Ramadan-specific nutrition education improves cardio-metabolic health and inflammation-a prospective nutrition intervention study from Pakistan

There are recent reports that Ramadan fasting (RF) results in weight gain instead of weight loss. In addition, the data on the efficacy of brief nutrition education on healthy eating practices in Ramadan for better health are scarce. Therefore, a study was conducted to investigate the effects of brief nutrition education before the start of RF on healthy eating practices during RF. For this purpose, a prospective observational study focused on "Dietary Education and Awareness for Ramadan (DEAR)" as an intervention was carried out. The participants (n = 74) were recruited and divided into two groups, i.e., intervention and control groups (n = 37 each). As an intervention, nutrition education lessons were given before and during RF month. The control group did not attend these nutrition education lessons. Data on anthropometrics, dietary intake, and other parameters were collected at three time points: before, in the end, and 4 weeks after RF. Weight was measured in kg; height, waist circumference (WC), and hip circumference (HC) were measured in cm; and body mass index (BMI) was calculated. Waist-to-hip ratio (WHR) was calculated by dividing the waist value by the hip value. Body composition analysis was performed by the body composition analyzer (BF-907). Blood pressure (BP) was measured using a validated automated blood pressure. A 3-5 ml of venous blood was collected, and plasma and serum were separated. Serum and plasma samples were processed for general blood chemistry (blood lipid profile, glucose, and CRP) within 2 h. CRP was determined by the immunoturbidimetry method using an auto-analyzer. An enzyme-linked immunosorbent assay (ELISA) was used to determine cytokine/chemokines. Adherence to nutrition education (intervention) was assessed. The results show that nutrition education has positive effects on overall nutrition. Significant improvement in dietary adherence to dietary advice in the intervention group was noted. Significant BW loss (mean loss: 1.21 kg) in the intervention group was observed. The majority (63.3%) had lost BW ≥ 1.0 kg. Other changes observed as a result of the intervention included improvements in blood glucose, cholesterol, CRP levels, and systolic and diastolic BP. There was a notable shift in pro- and anti-inflammatory cytokine concentrations: IL-7, IL-4, and TGF-α decreased, while IL-2, TNF-α and resistin, IL-1 RA, IL-17 A, and sCD40 increased. In conclusion, RF resulted in a loss in mean BW and an improvement in related blood chemistry and cytokine profiles. Furthermore, nutrition education before RF resulted in better nutrition practices during RF and a desirable healthy BW, blood lipid, and cytokine profiles.

Integrated assessment of eutrophication in the southern Black Sea waters, using the Nested Environmental Status Assessment Tool

This research deals with the land-based pressures on the southern Black Sea coast (Turkey), with the objective of assessing their eutrophication impacts. In this context, reference values of some of the eutrophication indicators were calculated, and eutrophication assessment was carried out for this area using the holistic approach NEAT (Nested Environmental Status Assessment Tool). In addition, correlations between NEAT results of coastal regions and pressure-impact analysis methods were investigated. In the determined Spatial Assessment Unit (SAU) areas, 9 indicators were evaluated according to the SAU surface, both with and without weighting by their size the overall assessment of the Turkish Black Sea coast is good (0.70) and moderate (0.57) environmental status, for non-weighting and weighting by SAUs, respectively, with a high confidence level. With this study, we concluded that the sensitivity of the assessment tool needs to be increased. Despite these results, an appropriate number of indicators to represent the water column should be added. It is important to include the phytoplankton variable in the evaluation in future studies. In addition, this study, which uses NEAT allows identifying problematic environmental areas that require attention and action from managers and policymakers.

Dyslipidemia initiates keratinocytes proliferation through upregulation of lncRNA NEAT in psoriasis patients

BACKGROUND

Psoriasis is a chronic inflammatory immune-mediated and hyper proliferative skin disorder that has underlying genetic factors. Psoriasis can result from interaction of cytokines between keratinocytes and T-lymphocytes. NEAT is a lncRNA involved in immune modulation and has been previously studied in cancers. This study aims to clarify the unprecedented role of NEAT in psoriasis pathogenesis.

