Scrub Typhus Presenting as Subdural Hemorrhage with Normal Platelet Counts: A Rare Case Presentation

Scrub typhus is a common zoonotic disease with high case fatality rate. The clinical presentation of this disease may vary from acute febrile illness, thrombocytopenia, gastrointestinal manifestations, coagulopathy to neurological manifestations. The common neurological manifestations are meningitis and meningoencephalitis, whereas subdural hemorrhage, cerebrovascular accident, i.e., intracerebral hemorrhage, infarct, subarachnoid hemorrhage, etc. are among rare neurological presentations. Scrub typhus-induced neurological disease should be investigated to provide a timely and appropriate diagnosis and to reduce the mortality in complicated scrub typhus infection. Here we report a case of scrub typhus complicated with subdural hemorrhage admitted in our hospital

Bedaquiline, Delamanid, Linezolid and Clofazimine for Treatment of Pre-extensively Drug-Resistant Tuberculosis.

BACKGROUND Treatment success rates for multidrug-resistant tuberculosis (MDR-TB) remain low globally. Availability of newer drugs has given scope to develop regimens that can be patient-friendly, less toxic, with improved outcomes. We proposed to determine the effectiveness of an entirely oral, short-course regimen with Bedaquiline and Delamanid in treating MDR-TB with additional resistance to fluoroquinolones (MDR-TBFQ+) or second-line injectable (MDR-TBSLI+). METHODS We prospectively determined the effectiveness and safety of combining two new drugs with two repurposed drugs - Bedaquiline, Delamanid, Linezolid, and Clofazimine for 24-36 weeks in adults with pulmonary MDR-TBFQ+ or/and MDR-TBSLI+. The primary outcome was a favorable response at end of treatment, defined as two consecutive negative cultures taken four weeks apart. The unfavorable outcomes included bacteriologic or clinical failure during treatment period. RESULTS Of the 165 participants enrolled, 158 had MDR-TBFQ+. At the end of treatment, after excluding 12 patients due to baseline drug susceptibility and culture negatives, 139 of 153 patients (91%) had a favorable outcome. Fourteen patients (9%) had unfavorable outcomes: four deaths, seven treatment changes, two bacteriological failures, and one withdrawal. During treatment, 85 patients (52%) developed myelosuppression, 69 (42%) reported peripheral neuropathy, and none had QTc(F) prolongation >500msec. At 48 weeks of follow-up, 131 patients showed sustained treatment success with the resolution of adverse events in the majority. CONCLUSION After 24-36 weeks of treatment, this regimen resulted in a satisfactory favorable outcome in pulmonary MDR-TB patients with additional drug resistance. Cardiotoxicity was minimal, and myelosuppression, while common, was detected early and treated successfully

An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12

Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research

Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Genome-wide association study of circulating interleukin 6 levels identifies novel loci

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67428 (ndiscovery=52654 and nreplication=14774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined=1.8x10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined=1.5x10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined=1.2x10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.</p

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing