Sample Weight Research Articles

Effect of aloe-vera coating on the quality of mechanically damaged zucchini during long-term storage

Zucchini is susceptible to mechanical damage, which can occur during postharvest operations and leads to produce quality reduction. Bruising is the most common type of mechanical damage that could result in economic losses due to its effect on the appearance and shelf life of produce. This study aims to examine the effect of bruising and coating on the quality parameters of zucchini. Zucchini was bruised through the drop impact test which produced mechanical damage with an impact energy of 0.353 J. Other zucchini samples were not bruised and set as control. Half of the samples were coated with aloe vera gel. The samples were kept at 5, 10, and 22 °C for 24 days. The effect of impact bruising, storage conditions, and coating on the bruising size and other quality attributes (weight, color, firmness, pH, and total soluble solids) was investigated. The results showed that bruising parameters were dependent on storage duration and coating. At all tested storage conditions, coating with aloe vera helped regulate the weight and yellowness changes in zucchini samples during the storage period. Storage at 10 °C showed the least reduction in weight on all treated and control samples compared to other storage conditions. The redness and greenness (a* value) color changes in all tested zucchini samples were steadily increasing at 22 °C. Coated, non-bruised zucchinis showed a gradual increment in total soluble solids and were highly maintained at 10 °C storage condition. A reduction in the firmness of zucchini was significantly observed due to storage duration. Meanwhile, pH increased but was not significantly affected by any of the tested factors. Moreover, this study indicated the importance of both aloe vera coating and storage management in preserving zucchini quality parameters and extending its shelf life. Hence, coating zucchini should be considered when attempting to increase its shelf life. Moreover, the findings of the study can provide baseline data to understand the mechanism of mechanical damage on the quality of zucchini.

Effects of a ketogenic diet on motor function and motor unit number estimation in aged C57BL/6 mice

ObjectivePathological, age-related loss of muscle function, commonly referred to as sarcopenia, contributes to loss of mobility, impaired independence, as well as increased risk of adverse health events. Sarcopenia has been attributed to changes in both neural and muscular integrity during aging. Current treatment options are primarily limited to exercise and dietary protein fortification, but the therapeutic impact of these approaches are often inadequate. Prior work has suggested that a ketogenic diet (KD) might improve healthspan and lifespan in aging mice. Thus, we sought to investigate the effects of a KD on neuromuscular indices of sarcopenia in aged C57BL/6 mice. DesignA randomized, controlled pre-clinical experiment consisting of longitudinal assessments performed starting at 22-months of age (baseline) as well as 2, 6 and 10 weeks after the start of a KD vs. regular chow intervention. SettingPreclinical laboratory study. Sample sizeThirty-six 22-month-old mice were randomized into 2 dietary groups: KD [n = 22 (13 female and 9 male)], and regular chow [n = 15 (7 female and 8 male)]. MeasurementsMeasures included body mass, hindlimb and all limb grip strength, rotarod for motor performance, plantarflexion muscle contractility, motor unit number estimations (MUNE), and repetitive nerve stimulation (RNS) as an index of neuromuscular junction transmission efficacy recorded from the gastrocnemius muscle. At end point, muscle wet weight and blood samples were collected to assess blood beta-hydroxybutyrate levels. Statistical analysisPrimary analyses were two-way mixed effects ANOVA (diet and time × diet) to determine the effect of a KD on indices of motor function (grip, rotarod) and indices of motor unit (MUNE) and muscle (contractility) function. ResultsBeta-hydroxybutyrate (BHB) was significantly higher at 10 weeks in mice on a KD vs control group (0.83 ± 0.44 mmol/l versus 0.42 ± 0.21 mmol/l, η2 = 0.265, unpaired t-test, p = 0.0060). Mice on the KD intervention demonstrated significantly increased hindlimb grip strength (diet, p = 0.0001; time × diet, p = 0.0030), all limb grip strength (diet, p = 0.0005; time × diet, p = 0.0523), and rotarod latency to fall (diet, p = 0.0126; time × diet, p = 0.0021). Mice treated with the KD intervention also demonstrated increased MUNE (diet, p = 0.0465; time × diet, p = 0.0064), but no difference in muscle contractility (diet, p = 0.5248; time × diet, p = 0.5836) or RNS (diet, p = 0.3562; time × diet, p = 0.9871). ConclusionKD intervention improved neuromuscular and motor function in aged mice. This pre-clinical work suggests that further research is needed to assess the efficacy and physiological effects of a KD on indices of sarcopenia.

