B cell depletion reduces T cell activation in pancreatic islets in a murine autoimmune diabetes model

Aims/hypothesis: Type 1 diabetes is a T cell-mediated autoimmune disease characterised by the destruction of beta cells in the islets of Langerhans, resulting in deficient insulin production. B cell depletion therapy has proved successful in preventing diabetes and restoring euglycaemia in animal models of diabetes, as well as in preserving beta cell function in clinical trials in the short term. We aimed to report a full characterisation of B cell kinetics post B cell depletion, with a focus on pancreatic islets. Methods: Transgenic NOD mice with a human CD20 transgene expressed on B cells were injected with an anti-CD20 depleting antibody. B cells were analysed using multivariable flow cytometry. Results: There was a 10 week delay in the onset of diabetes when comparing control and experimental groups, although the final difference in the diabetes incidence, following prolonged observation, was not statistically significant (p = 0.07). The co-stimulatory molecules CD80 and CD86 were reduced on stimulation of B cells during B cell depletion and repopulation. IL-10-producing regulatory B cells were not induced in repopulated B cells in the periphery, post anti-CD20 depletion. However, the early depletion of B cells had a marked effect on T cells in the local islet infiltrate. We demonstrated a lack of T cell activation, specifically with reduced CD44 expression and effector function, including IFN-γ production from both CD4+ and CD8+ T cells. These CD8+ T cells remained altered in the pancreatic islets long after B cell depletion and repopulation. Conclusions/interpretation: Our findings suggest that B cell depletion can have an impact on T cell regulation, inducing a durable effect that is present long after repopulation. We suggest that this local effect of reducing autoimmune T cell activity contributes to delay in the onset of autoimmune diabetes

Phenotypically distinct anti-insulin B cells repopulate pancreatic islets after anti-CD20 treatment in NOD mice

Aims/hypothesis Autoreactive B cells escape immune tolerance and contribute to the pathogenesis of type 1 diabetes. While global B cell depletion is a successful therapy for autoimmune disease, the fate of autoreactive cells during this treatment in autoimmune diabetes is unknown. We aimed to identify and track anti-insulin B cells in pancreatic islets and understand their repopulation after anti-CD20 treatment. Methods We generated a double transgenic system, the VH125.hCD20/NOD mouse. The VH125 transgenic mouse, expressing an increased frequency of anti-insulin B cells, was crossed with a human CD20 (hCD20) transgenic mouse, to facilitate B cell depletion using anti-CD20. B cells were analysed using multiparameter and ImageStream flow cytometry. Results We demonstrated that anti-insulin B cells were recruited to the pancreas during disease progression in VH125.hCD20/NOD mice. We identified two distinct populations of anti-insulin B cells in pancreatic islets, based on CD19 expression, with both populations enriched in the CD138int fraction. Anti-insulin B cells were not identified in the plasma-cell CD138hi fraction, which also expressed the transcription factor Blimp-1. After anti-CD20 treatment, anti-insulin B cells repopulated the pancreatic islets earlier than non-specific B cells. Importantly, we observed that a CD138intinsulin+CD19− population was particularly enriched after B cell depletion, possibly contributing to the persistence of disease still observed in some mice after anti-CD20 treatment. Conclusions/interpretation Our observations may indicate why the loss of C-peptide is only temporarily delayed following anti-CD20 treatment in human type 1 diabetes

Association between adiposity indicators, metabolic parameters and inflammatory markers in a sample of female adolescents

The aim of this study was to investigate the association between total and abdominal adiposity with metabolic parameters and inflammatory markers, in female adolescents. The sample consisted of 53 adolescents aged 13 to 17 years from a public school in Curitiba, Brazil. The adiposity indicators studied were body mass index (BMI), waist circumference (WC), trunk fat mass (TKFM), total fat mass (TFM) and body fat percentage (BF%) measured by dual-energy X-ray absorptiometry. The metabolic and inflammatory parameters studied were systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, insulin, homeostasis model assessment index for insulin resistance (HOMA-IR), lipids, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), leptin, adiponectin and resistin. Eighty percent of WC variation, 87% of TKFM and TFM, and 73% of BF% were predicted by BMI variation. There was a significant positive correlation between all indicators of adiposity with SBP, DBP, insulin, HOMA-IR, CRP and leptin. Triglycerides were positively correlated with BMI and WC, and adiponectin correlated negatively with BMI. TNF-α, IL-6, glucose, total cholesterol, and high- and low-density lipoprotein cholesterol did not correlate to the studied variables. BMI showed a significant association with most of the parameters studied, and WC was slightly better than BMI to predict insulin resistance in this specific population.59432533

