Functional Modules of the Proteostasis Network

Cells invest in an extensive network of factors to maintain protein homeostasis (proteostasis) and prevent the accumulation of potentially toxic protein aggregates. This proteostasis network (PN) comprises the machineries for the biogenesis, folding, conformational maintenance, and degradation of proteins with molecular chaperones as central coordinators. Here, we review recent progress in understanding the modular architecture of the PN in mammalian cells and how it is modified during cell differentiation. We discuss the capacity and limitations of the PN in maintaining proteome integrity in the face of proteotoxic stresses, such as aggregate formation in neurodegenerative diseases. Finally, we outline various pharmacological interventions to ameliorate proteostasis imbalance

Clostridium difficile-associated diarrhea in radiooncology: an underestimated problem for the feasibility of the radiooncological treatment?

Background and Purpose Over the last years an increasing incidence of Clostridium difficile-associated diarrhea (CDAD) has been reported. Especially haematology-oncology patients are at risk of developing CDAD. The aim of this analysis is to determine the incidence of CDAD in radiooncological patients and to find out what relevance CDAD has for the feasibility of the radiooncological treatment, as well as to detect and describe risk factors. Patients and Methods In a retrospective analysis from 2006 to 2010 34 hospitalized radiooncological patients could be identified having CDAD. The risk factors of these patients were registered, the incidence was calculated and the influence on the feasibility of the radiooncological therapy was evaluated. Induced arrangements for prophylaxis of CDAD were identified and have been correlated with the incidence. Results The incidence of CDAD in our collective is 1,6%. Most of the patients suffering from a CDAD were treated for carcinoma in the head and neck area. Common risk factors were antibiotics, proton pump inhibitors, cytostatic agents and tube feeding. Beside a high rate of electrolyte imbalance and hypoproteinemia a decrease of general condition was frequent. 12/34 patients had a prolonged hospitalization, in 14/34 patients radiotherapy had to be interrupted due to CDAD. In 21 of 34 patients a concomitant chemotherapy was planned. 4/21 patients could receive all of the planned cycles and only 2/21 patients could receive all of the planned cycles in time. 4/34 patients died due to CDAD. In 4/34 patients an initially curative treatment concept has to be changed to a palliative concept. With intensified arrangements for prophylaxis the incidence of CDAD decreased from 4,0% in 2007 to 0,4% in 2010. Conclusion The effect of CDAD on the feasibility of the radiotherapy and a concomitant chemotherapy is remarkable. The morbidity of patients is severe with a high lethality. Reducing of risk factors, an intense screening and the use of probiotics as prophylaxis can reduce the incidence of CDAD

Work-related correlates of occupational sitting in a diverse sample of employees in Midwest metropolitan cities

The worksite serves as an ideal setting to reduce sedentary time. Yet little research has focused on occupational sitting, and few have considered factors beyond the personal or socio-demographic level. The current study i) examined variation in occupational sitting across different occupations, ii) explored whether worksite level factors (e.g., employer size, worksite supports and policies) may be associated with occupational sitting. Between 2012 and 2013, participants residing in four Missouri metropolitan areas were interviewed via telephone and provided information on socio-demographic characteristics, schedule flexibility, occupation, work related factors, and worksite supports and policies. Occupational sitting was self-reported (daily minutes spent sitting at work), and dichotomized. Occupation-stratified analyses were conducted to identify correlates of occupational sitting using multiple logistic regressions. A total of 1668 participants provided completed data. Those employed in business and office/administrative support spent more daily occupational sitting time (median 330 min) compared to service and blue collar employees (median 30 min). Few worksite supports and policies were sitting specific, yet factors such as having a full-time job, larger employer size, schedule flexibility, and stair prompt signage were associated with occupational sitting. For example, larger employer size was associated with higher occupational sitting in health care, education/professional, and service occupations. Work-related factors, worksite supports and policies are associated with occupational sitting. The pattern of association varies among different occupation groups. This exploratory work adds to the body of research on worksite level correlates of occupational sitting. This may provide information on priority venues for targeting highly sedentary occupation groups

Workplace social and organizational environments and healthy-weight behaviors

<div><p>Background</p><p>The workplace is an important setting for health promotion including nutrition and physical activity behaviors to prevent obesity. This paper explores the relationship between workplace social environment and cultural factors and diet and physical activity (PA) behaviors and obesity among employees.</p><p>Methods</p><p>Between 2012 and 2013, telephone interviews were conducted with participants residing in four Missouri metropolitan areas. Questions included demographic characteristics, workplace socio/organizational factors related to activity and diet, and individual diet and PA behaviors, and obesity. Multivariate logistic regression was used to examine associations between the workplace socio/organizational environment and nutrition, PA, and obesity.</p><p>Results</p><p>There were differences in reported health behaviors and socio/organizational environment by gender, race, age, income, and worksite size. For example, agreement with the statement the ‘company values my health’ was highest among Whites, older employees, and higher income workers. As worksite size increased, the frequency of reporting seeing co-workers doing several types of healthy behaviors (eat fruits and vegetables, doing PA, and doing PA on breaks at work) increased. In adjusted analyses, employees agreeing the company values my health were more likely to engage in higher PA levels (aOR=1.54, 95% CI: 1.09-2.16) and less likely to be obese (aOR=0.73, 95% CI: 0.54-0.98). Seeing co-workers eating fruits and vegetables was associated with increased reporting of eating at least one vegetable per day (aOR=1.43, 95% CI: 1.06-1.91) and seeing co-workers being active was associated with higher PA levels (aOR 1.56, 95% CI: 1.19-2.05).</p><p>Conclusions</p><p>This research suggests that social/organizational characteristics of the workplace environment, particularly feeling the company values the workers’ health and to seeing co-workers engaging in healthy behaviors, may be related to nutrition and PA behaviors and obesity. These findings point to the potential for intervention targets including environment and policy changes.</p></div

