Milk fat globule membrane attenuates high fat diet-induced neuropathological changes in obese Ldlr-/-.Leiden mice.

BACKGROUND: Milk-fat globule membrane (MFGM) is a complex structure secreted by the mammary gland and present in mammalian milk. MFGM contains lipids and glycoproteins as well as gangliosides, which may be involved in myelination processes. Notably, myelination and thereby white matter integrity are often altered in obesity. Furthermore, MFGM interventions showed beneficial effects in obesity by affecting inflammatory processes and the microbiome. In this study, we investigated the impact of a dietary MFGM intervention on fat storage, neuroinflammatory processes and myelination in a rodent model of high fat diet (HFD)-induced obesity. METHODS: 12-week-old male low density lipoprotein receptor-deficient Leiden mice were exposed to a HFD, a HFD enriched with 3% whey protein lipid concentrate (WPC) high in MFGM components, or a low fat diet. The impact of MFGM supplementation during 24-weeks of HFD-feeding was examined over time by analyzing body weight and fat storage, assessing cognitive tasks and MRI scanning, analyzing myelinization with polarized light imaging and examining neuroinflammation using immunohistochemistry. RESULTS: We found in this study that 24 weeks of HFD-feeding induced excessive fat storage, increased systolic blood pressure, altered white matter integrity, decreased functional connectivity, induced neuroinflammation and impaired spatial memory. Notably, supplementation with 3% WPC high in MFGM components restored HFD-induced neuroinflammation and attenuated the reduction in hippocampal-dependent spatial memory and hippocampal functional connectivity. CONCLUSIONS: We showed that supplementation with WPC high in MFGM components beneficially contributed to hippocampal-dependent spatial memory, functional connectivity in the hippocampus and anti-inflammatory processes in HFD-induced obesity in rodents. Current knowledge regarding exact biological mechanisms underlying these effects should be addressed in future studies.

Reevaluation of the US Pathologist Workforce Size.

Importance: There is currently no national organization that publishes its data that serves as the authoritative source of the pathologist workforce in the US. Accurate physician numbers are needed to plan for future health care service requirements. Objective: To assess the accuracy of current pathologist workforce estimates in the US by examining why divergency appears in different published resources. Design, Setting, and Participants: This study examined the American Board of Pathology classification for pathologist primary specialty and subspecialties and analyzed previously published reports from the following data sources: the Association of American Medical Colleges (AAMC), the Accreditation Council for Graduate Medical Education (ACGME), a 2013 College of American Pathologists (CAP) report, a commercially available version of the American Medical Assoication (AMA) Physician Masterfile, and an unpublished data summary from June 10, 2019. Main Outcomes and Measures: Number of physicians classified as pathologists. Results: The most recent AAMC data from 2017 (published in 2018) reported 12 839 physicians practicing "anatomic/clinical pathology," which is a subset of the whole. In comparison, the current AMA Physician Masterfile, which is not available publicly, listed 21 292 active pathologists in June 2019. The AMA Physician Masterfile includes all pathologists in 15 subspecialized training areas as identified by the ACGME. By contrast, AAMC's data, which derive from the AMA Physician Masterfile data, only count physicians primarily associated with 3 general categories of pathologists and 1 subspecialty category (ie, chemical pathology). Thus, the AAMC pathology workforce estimate does not include those whose principal work is in 11 subspecialty areas, such as blood banking or transfusion medicine, cytopathology, hematopathology, or microbiology. An additional discrepancy relates to the ACGME residency (specialties) and fellowship (subspecialties) training programs in which pathologists with training in dermatopathology appear as dermatologists and pathologists with training in molecular genetic pathology appear as medical geneticists. Conclusions and Relevance: This analysis found that most sources reported only select categories of the pathologist workforce rather than the complete workforce. The discordant nature of reporting may pertain to other medical specialties that have undergone increased subspecialization during the past 2 decades (eg, surgery and medicine). Reconsideration of the methods for determining the pathologist workforce and for all workforces in medicine appears to be needed.

Whole slide imaging compared with light microscopy for primary diagnosis in surgical neuropathology: a validation study.

BACKGROUND: Digital pathology practice is rapidly gaining popularity among practicing anatomic pathologists. Acceptance is higher among the newer generation of pathologists who are willing to adapt to this new diagnostic method due to the advantages offered by whole slide imaging (WSI) compared to traditional light microscopy (TLM). We performed this validation study because we plan to implement the WSI system for diagnostic services. OBJECTIVES: Determine the feasibility of using digital pathology for diagnostic services by assessing the equivalency of WSI and TLM. DESIGN: A laboratory-based cross-sectional study. SETTING: Central laboratory at a tertiary health care center. MATERIALS AND METHODS: Four practicing surgical pathologists participated in this study. Each pathologist blindly reviewed 60 surgical neuropathology cases with a minimum 8-week washout-period between the two diagnostic modalities (WSI vs. TLM). Intraobserver concordance rates between WSI and TLM diagnoses as compared to the original diagnosis were calculated. MAIN OUTCOME MEASURES: Overall intraobserver concordance rates between each diagnostic method (WSI and TLM) and original diagnosis. SAMPLE SIZE: 60 in-house surgical neuropathology cases. RESULTS: The overall intraobserver concordance rate between TLM and original diagnosis was 86.3% (range 76.7%-91.7%) versus 80.8% for WSI (range 68.3%-88.3%). These findings are suggestive of the superiority of TLM, but the Fleiss' Kappa statistic indicated that the two methods are equivalent, despite the low level of the K value. CONCLUSION: WSI is not inferior to the light microscopy and is feasible for primary diagnosis in surgical neuropathology. However, to ensure the best results, only formally trained neuropathologists should handle the digital neuropathology service. LIMITATIONS: Only one diagnostic slide per case rather than the whole set of slides, sample size was relatively small, and there was an insufficient number of participating neuropathologists. CONFLICT OF INTEREST: None.

Neuropsychological latent classes at enrollment and postmortem neuropathology.

INTRODUCTION: We classified individuals based on their baseline performance on cognitive measures and investigated the association between cognitive classifications and neuropathological findings ∼7 years later, as an external validator. METHODS: Brain autopsies of 779 decedents were examined. Baseline latent class analysis on 10 neuropsychological measures was previously assigned: mixed-domains impairment (n = 39, 5%), memory-specific impairment (n = 210, 27%), frontal impairment (n = 113, 14.5%), average cognition (n = 360, 46.2%), and superior cognition (n = 57, 7.3%). Linear regressions and risks ratios were used to examine the relation of latent class assignment at enrollment with neuropathological indices. RESULTS: Amyloid ß, tau, and transactive response DNA-binding protein 43 were associated with mixed-domains impairment and memory-specific impairment classes ∼7 years before death. Moderate arteriolosclerosis was associated with membership in the frontal impairment class. DISCUSSION: Our findings support the use of latent class models that incorporate more comprehensive neuropsychological measures to classify cognitive impairment.

Neurological diseases of cattle in the state of Goiás, Brazil (2010-2017) / Doenças neurológicas de bovinos no estado de Goiás (2010-2017)

A retrospective study was conducted on neurological diseases of cattle in the state of Goiás, Brazil, from March 2010 to August 2017. Samples of three veterinary diagnostic laboratories were analyzed. Diagnosis was established in 170 out of 407 cattle with neurological signs. Epidemiological, clinical, and anatomic pathology features of each case were researched in the files. Main disorders included diseases caused by viruses (rabies 29.41%, meningoencephalitis by bovine herpesvirus 15.88%, and malignant catarrhal fever 1.76%), by bacteria (botulism 5.88%, suppurative meningitis 3.53%, encephalic abscesses 2.94%, listeriosis 1.76%, and thrombotic meningoencephalitis 1.76%), of metabolic origin (polioencephalomalacia 17.06%), of indefinite cause (lymphoplasmacytic meningoencephalitis 11.18%, traumatic hemorrhages 3.53%, and multifocal malacia with gliosis 1.18%), congenital (hydrocephaly 1.18% and multiple malformations 0.59%), toxic (urea poisoning 1.18% and insecticide poisoning 0.59%), and parasitic (meningoencephalitis associated with infection by Trypanosoma sp. 0.59%).(AU)

Foi realizado um estudo retrospectivo de doenças neurológicas de bovinos no estado de Goiás durante o período de março de 2010 a agosto de 2017, analisando amostras de três laboratórios de diagnóstico veterinário. De 407 bovinos que apresentaram sinais clínicos neurológicos, o diagnóstico foi estabelecido em 170 casos. Desses casos, foram pesquisadas nas fichas as características epidemiológicas, clínicas e anatomopatológicas. As principais doenças diagnosticadas foram causadas por vírus (raiva 29,41%, meningoencefalite por herpesvírus bovino 15,88% e febre catarral maligna 1,76%), de origem metabólica (polioencefalomalacia 17,06%), por bactérias (botulismo 5,88%, meningite supurativa 3,53%, abscessos encefálicos 2,94%, listeriose 1,76% e meningoencefalite trombótica 1,76%), sem causa definida (meningoencefalite linfoplasmocítica 11,18%, hemorragias traumáticas 3,53% e malacia multifocal com gliose 1,18%), congênitas (hidrocefalia 1,18% e malformações múltiplas 0,59%), tóxicas (intoxicação por ureia 1,18% e intoxicação por inseticida 0,59%), e parasitária (meningoencefalite associada à infecção por Trypanosoma sp. 0,59%).(AU)