METHODS

The study was conducted on 50 healthy control subjects and 50 psoriasis patients. Blood samples from all participants were collected for analysis of their lipid profile. qRT-PCR was done for lncRNA NEAT, TNF-α, VEGF genes expression. The levels of ROS and caspase-3 were estimated by ELISA. ROC analysis was done to detect the diagnostic value of lncRNA NEAT gene expression.

RESULTS

Dyslipidemia is more prevalent among psoriasis patients. A significant up regulation in lncRNA NEAT, TNF-α, VEGF genes expression (p value˂0.001) in psoriasis patients in addition to significant increase in ROS and caspase-3 levels (p value˂0.001) in compare to controls. Additionally, a positive significant correlation between TNF-α, ROS, NEAT, caspase-3 and dyslipidemia. NEAT had an area under the curve (AUC) of 0.931 (95% CI 0.844-0.978, p < 0.001).

CONCLUSION

Dyslipidemia is an initiating signal in psoriasis pathogenesis that creates a state of chronic inflammation and oxidative stress. This state induces keratinocytes proliferation and release of NEAT with subsequent caspase-3 activation to counteract the proliferating cells. NEAT could be considered as a good diagnostic biomarker for psoriasis.

Intensive care unit admission from the emergency department in the setting of National Emergency Access Targets

Purpose

Since the introduction of National Emergency Access Targets (NEATs) in 2012 there has been little research examining patients admitted to the intensive care unit (ICU).We assessed differences in baseline characteristics and outcomes of patients admitted from the Emergency Department (ED) to the ICU within 4 hours compared with patients who were not.

Methods

This retrospective observational study included all adults (≥18 years old) admitted to the ICU from the ED of Austin Hospital, Melbourne, Australia, between 1 January 2017 and 31st December 2019 inclusive.

Results

1544 patients were admitted from the ED to the ICU and 65% had an ED length of stay (EDLOS) > 4 hour. Such patients were more likely to be older, female, with less urgent triage category scores and lower illness severity. Sepsis and respiratory admission diagnoses, and winter presentations were significantly more prevalent in this group.After adjustment for confounders, patients with an EDLOS > 4 hours had lower hospital mortality; 8% v 21% (p = 0.029; OR, 1.62), shorter ICU length of stay 2.2 v 2.4 days (p = 0.043), but a longer hospital length of stay 6.2 v 6.8 days (p = < 0.001).

Conclusion

Almost two thirds of patients breached the NEAT of 4 hours. These patients were more likely to be older, female, admitted in winter with sepsis and respiratory diagnoses, and have lower illness severity and less urgent triage categories. NEAT breach was associated with reduced hospital mortality but an increased hospital length of stay.

Compensatory mechanisms from different exercise intensities in type 2 diabetes: a secondary analysis of a 1-year randomized controlled trial

AIMS

This investigation aimed to determine the effect of different intensities of training on non-exercise physical activity (NEPA) and estimated thermogenesis (NEAT) from a 1-year exercise randomized controlled trial (RCT) in individuals with type 2 diabetes mellitus (T2DM) on non-training days. Additionally, changes in NEPA and estimated NEAT in those who failed (low-responders) or succeeded (high-responders) in attaining exercise-derived clinically meaningful reductions in body weight (BW) and fat mass (FM) (i.e., 6% for FM and 3% for BW) was assessed.

METHODS

Individuals with T2DM (n = 80) were enrolled in a RCT with three groups: resistance training combined with moderate-intensity continuous training (MICT) or high-intensity interval training (HIIT) and a control group. Of the 80 participants, 56 (completed data) were considered for this secondary analysis. NEPA and estimated NEAT were obtained by accelerometry and body composition through dual-energy X-ray absorptiometry.

RESULTS

After adjustments, no time*group interactions were found for estimated NEAT in the MICT (β = - 5.33, p = 0.366) and HIIT (β = - 5.70, p = 0.283), as well as for NEPA in the MICT (β = - 452.83, p = 0.833) and HIIT (β = - 2770.76, p = 0.201), when compared to controls. No compensatory changes in NEPA and estimated NEAT were observed when considering both low-responders and high-responders to FM and BW when compared to controls.

CONCLUSIONS

Both MICT and HIIT did not result in any compensatory changes in estimated NEAT and NEPA with the intervention on non-training days. Moreover, no changes in estimated NEAT and NEPA were found when categorizing our participants as low-responders and high-responders to FM and BW when compared to controls. Trial registration clinicaltrials.gov ID. NCT03144505.

Early prediction of hospital admission of emergency department patients

OBJECTIVE

The early prediction of hospital admission is important to ED patient management. Using available electronic data, we aimed to develop a predictive model for hospital admission.

METHODS

We analysed all presentations to the ED of a tertiary referral centre over 7 years. To our knowledge, our data set of nearly 600 000 presentations is the largest reported. Using demographic, clinical, socioeconomic, triage, vital signs, pathology data and keywords in electronic notes, we trained a machine learning (ML) model with presentations from 2015 to 2020 and evaluated it on a held-out data set from 2021 to mid-2022. We assessed electronic medical records (EMRs) data at patient arrival (baseline), 30, 60, 120 and 240 min after ED presentation.

RESULTS

The training data set included 424 354 data points and the validation data set 53 403. We developed and trained a binary classifier to predict inpatient admission. On a held-out test data set of 121 258 data points, we predicted admission with 86% accuracy within 30 min of ED presentation with 94% discrimination. All models for different time points from ED presentation produced an area under the receiver operating characteristic curve (AUC) ≥0.93 for admission overall, with sensitivity/specificity/F1-scores of 0.83/0.90/0.84 for any inpatient admission at 30 min after presentation and 0.81/0.92/0.84 at baseline. The models retained lower but still high AUC levels when separated for short stay units or inpatient admissions.

CONCLUSION

We combined available electronic data and ML technology to achieve excellent predictive performance for subsequent hospital admission. Such prediction may assist with patient flow.

An integrated assessment of the Good Environmental Status of Mediterranean Marine Protected Areas

Local, regional and global targets have been set to halt marine biodiversity loss. Europe has set its own policy targets to achieve Good Environmental Status (GES) of marine ecosystems by implementing the Marine Strategy Framework Directive (MSFD) across member states. We combined an extensive dataset across five Mediterranean ecoregions including 26 Marine Protected Areas (MPAs), their reference unprotected areas, and a no-trawl case study. Our aim was to assess if MPAs reach GES, if their effects are local or can be detected at ecoregion level or up to a Mediterranean scale, and which are the ecosystem components driving GES achievement. This was undertaken by using the analytical tool NEAT (Nested Environmental status Assessment Tool), which allows an integrated assessment of the status of marine systems. We adopted an ecosystem approach by integrating data from several ecosystem components: the seagrass Posidonia oceanica, macroalgae, sea urchins and fish. Thresholds to define the GES were set by dedicated workshops and literature review. In the Western Mediterranean, most MPAs are in good/high status, with P. oceanica and fish driving this result within MPAs. However, GES is achieved only at a local level, and the Mediterranean Sea, as a whole, results in a moderate environmental status. Macroalgal forests are overall in bad condition, confirming their status at risk. The results are significantly affected by the assumption that discrete observations over small spatial scales are representative of the total extension investigated. This calls for large-scale, dedicated assessments to realistically detect environmental status changes under different conditions. Understanding MPAs effectiveness in reaching GES is crucial to assess their role as sentinel observatories of marine systems. MPAs and trawling bans can locally contribute to the attainment of GES and to the fulfillment of the MSFD objectives. Building confidence in setting thresholds between GES and non-GES, investing in long-term monitoring, increasing the spatial extent of sampling areas, rethinking and broadening the scope of complementary tools of protection (e.g., Natura 2000 Sites), are indicated as solutions to ameliorate the status of the basin.

Prediction of non-exercise activity thermogenesis (NEAT) using multiple linear regression in healthy Korean adults: a preliminary study

Purpose

This preliminary study aimed to develop a regression model to estimate the non-exercise activity thermogenesis (NEAT) of Korean adults using various easy-to-measure dependent variables.

Methods

NEAT was measured in 71 healthy adults (male n = 29; female n = 42). Statistical analysis was performed to develop a NEAT estimation regression model using the stepwise regression method.

Results

We confirmed that ageA, weightB, heart rate (HR)_averageC, weight × HR_averageD, weight × HR_sumE, systolic blood pressure (SBP) × HR_restF, fat mass ÷ height2G, gender × HR_averageH, and gender × weight × HR_sumI were important variables in various NEAT activity regression models. There was no significant difference between the measured NEAT values obtained using a metabolic gas analyzer and the predicted NEAT.

Conclusion

This preliminary study developed a regression model to estimate the NEAT in healthy Korean adults. The regression model was as follows: sitting = 1.431 - 0.013 × (A) + 0.00014 × (D) - 0.00005 × (F) + 0.006 × (H); leg jiggling = 1.102 - 0.011 × (A) + 0.013 × (B) + 0.005 × (H); standing = 1.713 - 0.013 × (A) + 0.0000017 × (I); 4.5 km/h walking = 0.864 + 0.035 × (B) + 0.0000041 × (E); 6.0 km/h walking = 4.029 - 0.024 × (C) + 0.00071 × (D); climbing up 1 stair = 1.308 - 0.016 × (A) + 0.00035 × (D) - 0.000085 × (F) - 0.098 × (G); and climbing up 2 stairs = 1.442 - 0.023 × (A) - 0.000093 × (F) - 0.121 × (G) + 0.0000624 × (E).

Structural and Electrical Characterization of 2" Ammonothermal Free-Standing GaN Wafers. Progress toward Pilot Production

Free-standing gallium nitride (GaN) substrates are in high demand for power devices, laser diodes, and high-power light emitting diodes (LEDs). SixPoint Materials Inc. has begun producing 2" GaN substrates through our proprietary Near Equilibrium AmmonoThermal (NEAT) growth technology. In a single 90 day growth, eleven c-plane GaN boules were grown from free-standing hydride vapor phase epitaxy (HVPE) GaN substrates. The boules had an average X-ray rocking curve full width at half maximum (FWHM) of 33 ± 4 in the 002 reflection and 44 ± 6 in the 201 reflection using 0.3 mm divergence slits. The boules had an average radius of curvature of 10.16 ± 3.63 m. The quality of the boules was highly correlated to the quality of the seeds. A PIN diode grown at Georgia Tech on a NEAT GaN substrate had an ideality factor of 2.08, a high breakdown voltage of 1430 V, and Baliga's Figure of Merit of >9.2 GW/cm². These initial results demonstrate the suitability of using NEAT GaN substrates for high-quality MOCVD growth and fabrication of high-power vertical GaN switching devices.

Sensitivity of indicators matters when using aggregation methods to assess marine environmental status

The sensitivity of the 15 indicators included in a complex aggregation method (Nested Environmental status Assessment Tool), applied to a case study in the Caspian Sea in Iran, has been studied to discriminate between areas impacted and non-impacted by bathing activities. Two methods were used: (i) the 15 indicators were grouped into four groups (physicochemical, bacteria, plankton, and benthos) and each group was investigated separately (one-way sensitivity analysis), calculating NEAT values after omitting each group independently; and (ii) indicators were selected randomly, using 1000 Monte Carlo iterations, and removing from 1 to 14 indicators at each iteration. The results revealed that the abundance of Pontogammarus was the single indicator that made the difference in assessing the status among locations, differentiating bathing and non-bathing areas. Hence, this indicator is regarded as a monitoring element detecting the impacts produced by a management measure (beach nourishment) taken by the authorities to maintain the bathing activity.

Refinement of the Nanoparticle Emission Assessment Technique into the Nanomaterial Exposure Assessment Technique (NEAT 2.0)

Engineered nanomaterial emission and exposure characterization studies have been completed at more than 60 different facilities by the National Institute for Occupational Safety and Health (NIOSH). These experiences have provided NIOSH the opportunity to refine an earlier published technique, the Nanoparticle Emission Assessment Technique (NEAT 1.0), into a more comprehensive technique for assessing worker and workplace exposures to engineered nanomaterials. This change is reflected in the new name Nanomaterial Exposure Assessment Technique (NEAT 2.0) which distinguishes it from NEAT 1.0. NEAT 2.0 places a stronger emphasis on time-integrated, filter-based sampling (i.e., elemental mass analysis and particle morphology) in the worker's breathing zone (full shift and task specific) and area samples to develop job exposure matrices. NEAT 2.0 includes a comprehensive assessment of emissions at processes and job tasks, using direct-reading instruments (i.e., particle counters) in data-logging mode to better understand peak emission periods. Evaluation of worker practices, ventilation efficacy, and other engineering exposure control systems and risk management strategies serve to allow for a comprehensive exposure assessment.

The orexin neuropeptide system: physical activity and hypothalamic function throughout the aging process

There is a rising medical need for novel therapeutic targets of physical activity. Physical activity spans from spontaneous, low intensity movements to voluntary, high-intensity exercise. Regulation of spontaneous and voluntary movement is distributed over many brain areas and neural substrates, but the specific cellular and molecular mechanisms responsible for mediating overall activity levels are not well understood. The hypothalamus plays a central role in the control of physical activity, which is executed through coordination of multiple signaling systems, including the orexin neuropeptides. Orexin producing neurons integrate physiological and metabolic information to coordinate multiple behavioral states and modulate physical activity in response to the environment. This review is organized around three questions: (1) How do orexin peptides modulate physical activity? (2) What are the effects of aging and lifestyle choices on physical activity? (3) What are the effects of aging on hypothalamic function and the orexin peptides? Discussion of these questions will provide a summary of the current state of knowledge regarding hypothalamic orexin regulation of physical activity during aging and provide a platform on which to develop improved clinical outcomes in age-associated obesity and metabolic syndromes.

A standardized approach to study human variability in isometric thermogenesis during low-intensity physical activity

Limitations of current methods: The assessment of human variability in various compartments of daily energy expenditure (EE) under standardized conditions is well defined at rest [as basal metabolic rate (BMR) and thermic effect of feeding (TEF)], and currently under validation for assessing the energy cost of low-intensity dynamic work. However, because physical activities of daily life consist of a combination of both dynamic and isometric work, there is also a need to develop standardized tests for assessing human variability in the energy cost of low-intensity isometric work.

EXPERIMENTAL OBJECTIVES

Development of an approach to study human variability in isometric thermogenesis by incorporating a protocol of intermittent leg press exercise of varying low-intensity isometric loads with measurements of EE by indirect calorimetry.

RESULTS

EE was measured in the seated position with the subject at rest or while intermittently pressing both legs against a press-platform at 5 low-intensity isometric loads (+5, +10, +15, +20, and +25 kg force), each consisting of a succession of 8 cycles of press (30 s) and rest (30 s). EE, integrated over each 8-min period of the intermittent leg press exercise, was found to increase linearly across the 5 isometric loads with a correlation coefficient (r) > 0.9 for each individual. The slope of this EE-Load relationship, which provides the energy cost of this standardized isometric exercise expressed per kg force applied intermittently (30 s in every min), was found to show good repeatability when assessed in subjects who repeated the same experimental protocol on 3 separate days: its low intra-individual coefficient of variation (CV) of ~ 10% contrasted with its much higher inter-individual CV of 35%; the latter being mass-independent but partly explained by height.

CONCLUSION

This standardized approach to study isometric thermogenesis opens up a new avenue for research in EE phenotyping and metabolic predisposition to obesity.