An Exploratory Survey of Self-Reported Joint Pain Among College Students

Topics in Exercise Science and Kinesiology Volume 4: Issue 1, Article 13, 2023. Prior research has shown that college students are a unique subset of our global population that commonly experience stresses and strains to their musculoskeletal system as they complete their traditional coursework. Most of this population is viewed as healthy since their joints and skeletal systems have yet to be subjected to the levels of wear and tear of their elder constituents. However, there are still individuals within this population that often report experiencing some level of joint pain or discomfort that would not fall underneath the classic diagnoses of arthritis or other severe joint-related pathologies. The purpose of this descriptive study was to examine joint pain in non-clinical college students and some of the potential contributions to that pain. An email was sent to the entire current student population at a southeastern university in the United States inviting them to complete an online questionnaire about joint pain. Prior to its distribution, a pilot version of the questionnaire was distributed and tested to ensure readability and to establish content validity. The final version of the questionnaire was distributed twice during the fall 2021 semester. From the total number of students who may have received the email invitation (n = 18,985), 211 students completed the survey for a response rate of 1.11%. Of the 116 respondents who had never seen a healthcare professional for a joint injury or joint surgery, 72 reported current joint pain (62%). Thirty participants (47.6%) reported that the duration of their pain has lasted longer than three months. Participants reported cervical pain (76%), lumbar spine pain (84.8%), knee pain (65.1%), and hip or pelvis pain (76.2%) as the most frequent joints being affected. While typically considered healthy, college students are experiencing joint health-related pain and discomfort. Due to lack of past and current research on joint health in college students, the results of this exploratory study may begin to shed light on the need to implement and fund more proactive methods to best address this emerging issue

Cerebral blood flow predicts differential neurotransmitter activity

Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. In particular, the sensitivity of cerebral blood flow to activity changes in specific neurotransmitter systems remains unclear. We address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action. We use a novel framework aimed at disentangling the observed effects to contribution from underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings suggest that cerebral blood flow is a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans

Electron Microscopy Methods for Virus Diagnosis and High Resolution Analysis of Viruses

The term “virosphere” describes both the space where viruses are found and the space they influence, and can extend to their impact on the environment, highlighting the complexity of the interactions involved. Studying the biology of viruses and the etiology of virus disease is crucial to the prevention of viral disease, efficient and reliable virus diagnosis, and virus control. Electron microscopy (EM) is an essential tool in the detection and analysis of virus replication. New EM methods and ongoing technical improvements offer a broad spectrum of applications, allowing in-depth investigation of viral impact on not only the host but also the environment. Indeed, using the most up-to-date electron cryomicroscopy methods, such investigations are now close to atomic resolution. In combination with bioinformatics, the transition from 2D imaging to 3D remodeling allows structural and functional analyses that extend and augment our knowledge of the astonishing diversity in virus structure and lifestyle. In combination with confocal laser scanning microscopy, EM enables live imaging of cells and tissues with high-resolution analysis. Here, we describe the pivotal role played by EM in the study of viruses, from structural analysis to the biological relevance of the viral metagenome (virome)

Novel multiplex technology for diagnostic characterization of rheumatoid arthritis

Abstract Introduction The aim of this study was to develop a clinical-grade, automated, multiplex system for the differential diagnosis and molecular stratification of rheumatoid arthritis (RA). Methods We profiled autoantibodies, cytokines, and bone-turnover products in sera from 120 patients with a diagnosis of RA of < 6 months' duration, as well as in sera from 27 patients with ankylosing spondylitis, 28 patients with psoriatic arthritis, and 25 healthy individuals. We used a commercial bead assay to measure cytokine levels and developed an array assay based on novel multiplex technology (Immunological Multi-Parameter Chip Technology) to evaluate autoantibody reactivities and bone-turnover markers. Data were analyzed by Significance Analysis of Microarrays and hierarchical clustering software. Results We developed a highly reproducible, automated, multiplex biomarker assay that can reliably distinguish between RA patients and healthy individuals or patients with other inflammatory arthritides. Identification of distinct biomarker signatures enabled molecular stratification of early-stage RA into clinically relevant subtypes. In this initial study, multiplex measurement of a subset of the differentiating biomarkers provided high sensitivity and specificity in the diagnostic discrimination of RA: Use of 3 biomarkers yielded a sensitivity of 84.2% and a specificity of 93.8%, and use of 4 biomarkers a sensitivity of 59.2% and a specificity of 96.3%. Conclusions The multiplex biomarker assay described herein has the potential to diagnose RA with greater sensitivity and specificity than do current clinical tests. Its ability to stratify RA patients in an automated and reproducible manner paves the way for the development of assays that can guide RA therapy.http://deepblue.lib.umich.edu/bitstream/2027.42/116025/1/13075_2010_Article_3144.pd

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio