Space-Occupying Brain Lesions, Trauma-Related Tau Astrogliopathy, and ARTAG: A Report of Two Cases and a Literature Review

Astrocytes with intracellular accumulations of misfolded phosphorylated tau protein have been observed in advanced-stage chronic traumatic encephalopathy (CTE) and in other neurodegenerative conditions. There is a growing awareness that astrocytic tau inclusions are also relatively common in the brains of persons over 70 years of age-affecting approximately one-third of autopsied individuals. The pathologic hallmarks of aging-related tau astrogliopathy (ARTAG) include phosphorylated tau protein within thorn-shaped astrocytes (TSA) in subpial, subependymal, perivascular, and white matter regions, whereas granular-fuzzy astrocytes are often seen in gray matter. CTE and ARTAG share molecular and histopathologic characteristics, suggesting that trauma-related mechanism(s) may predispose to the development of tau astrogliopathy. There are presently few experimental systems to study the pathobiology of astrocytic-tau aggregation, but human studies have made recent progress. For example, leucotomy (also referred to as lobotomy) is associated with a localized ARTAG-like neuropathology decades after the surgical brain injury, suggesting that chronic brain injury of any type may predispose to later life ARTAG. To examine this idea in a different context, we report clinical and pathologic features of two middle-aged men who came to autopsy with large (\u3e 6 cm in greatest dimension) arachnoid cysts that had physically displaced and injured the subjects\u27 left temporal lobes through chronic mechanical stress. Despite the similarity of the size and location of the arachnoid cysts, these individuals had dissimilar neurologic outcomes and neuropathologic findings. We review the evidence for ARTAG in response to brain injury, and discuss how the location and molecular properties of astroglial tau inclusions might alter the physiology of resident astrocytes. These cases and literature review point toward possible mechanism(s) of tau aggregation in astrocytes in response to chronic brain trauma

Pregabalin-Induced Myopathy in a Double Lung Transplant Recipient

Pregabalin is a gamma-aminobutyric acid (GABA) derivative that was commercially approved by the Food and Drug Administration (FDA) in 2004. It is commonly used in the treatment of diabetic neuropathy, peripheral neuropathy, and spinal cord injury. We present the case of a 36-year-old Caucasian male double lung transplant recipient who presented with an 18-month history of fatigue and muscle weakness. He had elevated creatinine kinase level and his muscle biopsy showed evidence of drug-induced myopathy that improved after the cessation of pregabalin. We present a case of drug-induced myopathy as a rare complication of pregabalin therapy in a double lung transplant recipient

Neurotropic Lineage III Strains of \u3cem\u3eListeria monocytogenes\u3c/em\u3e Disseminate to the Brain without Reaching High Titer in the Blood

Listeria monocytogenes is thought to colonize the brain using one of three mechanisms: direct invasion of the blood-brain barrier, transportation across the barrier by infected monocytes, and axonal migration to the brain stem. The first two pathways seem to occur following unrestricted bacterial growth in the blood and thus have been linked to immunocompromise. In contrast, cell-to-cell spread within nerves is thought to be mediated by a particular subset of neurotropic L. monocytogenes strains. In this study, we used a mouse model of foodborne transmission to evaluate the neurotropism of several L. monocytogenes isolates. Two strains preferentially colonized the brain stems of BALB/cByJ mice 5 days postinfection and were not detectable in blood at that time point. In contrast, infection with other strains resulted in robust systemic infection of the viscera but no dissemination to the brain. Both neurotropic strains (L2010-2198, a human rhombencephalitis isolate, and UKVDL9, a sheep brain isolate) typed as phylogenetic lineage III, the least characterized group of L. monocytogenes. Neither of these strains encodes InlF, an internalin-like protein that was recently shown to promote invasion of the blood-brain barrier. Acute neurologic deficits were observed in mice infected with the neurotropic strains, and milder symptoms persisted for up to 16 days in some animals. These results demonstrate that neurotropic L. monocytogenes strains are not restricted to any one particular lineage and suggest that the foodborne mouse model of listeriosis can be used to investigate the pathogenic mechanisms that allow L. monocytogenes to invade the brain stem. IMPORTANCE Progress in understanding the two naturally occurring central nervous system (CNS) manifestations of listeriosis (meningitis/meningoencephalitis and rhombencephalitis) has been limited by the lack of small animal models that can readily distinguish between these distinct infections. We report here that certain neurotropic strains of Listeria monocytogenes can spread to the brains of young otherwise healthy mice and cause neurological deficits without causing a fatal bacteremia. The novel strains described here fall within phylogenetic lineage III, a small collection of L. monocytogenes isolates that have not been well characterized to date. The animal model reported here mimics many features of human rhombencephalitis and will be useful for studying the mechanisms that allow L. monocytogenes to disseminate to the brain stem following natural foodborne transmission