Effects of expanded adverse childhood experiences including school bullying, childhood poverty, and natural disasters on mental health in adulthood

The study aimed to examine the association of expanded adverse childhood experiences (ACEs) with psychological distress in adulthood. The data from nation-wide online cohort was used for analysis. Community dwelling adults in Japan were included. The ACEs was assessed by 15 items of ACE-J, including childhood poverty and school bullying. Severe psychological distress was determined as the score of Kessler 6 over 13. Multivariable logistic regression analysis was conducted, by using sample weighting. A total of 28,617 participants were analyzed. About 75% of Japanese people had one or more ACEs. The prevalence of those with ACEs over 4 was 14.7%. Those with ACEs over 4 showed adjusted odds ratio = 8.18 [95% CI 7.14–9.38] for severe psychological distress. The prevalence of childhood poverty was 29% for 50–64 year old participants and 40% of 65 or older participants. The impact of childhood poverty on psychological distress was less than other ACEs in these age cohorts. Bullying was experienced 21–27% in young generations, but 10% in 65 or older participants. However, the impact on psychological distress in adulthood was relatively high in all age groups. ACEs have impacted mental health for a long time. Future research and practice to reduce ACEs are encouraged.

Modeling and process optimization of extraction conditions on the quality characteristics of oil from cashew kernel using Response Surface Methodology

The quest for edible oil for consumption could not be over-emphasized and problems encountered during the conventional shelling of cashew kernel are the exposure to extremely high levels of temperature which may affect the quality of the extracted oil. The effects and optimization of extraction conditions on the properties of cashew kernel oil was investigated. The oil was processed from the cashew kernel using varying sample weight (10, 30, 50 g), extraction time (1, 2, 3 h) and solvent volume (75, 200, 325 ml). The extracted oil was evaluated for physicochemical properties and oil yield. Result showed that the physicochemical properties of cashew oil were significantly (p < 0.05) influenced by the extraction conditions. Increase in extraction time and solvent volume increased the chemical properties (peroxide value, saponification value, iodine value) but decreased free fatty acid. The study optimization of the combined effects of the process conditions was achieved using sample weight of 10 g, extraction time of 2 h and solvent volume of 75 ml. These variables are important consideration for optimal quality of cashew kernel oil with maximum yield of 44.6 % and could therefore be utilized commercially as a source of edible oil for human consumption.

Re-weighting the randomized controlled trial for generalization: finite-sample error and variable selection

Abstract Randomized controlled trials (RCTs) may suffer from limited scope. In particular, samples may be unrepresentative: some RCTs over- or under-sample individuals with certain characteristics compared to the target population, for which one wants conclusions on treatment effectiveness. Re-weighting trial individuals to match the target population can improve the treatment effect estimation. In this work, we establish the expressions of the bias and variance of such re-weighting procedures—also called inverse propensity of sampling weighting (IPSW)—in presence of categorical covariates for any sample size. Such results allow us to compare the theoretical performance of different versions of IPSW estimates. Besides, our results show how the performance (bias, variance, and quadratic risk) of IPSW estimates depends on the two sample sizes (RCT and target population). A by-product of our work is the proof of consistency of IPSW estimates. In addition, we analyse how including covariates that are not necessary for identifiability of the causal effect may impact the asymptotic variance. Including covariates that are shifted between the two samples but not treatment-effect modifiers increases the variance while non-shifted but treatment-effect modifiers do not. We illustrate all the takeaways in a didactic example, and on a semi-synthetic simulation inspired from critical care medicine.

Association of risk factors for high blood pressure across 46 low- and middle-income countries: A multi-country cross-sectional analysis.

Despite acknowledging the influence of various lifestyle and metabolic risk factors on hypertension, it remains uncertain to identify the primary contributors and differentiate which modifiable risk factors mediate the causal effects of hypertension. We aimed to examine the hierarchical association of eight prominent lifestyle and metabolic risk factors, along with demographic variables, with hypertension in adults and to explore the mediating effects of modifiable metabolic risk factors on hypertension. A cross-sectional study was conducted in 46 low- and middle-income countries using the World Health Organization (WHO) STEPwise approach to noncommunicable disease risk factor surveillance from 2002 to 2020. In a sample of 179 535 non-pregnant adults, we assessed the weighted population-attributable risk percentages (PAR%) for hypertension associated with eight risk factors. Additionally, we investigated the mediating role of metabolic risk factors on the effects of lifestyle risk factors on hypertension. After adjusting for the sample weight in each country, 26.7% of participants had hypertension. The prevalence of hypertension was highest in those aged ≥65 years, with obesity-associated hypertension (45.7%) exceeding the rates for overweight (32.2%) and non-overweight individuals (18.2%). These eight risk factors collectively explain 83.7% of the PAR% associated with hypertension adjusted for the communal variance. Among the modifiable factors, obesity contributed to a weighted PAR% of 38.2%, while sedentary behaviour and low physical activity combined accounted for a weighted PAR% of 3.1%. Overweight/obesity played a predominant mediating role in the correlation between lifestyle risk factors and systolic and diastolic blood pressure, with the indirect effect accounting for approximately 25-64% and 13-80% of the total effect, respectively. These findings offer new insights into the modified risk factors associated with hypertension in adults in low- and middle-income countries, highlighting the crucial role of maintaining a normal body weight for the effective prevention and management of hypertension.

#2449 Prevalence and determinants of chronic kidney disease among older community-dwelling adults in Ireland

Abstract Background and Aims Chronic Kidney Disease (CKD) is a major global health challenge with substantial morbidity and mortality. In Ireland, a comprehensive understanding of the determinants of CKD is lacking, with limited data on the combined impact of socioeconomic and traditional risk factors. While the Irish Longitudinal Study on Ageing (TILDA) has offered insights into CKD burden, a detailed examination of its determinants remains unexplored. The goal of this study was to explore the prevalence and determinants of CKD at the community level within the Irish population. Method This is a retrospective cohort study that utilised cross sectional data from the first wave of TILDA conducted between 2009 and 2011. Participants aged 50 years and older who had health assessment and kidney function tests performed were included. The 2012 and 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were employed to calculate estimated glomerular filtration rates (eGFR) based on cystatin C and creatinine levels. CKD was classified as eGFR &amp;lt; 60 ml/min/1.73 m². We determined the weighted prevalence of CKD using sample weights. Stepwise multivariable logistic regression models were used to identify correlates of CKD and models’ performance were assessed using AUC-ROC curves and the Akaike Information Criterion (AIC). Associations were expressed using adjusted odds ratios (AOR) with 95% confidence intervals (CIs). Results Among the 5 386 participants tested for cystatin C and serum creatinine, the weighted CKD prevalence was 11.3% based on the 2021 CKD-EPI definition (excluding race) and 13.9% using the 2012 definition. Prevalence was significantly higher in women than men, and increased with age, reaching about 45% in women over 71 years versus 29% in men. Burden of comorbid conditions in CKD individuals varied from 11% (for cancer) to 89% (for hypertension) and were significantly higher than non-CKD individuals (P&amp;lt; 0.001). Adjusting for age, sex, education, and employment, the adjusted odds of CKD were significantly higher for individuals with hypertension AOR 2.15 (95% CI: 1.58–2.96), diabetes AOR 2.00 (95% CI: 1.50–2.66), cardiovascular disease AOR 1.72 (95% CI: 1.43–2.21), cancer AOR 1.64 (95% CI: 1.16–2.30), and obesity AOR 2.18 (95% CI: 1.61–2.96). The likelihood of CKD was also higher for patients with a hospital admission in the previous year AOR = 1.50 (95% CI: 1.14–1.96), possession of a medical card AOR 1.41 (95% CI: 1.06–1.89), and unemployed individuals AOR 1.61, (95% CI: 1.06–2.50), while the likelihood was significantly lower for individuals with a tertiary education (versus primary) AOR 0.73 (95% CI: 0.54–0.98). With further adjustment for medications, the magnitude of these associations was greatly attenuated with increasing odds of CKD for those receiving higher medication burden: 2-3 drugs AOR 2.02, (95% CI: 1.29–3.29), 3-4 drugs AOR 2.52 (95% CI: 1. 59–4.11), and &amp;gt; 5 drugs AOR 4.49 (95% CI: 2.81–7.39) (see Fig. 1). The AUC score ranged from 0.84 to 0.88, indicating strong model performance. Conclusion This study brings renewed attention to observed variation in national estimates of CKD prevalence (11.3% vs 13.9%) that are derived from current prediction equations with important implications for the strategic planning and resourcing of CKD care. This study emphasises the impact of socioeconomic factors, such as health coverage and financial barriers to heath care, education attainment, and employment, on CKD beyond traditional risk factors. Furthermore, the attenuation of known risk factors with increasing medication use highlights the influence of these treatments on CKD dynamics. These findings provide valuable insights for targeted public health strategies and awareness programs in Irish communities to address the increasing burden of CKD.

Association of dietary inflammatory indices with sarcopenia and all-cause mortality in COPD patients

BackgroundSarcopenia frequently occurs as a comorbidity in individuals with COPD. However, research on the impact of Appendicular Skeletal Muscle Mass (ASM) on survival in COPD patients is scarce. Moreover, there is a lack of research on the association between dietary pro-inflammatory capacity and sarcopenia in COPD.MethodsWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) covering the years 1999 to 2006 and 2011 to 2018. We aimed to investigate the relationship between the Dietary Inflammatory Index (DII) and sarcopenia prevalence among adults diagnosed with COPD in the United States. Furthermore, we sought to explore the relationship between sarcopenia, ASMI, and all-cause mortality. The study included a total of 1,429 eligible adult participants, divided into four groups based on quartiles of DII, with adjustments for sample weights. Methodologically, we used multivariable logistic regression analyses and to examine the association between DII and sarcopenia. Additionally, we used restricted cubic spline (RCS) tests to evaluate potential non-linear relationships. To assess the effect of sarcopenia on overall all-cause mortality, we used Kaplan–Meier models and Cox proportional hazards models. Moreover, we used RCS analyses to investigate potential non-linear relationships between ASMI and all-cause mortality. Subgroup analyses were conducted to confirm the reliability of our study findings.ResultsIn our COPD participant cohort, individuals with higher DII scores were more likely to be female, unmarried, have lower educational attainment, and show lower ASMI. Using multivariable logistic regression models, we found a positive association between the highest quartile of DII levels and sarcopenia incidence [Odds Ratio (OR) 2.37; 95% Confidence Interval (CI) 1.26–4.48; p = 0.01]. However, analysis of RCS curves did not show a non-linear relationship between DII and sarcopenia. Throughout the entire follow-up period, a total of 367 deaths occurred among all COPD patients. Kaplan–Meier survival curves showed a significantly higher all-cause mortality rate among individuals with concurrent sarcopenia (p &amp;lt; 0.0001). Cox proportional hazards model analysis showed a 44% higher risk of all-cause mortality among COPD patients with sarcopenia compared to those without sarcopenia [Hazard Ratio (HR): 1.44; 95% CI 1.05–1.99; p &amp;lt; 0.05]. Additionally, our final RCS analyses revealed a significant non-linear association between ASMI levels and all-cause mortality among COPD patients, with a turning point identified at 8.32 kg/m2. Participants with ASMI levels above this inflection point had a 42% lower risk of all-cause mortality compared to those with ASMI levels below it (HR 0.58; 95% CI 0.48–0.7).ConclusionWe observed a significant association between concurrent sarcopenia and an increased risk of all-cause mortality in COPD patients within the United States. Moreover, ASMI demonstrated a non-linear association with all-cause mortality, with a critical threshold identified at 8.32 kg/m2. Our findings also revealed an association between DII and the presence of sarcopenia. Consequently, further investigations are warranted to explore the feasibility of dietary DII adjustments as a means to mitigate muscle wasting and enhance the prognosis of COPD.

Determination of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat by ultrahigh-performance liquid chromatography-tandem mass spectrometry.

Succinic acid and lactic acid have been associated with diarrhea in weaned piglets. The level of succinic acid and lactic acid in serum, meat, and intestinal contents is important to elucidate the mechanism of diarrhea in weaned piglets. A facile method was developed for the quantification of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC/MS/MS). The serum samples underwent protein precipitation with methanol. The meat and intestinal contents were freeze-dried and homogenized using a tissue grinding apparatus. Methanol-water mixture (80:20, v/v) was used for homogenizing the meat, while water was used for homogenizing the intestinal contents. An additional step of protein precipitation with acetonitrile was required for the intestinal contents. The resulting solution was diluted with water before being analyzed by UHPLC/MS/MS. Separation of succinic acid and lactic acid could be achieved within 3min using a Kinetic XB-C18 column. The coefficients of variation for peak areas of succinic acid and lactic acid were less than 5.0%. The established method demonstrated good linearity as indicated by correlation coefficients exceeding 0.996. Additionally, satisfactory recoveries ranging from 88.58% to 108.8% were obtained. The detection limits (RS/N = 3) for succinic acid and lactic acid were determined to be 0.75 ng/mL and 0.02 μg/mL, respectively. This method exhibited high sensitivity, simplicity in operation, and small sample weight, making it suitable for quantitative determination of succinic acid and lactic acid in pigs' serum, intestinal contents, and meat. The method developed will provide valuable technical support in studying the metabolic mechanisms of succinic acid and lactic acid in pigs.

Study on lipid and fatty acid composition of \(\textit{Thelenota ananas}\) collected from Bai Dong Island, Ha Long Bay, Vietnam

The paper studies the lipid and fatty acid composition of the sea cucumber Thelenota ananas collected on Bai Dong Island, Ha Long Bay, Vietnam. The total lipid content of dry sample weight was relatively high (11.89%). The triacylglycerol TG has the highest concentration in total lipids with a ratio of up to 66.73%; the PL and PI classes do not have a significant difference with the proportions of 13.44 and 11.65% in total lipids. Two classes of sterol ST, hydrocarbon-wax HW and free fatty acid FFA account for a small proportion. The two main classes of phospholipids are PC and PE, with a ratio of 47.10% and 33.29% of total phospholipids. There are 36 fatty acids identified, of which total saturated fatty acids (SFA) account for 41.61%; Monounsaturated fatty acids (MUFA) account for 32.15%, and polyunsaturated fatty acids (PUFA) account for 25.63%; the main fatty acids are stearic acid (18:0) accounting for 13.15% of the total fatty acids; 16:1n-9 accounts for 14.87%, and 20:5n-3 EPA fatty acids account for 15.3% of the total fatty acids. Among the fatty acids, n-9 (omega 9) accounts for the highest proportion with 25.16%; n-3 fatty acids (omega 3) account for 18.43%; n-6 (omega 6), n-7 (omega 7) fatty acids account for 5.8 and 6.5%, respectively. In this study, the n3/n6 ratio of the sea cucumber sample Thelenota ananas was 3.18%, consistent with the evaluation standards of the World Health Organization (WHO) of n3/n6 ratio ≥ 0.1%. It is classified as a good foodstuff for human health; therefore, it can be considered a source of food that can be used to serve community health care needs.

Urban-Rural Differences in the Prevalence of Diabetes Among Adults in Haryana, India: The ICMR-INDIAB Study (ICMR-INDIAB-18).

Diabetes is a multifactorial disease with far-reaching consequences. Environmental factors, such as urban or rural residence, influence its prevalence and associated comorbidities. Haryana-a north Indian state-has undergone rapid urbanisation, and part of it is included in the National Capital Region (NCR). The primary aim of the study is to estimate the prevalence of diabetes in Haryana with urban-rural, NCR and non-NCR regional stratification and assess the factors affecting the likelihood of having diabetes among adults. This sub-group analysis of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study (a nationally representative cross-sectional population-based survey) was done for Haryana using data from 3722 participants. The dependent variable was diabetes, while residence in NCR/non-NCR and urban-rural areas were prime independent variables. Weighted prevalence was estimated using state-specific sampling weights and standardized using National Family Health Survey-5 (NFHS-5) study weights. Associations were depicted using bivariate analysis, and factors describing the likelihood of living with diabetes were explored using a multivariable binary logistic regression analysis approach. Overall, the weighted prevalence of diabetes in Haryana was higher than the national average (12.4% vs. 11.4%). The prevalence was higher in urban (17.9%) than in rural areas (9.5%). The prevalence of diabetes in rural areas was higher in the NCR region, while that of prediabetes was higher in rural non-NCR region. Urban-rural participants' anthropometric measurements and biochemical profiles depicted non-significant differences. Urban-rural status, age and physical activity levels were the most significant factors that affected the likelihood of living with diabetes. The current analysis provides robust prevalence estimates highlighting the urban-rural disparities. Urban areas continue to have a high prevalence of diabetes and prediabetes; rural areas depict a much higher prevalence of prediabetes than diabetes. With the economic transition rapidly bridging the gap between urban and rural populations, health policymakers should plan efficient strategies to tackle the diabetes epidemic.

Associations of tubal ligation and hysterectomy with serum androgen and estrogen metabolites among postmenopausal women in the Women's Health Initiative Observational Study.

Hysterectomy is associated with subsequent changes in circulating hormone levels, but the evidence of an association for tubal ligation is unclear. We evaluated whether circulating concentrations of androgens and estrogens differ by tubal ligation or hysterectomy status in postmenopausal women from the Women's Health Initiative (WHI)-Observational Study (OS). Serum androgens and estrogens were measured in 920 postmenopausal women who did not use menopausal hormone therapy at the time of blood draw, of whom 139 self-reported a history of tubal ligation and 102 reported hysterectomy (with intact ovaries). Geometric mean hormone concentrations (GMs) and 95% confidence intervals (CIs) associated with a history of tubal ligation or hysterectomy (ever/never), as well as time since procedures, were estimated using adjusted linear regression with inverse probability of sampling weights to account for selection. Circulating levels of 12 androgen/androgen metabolites and 20 estrogen/estrogen metabolites did not differ by tubal ligation status. Among women reporting prior hysterectomy compared to women without hysterectomy, we observed lower levels of several androgens (e.g., testosterone (nmol/L): GMyes 0.46 [95% CI:0.37-0.57] vs. GMno 0.62 [95% CI:0.53-0.72]) and higher levels of estrogen metabolites, for example, 2-hydroxyestrone-3-methyl ether (GMyes 11.1 [95% CI:8.95-13.9] pmol/L vs. GMno 8.70 [95% CI:7.38-10.3]) and 4-methoxyestrone (GMyes 6.50 [95% CI:5.05-8.37] vs. GMno 4.92 [95% CI:4.00-6.05]). While we did not observe associations between prior tubal ligation and postmenopausal circulating hormone levels, our findings support that prior hysterectomy was associated with lower circulating testosterone levels and higher levels of some estrogen metabolites, which may have implications for future hormone-related disease risks.

Representativeness of Participants in the ACCORD Trial Compared to Middle-aged and Older Adults Living with Diabetes in the United States.

We evaluated whether participants in the landmark Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial represent U.S. adults aged ≥40 with diabetes. Using the nationally representative 2017-2020 pre-pandemic National Health and Nutrition Examination Survey (NHANES) data, we made operational definitions of ACCORD eligibility criteria. We calculated the percentage of individuals aged ≥40 with diabetes and HbA1c ≥6.0% or ≥7.5% who met operational ACCORD eligibility criteria. Applying survey sampling weights to 715 NHANES participants aged ≥40 with diabetes and HbA1c ≥6.0% (representing 29,717,406 individuals), 12% (95% confidence interval [CI]: 8-18%) met the operational ACCORD eligibility criteria. Restricting to HbA1c ≥7.5%, 39% (95% CI: 28-51%) of respondents met the ACCORD criteria. ACCORD represented a minority of U.S. middle-aged and older adults with diabetes. Given the differential risk profile between ACCORD participants and the general population with diabetes, extrapolating the trial findings may not be appropriate.

Effect of Heat Treatment on the Supramolecular Structure of Copolymers Based on Poly(propylene glycol fumarate phthalate) with Acrylic Acid

Previous studies investigating the thermal decomposition of p-PGFPh:AA copolymers in an inert atmosphere have provided only a general understanding of the changes that occur during thermolysis. Comprehensive studies are required to gain a better understanding of these processes [1]. The most comprehensive information on the influence of various factors on both the kinetics and the supramolecular structure of the resulting products can be obtained by combining the method of thermal analysis with IR, mass spectrometry, and scanning electron microscopy. The compounds studied have two different compositions, namely p‑PGFPh:AA 6.77:93.23 mol % and p-PGFPh:AA 86.67:13.33 mol %. These compounds were then subjected to a thermolysis process, which resulted in the emission of gases and a decrease in sample weight. The degradation process can be divided into three stages: 1) Depolymerization of the main chain; 2) Depolymerization of the side chain; 3) Final decomposition. These processes occur sequentially at different temperature ranges. According to TG- and DTG studies, complete decomposition of p-PGFPh:AA copolymers occurred at Tterm = 340–350 °C. In this temperature range, a slight loss of sample mass (less than 10 wt %) was observed along with a slight gas evolution. The main gaseous products from the transformation of the studied samples were CO and CO2. This was supported by IR-CO (2000–2200 cm−1) and CO2 (2310–2370 cm−1) as well as mass spectrometric observations. The final products resulting from the thermolysis of p-PGFPh:AA copolymers were examined under an electron microscope. The results showed a similar morphological pattern of mesostructures with sizes ranging from 0.3–1.5 μm, which were observed depending on the porous structure of the initial polymer material. Based on the experimental data, it can be concluded that the p-PGFPh:AA copolymers (in proportions of 6.77:93.23 mol % and 86.67:13.33 mol %) have a relatively high degree of resistance to heating and do not undergo any changes in chemical composition, particle size and shape. In conclusion, the results clearly indicate that the selection of conditions for pyrolysis plays a crucial role in increasing the thermal stability of polymeric materials. This method allows for purposeful changes in the structure and properties of polymers.

