Notes

Uremic harmful toxins quantities through the gut microbiota seem to be never to be changed through exercising within hemodialysis individuals.
There is a strong policy impetus for the One Health cross-sectoral approach to address the complex challenge of zoonotic diseases, particularly in low/lower middle income countries (LMICs). Yet the implementation of this approach in LMIC contexts such as India has proven challenging, due partly to the relatively limited practical guidance and understanding on how to foster and sustain cross-sector collaborations. This study addresses this gap by exploring the facilitators of and barriers to successful convergence between the human, animal and environmental health sectors in India.

A mixed methods study was conducted using a detailed content review of national policy documents and in-depth semi-structured interview data on zoonotic disease management in India. In total, 29 policy documents were reviewed and 15 key informant interviews were undertaken with national and state level policymakers, disease managers and experts operating within the human-animal-environment interface of zoonotic disease control.
ipants as the way forward.

Our findings point to the importance of strengthening existing national policy frameworks as a first step for leveraging cross-sectoral capacity for improved disease surveillance and interventions. This requires the contextual adaptation of the One Health approach in a manner that is sensitive to the underlying socio-political, institutional and cultural context that determines and shapes outcomes of cross-sector collaborative arrangements.
Our findings point to the importance of strengthening existing national policy frameworks as a first step for leveraging cross-sectoral capacity for improved disease surveillance and interventions. This requires the contextual adaptation of the One Health approach in a manner that is sensitive to the underlying socio-political, institutional and cultural context that determines and shapes outcomes of cross-sector collaborative arrangements.
Concerning viral pneumonia, few large-scale comparative studies have been published describing non-HIV immunocompromised and immunocompetent patients, but the epidemiological characteristics of different viruses or underlying diseases in immunocompromised hosts are lacking.

We retrospectively recruited patients hospitalised with viral pneumonia from six academic hospitals in China between August 2016 and December 2019. We measured the prevalence of comorbidities, coinfections, nosocomial infections, and in-hospital mortalities.

Of the 806 patients, 370 were immunocompromised and 436 were immunocompetent. The disease severity and in-hospital mortality of immunocompromised patients were higher than those of immunocompetent patients. During the influenza season, an increased number of cases of influenza virus (IFV) infection were found in the immunocompromised group, followed by cases of cytomegalovirus (CMV) and respiratory syncytial virus (RSV) infection. During the non-influenza season, CMV was the mainThe type of viral infection varied with seasons.
Immunocompromised patients have a high frequency of coinfections, and a higher mortality rate was observed among those infected with CMV and two-or-more viruses. In addition, patients with IFV and non-IFV infection in immunocompromised patients had similar same disease severity and prognosis. The type of viral infection varied with seasons.
The COVID-19 outbreak holds public health concerns. The stay-at-home increases sedentary behavior, with unintended adverse outcomes. Since organized recreation and sports facilities were closed, we aimed to study how the crisis of closure affected exercise habits and weight gain among the trainee population in Israel. We examined differences in weight gain among individuals with different PA activities and assessed their ability to adapt to digital media as an alternative training structure.

A cross-sectional survey consisted of a multiple-choice questionnaire obtained using a web-based survey application. Trainees (1202) who exercised steadily anonymously answered the questionnaire sent by their coaches regarding their activity and weight gain during lockdown times.

Results confirmed that 70% of Israelis trained less than their usual routine, 60% used digital media for training, 55% gained weight. Half of the respondents gained more than 2 kg, with an average increase of 1.2 kg. However, those who exhibited a higher physical activity level gained less weight. Using digital media for training was associated with higher physical activity levels. The aged population was less likely to use digital media.

Since increased sedentary behavior could increase the risk for potential worsening of health conditions, health agencies should look for strategies, including digital remote media training to promote physical activity and subsequently, preventing the increased burden of future comorbidities worsening by a sedentary lifestyle. Approval by the Helsinki ethics committee of Sheba Medical Center (6504-19-SMC).
Since increased sedentary behavior could increase the risk for potential worsening of health conditions, health agencies should look for strategies, including digital remote media training to promote physical activity and subsequently, preventing the increased burden of future comorbidities worsening by a sedentary lifestyle. Approval by the Helsinki ethics committee of Sheba Medical Center (6504-19-SMC).
Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis worldwide. An association with neuralgic amyotrophy and Guillain-Barré syndrome (GBS) was previously described. Concerning GBS, studies from other countries found an acute HEV infection in 5-11% of cases. However, HEV prevalence shows considerable regional variations. Therefore, we retrospectively analyzed the frequency of HEV infections in association with GBS in a monocentric cohort in Southwestern Germany.

Overall, 163 patients with GBS treated in our clinic between 2008 and 2018 of whom serum and/or cerebrospinal fluid (CSF) samples were available, were identified. Serum samples were analyzed for anti-HEV immunoglobulin (Ig)M and IgG antibodies by ELISA. Additionally, both serum and cerebrospinal fluid (CSF) samples were tested for HEV RNA by PCR if IgM was positive or patients presented within the first 7 days from GBS symptom onset. A group of 167 healthy volunteers and 96 healthy blood donors served as controls.

An acute HEV infection was found in two GBS patients (1.2%) with anti-HEV IgM and IgG antibodies. HEV PCR in serum and CSF was negative in these two patients as well as in all other tested cases. Seroprevalences indicated that acute infection did not differ significantly from controls (0.8%). Anti-HEV IgG seroprevalence indicating previous infection was unexpectedly high (41%) and revealed an age-dependent increase to more than 50% in patients older than 60 years.

In this study, serological evidence of an acute HEV infection in patients with GBS was rare and not different from controls. Comparing our data with previous studies, incidence rates show considerable regional variations.
In this study, serological evidence of an acute HEV infection in patients with GBS was rare and not different from controls. Comparing our data with previous studies, incidence rates show considerable regional variations.
This study aimed to assess the utility of deep learning analysis using pretreatment FDG-PET images to predict local treatment outcome in oropharyngeal squamous cell carcinoma (OPSCC) patients.

One hundred fifty-four OPSCC patients who received pretreatment FDG-PET were included and divided into training (n = 102) and test (n = 52) sets. The diagnosis of local failure and local progression-free survival (PFS) rates were obtained from patient medical records. In deep learning analyses, axial and coronal images were assessed by three different architectures (AlexNet, GoogLeNET, and ResNet). In the training set, FDG-PET images were analyzed after the data augmentation process for the diagnostic model creation. A multivariate clinical model was also created using a binomial logistic regression model from a patient's clinical characteristics. The test data set was subsequently analyzed for confirmation of diagnostic accuracy. Assessment of local PFS rates was also performed.

Training sessions were successfully performed with an accuracy of 74-89%. Selleckchem 4-PBA ROC curve analyses revealed an AUC of 0.61-0.85 by the deep learning model in the test set, whereas it was 0.62 by T-stage, 0.59 by clinical stage, and 0.74 by a multivariate clinical model. The highest AUC (0.85) was obtained with deep learning analysis of ResNet architecture. Cox proportional hazards regression analysis revealed deep learning-based classification by a multivariate clinical model (P < .05), and ResNet (P < .001) was a significant predictor of the treatment outcome. In the Kaplan-Meier analysis, the deep learning-based classification divided the patient's local PFS rate better than the T-stage, clinical stage, and a multivariate clinical model.

Deep learning-based diagnostic model with FDG-PET images indicated its possibility to predict local treatment outcomes in OPSCCs.
Deep learning-based diagnostic model with FDG-PET images indicated its possibility to predict local treatment outcomes in OPSCCs.
Antenatal psychosocial vulnerability is a main concern in today's perinatal health care setting. Undetected psychosocially vulnerable pregnant women and their unborn child are at risk for unfavourable health outcomes such as poor birth outcomes or mental state. In order to detect potential risks and prevent worse outcomes, timely and accurate detection of antenatal psychosocial vulnerability is necessary. Therefore, this paper aims to develop a screening tool 'the Born in Brussels Screening Tool (ST)' aimed at detecting antenatal psychosocial vulnerability.

The Born in Brussels ST was developed based on a literature search of existing screening tools measuring antenatal psychosocial vulnerability. Indicators and items (i.e. questions) were evaluated and selected. The assigned points for the answer options were determined based on a survey sent out to caregivers experienced in antenatal (psychosocial) vulnerability. Further refinement of the tool's content and the assigned points was based on expert panels' advice.

The Born in Brussels ST consists of 22 items that focus on 13 indicators communication, place of birth, residence status, education, occupational status, partner's occupation, financial situation, housing situation, social support, depression, anxiety, substance use and domestic violence. Based on the 168 caregivers who participated in the survey, assigned points account between 0,5 and 4. Threshold scores of each indicator were associated with adapted care paths.

Generalied and accurate detection of antenatal psychosocial vulnerability is needed. The brief and practical oriented Born in Brussels ST is a first step that can lead to an adequate and adapted care pathway for vulnerable pregnant women.
Generalied and accurate detection of antenatal psychosocial vulnerability is needed. The brief and practical oriented Born in Brussels ST is a first step that can lead to an adequate and adapted care pathway for vulnerable pregnant women.
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