Limbic-Predominant Age-Related TDP-43 Encephalopathy Differs from Frontotemporal Lobar Degeneration

TAR-DNA binding protein-43 (TDP-43) proteinopathy is seen in multiple brain diseases. A standardized terminology was recommended recently for common age-related TDP-43 proteinopathy: limbic-predominant, age-related TDP-43 encephalopathy (LATE) and the underlying neuropathological changes, LATE-NC. LATE-NC may be co-morbid with Alzheimer’s disease neuropathological changes (ADNC). However, there currently are ill-defined diagnostic classification issues among LATE-NC, ADNC, and frontotemporal lobar degeneration with TDP-43 (FTLD-TDP). A practical challenge is that different autopsy cohorts are composed of disparate groups of research volunteers: hospital- and clinic-based cohorts are enriched for FTLD-TDP cases, whereas community-based cohorts have more LATE-NC cases. Neuropathological methods also differ across laboratories. Here, we combined both cases and neuropathologists’ diagnoses from two research centres—University of Pennsylvania and University of Kentucky. The study was designed to compare neuropathological findings between FTLD-TDP and pathologically severe LATE-NC. First, cases were selected from the University of Pennsylvania with pathological diagnoses of either FTLD-TDP (n = 33) or severe LATE-NC (mostly stage 3) with co-morbid ADNC (n = 30). Sections from these University of Pennsylvania cases were cut from amygdala, anterior cingulate, superior/mid-temporal, and middle frontal gyrus. These sections were stained for phospho-TDP-43 immunohistochemically and evaluated independently by two University of Kentucky neuropathologists blinded to case data. A simple set of criteria hypothesized to differentiate FTLD-TDP from LATE-NC was generated based on density of TDP-43 immunoreactive neuronal cytoplasmic inclusions in the neocortical regions. Criteria-based sensitivity and specificity of differentiating severe LATE-NC from FTLD-TDP cases with blind evaluation was ∼90%. Another proposed neuropathological feature related to TDP-43 proteinopathy in aged individuals is ‘Alpha’ versus ‘Beta’ in amygdala. Alpha and Beta status was diagnosed by neuropathologists from both universities (n = 5 raters). There was poor inter-rater reliability of Alpha/Beta classification (mean κ = 0.31). We next tested a separate cohort of cases from University of Kentucky with either FTLD-TDP (n = 8) or with relatively ‘pure’ severe LATE-NC (lacking intermediate or severe ADNC; n = 14). The simple criteria were applied by neuropathologists blinded to the prior diagnoses at University of Pennsylvania. Again, the criteria for differentiating LATE-NC from FTLD-TDP was effective, with sensitivity and specificity ∼90%. If more representative cases from each cohort (including less severe TDP-43 proteinopathy) had been included, the overall accuracy for identifying LATE-NC was estimated at \u3e 98% for both cohorts. Also across both cohorts, cases with FTLD-TDP died younger than those with LATE-NC (P \u3c 0.0001). We conclude that in most cases, severe LATE-NC and FTLD-TDP can be differentiated by applying simple neuropathological criteria

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

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe