bluuebunny/crossref_metadata_2025 huggingface dataset:
Validating a composite endpoint for acceptability evaluation of oral drug formulations in the pediatric population: a randomized, open-label, single dose, cross-over study
Authors: Münch Juliane , Schwarzwälder Anna Lena , Kloft Carolin , Bosse Hans Martin , Wargenau Manfred , Reidemeister Sibylle , Klingmann Ingrid , Klingmann Viviane
Published: August 2024

Objective

This study aimed to validate the newly developed composite acceptability endpoint to investigate acceptability of oral pediatric drug formulations that integrates swallowability and palatability assessments.

Methods

In this open-label study acceptability of oral formulations was tested in three age groups (1–<6 months, 6–<12 years, and 12–<18 years) with a 2-way cross-over design in children aged 1–<6 months (syrup and mini-tablets), and with an incomplete block design of four sequences with three out of four formulations (syrup, mini-tablets, oblong tablet, and round tablet) each in children aged 6–<18 years. The primary endpoint was acceptability derived from the composite acceptability endpoint. Secondary endpoints were palatability and acceptability derived from swallowability.

Results

A total of 320 children were stratified into three age groups (80 children aged 1–<6 months, 120 children aged 6–<12 years, and 120 children aged 12–<18 years). All participants completed the study. Age-specific differences were observed in acceptability derived from the composite acceptability endpoint. Mini-tablets had the highest acceptability in participants aged 1–<6 months and 6–<12 years while the oblong tablet was leading in adolescent participants (12–<18 years).

Conclusion

This study demonstrated that the composite acceptability endpoint method integrating both swallowability and palatability assessments is a sensitive method to assess acceptability of drug formulations in children of different age.

Clinical Trial Registration

https://drks.de/search/de, identifier DRKS00027948.
Graduate public health student learning experiences, social connectedness, and mental health during COVID-19: pedagogical implications for public health academic departments
Authors: Agroia Harit , Berkowitz Rachel , Carter Andrew , Gomez Vicky , Allen Monica
Published: August 2024

Introduction

The COVID-19 pandemic impacted college student learning both globally and nationally. Current literature points to decreases in social connectedness, adverse mental health outcomes, and decreased overall learning outcomes; however, there are limited findings from higher education institutions within the Bay Area, California. There are also limited studies that examine the COVID-19 impact among public health graduate students, especially to understand how the pandemic renewed their interest in the field. The purpose of this study was to investigate the effects of COVID-19 on graduate student learning experiences, social connectedness and mental health within the Master of Public Health program at San José State University in San Jose, California.

Methods

We employed a convergent mixed-methods design using a survey that quantitatively assessed student learning experiences through a retrospective pre-and post-design, and a semi-structured interview guide that qualitatively assessed student learning experiences and its relationship with mental health and social connectedness using a phenomenological design. Data were collected between September 2022 and June 2023 and analysis was performed using descriptive statistics and thematic analysis.

Results

A total of 22 students completed the survey and four participated in follow-up semi-structured interviews. Of the 22, 12(54%) were among the 18–29-year age group, 9(41%) identified as Asian, 21(95%) identified as female, and 9(41%) identified as a first-generation college student. When comparing survey responses, the median change in learning experiences pre and during-pandemic were statistically significant across several areas such as student ability to stay organized (p < 0.0001), participate actively in class (p < 0.001), retain course material (p < 0.0001), collaborate with peers (p < 0.0001), and maintain a sense of connection with their cohort (p = 0.0001) and broader campus community (p < 0.0001). Semi-structured interviews further revealed the following six themes: (1) Consistent faculty support; (2) Sense of community; (3) Reduced social connectedness; (4) Impact on mental health; (5) Deeper public health understanding; and (6) Facilitators and barriers.

Conclusion

Educational practitioners are encouraged to offer hybrid academic programs and establish resource infrastructures that provide students with social and mental wellness support when transitioning to different learning modalities.
Procrastination and risky health behaviors: a possible way to nurture health promotion among young adults in Italy
Authors: Licata Francesca , Citrino Emma Antonia , Maruca Riccardo , Di Gennaro Gianfranco , Bianco Aida
Published: August 2024

Background

The study’s main objectives were to evaluate the distribution of levels of procrastination and its relationship with sleep quality, smoking status, alcohol consumption, and skipping breakfast, as a proxy measure of an unhealthy dietary pattern, among Italian university students.

Methods

A cross-sectional study was conducted at the “Magna Græcia” University of Catanzaro in the Southern part of Italy, using stratified random sampling techniques. Eligible students were sent an anonymous online survey aimed at assessing sociodemographic characteristics, procrastination levels using the Pure Procrastination Scale, sleep quality using Pittsburgh Sleep Quality Index, smoking status, alcohol consumption using WHO’s Alcohol Use Disorders Identification Tool, and breakfast habits.

Results

The study included 518 participants with a mean age of 23 year. More than half of the sample was enrolled in medicine or life science majors and the procrastination mean score was 15 (±5.9 SD). Being procrastinators was significantly more frequently among students who were poor sleepers, hazardous alcohol consumers and breakfast skippers. When analyzing the clustering of risky behaviors, it was found that as the number of risky behaviors increased, the procrastination score exhibited an exponential increase.

Conclusion

The study findings showed that university students who engage in procrastination tend to adopt risky health behaviors. The data gathered could be useful to derive targeted interventions aimed at groups more exposed to harmful health behaviors and to encourage institutional policies to promote healthy lifestyles within universities. Universities can act as hubs for cultivating a culture of well-being and promoting a healthy environment.
Participatory mapping of transboundary pollution: the case of Imperial Beach, California
Authors: Maione Carol , Fernandez Gabriela , Vito Domenico
Published: August 2024

Introduction

Transboundary pollution is a major global challenge and monitoring beach litter along international borders can reveal some of the pathways by which litter enters water bodies, and hence advance the implementation of measures to prevent pollution emissions into international waters.

Methods

In this paper, participatory mapping was used to detect beach litter in Imperial Beach, California, along the U.S.-Mexico international border. This study implemented a 3-step protocol including an introductory awareness workshop, a macro-debris survey to categorize and remove beach litter, and a qualitative assessment of pollution drivers.

Results

Results show that plastic litter is the most dominant across all transects (304 debris, 52.6% of all litter observations), with an average density of 76 pieces/transect, with plastic being the most common material. Participants identified some of the major causes of pollution with paucity of waste management facilities, tourism activities near/on the beach, and inflow of pollution across the border.

Discussion

The paper highlights the role of citizen science in monitoring pollution along large and border regions. Implications of this study include methodological and practical contributions to the study of marine pollution to supplement the current paucity of information on pollution movement and distribution.
Gender Budgeting: A Contextual Analysis of the Higher-Education Sector in Albania
Authors: Llaftiu Brunilda , Shuli Ingrid
Published: August 2024

In this study, we chose to conduct a gender-based contextual analysis of research-performing organizations (RPOs) in the higher-education sector in Albania as a first step toward the implementation of gender budgeting (GB). Our rationale for conducting such a contextual analysis is the overarching need to achieve the European Commission’s strategic objectives regarding gender equality in research and innovation. To carry out this analysis, we used reports from She Figures to calculate dominant gender indicators; these reports were produced in collaboration with the statistics published by the Institute of Statistics of Albania. Our methodology is based on a mixed-methods approach that aims to better our understanding of the situation in Albania. The quantitative findings provided by our contextual analysis within academia were synthesized with qualitative findings resulting from a comparative analysis of the content of gender equality plans (GEPs) currently being implemented by thirteen universities in Albania. The results of our contextual analysis study show that even though women account for more than half of the total population of researchers at the national level, playing a significant role in research and innovation, we recommend that the government develop its first national GEP to counteract the inequality that persists in the career trajectories of women and men. GB represents an effective strategy for reducing gender inequality in this context. The supporting results of the content analysis indicate that the phenomenon of vertical segregation has been identified in the great majority of RPOs that have carried out gender-based contextual analyses; moreover, we observed the interaction of GB with GEPs within three such organizations’ approach to the gender-based allocation of finances.
Correction: Grabow et al. Triggering and Characterisation of Realistic Internal Short Circuits in Lithium-Ion Pouch Cells—A New Approach Using Precise Needle Penetration. Batteries 2023, 9, 496
Authors: Grabow Jens , Klink Jacob , Orazov Nury , Benger Ralf , Hauer Ines , Beck Hans-Peter
Published: August 2024