Discovery of 74 new bright ZZ Ceti stars in the first three years of TESS

We report the discovery of 74 new pulsating DA white dwarf stars, or ZZ Cetis, from the data obtained by the Transiting Exoplanet Survey Satellite mission, from Sectors 1 to 39, corresponding to the first 3 cycles. This includes objects from the Southern hemisphere (Sectors 1–13 and 27–39) and the Northern hemisphere (Sectors 14–26), observed with 120 s- and 20 s-cadence. Our sample likely includes 13 low-mass and one extremely low-mass white dwarf candidate, considering the mass determinations from fitting Gaia magnitudes and parallax. In addition, we present follow-up time series photometry from ground-based telescopes for 11 objects, which allowed us to detect a larger number of periods. For each object, we analysed the period spectra and performed an asteroseismological analysis, and we estimate the structure parameters of the sample, i.e. stellar mass, effective temperature, and hydrogen envelope mass. We estimate a mean asteroseismological mass of 〈Msis〉 = 0.635 ± 0.015 M⊙, excluding the candidate low or extremely low-mass objects. This value is in agreement with the mean mass using estimates from Gaia data, which is 〈Mphot〉 = 0.631 ± 0.040 M⊙, and with the mean mass of previously known ZZ Cetis of 〈M*〉 = 0.644 ± 0.034 M⊙. Our sample of 74 new bright ZZ Cetis increases the number of known ZZ Cetis by ∼20 per cent

PERCEPÇÃO DE SAÚDE DOS ACADÊMICOS DA UNOESC CHAPECÓ: UMA EXPERIÊNCIA DO COMPONENTE DE BIOESTATÍSTICA DO CURSO DE EDUCAÇÃO FÍSICA

Os métodos estatísticos desempenham um papel crescente e importante em praticamente todas as fases da realização de uma pesquisa. Por isso, a importância de relatar a vivência dos acadêmicos do 5º período de Educação Física Bacharelado no componente de bioestatística. O objetivo foi de registrar os resultados dos dados coletados e as experiências dos acadêmicos. Desenvolveu-se um trabalho escrito contendo os objetivos, a metodologia, os resultados com tabelas e gráfico e a conclusão do trabalho, bem como, uma apresentação em Power Point®  para a socialização. Verificou-se que o método de aprendizagem por meio da teoria e da prática, foi eficiente para a aquisição de conhecimento dos acadêmicos sobre a bioestatística. &nbsp

Marine substrate response from the analysis of seismic attributes in CHIRP sub-bottom profiles

O presente trabalho tem por objetivo apresentar uma avaliação da resposta dos atributos sísmicos (Amplitude Instantânea, Amplitude RMS, Energia e Frequência Instantânea) em diferentes tipos de substratos marinhos, correlacionando-os com características sedimentológicas das amostras coletadas. Foram analisados perfis sísmicos obtidos com um perfilador de subsuperfície com sinal do tipo CHIRP modelo SB-216S da marca EdgeTech, com frequência de trabalho de 2 e 16 kHz. O método se deu a partir da análise estatística não-paramétrica de Kruskal-Wallis foi aplicada para comparar o comportamento dos atributos com as diferentes classes dos grãos das amostras (subagrupadas segundo o grau de seleção) e com diferentes feições. Com base na análise dos resultados, foi possível distinguir dois grupos distintos nas amostras, o grupo SAMF (silte e areia muito fina) e o grupo AFMG (areia fina, areia média e areia grossa). Como conclusão, pode-se dizer que os atributos não foram capazes de distinguir entre as classes mais próximas dos grãos. Utilizando o coeficiente de Spearman foi verificado que o atributo "Amplitude Instantânea" mostrou-se mais eficiente em separar os dois conjuntos. Comparando sedimentos, gás e rocha, os atributos que utilizaram o atributo "amplitude" foram eficazes em separar os sedimentos do gás e da rocha, porém não os distinguiram entre as duas feições, visto que elas apresentaram amplitudes muito altas, mas semelhantes entre si. O atributo "Frequência Instantânea" mostrou-se eficaz na diferenciação entre sedimento, rocha e gás, o sedimento apresentou uma maior banda de frequência, a rocha uma faixa intermediária e o gás a menor delas.This paper presents an evaluation of the response of seismic reflection attributes in different types of marine substrate (rock, shallow gas, sediments) using seafloor samples for ground-truth statistical comparisons. The data analyzed include seismic reflection profiles collected using two CHIRP subbottom profilers (Edgetech Model 3100 SB-216S), with frequency ranging between 2 and 16 kHz, and a number (38) of sediment samples collected from the seafloor. The statistical method used to discriminate between different substratum responses was the non-parametric Kruskal-Wallis analysis, carried out in two steps: 1) comparison of Seismic Attributes between different marine substrates (unconsolidated sediments, rock and shallow gas); 2) comparison of Seismic Attributes between different sediment classes in seafloors characterized by unconsolidated sediments (subdivided according to sorting). These analyses suggest that amplitude-related attributes were effective in discriminating between sediment and gassy/rocky substratum, but did not differentiate between rocks and shallow gas. On the other hand, the Instantaneous Frequency attribute was effective in differentiating sediments, rocks and shallow gas, with sediment showing higher frequency range, rock an intermediate range, and shallow gas the lowest response. Regarding grain-size classes and sorting, statistical analysis discriminated between two distinct groups of samples, the SVFS (silt and very fine sand) and the SFMC (fine, medium and coarse sand) groups. Using a Spearman coefficient, it was found that the Instantaneous Amplitude was more efficient in distinguishing between the two groups. None of the attributes was able to distinguish between the closest grain size classes such as those of silt and very fine sand

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic