Fighting viral infections and virus-driven tumors with cytotoxic CD4+ T cells

CD4+ T cells have been and are still largely regarded as the orchestrators of immune responses, being able to differentiate into distinct T helper cell populations based on differentiation signals, transcription factor expression, cytokine secretion, and specific functions. Nonetheless, a growing body of evidence indicates that CD4+ T cells can also exert a direct effector activity, which depends on intrinsic cytotoxic properties acquired and carried out along with the evolution of several pathogenic infections. The relevant role of CD4+ T cell lytic features in the control of such infectious conditions also leads to their exploitation as a new immunotherapeutic approach. This review aims at summarizing currently available data about functional and therapeutic relevance of cytotoxic CD4+ T cells in the context of viral infections and virus-driven tumors

Mechanism of KMT5B haploinsufficiency in neurodevelopment in humans and mice.

Pathogenic variants in KMT5B, a lysine methyltransferase, are associated with global developmental delay, macrocephaly, autism, and congenital anomalies (OMIM# 617788). Given the relatively recent discovery of this disorder, it has not been fully characterized. Deep phenotyping of the largest (n = 43) patient cohort to date identified that hypotonia and congenital heart defects are prominent features that were previously not associated with this syndrome. Both missense variants and putative loss-of-function variants resulted in slow growth in patient-derived cell lines. KMT5B homozygous knockout mice were smaller in size than their wild-type littermates but did not have significantly smaller brains, suggesting relative macrocephaly, also noted as a prominent clinical feature. RNA sequencing of patient lymphoblasts and Kmt5b haploinsufficient mouse brains identified differentially expressed pathways associated with nervous system development and function including axon guidance signaling. Overall, we identified additional pathogenic variants and clinical features in KMT5B-related neurodevelopmental disorder and provide insights into the molecular mechanisms of the disorder using multiple model systems

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Perspectivas epidemiológicas, clínicas e terapêuticas do transtorno bipolar em comorbidade com o uso de drogas: revisão de sistemática: Epidemiological, clinical and therapeutic perspectives of bipolar disorder in comorbidity with drug use: a systematic review

Conhecida como transtorno maníaco-depressivo, atualmente possui um novo nome: Transtorno Afetivo Bipolar, visto que com o passar do tempo foi se percebendo que esse transtorno não se tratava de uma alteração psicótica, e mais de um prejuízo afetivo. O transtorno bipolar possui alguns tipos, não se caracterizando em apenas uma forma, sua manifestação varia conforme o indivíduo e suas tendências, disforia e/ou euforia porém independente da forma expressa o paciente bipolar pode ter sua vida social comprometida, se não tratada, visto a irregularidade no estado de humor; bem como pode fazer uso de substâncias psicoativas, o que prejudica a sua condição clínica. Objetivo central da pesquisa é de apresentar a correlação do transtorno bipolar com o uso de drogas, mediante uma revisão de literatura integrativa realizada entre os meses de março de 2022 a julho de 2022, através da busca de artigos científicos nos bancos de dados online PubMed, Scielo e Google Acadêmico, utilizando como critério de refinamento de pesquisa artigos de todas as línguas publicados entre os anos 2000 e 2022

Uso de drogas e o aumento das infecções sexualmente transmissíveis: uma revisão sistemática: Drug use and the increase in sexually transmitted infections: a systematic review

Populações de usuários de drogas têm sido associadas a epidemias de infecções ou Infecções Sexualmente Transmissíveis, especialmente a infecção pelo HIV (que está associada a drogas injetáveis, uso de equipamentos contaminados para drogas injetáveis e sexo inseguro). A droga mais associada às DSTs é a cocaína fumável de base livre (crack), devido ao aumento dos comportamentos sexuais de risco. Diante disso, o presente estudo teve como objetivo compreender o impacto do uso de drogas no aumento das infecções sexualmente transmissíveis. Para isso, adotou-se como metodologia a revisão sistemática de literatura, realizando buscas nas bases de dados Scielo, Pubmed e BVS/Medline a partir do uso de descritores DeCS/MeSH e aplicação de critérios de inclusão e exclusão. A partir da análise e interpretação dos dados, concluiu-se que que pessoas que fazem uso abusivo de drogas lícitas ou ilícitas, sejam elas mulheres, homens, adolescentes, jovens, adultos, idosos, em situação de rua ou não, tendem a desenvolver comportamentos vulneráveis que pode resultar em IST. Somado a isso, enquanto comportamento de risco, tem-se a preferência por não usar preservativo, seja em relações sexuais com pessoas monogâmicas como com dois ou mais parceiros. Nesses casos, tanto o uso exacerbado de drogas como a falta de informação sobre comportamento sexual demonstram-se insuficientes

Spatial analyses of immune cell infiltration in cancer : current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.http://www.thejournalofpathology.com/hj2024ImmunologySDG-03:Good heatlh and well-bein

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer

A Reuse Technique for Performance Testing of Software Product Lines

Testing that the applications of a software product line comply with their functional as well as with their nonfunctional requirements (for example performance) is important for achieving the desired product quality. Existing approaches for software product line testing only deal with testing an application against its functional requirements. In this paper we present a technique that supports the development of reusable performance test case scenarios in domain engineering and the reuse of these scenarios in application engineering. The technique is an extension of the ScenTED technique for system testing from our previous work. The technique focuses on load testing and performance profiling, two types of performance testing, and it has been validated in a case study at Siemens Medical Solutions HS IM. 1