCC cells in vivo without causing significant damage to major organs. This study presents promising effect of the MoS2@RP heterojunction-based photo-responsive therapy for effective ccRCC treatment.

Personalized prediction of mortality in patients with acute ischemic stroke using explainable artificial intelligence.

BACKGROUND: Research into the acute kidney disease (AKD) after acute ischemic stroke (AIS) is rare, and how clinical features influence its prognosis remain unknown. We aim to employ interpretable machine learning (ML) models to study AIS and clarify its decision-making process in identifying the risk of mortality. METHODS: We conducted a retrospective cohort study involving AIS patients from January 2020 to June 2021. Patient data were randomly divided into training and test sets. Eight ML algorithms were employed to construct predictive models for mortality. The performance of the best model was evaluated using various metrics. Furthermore, we created an artificial intelligence (AI)-driven web application that leveraged the top ten most crucial features for mortality prediction. RESULTS: The study cohort consisted of 1633 AIS patients, among whom 257 (15.74%) developed subacute AKD, 173 (10.59%) experienced AKI recovery, and 65 (3.98%) met criteria for both AKI and AKD. The mortality rate stood at 4.84%. The LightGBM model displayed superior performance, boasting an AUROC of 0.96 for mortality prediction. The top five features linked to mortality were ACEI/ARE, renal function trajectories, neutrophil count, diuretics, and serum creatinine. Moreover, we designed a web application using the LightGBM model to estimate mortality risk. CONCLUSIONS: Complete renal function trajectories, including AKI and AKD, are vital for fitting mortality in AIS patients. An interpretable ML model effectively clarified its decision-making process for identifying AIS patients at risk of mortality. The AI-driven web application has the potential to contribute to the development of personalized early mortality prevention.

Evolutionary dynamics and comparative pathogenicity of clade 2.3.4.4b H5 subtype avian influenza viruses, China, 2021-2022.

The recent concurrent emergence of H5N1, H5N6, and H5N8 avian influenza viruses (AIVs) has led to significant avian mortality globally. Since 2020, frequent human-animal interactions have been documented. To gain insight into the novel H5 subtype AIVs (i.e., H5N1, H5N6 and H5N8), we collected 6102 samples from various regions of China between January 2021 and September 2022, and identified 41 H5Nx strains. Comparative analyses on the evolution and biological properties of these isolates were conducted. Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b, with 13 related to H5N1, 19 to H5N6, and 9 to H5N8. Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8, exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015-2022 worldwide. H5N1 showed a higher rate of evolution in 2021-2022 and more sites under positive selection pressure in 2015-2022. The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations. Further hemagglutination inhibition assay suggested that some A(H5N1) viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains. Mammalian challenge assays demonstrated that the H5N8 virus (21GD001_H5N8) displayed the highest pathogenicity in mice, followed by the H5N1 virus (B1557_H5N1) and then the H5N6 virus (220086_H5N6), suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts. Based on the above results, we speculate that A(H5N1) viruses have a higher risk of emergence in the future. Collectively, these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b, contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs.