Effectiveness of traffic light system on Brazilian consumers perception of food healthfulness

Front-of-package(FOP)nutrition labelling schemes were developed to improve consumer’s comprehension about the food nutrients associated with non-communicable diseases(NCDs).Several FOPs have already been developed,and Brazil is in the process of evaluating a scheme to introduce in the products.The aim of this study was to investigate the impact of TLS,the scheme proposed by the food industry,on the product healthfulness perception.A study with 141 participants was carried out.A conjoint task was designed considering three categories and levels:types of dairy products(light yogurt,prato cheese,and chocolate flavoured milk),Traffic Light System(yes vs.no)and brand(well-known vs.unknown).The effect of TLS on perceived healthfulness was evaluated using a 9-point scales(1:not healthy;9:very healthy).Results showed that the inclusion of TLS did not influence the perceived healthfulness of the products by consumers,even among consumers with higher interest in healthy eating.These findings suggest that the proposal supported by the food industry does not seem to be the most appropriate,being recommended the development of further studies to compare the efficacy of TLS and other FOP schemes.

Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

Low‑Temperature Fabrication of Stable Black‑Phase CsPbI_(3)Perovskite Flexible Photodetectors Toward Wearable Health Monitoring

Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.

Decoding the nexus:branched-chain amino acids and their connection with sleep,circadian rhythms,and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and,either directly or indirectly,overall body health,encompassing metabolic and cardiovascular well-being.Given the heightened metabolic activity of the brain,there exists a considerable demand for nutrients in comparison to other organs.Among these,the branched-chain amino acids,comprising leucine,isoleucine,and valine,display distinctive significance,from their contribution to protein structure to their involvement in overall metabolism,especially in cerebral processes.Among the first amino acids that are released into circulation post-food intake,branched-chain amino acids assume a pivotal role in the regulation of protein synthesis,modulating insulin secretion and the amino acid sensing pathway of target of rapamycin.Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors,competing for a shared transporter.Beyond their involvement in protein synthesis,these amino acids contribute to the metabolic cycles ofγ-aminobutyric acid and glutamate,as well as energy metabolism.Notably,they impact GABAergic neurons and the excitation/inhibition balance.The rhythmicity of branchedchain amino acids in plasma concentrations,observed over a 24-hour cycle and conserved in rodent models,is under circadian clock control.The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood.Disturbed sleep,obesity,diabetes,and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics.The mechanisms driving these effects are currently the focal point of ongoing research efforts,since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies.In this context,the Drosophila model,though underutilized,holds promise in shedding new light on these mechanisms.Initial findings indicate its potential to introduce novel concepts,particularly in elucidating the intricate connections between the circadian clock,sleep/wake,and metabolism.Consequently,the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle.They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health,paving the way for potential therapeutic interventions.

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

Decoding molecular mechanisms:brain aging and Alzheimer's disease

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for centuries.The aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's disease.Beyond these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging brain.Understanding these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect cognition.This review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.

Metaverse for mental health disorders:Opportunities and challenges

Several articles on the mental health impact of the metaverse and the need to balance its potential benefits with the risks of metaverse use has recently published.The metaverse consists of a combination of immersive technologies and artificial intelligence algorithms.The metaverse differs from the preceding digital psychiatric interventions due to its complex structure and interactions between components.The diverse functions of the metaverse ensure that it may have a substantial impact on mental health.However,the evidence for its efficacy in treating mental health disorders is limited to a few trials.The mental health benefits of immersive technologies are well-documented and suggest that metaverse-based psychiatric treatment may be similarly efficacious.The mental health risks of the metaverse are largely unknown,and it is not clear whether they will be greater than other digital psychiatric interventions.Much more research is needed to determine whether metaverse-based psychiatric treatment will meet the standards of appropriate mental healthcare.

Assessing healthcare workers’knowledge and confidence in the diagnosis,management and prevention of Monkeypox

BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.

Mediating role of health literacy in the relationship between social isolation and psychological distress among pre-frail older adults

BACKGROUND Frailty has become a significant public health issue.The recent increase in the number of frail older adults has led to increased attention being paid to psycho-logical care services in communities.The social isolation of pre-frail older adults can impact their psychological distress.AIM To explore the mediating effect of health literacy between social isolation and psychological distress among communitydwelling older adults with pre-frailty.METHODS This descriptive cross-sectional study was conducted with 254 pre-frail older individuals aged 60 years and over.Social isolation,health literacy,and psycholo-gical distress were comprehensively measured using the Lubben Social Network Scale-6,12-item Short-Form Health Literacy Questionnaire,and the Kessler Psy-chological Distress Scale-10.Data were evaluated using the SPSS 27.0 package program and the PROCESS macro tool.Descriptive statistical analyses,correlation analyses,and bootstrap mediation tests were used to assess associations between the variables.RESULTS The results showed that social isolation had an effect on health literacy among pre-frail older adults(β=0.240,P<0.001),social isolation impact on psycho-logical distress pre-frail older adults(β=-0.415,P<0.001);health literacy was identified effect on psychological distress among pre-frail older persons(β=-0.307,P<0.001).Health literacy partially mediated the relationship between social isolation and psychological distress among community-dwelling older adults with pre-frailty,with a mediation effect of-0.074,accounting for 17.83%of the total effect.

Relationship between the use of smart medical services and mental health status

In this editorial,I comment on the article by Zhang et al.To emphasize the importance of the topic,I discuss the relationship between the use of smart medical devices and mental health.Smart medical services have the potential to positively influence mental health by providing monitoring,insights,and inter-ventions.However,they also come with challenges that need to be addressed.Understanding the primary purpose for which individuals use these smart tech-nologies is essential to tailoring them to specific mental health needs and prefe-rences.

Impact of community public health care on treatment effect,health cognition,and self-management in patients with type 2 diabetes

BACKGROUND At present,China has become the country with the largest number of individuals with diabetes mellitus(DM)in the world,with a total of approximately 140 million patients,the majority of whom have type 2 DM(T2DM).Based on conven-tional nursing methods,community home care has important clinical significance in controlling blood sugar and disease progression.AIM To explore the impact of community public health nursing on treatment effect,health cognition,and self-management in patients with T2DM.METHODS One hundred patients with T2DM were selected as the research subjects.The patients were divided into either a conventional nursing group or community nursing(CN)group using the random number table method.The conventional nursing group(50 cases)received routine care,while the CN group(50 cases)received community public health care in addition to routine care as that for the conventional nursing group.The rate of excellent and good blood glucose control,fasting blood glucose before and after care,2-h postprandial blood glucose,health cognition,and self-management ability,and patient satisfaction were compared between the two groups.RESULTS The CN group had a higher rate of excellent blood sugar control than the conventional nursing group(88%vs 70%,P<0.05).Before care,there was no significant difference in fasting blood glucose or 2-h postprandial blood glucose between the two groups of patients(P>0.05).After nursing,fasting blood glucose and 2-h postprandial blood glucose were reduced to varying degrees in both groups,and both blood glucose levels in the CN group were lower than those of the conventional nursing group(P<0.05).Compared with the scores before care,the cognitive level score for diabetes and self-management ability score improved after care in both groups.The cognitive level and self-management ability of patients in the CN group were higher than those of the conventional nursing group(P<0.05).The overall satisfaction of the CN group was better than that of the conventional nursing group(98%vs 86%,P<0.05).CONCLUSION Community public health care based on conventional care of T2DM can achieve better blood sugar control,and improve patients’health cognitive level and self-management ability.

Posttraumatic stress symptoms among Chinese university students during the COVID-19 pandemic:Prevalence,correlates,and mental health help-seeking

BACKGROUND Revisiting the epidemiology of posttraumatic stress symptoms(PTSSs)among university students during the coronavirus disease 2019(COVID-19)pandemic as well as understanding the mental health help-seeking behavior of individuals with PTSSs has critical implications for public mental health strategies in future medical pandemics.AIM To investigate the prevalence and correlates of PTSSs among university students during the first wave of the COVID-19 pandemic in China and to examine mental health help-seeking behaviors among these students.METHODS A total of 2507 Chinese university students were recruited via snowball sampling.The students completed the Seven-item Screening Scale for Post-traumatic Stress Disorder during the first wave of the COVID-19 pandemic in China.Sociodemo-graphic characteristics,pandemic-related characteristics,and mental health help-seeking behaviors of students with PTSSs were also collected.RESULTS The prevalence of PTSSs among the participants was 28.0%.Seven significant correlates of PTSSs were identified(odds ratio=1.23-3.65,P≤0.024):Female sex,being 19 years old or older,living with others or alone,a low level of family economic status,fair or poor interpersonal relationships,severe or very severe local pandemic,and having family members diagnosed with COVID-19.However,only 3.28%of the students with PTSSs reported seeking help from mental health specialists.Among the 23 students who sought help from mental health specialists,13 opted for online or telephone-based psychological consultation.CONCLUSION Our data suggest that there was a high risk of PTSSs among university students and a high level of unmet mental health needs during the COVID-19 pandemic.The delivery of mental health services online or via telephone is a promising approach to address these unmet needs.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

Health anxiety and work loss in patients diagnosed with serrated polyposis syndrome:A cross sectional study

BACKGROUND Serrated polyposis syndrome(SPS)is a polyposis condition with neoplastic potential,but its psychological impact is not well understood.AIM To assess health anxiety prevalence in a regional Australian cohort of SPS patients and explore factors influencing it,including workforce impacts of regular surveillance.METHODS This cross-sectional study screened patients aged 18-65 undergoing colonoscopy in a regional gastroenterology practice between January 2015 and June 2022.Eligible SPS patients were invited to participate.Data included the Short Health Anxiety Inventory,employment status,and previous demographic and medical findings.RESULTS Health anxiety was found in 21.57%of SPS patients,with anxious patients being significantly more concerned about surveillance(OR=7.70).Patients lost an average of 11.04 work hours per colonoscopy.CONCLUSION Health anxiety in SPS patients aligns with rates in other gastroenterology populations.Identifying it may improve management,though further research is needed to better understand prevalence and care improvements.

