Whole Grain Consumption and Inflammatory Markers: A Systematic Literature Review of Randomized Control Trials

Whole grain foods are rich in nutrients, dietary fibre, a range of antioxidants, and phytochemicals, and may have potential to act in an anti-inflammatory manner, which could help impact chronic disease risk. This systematic literature review aimed to examine the specific effects of whole grains on selected inflammatory markers from human clinical trials in adults. As per the Preferred Reporting Items for Systematic Reviews (PRISMA) protocol, the online databases MEDLINE, Embase, Cochrane, CINAHL, and Scopus were searched from inception through to 31 August 2021. Randomized control trials (RCTs) ≥ 4 weeks in duration, reporting ≥1 of the following: C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor (TNF), were included. A total of 31 RCTs were included, of which 16 studies recruited overweight/obese individuals, 12 had pre-existing conditions, two were in a healthy population, and one study included participants with prostate cancer. Of these 31 RCTs, three included studies with two intervention arms. A total of 32 individual studies measured CRP (10/32 were significant), 18 individual studies measured IL-6 (2/18 were significant), and 13 individual studies measured TNF (5/13 were significant). Most often, the overweight/obese population and those with pre-existing conditions showed significant reductions in inflammatory markers, mainly CRP (34% of studies). Overall, consumption of whole grain foods had a significant effect in reducing at least one inflammatory marker as demonstrated in 12/31 RCTs.

Diagnostic Approach to Macrocephaly in Children

Macrocephaly affects up to 5% of the pediatric population and is defined as an abnormally large head with an occipitofrontal circumference (OFC) >2 standard deviations (SD) above the mean for a given age and sex. Taking into account that about 2–3% of the healthy population has an OFC between 2 and 3 SD, macrocephaly is considered as “clinically relevant” when OFC is above 3 SD. This implies the urgent need for a diagnostic workflow to use in the clinical setting to dissect the several causes of increased OFC, from the benign form of familial macrocephaly and the Benign enlargement of subarachnoid spaces (BESS) to many pathological conditions, including genetic disorders. Moreover, macrocephaly should be differentiated by megalencephaly (MEG), which refers exclusively to brain overgrowth, exceeding twice the SD (3SD—“clinically relevant” megalencephaly). While macrocephaly can be isolated and benign or may be the first indication of an underlying congenital, genetic, or acquired disorder, megalencephaly is most likely due to a genetic cause. Apart from the head size evaluation, a detailed family and personal history, neuroimaging, and a careful clinical evaluation are crucial to reach the correct diagnosis. In this review, we seek to underline the clinical aspects of macrocephaly and megalencephaly, emphasizing the main differential diagnosis with a major focus on common genetic disorders. We thus provide a clinico-radiological algorithm to guide pediatricians in the assessment of children with macrocephaly.

Longitudinal Changes and Recovery in Heart Rate Variability of Young Healthy Subjects When Exposure to a Hypobaric Hypoxic Environment

Background: The autonomic nervous system (ANS) is crucial for acclimatization. Investigating the responses of acute exposure to a hypoxic environment may provide some knowledge of the cardiopulmonary system’s adjustment mechanism.Objective: The present study investigates the longitudinal changes and recovery in heart rate variability (HRV) in a young healthy population when exposed to a simulated plateau environment.Methods: The study followed a strict experimental paradigm in which physiological signals were collected from 33 healthy college students (26 ± 2 years, 171 cm ± 7 cm, 64 ± 11 kg) using a medical-grade wearable device. The subjects were asked to sit in normoxic (approximately 101 kPa) and hypoxic (4,000 m above sea level, about 62 kPa) environments. The whole experimental process was divided into four stable resting measurement segments in chronological order to analyze the longitudinal changes of physical stress and recovery phases. Seventy-six time-domain, frequency-domain, and non-linear indicators characterizing rhythm variability were analyzed in the four groups.Results: Compared to normobaric normoxia, participants in hypobaric hypoxia had significantly lower HRV time-domain metrics, such as RMSSD, MeanNN, and MedianNN (p < 0.01), substantially higher frequency domain metrics such as LF/HF ratio (p < 0.05), significantly lower Poincaré plot parameters such as SD1/SD2 ratio and other Poincaré plot parameters are reduced considerably (p < 0.01), and Refined Composite Multi-Scale Entropy (RCMSE) curves are reduced significantly (p < 0.01).Conclusion: The present study shows that elevated heart rates, sympathetic activation, and reduced overall complexity were observed in healthy subjects exposed to a hypobaric and hypoxic environment. Moreover, the results indicated that Multiscale Entropy (MSE) analysis of RR interval series could characterize the degree of minor physiological changes. This novel index of HRV can better explain changes in the human ANS.

Cardiorespiratory fitness and mortality from all causes, cardiovascular disease and cancer: dose–response meta-analysis of cohort studies

ObjectiveCurrent evidence of the associations between cardiorespiratory fitness (CRF) and mortality is limited. We performed a meta-analysis to assess the dose–response association of CRF with mortality from all causes, cardiovascular disease (CVD) and cancer in healthy population.MethodsPubMed, EMBASE and Web of Science were searched up to 26 December 2019 for reports of cohort studies giving risk estimates for all-cause, CVD and cancer mortality by level of CRF. Cohort studies were included if CRF was assessed by an exercise stress test and reported as at least three levels or per incremental increase, and the association of CRF with all-cause, CVD and cancer mortality was evaluated. Generalised least-squares regression models were used to assess the quantitative relation of CRF with all-cause, CVD and cancer mortality.Results34 cohort studies were eligible for the meta-analysis. The pooled relative risks (RRs) for all-cause, CVD and cancer mortality per one-metabolic equivalent increase in CRF were 0.88 (95% CI 0.83 to 0.93), 0.87 (95% CI0.83 to 0.91) and 0.93 (95% CI 0.91 to 0.96), respectively. As compared with lowest CRF, with intermediate CRF, the summary RRs for all-cause, CVD and cancer mortality were 0.67 (95% CI 0.61 to 0.74), 0.60 (95% CI 0.51 to 0.69) and 0.76 (95% CI 0.69 to 0.84), respectively, and with highest CRF were 0.47 (95% CI 0.39 to 0.56), 0.49 (95% CI 0.42 to 0.56) and 0.57 (95% CI 0.46 to 0.70), respectively.ConclusionOur analysis showed inverse dose–response associations of CRF with all-cause, CVD and cancer mortality, which provides evidence for public health recommendations for preventing all-cause, CVD and cancer mortality.PROSPERO registration numberCRD42020208883.

Does grip strength correlate with rotator cuff strength in patients with atraumatic shoulder instability?

Aim To investigate if there is a correlation between grip strength (GS) and rotator cuff (RC) strength in patients with atraumatic shoulder instability (ASI) and to compare the relationship between these two measures with that previously published for a healthy population. Moreover, to determine if testing GS could be incorporated as a surrogate clinical assessment for RC strength in these patients. Methods A total of 20 subjects with ASI were included. Out of the 20 patients, eight presented with bilateral instability, which constituted a total of 28 atraumatic unstable shoulders (N = 28). GS was measured using a Jamar hand-dynamometer. External rotation (ER) and internal rotation (IR) strength was tested in inner and outer ranges using a hand-held dynamometer (HHD). Pearson’s correlation test was computed to investigate the relationship. Multiple linear regression was conducted to predict GS based on RC strength. Results Significant and strong positive correlations were found between GS and inner-range IR (r = 0.764, P < 0.001), inner-range ER (r = 0.611, P = 0.001), outer-range IR (r = 0.817, P < 0.001), and outer-range ER (r = 0.736, P < 0.001). A significant regression equation was found (F (4, 23) = 13.254, P < 0.001), with an R2 of 0.697 indicating that RC strength explained 69.7% of the variance in GS. Conclusions The results support the hypothesis showing that GS is strongly associated with RC strength in ASI patients. The simplicity of handgrip testing allows it to be used in clinical scenarios where sophisticated assessment tools are not available. GS is a convenient means to monitor patient progress during shoulder rehabilitation programs.

Early Biomarkers Associated with P53 Signaling for Acute Radiation Injury

Accurate dose assessment within 1 day or even 12 h after exposure through current methods of dose estimation remains a challenge, in response to a large number of casualties caused by nuclear or radiation accidents. P53 signaling pathway plays an important role in DNA damage repair and cell apoptosis induced by ionizing radiation. The changes of radiation-induced P53 related genes in the early stage of ionizing radiation should compensate for the deficiency of lymphocyte decline and γ-H2AX analysis as novel biomarkers of radiation damage. Bioinformatic analysis was performed on previous data to find candidate genes from human peripheral blood irradiated in vitro. The expression levels of candidate genes were detected by RT-PCR. The expressions of screened DDB2, AEN, TRIAP1, and TRAF4 were stable in healthy population, but significantly up-regulated by radiation, with time specificity and dose dependence in 2–24 h after irradiation. They are early indicators for medical treatment in acute radiation injury. Their effective combination could achieve a more accurate dose assessment for large-scale wounded patients within 24 h post exposure. The effective combination of p53-related genes DDB2, AEN, TRIAP1, and TRAF4 is a novel biodosimetry for a large number of people exposed to acute nuclear accidents.

Comorbidity of Mental Disorder in Patients with Chronic Dis-ease: A Comparative Study of Heroin Dependence Patients and Diabetes Mellitus Patients

Background: Chronic patients are at greater risk for a psychiatric problem than the normal population; yet, the increased rate of mental disorder among one chronic patient compared to another chronic patient is uncertain. We aimed to assess the rate of mental disorder among people with heroin dependence and diabetes mellitus in comparison with the healthy population. Methods: This cross-sectional study was carried out in Kuala Lumpur, Malaysia in 2017-2020. The study consisted of 648 participants including heroin dependence patients, diabetes mellitus patients, and healthy population. The GHQ-28 and SCL-90-R scales were used to assess mental disorder among the study populations. Results: The current study revealed the rate of mental disorder among heroin dependence patients, diabetes mellitus patients, and healthy population respectively at 52.1%, 49.5%, and 23.2% using SCL-90-R and GHQ-28. The rate of mental disorder in both heroin dependent (OR 95%= 3.59: 2.37-5.44) and diabetic groups (OR 95%=3.25: 2.14-4.92) were significantly more than the healthy population; however, the odds ratio of mental disorder was not significantly different between heroin dependent and diabetic groups. Furthermore, the results revealed an acceptable agreement between SCL-90-R and GHQ-28 to detect mental disorders (Kappa=0.60; P<0.001). Conclusion: People with diabetes mellitus and heroin dependence have significantly poorer mental health than healthy people in Malaysia have. Furthermore, the equivalent rate of mental disorder among such patients suggests that heroin dependence patients are not more distressed than diabetes mellitus patients are. However, further comparative studies are needed to prove these findings.

Identifying healthy individuals with Alzheimer neuroimaging phenotypes in the UK Biobank

Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer's disease (AD) in particular, to identify populations suitable for preventive and early disease modifying trials. Evidence from genetic studies suggest the neurodegeneration of Alzheimer's disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be detected in sporadic disease. To address this challenge we train a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD-score representing the probability of AD using structural MRI data in the Alzheimer's Disease Neuroimaging Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real world dataset of the National Alzheimer's Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80), and demonstrate correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer's disease. This cohort have a cognitive profile in keeping with Alzheimer's disease, with strong evidence for poorer fluid intelligence, and with some evidence of poorer performance on tests of numeric memory, reaction time, working memory and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer's disease.

Quality of Beverage Intake and Cardiometabolic and Kidney Outcomes: Insights From the STANISLAS Cohort

Background and Aims: Beverages are an important aspect of diet, and their quality can possibly affect health. The Healthy Beverage Index (HBI) has been developed to take into account these effects. This study aimed to highlight the relationships between health and beverage quality by assessing the association of the HBI and its components with kidney and cardiometabolic (CM) outcomes in an initially healthy population-based familial cohort.Methods: This study included 1,271 participants from the STANISLAS cohort. The HBI, which includes 10 components of habitual beverage consumption, was calculated. Associations of the HBI and its components with estimated glomerular filtration rate (eGFR), albuminuria, hypertriglyceridemic waist (HTG waist), metabolic syndrome (MetS), carotid-femoral pulse wave velocity (cfPWV), carotid intima-media thickness (cIMT), and left ventricular mass (LV mass) were analyzed using multivariable linear or logistic regression models.Results: The median HBI score was 89.7 (78.6–95) out of 100 points. While the overall HBI score was not significantly associated with any of the studied outcomes, individual HBI components were found differently associated with the outcomes. cfPWV and cIMT were lower in participants who did not meet the full-fat milk criteria (p = 0.03 and 0.001, respectively). In men, higher cfPWV was observed for the “low Fat milk” (p = 0.06) and “alcohol” (p = 0.03) non-adherence criteria. Odds of HTG waist were higher with the non-adherence to sugar-sweetened beverages criteria (p &lt; 0.001). eGFR was marginally higher with non-adherence to the coffee/tea criteria (p = 0.047).Conclusions: In this initially healthy population, HBI components were differently associated with kidney and cardiometabolic outcomes, despite a good overall HBI score. Our results highlight specific impacts of different beverage types and suggest that beverages could have an impact on kidney and cardiometabolic health.