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Depression and anxiety screening process in urgent situation division people using recurrent belly ache: An proof synthesis for any clinical apply guide.
01). read more Multiple regression analysis showed that pro-inflammatory diet consumption increased the risk of both early-onset-hypertensive disorders of pregnancy (adjusted odds ratio 1.53, 95% confidence interval 1.06-2.20) and hypertensive disorders of pregnancy without small for gestational age birth (adjusted odds ratio 1.26, 95% confidence interval 1.03-1.54) among multiparous women.

Consumption of diet with a high dietary inflammatory index score before pregnancy increases maternal inflammation and oxidative stress during pregnancy. Preconception lifestyle influences the risk of hypertensive disorders of pregnancy, especially among multiparous women.
Consumption of diet with a high dietary inflammatory index score before pregnancy increases maternal inflammation and oxidative stress during pregnancy. Preconception lifestyle influences the risk of hypertensive disorders of pregnancy, especially among multiparous women.
This study aimed to evaluate womens' perspectives about current and novel preeclampsia testing methods at an urban tertiary medical center.

This was an observational survey study conducted between October 1, 2020 and December 31, 2020. Subjects were eligible if they were≥18years of age and had a diagnosis of gestational hypertension, preeclampsia, or superimposed preeclampsia at the time of delivery. Informed consent was obtained, and the 26-question survey was administered after delivery. A detailed medical record review was completed for respondents (patients) and their neonates.

A total of 100 women were included in the study. The majority of participants were Black (78%) and/or on Medicaid (51%). Most respondents agreed that they fully trust their doctor and medical team (96%) and that the newest medical tests, treatments, and technologies should always be used (91%). Most women (80%) at least somewhat agreed they have enough knowledge about preeclampsia and its complications. Over 90% of women agreed a test to predict complications of preeclampsia would be useful to them. Most women reported a rule out test would be useful to them because it would help them worry less (68%), reduce hospitalizations (32%) and reduce interventions (17%).

There was majority support for novel methods such as biomarker testing among this cohort. Most patients reported the test would decrease worry associated with preeclampsia development and complications.
There was majority support for novel methods such as biomarker testing among this cohort. Most patients reported the test would decrease worry associated with preeclampsia development and complications.Over the past two decades, diabetes mellitus (DM) has been receiving increasing attention among autoimmune diseases. The prevalence of type 1 and type 2 diabetes has increased rapidly and has become one of the leading causes of death worldwide. Therefore, a better understanding of the genetic and environmental risk factors that trigger the onset of DM would help develop more efficient therapeutics and preventive measures. The role and mechanism of respiratory viruses in inducing autoimmunity have been frequently reported. On the other hand, the association of DM with respiratory infections might result in severe complications or even death. Since influenza is the most common respiratory infection, DM patients experience disease severity and increased hospitalization during influenza season. Vaccinating diabetic patients against influenza would significantly reduce hospitalization due to disease severity. However, recent studies also report the role of viral vaccines in inducing autoimmunity, specifically diabetes. This review reports causes of diabetes, including genetic and viral factors, with a special focus on respiratory viruses. We further brief the burden of influenza-associated complications and the effectiveness of the influenza vaccine in DM patients.
Phlebotomine sand flies are known as vectors of various pathogens such as Leishmania sp parasite and Toscana virus (TOSV). Leishmaniasis is endemic in Morocco, and TOSV is increasingly reported. Our objective is to analyze the specific composition of the natural population of sand flies in endemic and non endemic area of leishmaniasis in Morocco, thus evaluated their infection by Toscana virus.

Sand flies were collected by CDC miniature light traps from seven different localities with an altitude range from 399m to 1496m. Synanthropic index was calculated for each sand fly species. The collected female sand flies were grouped in 73 pools, with a maximum of 50 specimens per pool, and submitted to real time PCR for TOSV detection.

8 sand fly species were identified morphologically 5 of the Phlebotomus genus and 3 of the Sergentomyia genus. Phlebotomus sergenti was the most abundant species comprising of 43,12% of identified sand flies, followed by P. papatasi (18,89%) and P. longicuspis (13,43%). Estimated synanthropic indices for these species were between +1.1 and +12.6 suggesting a high preference to anthropogenic environments. A total of 3558 sand fly females were grouped in 73 pools (up to 50 sand flies per pool) for TOSV detection. TOSV was detected in one pool (out of 6 tested) from Lalla Laaziza locality (Chichaoua Province) where P. sergenti was the most abundant sand fly species.