The authors wish to make the following corrections to their paper [...]
Feasibility Study of Edge Computing Empowered by Artificial Intelligence—A Quantitative Analysis Based on Large Models
Authors: Chen Yan , Wu Chaonan , Sui Runqi , Zhang Jingjia
Published: August 2024

The advancement of artificial intelligence (AI) demands significant data and computational resources that have an adverse impact on the environment. To address this issue, a novel computing architecture that is both energy efficient and eco-friendly is urgently required. Edge computing has emerged as an increasingly popular solution to this problem. In this study, we explore the development history of edge computing and AI and analyze the potential of model quantization to link AI and edge computing. Our comparative analysis demonstrates that the quantization approach can effectively reduce the model’s size and accelerate model inference while maintaining its functionality, thereby enabling its deployment on edge devices. This research serves as a valuable guide and reference for future advancements in edge AI.
Beat-by-Beat Estimation of Hemodynamic Parameters in Left Ventricle Based on Phonocardiogram and Photoplethysmography Signals Using a Deep Learning Model: Preliminary Study
Authors: Mi Jiachen , Feng Tengfei , Wang Hongkai , Pei Zuowei , Tang Hong
Published: August 2024

Beat-by-beat monitoring of hemodynamic parameters in the left ventricle contributes to the early diagnosis and treatment of heart failure, valvular heart disease, and other cardiovascular diseases. Current accurate measurement methods for ventricular hemodynamic parameters are inconvenient for monitoring hemodynamic indexes in daily life. The objective of this study is to propose a method for estimating intraventricular hemodynamic parameters in a beat-to-beat style based on non-invasive PCG (phonocardiogram) and PPG (photoplethysmography) signals. Three beagle dogs were used as subjects. PCG, PPG, electrocardiogram (ECG), and invasive blood pressure signals in the left ventricle were synchronously collected while epinephrine medicine was injected into the veins to produce hemodynamic variations. Various doses of epinephrine were used to produce hemodynamic variations. A total of 40 records (over 12,000 cardiac cycles) were obtained. A deep neural network was built to simultaneously estimate four hemodynamic parameters of one cardiac cycle by inputting the PCGs and PPGs of the cardiac cycle. The outputs of the network were four hemodynamic parameters: left ventricular systolic blood pressure (SBP), left ventricular diastolic blood pressure (DBP), maximum rate of left ventricular pressure rise (MRR), and maximum rate of left ventricular pressure decline (MRD). The model built in this study consisted of a residual convolutional module and a bidirectional recurrent neural network module which learnt the local features and context relations, respectively. The training mode of the network followed a regression model, and the loss function was set as mean square error. When the network was trained and tested on one subject using a five-fold validation scheme, the performances were very good. The average correlation coefficients (CCs) between the estimated values and measured values were generally greater than 0.90 for SBP, DBP, MRR, and MRD. However, when the network was trained with one subject’s data and tested with another subject’s data, the performance degraded somewhat. The average CCs reduced from over 0.9 to 0.7 for SBP, DBP, and MRD; however, MRR had higher consistency, with the average CC reducing from over 0.9 to about 0.85 only. The generalizability across subjects could be improved if individual differences were considered. The performance indicates the possibility that hemodynamic parameters could be estimated by PCG and PPG signals collected on the body surface. With the rapid development of wearable devices, it has up-and-coming applications for self-monitoring in home healthcare environments.
Correction: Oglat et al. The Effect of an Energy Window with an Ellipsoid Phantom on the Differential Defect Contrast on Myocardial SPECT Images. Bioengineering 2022, 9, 341
Authors: Oglat Ammar A. , Sayah Mohannad Adel , Kabir Norlaili A.
Published: August 2024

Norlaili A [...]
Metabolic Changes Following Smoking Cessation in Patients with Type 2 Diabetes Mellitus
Authors: Driva Stamatina , Korkontzelou Aliki , Tonstad Serena , Tentolouris Nikolaos , Litsiou Eleni , Vasileiou Vasiliki , Vassiliou Alice G. , Saltagianni Vassiliki , Katsaounou Paraskevi
Published: August 2024

Background: Smoking cessation is crucial for reducing complications of type 2 diabetes mellitus (T2DM), but associated weight gain can worsen glycemic control, discouraging quitting attempts. Varenicline, a partial agonist of α4β2 nicotinic receptors, aids smoking cessation. This study examines the effects of varenicline on body weight and metabolic parameters in patients with T2DM and prediabetes. Methods: Fifty-three patients were enrolled, of which 32 successfully quit smoking after a three-month course of varenicline and were examined after an additional month with no medication. Measurements taken at baseline, 2.5 months, and 4 months included body weight, blood pressure, resting metabolic rate (RMR), glycated hemoglobin (HbA1c), fasting glucose, blood lipids, C-reactive protein (CRP), appetite-related hormones, and physical activity. Results: Post-treatment, there were no significant changes in body weight, blood pressure, RMR, or glycemic control. Total (CHOL) and low-density lipoprotein (LDL-C) cholesterol decreased significantly at 4 months of the study (from 168 to 156 mg/dL, p = 0.013, and from 96 to 83 mg/dL, p = 0.013, respectively). Leptin levels increased (from 11 to 13.8 ng/dL, p = 0.004), as did glucagon-like peptide-1 (GLP-1) levels (from 39.6 to 45.8 pM, p = 0.016) at 4 months of follow-up. The percentage of participants who reported moderate-intensity activity increased from 28% to 56%, while those reporting high-intensity activity increased from 19% to 22%, respectively (p = 0.039). Conclusions: Our study showed that smoking cessation with varenicline in smokers with T2DM and prediabetes led to significant improvements in lipid profile, significant increase in plasma leptin and GLP-1 levels, and increased physical activity, without significant weight gain. Thus, smoking cessation without weight gain or deteriorated glycemic control is feasible for these smokers, with added benefits to lipid profiles, GLP-1 regulation, and physical activity.
Unmasking Protein Phosphatase 2A Regulatory Subunit B as a Crucial Factor in the Progression of Dilated Cardiomyopathy
Authors: Lin Fang , Liang Xiaoting , Meng Yilei , Zhu Yuping , Li Chenyu , Zhou Xiaohui , Hu Sangyu , Yi Na , Lin Qin , He Siyu , Sun Yizhuo , Sheng Jie , Fan Huimin , Li Li , Peng Luying
Published: August 2024

Dilated cardiomyopathy (DCM) is one of the major causes of heart failure. Although significant progress has been made in elucidating the underlying mechanisms, further investigation is required for clarifying molecular diagnostic and therapeutic targets. In this study, we found that the mRNA level of protein phosphatase 2 regulatory subunit B’ delta (Ppp2r5d) was altered in the peripheral blood plasma of DCM patients. Knockdown of Ppp2r5d in murine cardiomyocytes increased the intracellular levels of reactive oxygen species (ROS) and inhibited adenosine triphosphate (ATP) synthesis. In vivo knockdown of Ppp2r5d in an isoproterenol (ISO)-induced DCM mouse model aggravated the pathogenesis and ultimately led to heart failure. Mechanistically, Ppp2r5d-deficient cardiomyocytes showed an increase in phosphorylation of STAT3 at Y705 and a decrease in phosphorylation of STAT3 at S727. The elevated levels of phosphorylation at Y705 in STAT3 triggered the upregulation of interleukin 6 (IL6) expression. Moreover, the decreased phosphorylation at S727 in STAT3 disrupted mitochondrial electron transport chain function and dysregulated ATP synthesis and ROS levels. These results hereby reveal a novel role for Ppp2r5d in modulating STAT3 pathway in DCM, suggesting it as a potential target for the therapy of the disease.
Predictors of Diabetic Retinopathy in Type 2 Diabetes: A Cross-Sectional Study
Authors: Ivanescu Adriana , Popescu Simona , Ivanescu Radu , Potra Monica , Timar Romulus
Published: August 2024

