Polymyxin B, which is a last-line antibiotic for extensively drug-resistant Gram-negative bacterial infections, became available in China in Dec. 2017. As dose adjustments are based solely on clinical experience of risk toxicity, treatment failure, and emergence of resistance, there is an urgent clinical need to perform therapeutic drug monitoring (TDM) to optimize the use of polymyxin B. It is thus necessary to standardize operating procedures to ensure the accuracy of TDM and provide evidence for their rational use. We report a consensus on TDM guidelines for polymyxin B, as endorsed by the Infection and Chemotherapy Committee of the Shanghai Medical Association and the Therapeutic Drug Monitoring Committee of the Chinese Pharmacological Society. The consensus panel was composed of clinicians, pharmacists, and microbiologists from different provinces in China and Australia who made recommendations regarding target concentrations, sample collection, reporting, and explanation of TDM results. The guidelines provide the first-ever consensus on conducting TDM of polymyxin B, and are intended to guide optimal clinical use.
Humans ; Anti-Bacterial Agents/therapeutic use* ; China ; Drug Monitoring/methods* ; Polymyxin B ; Practice Guidelines as Topic

The twenty-first century has already recorded more than ten major epidemics or pandemics of viral disease, including the devastating COVID-19. Novel effective antivirals with broad-spectrum coverage are urgently needed. Herein, we reported a novel broad-spectrum antiviral compound PAC5. Oral administration of PAC5 eliminated HBV cccDNA and reduced the large antigen load in distinct mouse models of HBV infection. Strikingly, oral administration of PAC5 in a hamster model of SARS-CoV-2 omicron (BA.1) infection significantly decreases viral loads and attenuates lung inflammation. Mechanistically, PAC5 binds to a pocket near Asp49 in the RNA recognition motif of hnRNPA2B1. PAC5-bound hnRNPA2B1 is extensively activated and translocated to the cytoplasm where it initiates the TBK1-IRF3 pathway, leading to the production of type I IFNs with antiviral activity. Our results indicate that PAC5 is a novel small-molecule agonist of hnRNPA2B1, which may have a role in dealing with emerging infectious diseases now and in the future.
Animals ; Mice ; Antiviral Agents/pharmacology* ; COVID-19 ; Hepatitis B virus ; Interferon Type I/metabolism* ; SARS-CoV-2/drug effects* ; Heterogeneous-Nuclear Ribonucleoprotein Group A-B/antagonists & inhibitors*

Purpose: There has been limited work assessing the use of re-irradiation (re-RT) for local failure following stereotactic spinal radiosurgery (SSRS). We reviewed our institutional experience of conventionally-fractionated external beam radiation (cEBRT) for salvage therapy following SSRS local failure. Materials and Methods: We performed a retrospective review of 54 patients that underwent salvage conventional re-RT at previously SSRS-treated sites. Local control following re-RT was defined as the absence of progression at the treated site as determined by magnetic resonance imaging. Results: Competing risk analysis for local failure was performed using a Fine-Gray model. The median follow-up time was 25 months and median overall survival (OS) was 16 months (95% confidence interval [CI], 10.8–24.9 months) following cEBRT re-RT. Multivariable Cox proportional-hazards analysis revealed Karnofsky performance score prior to re-RT (hazard ratio [HR] = 0.95; 95% CI, 0.93–0.98; p = 0.003) and time to local failure (HR = 0.97; 95% CI, 0.94–1.00; p = 0.04) were associated with longer OS, while male sex (HR = 3.92; 95% CI, 1.64–9.33; p = 0.002) was associated with shorter OS. Local control at 12 months was 81% (95% CI, 69.3–94.0). Competing risk multivariable regression revealed radioresistant tumors (subhazard ratio [subHR] = 0.36; 95% CI, 0.15–0.90; p = 0.028) and epidural disease (subHR = 0.31; 95% CI, 0.12–0.78; p =0.013) were associated with increased risk of local failure. At 12 months, 91% of patients maintained ambulatory function. Conclusion Our data suggest that cEBRT following SSRS local failure can be used safely and effectively. Further investigation is needed into optimal patient selection for cEBRT in the retreatment setting.