Selenoprotein P1 as a biomarker of insulin resistance in pediatric obesity:Insights and implications

This editorial discusses the findings of Elbarky et al on the role of selenoprotein P1(SEPP1)in pediatric obesity and insulin resistance.Their study uncovered si-gnificantly lower SEPP1 Levels in children who were obese compared with hea-lthy peers,demonstrating a negative correlation between SEPP1 levels and mea-sures of adiposity and insulin resistance.These findings suggest that SEPP1 is a biomarker useful in the early identification of insulin resistance in pediatric populations.This editorial emphasizes the clinical implications of the study and calls for further research to validate and explore the role of SEPP1 in metabolic health.

Effect of dietary fibre on the gastrointestinal microbiota during critical illness:A scoping review

The systemic effects of gastrointestinal(GI)microbiota in health and during chronic diseases is increasingly recognised.Dietary strategies to modulate the GI microbiota during chronic diseases have demonstrated promise.While changes in dietary intake can rapidly change the GI microbiota,the impact of dietary changes during acute critical illness on the microbiota remain uncertain.Dietary fibre is metabolised by carbohydrate-active enzymes and,in health,can alter GI microbiota.The aim of this scoping review was to describe the effects of dietary fibre supplementation in health and disease states,specifically during critical illness.Randomised controlled trials and prospective cohort studies that include adults(>18 years age)and reported changes to GI microbiota as one of the study outcomes using non-culture methods,were identified.Studies show dietary fibres have an impact on faecal microbiota in health and disease.The fibre,inulin,has a marked and specific effect on increasing the abundance of faecal Bifidobacteria.Short chain fatty acids produced by Bifidobacteria have been shown to be beneficial in other patient populations.Very few trials have evaluated the effect of dietary fibre on the GI microbiota during critical illness.More research is necessary to establish optimal fibre type,doses,duration of intervention in critical illness.

Beyond statistical significance:Embracing minimal clinically important difference for better patient care

The minimal clinically important difference(MCID)represents a pivotal metric in bridging the gap between statistical significance and clinical relevance,addressing the direct impact of medical interventions from the patient's perspective.This comprehensive review analyzes the evolution,applications,and challenges of MCID across medical specialties,emphasizing its necessity in ensuring that clinical outcomes not only demonstrate statistical significance but also offer genuine clinical utility that aligns with patient expectations and needs.We discuss the evolution of MCID since its inception in the 1980s,its current applications across various medical specialties,and the methodologies used in its calculation,highlighting both anchor-based and distribution-based approaches.Furthermore,the paper delves into the challenges associated with the application of MCID,such as methodological variability and the interpretation difficulties that arise in clinical settings.Recommendations for the future include standardizing MCID calculation methods,enhancing patient involvement in setting MCID thresholds,and extending research to incorporate diverse global perspectives.These steps are critical to refining the role of MCID in patient-centered healthcare,addressing existing gaps in methodology and interpretation,and ensuring that medical interventions lead to significant,patient-perceived improvements.

Convergence of COVID-19 and recurrent stroke:In-hospital mortality risks explored

This editorial comments on the article by Desai et al,which investigates the impact of coronavirus disease 2019(COVID-19)on in-hospital mortality among patients with recurrent stroke using data from the 2020 National Inpatient Sample.The findings reveal significantly higher mortality rates in COVID-19-positive patients compared to non-COVID-19 patients,particularly among middle-aged individuals,males,and ethnic minorities.This editorial explores the underlying mechanisms contributing to these outcomes and discusses the clinical implications for targeted management strategies in high-risk groups.The results emphasize the need for comprehensive approaches to mitigate the heightened risks faced by recurrent stroke patients during the COVID-19 pandemic.

Reevaluating health metrics:Unraveling the limitations of disabilityadjusted life years as an indicator in disease burden assessment

In 1993,the World Bank released a global report on the efficacy of health promotion,introducing the disability-adjusted life years(DALY)as a novel indicator.The DALY,a composite metric incorporating temporal and qualitative data,is grounded in preferences regarding disability status.This review delineates the algorithm used to calculate the value of the proposed DALY synthetic indicator and elucidates key methodological challenges associated with its application.In contrast to the quality-adjusted life years approach,derived from multi-attribute utility theory,the DALY stands as an independent synthetic indicator that adopts the assumptions of the Time Trade Off utility technique to define Disability Weights.Claiming to rely on no mathematical or economic theory,DALY users appear to have exempted themselves from verifying whether this indicator meets the classical properties required of all indicators,notably content validity,reliability,specificity,and sensitivity.The DALY concept emerged primarily to facilitate comparisons of the health impacts of various diseases globally within the framework of the Global Burden of Disease initiative,leading to numerous publications in international literature.Despite widespread adoption,the DALY synthetic indicator has prompted significant methodological concerns since its inception,manifesting in inconsistent and non-reproducible results.Given the substantial diffusion of the DALY indicator and its critical role in health impact assessments,a reassessment is warranted.This reconsideration is imperative for enhancing the robustness and reliability of public health decisionmaking processes.

Physiology and health assessment,risk balance,and model for endstage liver disease scores:Postoperative outcome of liver transplantation

BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.