Weighted metrics are required when evaluating the performance of prediction models in nested case–control studies

BackgroundNested case–control (NCC) designs are efficient for developing and validating prediction models that use expensive or difficult-to-obtain predictors, especially when the outcome is rare. Previous research has focused on how to develop prediction models in this sampling design, but little attention has been given to model validation in this context. We therefore aimed to systematically characterize the key elements for the correct evaluation of the performance of prediction models in NCC data.MethodsWe proposed how to correctly evaluate prediction models in NCC data, by adjusting performance metrics with sampling weights to account for the NCC sampling. We included in this study the C-index, threshold-based metrics, Observed-to-expected events ratio (O/E ratio), calibration slope, and decision curve analysis. We illustrated the proposed metrics with a validation of the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA version 5) in data from the population-based Rotterdam study. We compared the metrics obtained in the full cohort with those obtained in NCC datasets sampled from the Rotterdam study, with and without a matched design.ResultsPerformance metrics without weight adjustment were biased: the unweighted C-index in NCC datasets was 0.61 (0.58–0.63) for the unmatched design, while the C-index in the full cohort and the weighted C-index in the NCC datasets were similar: 0.65 (0.62–0.69) and 0.65 (0.61–0.69), respectively. The unweighted O/E ratio was 18.38 (17.67–19.06) in the NCC datasets, while it was 1.69 (1.42–1.93) in the full cohort and its weighted version in the NCC datasets was 1.68 (1.53–1.84). Similarly, weighted adjustments of threshold-based metrics and net benefit for decision curves were unbiased estimates of the corresponding metrics in the full cohort, while the corresponding unweighted metrics were biased. In the matched design, the bias of the unweighted metrics was larger, but it could also be compensated by the weight adjustment.ConclusionsNested case–control studies are an efficient solution for evaluating the performance of prediction models that use expensive or difficult-to-obtain biomarkers, especially when the outcome is rare, but the performance metrics need to be adjusted to the sampling procedure.

Phenolic and Antioxidant Characterization of Fruit By-Products for Their Nutraceuticals and Dietary Supplements Valorization under a Circular Bio-Economy Approach.

Agri-food by-products, obtained as waste from the food industry, negatively impact the global economy and the environment. In order to valorize waste materials from fruit juices and tomato sauces as upcycled materials rich in health-promoting compounds, they were characterized in terms of polyphenolic and protein content. The results obtained were compared with those collected for their final products. The recovery of polyphenols was performed via ultrasound-assisted extraction (UAE). A high-performance liquid chromatography-diode array detector (HPLC-DAD) method was developed and validated to depict the quali-quantitative polyphenolic profile of both the by-products and the final products. The antioxidant capacity of the resulting extracts was characterized by UV-Vis spectrophotometric assays in terms of total phenolic content (TPC) and total antioxidant status (TAS). Moreover, the protein content was assessed with the Kjeldahl method too. The results highlighted a significant quantity of polyphenols remaining in peach, apricot, and apple by-products, which were able to exert an antioxidant activity (in the range of 4.95 ± 5.69 × 10-1 to 7.06 ± 7.96 × 10-1 mmol Trolox 100 g-1 of dry weight (DW) sample). Conversely, the tomato by-products were highly rich in proteins (11.0 ± 2.00 to 14.4 ± 2.60 g of proteins 100 g-1 DW). The results proved that all by-products may potentially be sustainable ingredients with nutritional and functional value in a circular bio-economy prospect.

Boundary sample-based class-weighted semi-supervised learning for malignant tumor classification of medical imaging.

Medical image classification plays a pivotal role within the field of medicine. Existing models predominantly rely on supervised learning methods, which necessitate large volumes of labeled data for effective training. However, acquiring and annotating medical image data is both an expensive and time-consuming endeavor. In contrast, semi-supervised learning methods offer a promising approach by harnessing limited labeled data alongside abundant unlabeled data to enhance the performance of medical image classification. Nonetheless, current methods often encounter confirmation bias due to noise inherent in self-generated pseudo-labels and the presence of boundary samples from different classes. To overcome these challenges, this study introduces a novel framework known as boundary sample-based class-weighted semi-supervised learning (BSCSSL) for medical image classification. Our method aims to alleviate the impact of intra- and inter-class boundary samples derived from unlabeled data. Specifically, we address reliable confidential data and inter-class boundary samples separately through the utilization of an inter-class boundary sample mining module. Additionally, we implement an intra-class boundary sample weighting mechanism to extract class-aware features specific to intra-class boundary samples. Rather than discarding such intra-class boundary samples outright, our approach acknowledges their intrinsic value despite the difficulty associated with accurate classification, as they contribute significantly to model prediction. Experimental results on widely recognized medical image datasets demonstrate the superiority of our proposed BSCSSL method over existing semi-supervised learning approaches. By enhancing the accuracy and robustness of medical image classification, our BSCSSL approach yields considerable implications for advancing medical diagnosis and future research endeavors.

The magnitude of stunting and its determinants among late adolescent girls in East Africa: Multilevel binary logistics regression analysis.

Stunting poses a significant health risk to adolescent girls aged 15-19 in low- and middle-income countries, leading to lower education levels, reduced productivity, increased disease vulnerability, and intergenerational malnutrition. Despite the inclusion of adolescent nutrition services in the Sustainable Development Goals, little progress has been made in addressing malnutrition among adolescent girls in several African nations. Limited evidence exists in East Africa due to small sample sizes and methodological limitations. To overcome these constraints, this study utilizes the latest Demographic and Health Survey data to estimate the prevalence and factors influencing stunting among late adolescent girls in ten East African countries. This study utilized the most recent Demographic and Health Survey (DHS) data from 10 East African countries, including a total sample weight of 22,504 late-adolescent girls. A multilevel mixed-effect binary logistic regression model with cluster-level random effects was employed to identify factors associated with stunting among these girls. The odds ratio, along with the 95% confidence interval, was calculated to determine individual and community-level factors related to stunting. A p-value less than 0.05 was considered statistically significant in determining the factors influencing stunting among late-adolescent girls. The prevalence of stunting among late adolescent girls in East Africa was found to be 13.90% (95% CI: 0.13-0.14). Religion, relationship to the head, presence of under-five children in the household, lactating adolescent, marital status, Time to get water source, and country of residence were significantly associated with Stunting. This study highlights the complexity of stunting in East Africa and identifies key factors that need attention to reduce its prevalence. Interventions should focus on improving water access, supporting lactating girls, addressing socioeconomic disparities, promoting optimal care practices, and implementing country-specific interventions to combat stunting and improve adolescent girls' nutrition.

Suppressing label noise in medical image classification using mixup attention and self-supervised learning

Deep neural networks (DNNs) have been widely applied in medical image classification and achieve remarkable classification performance. These achievements heavily depend on large-scale accurately annotated training data. However, label noise is inevitably introduced in the medical image annotation, as the labeling process heavily relies on the expertise and experience of annotators. Meanwhile, DNNs suffer from overfitting noisy labels, degrading the performance of models. Therefore, in this work, we innovatively devise a noise-robust training approach to mitigate the adverse effects of noisy labels in medical image classification. Specifically, we incorporate contrastive learning and intra-group mixup attention strategies into vanilla supervised learning. The contrastive learning for feature extractor helps to enhance visual representation of DNNs. The intra-group mixup attention module constructs groups and assigns self-attention weights for group-wise samples, and subsequently interpolates massive noisy-suppressed samples through weighted mixup operation. We conduct comparative experiments on both synthetic and real-world noisy medical datasets under various noise levels. Rigorous experiments validate that our noise-robust method with contrastive learning and mixup attention can effectively handle with label noise, and is superior to state-of-the-art methods. An ablation study also shows that both components contribute to boost model performance. The proposed method demonstrates its capability of curb label noise and has certain potential toward real-world clinic applications.

Fintech and financial stability: Evidence from spatial analysis for 25 countries

Fintech has experienced rapid advances in recent years. This study examines the impact of Fintech on financial stability for a group of 25 countries during 2013–2020. We adopt the novel Fintech-enabled financing volume to directly measure Fintech development. We utilise both the aggregate and disaggregated level of Fintech financing; the latter includes crowdfunding, business lending and consumer lending, each has a different funding process and default rates. We account for spatial dependence in financial stability across countries by employing various spatial models. Our findings first reveal that there is positive spatial dependence of financial stability across countries. It implies that financial stability has a positive spillover to neighbouring countries and validates the necessity of spatial analysis. Second, based on the Spatial Durbin Model which best describes our data, Fintech financing makes a positive local and cross-border contribution towards financial stability, irrespective of alternative weight matrices and sample sizes. Such positive impact is more profound in countries with smaller sizes of Fintech financing volume, and the cross-border effect is stronger with closer geographic proximity. Finally, crowdfunding enhances financial stability, whilst consumer lending has a contrasting destabilising effect.