Berberine (BBR) as one of the most effective natural products has been increasingly used to treat various chronic diseases due to its immunosuppressive/tolerogenic activities. However, it is unknown if BBR can be applied without abrogating the efforts of vaccination. Here we show that priming of CD8⁺ T cells in the presence of BBR lead to improved central memory formation (Tcm) with substantially reduced effector proliferation, primarily orchestrated through activation of AMPK and Stat5. Tcm derived from vaccinated mice fed with BBR were able to adoptively transfer protective immunity to naïve recipients. Vaccination of BBR-fed mice conferred better memory protection against infection without losing immediate effector efficacy, suggesting appreciable benefits from using BBR in vaccination. Thus, our study may help to lay the groundwork for mechanistic understanding of the immunomodulatory effects of natural products and their potential use as adjuvant that allows the design of novel vaccines with more desirable properties.

Objective: To analyze the prevalence of dry and wet age-related macular degeneration (AMD) in patients with diabetes, hypertension and hyperlipidemia, and to analyze the risk factors for AMD. Methods: A population-based cross-sectional epidemiologic study was conducted involving 14,440 individuals. We assessed the prevalence of dry and wet AMD in diabetic and non-diabetic subjects and analyzed the risk factors for AMD. Results: The prevalence of wet AMD in diabetic and non-diabetic patients was 0.3% and 0.5%, respectively, and the prevalence of dry AMD was 17% and 16.4%, respectively. The prevalence of wet AMD in healthy, hypertensive, hyperlipidemic, and hypertensive/hyperlipidemic populations was 0.5%, 0.3%, 0.2%, and 0.7%, respectively. The prevalence of dry AMD in healthy, hypertensive, hyperlipidemic, and hypertensive/hyperlipidemic populations was 16.6%, 16.2%, 15.2%, and 17.2%, respectively. Age, sex, body mass index, and use of hypoglycemic drugs or lowering blood pressure drugs were corrected in the risk factor analysis of AMD. Diabetes, diabetes/hypertension, diabetes/hyperlipidemia, and diabetes/hypertension/hyperlipidemia were analyzed. None of the factors analyzed in the current study increased the risk for the onset of AMD. Conclusion There was no significant difference in the prevalence of wet and dry AMD among diabetic and non-diabetic subjects. Similarly, there was no significant difference in the prevalence of wet and dry AMD among subjects with hypertension and hyperlipidemia. Diabetes co-existing with hypertension and hyperlipidemia were not shown to be risk factors for the onset of dry AMD.
Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Humans ; Hyperlipidemias/epidemiology* ; Hypertension/epidemiology* ; Macular Degeneration/etiology* ; Risk Factors

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size-signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses.
Anisotropy ; Brain/diagnostic imaging* ; Corpus Callosum ; Diffusion Tensor Imaging ; Humans ; Parkinson Disease/diagnostic imaging* ; White Matter/diagnostic imaging*

Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.
Adult ; Aged ; Aged, 80 and over ; Aging ; genetics ; immunology ; Betacoronavirus ; CD4-Positive T-Lymphocytes ; metabolism ; Cell Lineage ; Chromatin Assembly and Disassembly ; Coronavirus Infections ; immunology ; Cytokine Release Syndrome ; etiology ; immunology ; Cytokines ; biosynthesis ; genetics ; Disease Susceptibility ; Flow Cytometry ; methods ; Gene Expression Profiling ; Gene Expression Regulation, Developmental ; Gene Rearrangement ; Humans ; Immune System ; cytology ; growth & development ; immunology ; Immunocompetence ; genetics ; Inflammation ; genetics ; immunology ; Mass Spectrometry ; methods ; Middle Aged ; Pandemics ; Pneumonia, Viral ; immunology ; Sequence Analysis, RNA ; Single-Cell Analysis ; Transcriptome ; Young Adult

In the original publication the bands in Fig. 1J and Fig. 2B were not visible. The correct versions of Fig. 1J and Fig. 2B are provided in this correction.