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Coexistence of obesity and decreased muscle strength, defined as sarcopenic obesity, is often observed in the older adults. The present study investigated whether sarcopenic obesity, defined as reduced handgrip strength and increased body mass index (BMI), is associated with cognitive impairment.

Study participants include 1615 older adults aged 65-84 years who lived in an urban area of Tokyo, Japan and participated in the Bunkyo Health Study. Mild cognitive impairment (MCI) and dementia were defined based on ≤22 points of Montreal Cognitive Assessment and ≤23 points of the Mine-Mental State Examination, respectively. Handgrip strength was measured using a dynamometer in a standing position. We divided participants into four groups according to their sarcopenia (probable) (handgrip strength <28kg in men and <18kg in women) and obesity status (BMI ≥25kg/m
) as control, obesity, sarcopenia and sarcopenic obesity, and investigated the association between cognitive function, sarcopenia, and obesity status.

Mean age was 73.1±5.4 years, and 57.6% of study participants were female. The prevalence of control, obesity, sarcopenia, and sarcopenic obesity was 59.4%, 21.2%, 14.6%, and 4.7%, respectively. The prevalence of MCI and dementia, respectively, was highest in participants with sarcopenic obesity, followed by those with sarcopenia, obesity, and control. After multivariate adjustment, sarcopenic obesity was independently associated with increased odds of MCI and dementia compared with the control (MCI 2.11 [95% confidence interval, 1.12-3.62]; dementia 6.17 [2.50-15.27]).

Sarcopenic obesity was independently associated with MCI and dementia among Japanese older adults. Future studies are necessary to clarify the causal relationship.
Sarcopenic obesity was independently associated with MCI and dementia among Japanese older adults. Future studies are necessary to clarify the causal relationship.
Resistance training and a sufficient amount of dietary protein have been suggested to build up and maintain muscle mass, strength and function into old age. As there is still no consensus on the optimum amount of protein intake in older people, this study aims to evaluate first whether it is achievable to double the recommended amount, which is 1g/kg BW/d in German speaking countries, via food administration and secondly whether this would lead to stronger improvements when subsequently combined with resistance training.

In total, 136 community-dwelling older adults (54% females, 72.9±4.8yrs) were randomly assigned to one of the three study groups observational control (CON), recommended protein (RP+T) and high protein (HP+T) intake groups. After six weeks of observation or nutritional counselling to achieve the respective protein target levels, eight weeks of resistance training (2x/week) were applied in RP+T and HP+T groups. Parameters indicative for muscle mass, strength and function were measured at bindings suggest that a substantial increase of habitual protein intake above the currently recommended levels is achievable within 17 weeks in community-dwelling older adults, whereby the extra amount of protein led to minor changes in body composition but not physical performance or muscle quality (NCT04023513).
Biological age (BA) is the hypothetical underlying age of an organism and has been proposed as a more powerful predictor of health than chronological age (CA). The difference between BA and CA (Δage) reflects the rate of biological aging, with lower values indicating slowed-down aging. We sought to compare the relationship of four a priori-defined dietary patterns, including a traditional Mediterranean diet (MD) and three non-Mediterranean diets, with biological aging (Δage) among Italian adults. We also examined distinctive nutritional traits of these diets as potential mediators of such associations.

Cross-sectional analysis on a sub-cohort of 4510 subjects (aged ≥35y; 52.0% women) from the Moli-sani Study (enrolment, 2005-2010). Food intake was recorded by a 188-item semi-quantitative food-frequency questionnaire. A Mediterranean diet score (MDS) was used as exposure and compared with non-Mediterranean dietary patterns, i.e. DASH (Dietary Approaches to Stop Hypertension), Palaeolithic and the Nordic didelayed biological aging, possibly through their high polyphenol content.
Metal elements have been associated with a wide range of clinical outcomes. The available epidemiological evidence for these associations is often inconsistent and suffers from confounding and reverse causation. We aimed to explore the broad clinical effects of varying blood metal element levels and possible underlying mechanisms.

We performed a two-sample Mendelian randomization (MR) analysis by using metal element-associated genetic loci as instrumental variable to evaluate the causal associations between blood metal element levels and 1050 disease outcomes in a UK Biobank cohort. A total of 408,910 White British participants were enrolled in the analysis. SRT2104 mouse We further used the metal element-related genes and disease-related genes to construct a protein-protein interaction (PPI) network.

Eight metal elements were associated with 63 diseases in total. Notably, we found nine pairs of suggestive evidence between two different metal elements for the same disease. Selenium and lead share some of the associature of blood metal elements and the potential for clinical interventions, these findings warrant further investigation.
Consumer-level cameras have provided an advantage of designing cost-effective, non-contact physiological parameters estimation approaches which is not possible with gold standard estimation techniques. This encourages the development of non-contact estimation methods using camera technology. Therefore, this work aims to present a systematic review summarizing the currently existing face-based non-contact methods along with their performance.

This review includes all heart rate (HR) and oxygen saturation (SpO2) studies published in journals and a few reputed conferences, which have compared the proposed estimation methods with one or more standard reference devices. The articles were collected from the following research databases Institute of Electrical and Electronics Engineers (IEEE), PubMed, Web of Science (WoS), Science Direct, and Association of Computer Machinery (ACM) digital library. All database searches were completed on May 20, 2021. Each study was assessed using a finite set of identified factuffering from any related disease. SpO2 estimation studies are challenging and need to be tested by conducting hypoxemic events. The authors would encourage reporting the detailed information about the study population, the use of longer videos, and appropriate performance metrics and testing under abnormal HR and SpO2 ranges for future estimation studies.
Intracranial hemorrhage (ICH) is a life-threatening emergency that can lead to brain damage or death, with high rates of mortality and morbidity. The fast and accurate detection of ICH is important for the patient to get an early and efficient treatment. To improve this diagnostic process, the application of Deep Learning (DL) models on head CT scans is an active area of research. Although promising results have been obtained, many of the proposed models require slice-level annotations by radiologists, which are costly and time-consuming.

We formulate the ICH detection as a problem of Multiple Instance Learning (MIL) that allows training with only scan-level annotations. We develop a new probabilistic method based on Deep Gaussian Processes (DGP) that is able to train with this MIL setting and accurately predict ICH at both slice- and scan-level. The proposed DGPMIL model is able to capture complex feature relations by using multiple Gaussian Process (GP) layers, as we show experimentally.

To highlight ng, our model can be applied to a broader range of other tasks, especially in medical image classification, where it can help the diagnostic process.
The competitive performance at slice- and scan-level shows that DGPMIL model provides an accurate diagnosis on slices without the need for slice-level annotations by radiologists during training. As MIL is a common problem setting, our model can be applied to a broader range of other tasks, especially in medical image classification, where it can help the diagnostic process.
Expectations of painful sensations constitute a core feature of chronic pain. An important clinical question is whether such expectations are revised when disconfirming experiences are made (e.g., less pain than expected). This study examined how people adjust their pain expectations when the experience of decreasing pain is expected vs. unexpected.

In a novel randomized between-subjects design, a subclinical sample of people who frequently experience pain was provided with painful thermal stimulations. Unbeknownst to participants, the temperature applied was decreased from trial to trial. Based on the experimental instructions provided, this experience of decreasing pain was expected in one condition (expectation-confirmation; n=34), whereas it was unexpected in another (expectation-disconfirmation; n=39).

Perceived pain intensity was lower in the expectation-confirmation condition than in the expectation-disconfirmation condition (p=.014, η

=0.083). The expectation-confirmation condition also showe condition is consistent with a confirmation bias in pain perception. Though participants who experienced large discrepancies between expected and experienced pain were hesitant to adjust their pain expectations immediately, expectation violations increased their ability to cope with pain one week later, suggesting some beneficial longer-term effects of expectation violations.The MANAGE-PD tool may help general neurologists in deciding whether a patient with advanced Parkinson's disease should be referred for an advanced therapy. Although the development and clinical validation of MANAGE-PD would appear to serve an important need, we urge the reader to be aware of several methodological concerns.Cardiac troponin I (cTnI) plays an important role in emergency diagnosis of cardiovascular diseases, which exists predominately in the form of cardiac troponin I-C (cTnI-C) complex. We proposed a fiber-integrated optofluidic chip immunosensor with time-delay-dispersion based microwave photonic analyzer (MPA) for cTnI-C detection. The whispering gallery mode (WGM) fiber probe was fabricated by embedding a polydopamine functionalized hollow glass microsphere (HGMS) into the etched capillary-fiber structure, and the WGMs could be excited through the efficient coupling between the thin-wall capillary and the HGMS. The reflective WGM optofluidic chip functioned as a wavelength tuner to construct fiber ring laser cavity, whose laser output wavelength was cTnI-C concentration-dependent. The tiny wavelength variation of sensing laser was converted into a radio-frequency (RF) response, which was retrieved by measuring the change of RF-domain free spectrum range (FSR) in time-delay-dispersion based MPA, and the quantitative detection of cTnI-C complex can be achieved with high resolution. Experimental results show that this immunosensor had a limit of detection (LOD) of 0.59 ng/mL, and a detection resolution of 1.2 fg/mL. The relative resolving power was 102-104-fold higher than that of others optical fiber cTnI biosensors. The proposed fiber-integrated optofluidic chip provides an innovative lab-on-chip diagnostic tool for myocardial damage.
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