White matter hyperintensity longitudinal morphometric analysis in association with Alzheimer disease.

INTRODUCTION: Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS: WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS: The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION: These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.

Analysis of macrophages and neutrophils infiltrating murine mammary carcinoma sites within hours of tumor delivery.

Here we used three different murine mammary carcinomas to study the immune environment associated with early tumor sites. While it was not surprising that the early immune response was predominated by macrophages and neutrophils, there were some novel findings at this early stage of disease. For instance, the macrophages and neutrophils expressed a mixed cytokine profile with TNF-α and TGF-ß both produced at appreciable levels. Moreover, while the cells retained their phagocytic capacity, production of reactive oxygen species by the macrophages and neutrophils was in decline. Alterations in the metabolic profile of the tumor associated macrophages were also evident with a decrease in the ATP production rate, and a higher dependence on oxidative phosphorylation for ATP production. Collectively, these data indicate a mixed phenotype of tumor-associated macrophages and neutrophils evident within hours of murine mammary carcinoma delivery.

Clinical prediction for surgical versus nonsurgical interventions in patients with vertebral osteomyelitis and discitis.

Background: Vertebral osteomyelitis and discitis (VOD), an infection of intervertebral discs, often requires spine surgical intervention and timely management to prevent adverse outcomes. Our study aims to develop a machine learning (ML) model to predict the indication for surgical intervention (during the same hospital stay) versus nonsurgical management in patients with VOD. Methods: This retrospective study included adult patients (≥18 years) with VOD (ICD-10 diagnosis codes M46.2,3,4,5) treated at a single institution between 01/01/2015 and 12/31/2019. The primary outcome studied was surgery. Candidate predictors were age, sex, race, Elixhauser comorbidity index, first-recorded lab values, first-recorded vital signs, and admit diagnosis. After splitting the dataset, XGBoost, logistic regression, and K-neighbor classifier algorithms were trained and tested for model development. Results: A total of 1,111 patients were included in this study, among which 30% (n=339) of patients underwent surgical intervention. Age and sex did not significantly differ between the two groups; however, race did significantly differ (P<0.0001), with the surgical group having a higher percentage of white patients. The top ten model features for the best-performing model (XGBoost) were as follows (in descending order of importance): admit diagnosis of fever, negative culture, Staphylococcus aureus culture, partial pressure of arterial oxygen to fractional inspired oxygen ratio (PaO2:FiO2), admit diagnosis of intraspinal abscess and granuloma, admit diagnosis of sepsis, race, troponin I, acid-fast bacillus culture, and alveolar-arterial gradient (A-a gradient). XGBoost model metrics were as follows: accuracy =0.7534, sensitivity =0.7436, specificity =0.7586, and area under the curve (AUC) =0.8210. Conclusions: The XGBoost model reliably predicts the indication for surgical intervention based on several readily available patient demographic information and clinical features. The interpretability of a supervised ML model provides robust insight into patient outcomes. Furthermore, it paves the way for the development of an efficient hospital resource allocation instrument, designed to guide clinical suggestions.

Analysis of the risk of infection in patients with chronic lymphocytic leukemia in the era of novel therapies.

We studied the risk of infections in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). Major infections were defined as requiring hospital admission or intravenous antimicrobial treatment. Incidence rate (IR) ratios (IRR) were used to compare infection rates. Of 263 CLL patients followed for 936.9 person-years, 60% required treatment for progressive CLL (66 received ibrutinib). Infections occurred in 71.9% patients (IR 92.4/100 person-years) with 31.9% having major infections (IR 20.3/100 person-years) and infections causing 37.5% of deaths. CLL treatment was associated with significantly higher risk of major (IRR 3.31, 95% CI 2.10, 5.21) and minor (IRR 1.78, 95% CI 1.43, 2.22) infections. Compared to their previous chemoimmunotherapy patients receiving salvage ibrutinib therapy (n = 47) had a significantly increased risk of a major infection (IRR 2.35 95% CI 1.27, 4.34). The risk of infection in CLL patients remains high even with use of less immunosuppressive therapies.

gb4gv: a genome browser for geminivirus.

BACKGROUND: Geminiviruses (family Geminiviridae) are prevalent plant viruses that imperil agriculture globally, causing serious damage to the livelihood of farmers, particularly in developing countries. The virus evolves rapidly, attributing to its single-stranded genome propensity, resulting in worldwide circulation of diverse and viable genomes. Genomics is a prominent approach taken by researchers in elucidating the infectious mechanism of the virus. Currently, the NCBI Viral Genome website is a popular repository of viral genomes that conveniently provides researchers a centralized data source of genomic information. However, unlike the genome of living organisms, viral genomes most often maintain peculiar characteristics that fit into no single genome architecture. By imposing a unified annotation scheme on the myriad of viral genomes may downplay their hallmark features. For example, the viron of begomoviruses prevailing in America encapsulates two similar-sized circular DNA components and both are required for systemic infection of plants. However, the bipartite components are kept separately in NCBI as individual genomes with no explicit association in linking them. Thus, our goal is to build a comprehensive Geminivirus genomics database, namely gb4gv, that not only preserves genomic characteristics of the virus, but also supplements biologically relevant annotations that help to interrogate this virus, for example, the targeted host, putative iterons, siRNA targets, etc. METHODS: We have employed manual and automatic methods to curate 508 genomes from four major genera of Geminiviridae, and 161 associated satellites obtained from NCBI RefSeq and PubMed databases. RESULTS: These data are available for free access without registration from our website. Besides genomic content, our website provides visualization capability inherited from UCSC Genome Browser. DISCUSSION: With the genomic information readily accessible, we hope that our database will inspire researchers in gaining a better understanding of the incredible degree of diversity of these viruses, and of the complex relationships within and between the different genera in the Geminiviridae. AVAILABILITY AND IMPLEMENTATION: The database can be found at: http://gb4gv.lafayette.edu.