We reported the TOSV for the first time in a central Morocco, where cutaneous leishmaniasis by L. tropica is endemic. This result has epidemiological importance for both researchers and health authorities to monitor circulation of TOSV and implement a surveillance plan of sand fly-borne phleboviruses in Morocco.
We reported the TOSV for the first time in a central Morocco, where cutaneous leishmaniasis by L. tropica is endemic. This result has epidemiological importance for both researchers and health authorities to monitor circulation of TOSV and implement a surveillance plan of sand fly-borne phleboviruses in Morocco.CGA47-66 (Chromofungin, CHR), is a peptide derived from the N-terminus of chromogranin A (CgA), has been proven to inhibit the lipopolysaccharide (LPS)-induced brain injury. However, the underlying mechanism is still unknown. We found that CGA47-66 exerted a protective effect on cognitive impairment by inhibiting the destruction of the blood-brain barrier (BBB) in the LPS-induced sepsis mice model. In addition, the hCMEC/D3 cell line was used to establish an in vitro BBB model. Under LPS stimulation, CGA47-66 could significantly alleviate the hyperpermeability of the BBB, the destruction of tight junction proteins, and the rearrangement of F-actin. To investigate the underlying mechanism, we used LY294002, a PI3K inhibitor, which partially reduced the protective effect of CGA47-66 on the integrity of BBB. Indicating that the PI3K/AKT pathway plays a vital role in the brain-protective function of CGA47-66, which might be a potential therapeutic target for septic brain injury.Accurate classification of the children's epilepsy syndrome is vital to the diagnosis and treatment of epilepsy. But existing literature mainly focuses on seizure detection and few attention has been paid to the children's epilepsy syndrome classification. In this paper, we present a study on the classification of two most common epilepsy syndromes the benign childhood epilepsy with centro-temporal spikes (BECT) and the infantile spasms (also known as the WEST syndrome), recorded from the Children's Hospital, Zhejiang University School of Medicine (CHZU). A novel feature fusion model based on the deep transfer learning and the conventional time-frequency representation of the scalp electroencephalogram (EEG) is developed for the epilepsy syndrome characterization. A fully connected network is constructed for the feature learning and syndrome classification. Experiments on the CHZU database show that the proposed algorithm can offer an average of 92.35% classification accuracy on the BECT and WEST syndromes and their corresponding normal cases.Building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an artificial system to achieve cognitive development will be an excellent reference for brain and cognitive science. This paper describes an approach to develop a cognitive architecture by integrating elemental cognitive modules to enable the training of the modules as a whole. This approach is based on two ideas (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2) a probabilistic generative model (PGM)-based cognitive architecture to develop a cognitive system for developmental robots by integrating PGMs. The proposed development framework is called a whole brain PGM (WB-PGM), which differs fundamentally from existing cognitive architectures in that it can learn continuously through a system based on sensory-motor information. In this paper, we describe the rationale for WB-PGM, the current status of PGM-based elemental cognitive modules, their relationship with the human brain, the approach to the integration of the cognitive modules, and future challenges. Our findings can serve as a reference for brain studies. As PGMs describe explicit informational relationships between variables, WB-PGM provides interpretable guidance from computational sciences to brain science. By providing such information, researchers in neuroscience can provide feedback to researchers in AI and robotics on what the current models lack with reference to the brain. Further, it can facilitate collaboration among researchers in neuro-cognitive sciences as well as AI and robotics.Inspired by the human vision system and learning, we propose a novel cognitive architecture that understands the content of raw videos in terms of objects without using labels. The architecture achieves four objectives (1) Decomposing raw frames in objects by exploiting foveal vision and memory. (2) Describing the world by projecting objects on an internal canvas. (3) Extracting relevant objects from the canvas by analyzing the causal relation between objects and rewards. (4) Exploiting the information of relevant objects to facilitate the reinforcement learning (RL) process. In order to speed up learning, and better identify objects that produce rewards, the architecture implements learning by causality from the perspective of Wiener and Granger using object trajectories stored in working memory and the time series of external rewards. A novel non-parametric estimator of directed information using Renyi's entropy is designed and tested. Experiments on three environments show that our architecture extracts most of relevant objects. It can be thought of as 'understanding' the world in an object-oriented way. As a consequence, our architecture outperforms state-of-the-art deep reinforcement learning in terms of training speed and transfer learning.
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS), which usually affects young adults between 20 and 40 years old. In chronic neurodegenerative diseases such as multiple sclerosis, CNS cells take on several adaptations during neuroinflammation. The main cells involved in this inflammatory process are the glial cells, in which the astrocytes stand out. These cells play a complex role, and several studies report that reactive astrocytes lose their supporting role and gain toxic function in the progression of these diseases.

The beneficial and injurious effects of this group of cells in MS are addressed in this work, as well as some drugs that are already used in the treatment of patients with multiple sclerosis, aiming to regulate astrocytic activities.

The knowledge about the functions of astrocytes is essential for the expansion of scientific research in this area, since these cells are so important and involved in different mechanisms of action, especially in neurodegenerative and autoimmune diseases.
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