Novel molecularly imprinted photonic sensors applied to IBD detection

Sara Resende gratefully acknowledges the financial support from Fundação para a Ciência e a Tecnologia (FCT) through PhD grant SFRH/BD/139634/2018info:eu-repo/semantics/publishedVersio

Peripheral brain-derived neurotrophic factor (BDNF) as a biomarker in bipolar disorder: a meta-analysis of 52 studies

Background: The neurotrophic hypothesis postulates that mood disorders such as bipolar disorder (BD) are associated with a lower expression of brain-derived neurotrophic factor (BDNF). However, its role in peripheral blood as a biomarker of disease activity and of stage for BD, transcending pathophysiology, is still disputed. In the last few years an increasing number of clinical studies assessing BDNF in serum and plasma have been published. Therefore, it is now possible to analyse the association between BDNF levels and the severity of affective symptoms in BD as well as the effects of acute drug treatment of mood episodes on BDNF levels. Methods: We conducted a systematic review and meta-analysis of all studies on serum and plasma BDNF levels in bipolar disorder. Results: Through a series of meta-analyses including a total of 52 studies with 6,481 participants, we show that, compared to healthy controls, peripheral BDNF levels are reduced to the same extent in manic (Hedges' g = -0.57, P = 0.010) and depressive (Hedges' g = -0.93, P = 0.001) episodes, while BDNF levels are not significantly altered in euthymia. In meta-regression analyses, BDNF levels additionally negatively correlate with the severity of both manic and depressive symptoms. We found no evidence for a significant impact of illness duration on BDNF levels. In addition, in plasma, but not serum, peripheral BDNF levels increase after the successful treatment of an acute mania episode, but not of a depressive one. Conclusions: In summary, our data suggest that peripheral BDNF levels, more clearly in plasma than in serum, is a potential biomarker of disease activity in BD, but not a biomarker of stage. We suggest that peripheral BDNF may, in future, be used as a part of a blood protein composite measure to assess disease activity in BD.BSF is supported by a postdoctoral scholarship and by a research grant MCTI/CNPQ/Universal 14/2014461833/2014-0, both from CNPq, Brazil. CAK is a recipient of a postdoctoral fellowship from CAPES, Brazil. JCS is supported by NIMH grant R01 085667, the Dunn Foundation and the JQ are supported by research fellowship awards from CNPq (Brazil, level IA). AFC is the recipient of a research fellowship from CNPq (Brazil, level II). MB is supported by a NHMRC Senior Principal Research Fellowship 1059660. None of these agencies had any role in the design and conduct of the study, or decision to submit the manuscript for publication. We thank all authors of the included papers, particularly Drs. Natalie L. Rasgon, Deniz Ceylan, Camilla Langan, Pedro Magalhaes, Antonio L. Teixeira, Yuan-Hwa Chou, Iria Grande, Chenyu Ye, Izabela Barbosa, Menan Rabie, Ru-Band Lu, Ana Gonzales-Pinto, Reiji Yoshimura, Flavio Kapczinski, and Christoph Laske, who kindly provided unpublished data for the paper

Development of technologies to support the diagnosis of infectious diseases and cancer to support the primary health care

54/2017). Publisher Copyright: © 2022, The Author(s).Purpose: Primary Health Care (PHC) is the coordinator of health care in Brazil and needs to be strengthened in the diagnostic field to increase health care quality. Aiming to improve the diagnostic tools currently available in PHC, this work describes the process of development and validation of two point-of-care biomedical devices for screening patients with syphilis or different kinds of cancer. Methods: The development of these devices followed nine stages of action based on the requirements established by the Ministry of Health. During development, both systems followed the stages of circuit planning, software simulation to verify the components used, cost assessment for the acquisition of features, simulation in contact matrix, development of the embedded system, and planning of the printed circuit board and storage box. Results: Both devices underwent preliminary functionality tests to assess their quality. The performance tests applied on the device to diagnose syphilis performed 8,733,194 requests, with a flow of 2426 requests/second, reaching the desired parameters of robustness, integrity, durability, and stability. In addition, functioning tests on the cancer-screening device indicated the ability to detect standard fluorescence in a minimal (150 uL) sample volume. Conclusions: Together, the methodology used for developing the devices resulted in promising equipment to improve the diagnosis and meet the requirements for executing technologies for testing and triaging patients in PHC.publishersversionpublishe

Expanding the phenotypic spectrum of CLCN2-related leucoencephalopathy and ataxia

Mutations in CLCN2 are a rare cause of autosomal recessive leucoencephalopathy with ataxia and specific imaging abnormalities. Very few cases have been reported to date. Here, we describe the clinical and imaging phenotype of 12 additional CLCN2 patients and expand the known phenotypic spectrum of this disorder. Informed consent was obtained for all patients. Patients underwent either whole-exome sequencing or focused/panel-based sequencing to identify variants. Twelve patients with biallelic CLCN2 variants are described. This includes three novel likely pathogenic missense variants. All patients demonstrated typical MRI changes, including hyperintensity on T2-weighted images in the posterior limbs of the internal capsules, midbrain cerebral peduncles, middle cerebellar peduncles and cerebral white matter. Clinical features included a variable combination of ataxia, headache, spasticity, seizures and other symptoms with a broad range of age of onset. This report is now the largest case series of patients with CLCN2-related leucoencephalopathy and reinforces the finding that, although the imaging appearance is uniform, the phenotypic expression of this disorder is highly heterogeneous. Our findings expand the phenotypic spectrum of CLCN2-related leucoencephalopathy by adding prominent seizures, severe spastic paraplegia and developmental delay

Computational methods applied to syphilis: where are we, and where are we going?

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

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