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Endocrine-disrupting compounds (EDCs) are emerging pollutants that can potentially accumulate in aquatic ecosystems at significant levels, with the potential to impact the health of both animals and humans. Many scientists have correlated human exposure to high concentrations of EDCs with critical physiological impacts, including infertility, thyroid imbalance, early sexual development, endometriosis, diabetes, and obesity. Several substances, such as heavy metals, belong to this family, ranging from natural to synthetic compounds, including pesticides, pharmaceuticals, and plastic-derived compounds. Domestic sewage represents a significant source of EDCs in the surrounding aquatic ecosystems. To this day, most rural and urban domestic wastewater in the municipality of Maricá is directly discharged into local aquatic environments without any treatment. The present study aimed to assess the potential contamination of the riverine and lagoonal environment in the municipality of Maricá. Water and sediment samples were collected seasonally at 18 sites along the Maricá watershed and the main lagoon, into which most of the watershed’s contributors flow. Water physico-chemical parameters (pH, reduction–oxidation potential—Eh, dissolved oxygen levels, salinity, turbidity, temperature, and fecal coliforms) were analyzed to characterize the urban influence on the aquatic environment. Sediment samples were also analyzed for grain size, total organic carbon percentage, potential bioavailable fraction of trace metals (Cd, Pb, Cu, Cr, Hg, Ni, Zn), and metalloid As. Finally, the sediment toxicity was assessed using yeast estrogen screen (YES) assays. The results obtained already demonstrate the presence of estrogenic effects and raise concerns about water quality. The current study indicates that, despite the absence of agricultural and industrial activities in the city of Maricá, EDCs are already present and have the potential to impact the local ecosystem, posing potential risks to human health.

Abstract In oxygen (O2)‐controlled cell culture, an indispensable tool in biological research, it is presumed that the incubator setpoint equals the O2 tension experienced by cells (i.e., pericellular O2). However, it is discovered that physioxic (5% O2) and hypoxic (1% O2) setpoints regularly induce anoxic (0% O2) pericellular tensions in both adherent and suspension cell cultures. Electron transport chain inhibition ablates this effect, indicating that cellular O2 consumption is the driving factor. RNA‐seq analysis revealed that primary human hepatocytes cultured in physioxia experience ischemia‐reperfusion injury due to cellular O2 consumption. A reaction‐diffusion model is developed to predict pericellular O2 tension a priori, demonstrating that the effect of cellular O2 consumption has the greatest impact in smaller volume culture vessels. By controlling pericellular O2 tension in cell culture, it is found that hypoxia vs. anoxia induce distinct breast cancer transcriptomic and translational responses, including modulation of the hypoxia‐inducible factor (HIF) pathway and metabolic reprogramming. Collectively, these findings indicate that breast cancer cells respond non‐monotonically to low O2, suggesting that anoxic cell culture is not suitable for modeling hypoxia. Furthermore, it is shown that controlling atmospheric O2 tension in cell culture incubators is insufficient to regulate O2 in cell culture, thus introducing the concept of pericellular O2‐controlled cell culture.

Thin films based on tungsten oxide (WO3) were grown by nanosecond pulsed laser deposition on alumina printed-circuit boards to fabricate electrochemical sensors for nitrogen dioxide (NO2) detection. Samples exposed to thermal annealing (400 °C for 3 h) were also produced to compare the main properties and the sensor performance. Before gas testing, the morphology and structural properties were investigated. Scanning electron microscopy and atomic force microscopy showed the formation of granular films with a more compact structure before the thermal treatment. Features of the main WO3 phases were identified for both as-deposited and annealed samples by Raman spectroscopy, whereas X-ray diffraction evidenced the amorphous nature of the as-deposited samples and the formation of crystalline phases after thermal annealing. The as-deposited samples showed a higher W/O ratio, as displayed by energy-dispersive X-ray spectroscopy. An Arrhenius plot revealed a lower activation energy (0.11 eV) for the as-deposited thin films, which are the most electrically conductive samples, presenting a better gas response (30% higher than the response of the annealed ones) in the investigated NO2 concentration range of 5–20 ppm at the moderate device operating temperature of 75 °C. This behavior is explained by a larger quantity of oxygen vacancies, which enhances the sensing mechanism.

Red raspberries (Rubus idaeus L.) are often chosen by consumers for their flavour, taste, and health-promoting properties A relevant issue related to these fruits is their high perishability. The aim of this study was to investigate the effect of the ultraviolet C light-emitting diode (UVC-LED) treatment on soil-grown and pot-grown raspberries in extending their shelf-life, maintaining their high quality throughout the preservation period, and improving features related to their phenolic compound content. The UVC-LED treatment increased the total phenolic content (158 to 200 mg GAE/100 g) and ferric reducing antioxidant power (55.3 to 78.6 mmol Fe 2 +/kg) of the pot-grown raspberries when the UVC-LED treatment was followed by storage in a climate-controlled room (20°C). Total anthocyanin content did not increase significantly compared to the control samples. Contrary to expectations, no effect of reducing the microbial count after storage was observed due to the exposure of raspberries to the UVC-LED radiation. The positive outcomes derived from the analyses of bioactive compounds may be implemented in further studies on the same matrix to better manage the treatment and its conditions, such as the exposure time, the distance from the LED lamps, and the UVC-rays’ dose, in order to find the best combination in terms of efficacy and efficiency.

Abstract Tumor recognition by T cells is essential for antitumor immunity. A comprehensive characterization of T cell diversity may be key to understanding the success of immunomodulatory drugs and failure of PD-1 blockade in tumors such as multiple myeloma (MM). Here, we use single-cell RNA and T cell receptor sequencing to characterize bone marrow T cells from healthy adults (n = 4) and patients with precursor (n = 8) and full-blown MM (n = 10). Large T cell clones from patients with MM expressed multiple immune checkpoints, suggesting a potentially dysfunctional phenotype. Dual targeting of PD-1 + LAG3 or PD-1 + TIGIT partially restored their function in mice with MM. We identify phenotypic hallmarks of large intratumoral T cell clones, and demonstrate that the CD27− and CD27+ T cell ratio, measured by flow cytometry, may serve as a surrogate of clonal T cell expansions and an independent prognostic factor in 543 patients with MM treated with lenalidomide-based treatment combinations.

Abstract Breast cancer is the most diagnosed cancer among women. Approximately 15–20% of all breast cancers are highly invasive triple-negative breast cancer (TNBC) and lack estrogen, progesterone, and ERBB2 receptors. TNBC is challenging to treat due to its aggressive nature with far fewer targeted therapies than other breast cancer subtypes. Current treatments for patients with TNBC consist of cytotoxic chemotherapies, surgery, radiation, and in some instances PARP inhibitors and immunotherapy. To advance current therapeutics, we repurposed mebendazole (MBZ), an orally available FDA-approved anthelmintic that has shown preclinical efficacy for cancers. MBZ has low toxicity in humans and efficacy in multiple cancer models including breast cancer, glioblastoma multiforme, medulloblastoma, colon cancer, pancreatic and thyroid cancer. MBZ was well-tolerated in a phase I clinical trial of adults recently diagnosed with glioma. We determined that the half-maximal inhibitory concentration (IC50) of MBZ in four breast cancer cell lines is well within the range reported for other types of cancer. MBZ reduced TNBC cell proliferation, induced apoptosis, and caused G2/M cell cycle arrest. MBZ reduced the size of primary tumors and prevented lung and liver metastases. In addition, we uncovered a novel mechanism of action for MBZ. We found that MBZ reduces integrin β4 (ITGβ4) expression and cancer stem cell properties. ITGβ4 has previously been implicated in promoting “cancer stemness,” which may contribute to the efficacy of MBZ. Collectively, our results contribute to a growing body of evidence suggesting that MBZ should be considered as a therapeutic to slow tumor progression and prevent metastasis.

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

Spontaneous intracranial hypotension (SIH) is a debilitating condition caused by spinal CSF leaks or CSF-venous fistulas (CVFs). Localizing the causative CSF leak or CVF is critical for definitive treatment but can be difficult using conventional myelographic techniques because these lesions are often low contrast compared to background, diminutive, and in some cases may be mistaken for calcified structures. Dual energy CT (DECT) can increase the conspicuity of iodinated contrast compared to background and can provide the ability to distinguish materials based on differing anatomic properties, making it well suited to address the shortcomings of conventional myelography in SIH. The purpose of this report is to illustrate the potential benefits of using DECT as an adjunct to traditional myelographic techniques in order to increase the conspicuity of these often-subtle CVFs and CSF leaks. This retrospective case series included 4 adult patients with SIH who demonstrated findings equivocal for either CVF or CSF leak using our institution's standard initial CT myelogram and in whom subsequent evaluation with DECT ultimately helped to identify the CVF or CSF leak. DECT demonstrated utility by increasing the conspicuity of two subtle CVFs compared to background and also helped to differentiate between calcified osteophytes and extradural contrast in 2 CSF leaks, confirming their presence and identifying the causative pathology. Our observations demonstrate the benefit of DECT as a problem-solving tool in the accurate diagnosis and localization of CVFs and CSF leaks.

Hypoxia, or a state of low tissue oxygenation, has been characterized as an important feature of solid tumors that is related to aggressive phenotypes. The cellular response to hypoxia is controlled by Hypoxia-inducible factors (HIFs), a family of transcription factors. HIFs promote the transcription of gene products that play a role in tumor progression including proliferation, angiogenesis, metastasis, and drug resistance. HIF-1 and HIF-2 are well known and widely described. Although these proteins share a high degree of homology, HIF-1 and HIF-2 have non-redundant roles in cancer. In this review, we summarize the similarities and differences between HIF-1α and HIF-2α in their structure, expression, and DNA binding. We also discuss the canonical and non-canonical regulation of HIF-1α and HIF-2α under hypoxic and normal conditions. Finally, we outline recent strategies aimed at targeting HIF-1α and/or HIF-2α. [ABSTRACT FROM AUTHOR]

Effectively responding to drug-resistant tuberculosis (TB) requires accurate and timely information on resistance levels and trends. In contexts where use of drug susceptibility testing has not been universal (i.e. not all patients are offered testing), surveillance for rifampicin-resistance—one of the core drugs in the TB treatment regimen—has relied on resource-intensive and infrequent nationally-representative prevalence surveys. The expanded availability of rapid diagnostic tests (RDTs) over the past decade has increased testing coverage in many settings. However, RDT data collected in the course of routine (but not universal) use may provide biased estimates of resistance if the subset of patients receiving RDTs is not representative of the overall cohort. Here, we developed a method that attempts to correct for non-random use of RDT testing in the context of routine TB diagnosis to recover unbiased estimates of resistance among new and previously treated TB cases. Specifically, we employed statistical corrections to model rifampicin resistance among TB notifications with observed Xpert MTB/RIF (a WHO-recommended RDT) results using a hierarchical generalized additive regression model, and then used model output to impute results for untested individuals. We applied this model to 2017–2023 case-level data on over 800,000 patients from Brazil. Modeled estimates of the prevalence of rifampicin resistance were substantially higher than naïve estimates, with estimated prevalence ranging between 28–44% higher for new cases and 2–17% higher for previously treated cases. Our estimates of RR-TB incidence were estimated with narrower uncertainty intervals relative to WHO estimates for the same time period, and were robust to alternative model specifications. Our approach provides a generalizable method to leverage routine RDT data to derive timely estimates of RR-TB prevalence among notified TB cases in settings where testing for TB drug resistance is not universal. Author summary: While data on drug-resistant tuberculosis (DR-TB) may be routinely collected by National TB Control Programs using rapid diagnostic tests (RDTs), these data streams may not be fully utilized for DR-TB surveillance where low testing coverage may bias inferences due to systematic differences in RDT access. Here, we develop a method to correct for potential biases in routine RDT data to estimate trends in the prevalence of TB drug resistance among notified TB cases. Applying this approach to recent national case-level data from Brazil, we find that modeled estimates were higher than naïve estimates, and with narrower uncertainty intervals compared to estimates produced by the World Health Organization. We highlight the value of this approach to settings where testing coverage is low or variable, as well as settings where coverage may surpass existing coverage thresholds, but that could nonetheless benefit from additional statistical correction. [ABSTRACT FROM AUTHOR]

Endocrine-disrupting compounds (EDCs) are emerging pollutants that can potentially accumulate in aquatic ecosystems at significant levels, with the potential to impact the health of both animals and humans. Many scientists have correlated human exposure to high concentrations of EDCs with critical physiological impacts, including infertility, thyroid imbalance, early sexual development, endometriosis, diabetes, and obesity. Several substances, such as heavy metals, belong to this family, ranging from natural to synthetic compounds, including pesticides, pharmaceuticals, and plastic-derived compounds. Domestic sewage represents a significant source of EDCs in the surrounding aquatic ecosystems. To this day, most rural and urban domestic wastewater in the municipality of Maricá is directly discharged into local aquatic environments without any treatment. The present study aimed to assess the potential contamination of the riverine and lagoonal environment in the municipality of Maricá. Water and sediment samples were collected seasonally at 18 sites along the Maricá watershed and the main lagoon, into which most of the watershed's contributors flow. Water physico-chemical parameters (pH, reduction–oxidation potential—Eh, dissolved oxygen levels, salinity, turbidity, temperature, and fecal coliforms) were analyzed to characterize the urban influence on the aquatic environment. Sediment samples were also analyzed for grain size, total organic carbon percentage, potential bioavailable fraction of trace metals (Cd, Pb, Cu, Cr, Hg, Ni, Zn), and metalloid As. Finally, the sediment toxicity was assessed using yeast estrogen screen (YES) assays. The results obtained already demonstrate the presence of estrogenic effects and raise concerns about water quality. The current study indicates that, despite the absence of agricultural and industrial activities in the city of Maricá, EDCs are already present and have the potential to impact the local ecosystem, posing potential risks to human health. [ABSTRACT FROM AUTHOR]

Thin films based on tungsten oxide (WO3) were grown by nanosecond pulsed laser deposition on alumina printed-circuit boards to fabricate electrochemical sensors for nitrogen dioxide (NO2) detection. Samples exposed to thermal annealing (400 °C for 3 h) were also produced to compare the main properties and the sensor performance. Before gas testing, the morphology and structural properties were investigated. Scanning electron microscopy and atomic force microscopy showed the formation of granular films with a more compact structure before the thermal treatment. Features of the main WO3 phases were identified for both as-deposited and annealed samples by Raman spectroscopy, whereas X-ray diffraction evidenced the amorphous nature of the as-deposited samples and the formation of crystalline phases after thermal annealing. The as-deposited samples showed a higher W/O ratio, as displayed by energy-dispersive X-ray spectroscopy. An Arrhenius plot revealed a lower activation energy (0.11 eV) for the as-deposited thin films, which are the most electrically conductive samples, presenting a better gas response (30% higher than the response of the annealed ones) in the investigated NO2 concentration range of 5–20 ppm at the moderate device operating temperature of 75 °C. This behavior is explained by a larger quantity of oxygen vacancies, which enhances the sensing mechanism. [ABSTRACT FROM AUTHOR]

Abstract Dengue is recognized as a health problem that causes significant socioeconomic impacts throughout the world, affecting millions of people each year. A commonly used method for monitoring the dengue vector is to count the eggs that Aedes aegypti mosquitoes have laid in spatially distributed ovitraps. Given this approach, the present study uses a database collected from 397 ovitraps allocated across the city of Natal, RN—Brazil. The Egg Density Index for each neighborhood was computed weekly, over four complete years (from 2016 to 2019), and simultaneously analyzed with the dengue case incidence. Our results illustrate that the incidence of dengue is related to the socioeconomic level of the neighborhoods in the city of Natal. A deep learning algorithm was used to predict future dengue case incidence, either based on the previous weeks of dengue incidence or the number of eggs present in the ovitraps. The analysis reveals that ovitrap data allows earlier prediction (four to six weeks) compared to dengue incidence itself (one week). Therefore, the results validate that the quantification of Aedes aegypti eggs can be valuable for the early planning of public health interventions.

Abstract Introduction Syphilis is a sexually transmitted disease (STD) caused by Treponema pallidum subspecies pallidum. In 2016, it was declared an epidemic in Brazil due to its high morbidity and mortality rates, mainly in cases of maternal syphilis (MS) and congenital syphilis (CS) with unfavorable outcomes. This paper aimed to mathematically describe the relationship between MS and CS cases reported in Brazil over the interval from 2010 to 2020, considering the likelihood of diagnosis and effective and timely maternal treatment during prenatal care, thus supporting the decision-making and coordination of syphilis response efforts. Methods The model used in this paper was based on stochastic Petri net (SPN) theory. Three different regressions, including linear, polynomial, and logistic regression, were used to obtain the weights of an SPN model. To validate the model, we ran 100 independent simulations for each probability of an untreated MS case leading to CS case (PUMLC) and performed a statistical t-test to reinforce the results reported herein. Results According to our analysis, the model for predicting congenital syphilis cases consistently achieved an average accuracy of 93% or more for all tested probabilities of an untreated MS case leading to CS case. Conclusions The SPN approach proved to be suitable for explaining the Notifiable Diseases Information System (SINAN) dataset using the range of 75–95% for the probability of an untreated MS case leading to a CS case (PUMLC). In addition, the model’s predictive power can help plan actions to fight against the disease.

Introduction: Oxford Nanopore Technologies (ONT) is a third generation sequencing approach that allows the analysis of individual, full-length nucleic acids. ONT records the alterations of an ionic current flowing across a nano-scaled pore while a DNA or RNA strand is threading through the pore. Basecalling methods are then leveraged to translate the recorded signal back to the nucleic acid sequence. However, basecall generally introduces errors that hinder the process of barcode demultiplexing, a pivotal task in single-cell RNA sequencing that allows for separating the sequenced transcripts on the basis of their cell of origin.Methods: To solve this issue, we present a novel framework, called UNPLEX, designed to tackle the barcode demultiplexing problem by operating directly on the recorded signals. UNPLEX combines two unsupervised machine learning methods: autoencoders and self-organizing maps (SOM). The autoencoders extract compact, latent representations of the recorded signals that are then clustered by the SOM.Results and Discussion: Our results, obtained on two datasets composed of in silico generated ONT-like signals, show that UNPLEX represents a promising starting point for the development of effective tools to cluster the signals corresponding to the same cell.

Viperin, an IFN-regulated gene product, is known to inhibit fatty acid β-oxidation in the mitochondria, which enhances glycolysis and lipogenesis during viral infections. Yet, its role in altering the phenotype of cancer cells has not been established. In this issue of the JCI, Choi, Kim, and co-authors report on a role of viperin in regulating metabolic alterations in cancer cells. The authors showed a correlation between clinical outcomes and viperin expression levels in multiple cancer tissues and proposed that viperin expression was upregulated in the tumor microenvironment via the JAK/STAT and PI3K/AKT/mTOR/HIF-1α pathways. Functionally, viperin increased lipogenesis and glycolysis in cancer cells by inhibiting fatty acid β-oxidation. Viperin expression also enhanced cancer stem cell properties, ultimately promoting tumor initiation in murine models. This study proposes a protumorigenic role for viperin and identifies HIF-1α as a transcription factor that increases viperin expression under serum starvation and hypoxia.

Electronic Health Records (EHR) are critical tools for advancing digital health worldwide. In Brazil, EHR development must follow specific standards, laws, and guidelines that contribute to implementing beneficial resources for population health monitoring. This paper presents an audit of the main approaches used for EHR development in Brazil, thus highlighting prospects, challenges, and existing gaps in the field. We applied a systematic review protocol to search for articles published from 2011 to 2021 in seven databases (Science Direct, Web of Science, PubMed, Springer, IEEE Xplore, ACM Digital Library, and SciELO). Subsequently, we analyzed 14 articles that met the inclusion and quality criteria and answered our research questions. According to this analysis, 78.58% (11) of the articles state that interoperability between systems is essential for improving patient care. Moreover, many resources are being designed and deployed to achieve this communication between EHRs and other healthcare systems in the Brazilian landscape. Besides interoperability, the articles report other considerable elements: (i) the need for increased security with the deployment of permission resources for viewing patient data, (ii) the absence of accurate data for testing EHRs, and (iii) the relevance of defining a methodology for EHR development. Our review provides an overview of EHR development in Brazil and discusses current gaps, innovative approaches, and technological solutions that could potentially address the related challenges. Lastly, our study also addresses primary elements that could contribute to relevant components of EHR development in the context of Brazil's public health system.Systematic review registration: PROSPERO, identifier CRD42021233219, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233219.

Chagas es una enfermedad endemoepidémica de transmisión vec-torial en la Provincia de Rio Negro causada por Trypanosoma cruzi, transmitido por insectos vectores denominados triatominos (vinchu-cas). El programa de control de Chagas de la provincia de Rio Negro certifico, a través de indicadores serológicos y entomológicos, la in-terrupción de la transmisión vectorial en todo el territorio provin-cial. Sin embargo, en los últimos años se han generado condiciones que pueden posibilitar la reemergencia de la enfermedad, tal como la eventual domiciliación de vinchucas silvestres, tal el caso de Triatoma patagónica. El objetivo fue evaluar la situación epidemiológica del vec-tor mediante estudios de infestación domiciliaria y peri domiciliaria por triatominos y efectuar análisis de resistencia al principal insectici-da que fue aplicado durante muchos años en control. Como resultado se evaluaron 143 viviendas y se colocaron 66 trampas de luz. En el intradomicilio todas las viviendas resultaron negativas, resultando 3 positivas en el peri-domicilio (2.1%) con capturas de T- infestans y T. patagonica. Con las trampas de luz no se capturaron triatominos. Los insectos capturados fueron T. infestans y T. patagonica los que resulta-ron todos negativos a T. cruzi. Los estudios de resistencia a insecticidas mostraron que las colonias siguen siendo susceptibles a deltametrina.

Abstract Breast cancer is the most commonly diagnosed cancer in women worldwide. Approximately one-tenth of all patients with advanced breast cancer develop brain metastases resulting in an overall survival rate of fewer than 2 years. The challenges lie in developing new approaches to treat, monitor, and prevent breast cancer brain metastasis (BCBM). This review will provide an overview of BCBM from the integrated perspective of clinicians, researchers, and patient advocates. We will summarize the current management of BCBM, including diagnosis, treatment, and monitoring. We will highlight ongoing translational research for BCBM, including clinical trials and improved detection methods that can become the mainstay for BCBM treatment if they demonstrate efficacy. We will discuss preclinical BCBM research that focuses on the intrinsic properties of breast cancer cells and the influence of the brain microenvironment. Finally, we will spotlight emerging studies and future research needs to improve survival outcomes and preserve the quality of life for patients with BCBM.