Background: Type 2 diabetes mellitus (T2DM) represents one of the most impacting health issues of the modern era, as it is associated with an extensive range of comorbidities. Diabetic retinopathy (DR) is one the utmost severe diabetes complications as it is one of the major causes of vision loss among these patients. Our present research aims to evaluate the most frequent risk factors related to the occurrence of DR in T2DM patients. Method: This study consisted of a research group of 302 participants, priorly diagnosed with T2DM, that were evaluated for the most important risk factors related to the occurrence of DR. Results: Patients had a median age of 64 years, 48% of them being women, with a 12-year median duration of DM and presenting a deficient glycaemic control echoed by a median HbA1C value of 7.5%. From the total number of participants, the total prevalence of DR in different stages of severity was 34.8% with a 95% CI. Statistically significant values were found regarding DM duration (p = 0.007), HbA1c > 7.2% (p = 0.001) and patients aged over 67 years (p = 0.0035), all these parameters being directly linked to DR. Conclusions: Older patients with T2DM that have a longer disease duration and simultaneous comorbidities present a higher risk of DR development, consequently a stringent management of these pathologies is needed.
Effect of Menopausal Hormone Therapy on Cellular Immunity Parameters and Cytokine Profile
Authors: Averyanova Marina , Yureneva Svetlana , Kiseleva Viktoriia , Yakushevskaya Oksana , Iskusnykh Marina , Pavlova Anna , Elchaninov Andrey , Fatkhudinov Timur , Mikhanoshina Natalia , Ivanets Tatiana , Vtorushina Valentina , Krechetova Lyubov , Vishnyakova Polina , Sukhikh Gennady
Published: August 2024

Background: A woman’s entry into the menopause period is associated with a number of changes in the body, including those related to the immune system. Immune aging is a consequence of age-related changes in the function of immune cells and the composition of their subpopulations. Menopausal hormone therapy (MHT) is thought to partially neutralize the negative effects of aging on the immune system. Objective: We aimed to evaluate the effect of oral and transdermal MHT on cellular immunity parameters and cytokine profile in menopausal women. Methods: Fifty peri- and early postmenopausal women were included. Immune parameters were assessed by flow cytometry and multiplex analysis. Results: We showed that different routes of MHT administration led to significant changes in monocyte phenotype and a decrease in monocyte chemoattractant protein-1 (MCP-1) level in menopausal patients. In addition, oral MHT resulted in a significant increase in NK and B cells. A significant increase in the number of T-helper cells was observed with transdermal MHT. In addition, oral MHT resulted in a significant decrease in IL-1β level. Conclusions: We have demonstrated for the first time that oral therapy, in contrast to transdermal therapy, has a more pronounced effect on specific immune subpopulations of blood cells in menopausal women. This effect is likely to be responsible for its anti-aging properties in the context of immune aging as well as its protective effects in infectious diseases. Perhaps testing blood immune parameters or assessing immune status before prescribing MHT could become a routine step in clinical practice before choosing a patient management strategy.
Exploring Stress and Coping in Caregivers of Children with Pulmonary Vein Stenosis: A Mixed-Method Study
Authors: Fuller Mark , Ireland Christina , Zmora Rachel , Jenkins Kathy
Published: August 2024

(1) Background: This mixed-method study aims to identify and describe factors associated with acute and long-term parenting stressors and coping strategies in caregivers of children with intraluminal pulmonary vein stenosis (PVS). (2) Methods: Parents of children with severe PVS were recruited from a large quaternary hospital to complete a survey that included demographics, the Pediatric Inventory for Parents (PIP), and the Coping Health Inventory for Parents (CHIP). We determined the Social Vulnerability Index (SVI) based on self-reported home address. A subset of caregivers completed a 60 min semi-structured interview via Zoom exploring the impact their child’s diagnosis had on their family; experience managing stress in the hospital and at home; current resources and processes for coping; and potential recommendations for hospitals to build resilience and coping. We used multivariable linear regression to examine the association between SVI and parental stress and coping while adjusting for possible confounders. Thematic analysis identified themes related to stress and coping. Finally, we assessed instances of convergence and difference between the qualitative and quantitative results. (3) Results: Participants included 32 caregivers who were 91% female with a mean age of 39 years. The children of participants were 66% female, with a mean age of five years. The parents reported a high amount of stress with an average PIP score of 120, nearly 46 points higher than similar studies in the congenital heart community. We observed no significant associations between SVI and either parental stress or coping in adjusted models. We identified 13 themes, including medical care, hospital, family, support systems, and home medical routine or support. (4) Conclusions: Our study found high levels of illness-related parental stress among caregivers of children with PVS. Stress evolved over time from what caregivers described as ‘survival mode’ to a future-oriented outlook. Currently, caregivers rely heavily on support networks that are not available to all caregivers or may experience strain over time. Caregivers indicated that communication and parental role functioning were coping strategies that could be better supported by providers and health systems.
Cytomegalovirus, a “Friend” of SARS-CoV-2: A Case Report
Authors: Tomşa Nicoleta-Ana , Meliţ Lorena Elena , Bucur Gabriela , Văsieșiu Anca-Meda , Mărginean Cristina Oana
Published: August 2024

Introduction: Cytomegalovirus (CMV) infection is present in a latent state in 70–90% of the immunocompetent population, and its reactivation might be triggered by inflammatory conditions such as post-COVID multisystem inflammatory syndrome (MIS-C) or by immunosuppression induced by steroids. The aim of this paper was to highlight the unexpected complications associated with SARS-CoV-2 infection that require a complex clinical approach for accurate diagnosis. Materials and Methods: We present the case of a 4-year-old male patient who, during an initially favorable course of PIMS, experienced symptoms of respiratory failure. Results: The patient initially presented with clinical and paraclinical signs of PIMS with cardiac involvement, for which high-dose corticosteroid therapy was initiated, followed by gradual tapering, along with immunoglobulins, anticoagulants, antiplatelet agents, and symptomatic treatment. After 10 days of favorable progress, the patient’s general condition deteriorated, showing tachypnea, desaturation, and a ground-glass appearance on thoracic CT. Negative inflammatory markers and favorable cardiac lesion evolution ruled out MIS-C relapse. The presence of anti-CMV IgM antibodies and viral DNA in the blood confirmed acute CMV infection, likely triggered by prior severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2) infection and secondary immunosuppression due to steroids. Non-specific immunomodulatory treatment was initiated but led to worsening of pulmonary lesions, prompting the initiation of specific antiviral treatment with ganciclovir, resulting in rapid clinical and imaging improvement. Conclusions: CMV infection can be reactivated by immunosuppression induced by corticosteroid therapy for MIS-C and may require specific etiological treatment.
The Solution Combustion Synthesis of ZnO Nanoparticles Using Allium schoenoprasum (Chives) as a Green Fuel
Authors: Sheibani Elyas , Soltani Alasvand Saman , Sami Neda , Vahdati Khaki Jalil , Mollazadeh Beidokhti Sahar
Published: August 2024

Zinc oxide (ZnO) nanoparticles are widely recognized for their distinctive properties and versatile applications across diverse technological domains. However, traditional methods of synthesizing ZnO nanoparticles are characterized by environmental incompatibility, high costs, and the necessity for precise process control to attain the intended particle dimensions and morphology. The present study utilized a chives extract as a sustainable and eco-friendly fuel in the solution combustion synthesized (SCS) process to produce ZnO nanoparticles. The investigation encompassed an analysis of the impact of the fuel-to-oxidizer (F/O) ratio on the synthesized ZnO nanoparticles’ size, morphology, and crystallinity. X-ray diffraction (XRD) results showed that the particle’s crystallite size increased significantly from 12 nm to 42 nm after decreasing the F/O ratio. Furthermore, electron microscopic imagery and FTIR spectroscopy outcomes indicated that modifications in the F/O ratio significantly influenced the SCS process parameters, forming particles with diverse morphologies, including spherical, pyramid-like, hexagonal, and hexagonal plate-like shapes. This research presents a straightforward, cost-efficient, and environmentally sustainable approach for producing ZnO nanoparticles with diverse morphologies, presenting a broad potential for various applications.
Association between Glycosylated Hemoglobin Levels and Vaccine Preventable Diseases: A Systematic Review
Authors: De Vita Elda , Limongi Federica , Veronese Nicola , Di Gennaro Francesco , Saracino Annalisa , Maggi Stefania
Published: August 2024

People with diabetes are at higher risk of serious complications from many vaccine-preventable diseases (VPDs). Some studies have highlighted the potential impact of glycosylated hemoglobin levels (HbA1c), but no systematic review has synthesized these findings. Of the 823 identified studies, 3 were included, for a total of 705,349 participants. Regarding the incidence of herpes zoster (HZ), one study found that higher HbA1c levels at the baseline (>10.3%) were associated with a significantly higher risk of HZ of 44%, compared to those with a good HbA1c control (6.7%). On the contrary, the second one reported that when compared to the reference group (HbA1c of 5.0–6.4%), participants with a HbA1c less than 5.0% were at higher risk of HZ of 63%, whilst participants with a HBA1c more than 9.5% had a similar risk. Finally, the third study observed that diabetes, defined using a value of HbA1c more than 7.5%, was associated with an increased risk of mortality in men with COVID-19. In conclusion, both high and low HBA1c levels appear to be associated with a higher risk of HZ. Regarding COVID-19, a value of HbA1c more than 7.5% was associated with a higher risk of death in COVID-19, but only in men.
Multi-Unmanned Aerial Vehicles Cooperative Trajectory Optimization in the Approaching Stage Based on the Attitude Correction Algorithm
Authors: Shi Haoran , Lu Junyong , Li Kai , Wu Pengfei , Guo Yun
Published: August 2024

This study investigated the problem of multi-UAVs cooperative trajectory optimization for remote maritime targets in the approach phase. First, based on the precise location information of the cooperative target, a real-time algorithm for correcting UAV attitude angles is proposed to reduce the impact of UAV attitude angle errors and observation system errors on target positioning accuracy. Then, the attitude correction algorithm is integrated into the interacting multiple model-cubature information filter (IMM-CIF) algorithm to achieve the fusion of multi-UAVs observation information. Furthermore, an improved receding horizon optimization (RHO) method is employed to plan the cooperative observation trajectories for UAVs in real time at the target approaching stage. Finally, numerical simulations are conducted to examine the proposed attitude correction and trajectory optimization algorithm, verifying the effectiveness of the proposed method and enhancing the tracking accuracy of the remote target.
A Comparative Study of Machine Learning Models for Predicting Meteorological Data in Agricultural Applications
Authors: Šuljug Jelena , Spišić Josip , Grgić Krešimir , Žagar Drago
Published: August 2024

This study aims to address the challenges of climate change, which has led to extreme temperature events and reduced rainfall, using Internet of Things (IoT) technologies. Specifically, we monitored the effects of drought on maize crops in the Republic of Croatia. Our research involved analyzing an extensive dataset of 139,965 points of weather data collected during the summer of 2022 in different areas with 18 commercial sensor nodes using the Long-Range Wide Area Network (LoRaWAN) protocol. The measured parameters include temperature, humidity, solar irradiation, and air pressure. Newly developed maize-specific predictive models were created, taking into account the impact of urbanization on the agrometeorological parameters. We also categorized the data into urban, suburban, and rural segments to fill gaps in the existing literature. Our approach involved using 19 different regression models to analyze the data, resulting in four regional models per parameter and four general models that apply to all areas. This comprehensive analysis allowed us to select the most effective models for each area, improving the accuracy of our predictions of agrometeorological parameters and helping to optimize maize yields as weather patterns change. Our research contributes to the integration of machine learning and AI into the Internet of Things for agriculture and provides innovative solutions for predictive analytics in crop production. By focusing on solar irradiation in addition to traditional weather parameters and accounting for geographical differences, our models provide a tool to address the pressing issue of agricultural sustainability in the face of impending climate change. In addition, our results have practical implications for resource management and efficiency improvement in the agricultural sector.
ESG-Driven Investment Decisions in Photovoltaic Projects
Authors: Wei Ruolan , Ma Yunlong , Bi Huina , Dong Qi
Published: August 2024

As global climate change intensifies and environmental awareness increases, investing in renewable energy has become a primary economic and social development priority. Photovoltaic (PV) projects, as a clean and sustainable energy technology, have garnered significant attention due to their notable environmental and economic benefits. However, traditional investment evaluation methods such as net present value (NPV) analysis fail to adequately capture the flexibility and future uncertainties inherent in PV project investments. This paper presents a case study analysis proposing a delay option model that incorporates environmental, social, and governance (ESG) factors, providing a more scientific and flexible investment decision framework for PV projects. The case study results indicate that considering ESG factors significantly enhances the investment value of PV projects. This model not only provides comprehensive support for PV project investment decisions but also underscores the importance of establishing stringent carbon trading markets and policy incentive mechanisms to promote the widespread adoption and sustainable development of renewable energy projects.
Enhancing the Nutritional Quality of Defatted Cottonseed Meal by Solid-State Fermentation with Probiotic Microbes
Authors: Lin Jicong , Zhang Jingxian , Zou Gen , Zhang Xiaoling , Shang Haihong , Ji Boyang , Bai Yueyu , Qu Lingbo , Wei Yongjun
Published: August 2024

Defatted cottonseed meal (DCSM), a byproduct of the cotton industry, is highly regarded for its high protein content, making it a source of nutrients in animal feed. Traditional physical and chemical treatments of DCSM can lead to a reduction in nutrient content and the presence of residual organic solvents. Probiotic fermentation of DCSM offers several advantages, including degradation of anti-nutritional factors, an increase in nutrient content, and production of beneficial metabolites. This study employed probiotic fermentation of DCSM using a probiotic microbe collection composed of Saccharomyces cerevisiae, Enterococcus faecium, and Lactiplantibacillus plantarum. This fermentation process significantly enhanced the nutritional quality of DCSM. Specifically, the contents of crude protein, free amino acid, total phosphorus, and moisture increased by 1.14-fold, 1.14-fold, 1.24-fold, and 3-fold, respectively. In the meanwhile, there was a substantial reduction in the content of dry matter, crude ash, and crude fat, with decreases of 27.83%, 25.74%, and 88.23%, respectively. Probiotic fermentation of DCSM resulted in an overall enhancement of the palatability of DCSM. This study provides valuable insights into the potential of mixed probiotic fermentation as a promising approach for improving the nutritional quality of DCSM.
Hydrogen Production from Sugarcane Bagasse Pentose Liquor Fermentation Using Different Food/Microorganism and Carbon/Nitrogen Ratios under Mesophilic and Thermophilic Conditions
Authors: Mattiello-Francisco Luísa , Ferreira Filipe Vasconcelos , Peixoto Guilherme , Mockaitis Gustavo , Zaiat Marcelo
Published: August 2024

Hydrogen is a well-known clean energy carrier with a high energetic yield. Its versatility allows it to be produced in diverse ways, including biologically. Specifically, dark fermentation takes advantage of organic wastes, such as agro-industrial residues, to obtain hydrogen. One of these harmful wastes that is poorly discharged into streams is sugarcane bagasse pentose liquor (SBPL). The present study aimed to investigate hydrogen generation from SBPL fermentation in batch reactors by applying different food/microorganism (2–10 F/M) and carbon/nitrogen (10–200 C/N) ratios under mesophilic and thermophilic conditions. Biohydrogen was produced in all pentose liquor experiments along with other soluble microbial products (SMPs): volatile fatty acids (VFAs) (at least 1.38 g L−1 and 1.84 g L−1 by the average of C/N and F/M conditions, respectively) and alcohols (at least 0.67 g L−1 and 0.325 g L−1 by the average of C/N and F/M conditions, respectively). Thermophilic pentose liquor reactors (t-PLRs) showed the highest H2 production (H2 maximum: 1.9 ± 0.06 L in 100 C/N) and hydrogen yield (HY) (1.9 ± 0.54 moles of H2 moles of substrate−1 in 2 F/M) when compared to mesophilic ones (m-PLRs). The main VFA produced was acetate (>0.85 g L−1, considering the average of both nutritional conditions), especially through the butyrate pathway, which was the most common metabolic route of experimental essays. Considering the level of acid dilution used in the pretreatment of bagasse (H2SO4 (1%), 1.1 atm, 120 °C, 60 min), it is unlikely that toxic compounds such as furan derivatives, phenol-like substances (neither was measured), and acetate (<1.0 g L−1) hinder the H2 production in the pentose liquor reactors (PLRs). Sugarcane bagasse pentose liquor fermentation may become a suitable gateway to convert a highly polluting waste into a renewable feedstock through valuable hydrogen production.
CR-YOLOv9: Improved YOLOv9 Multi-Stage Strawberry Fruit Maturity Detection Application Integrated with CRNET
Authors: Ye Rong , Shao Guoqi , Gao Quan , Zhang Hongrui , Li Tong
Published: August 2024

Strawberries are a commonly used agricultural product in the food industry. In the traditional production model, labor costs are high, and extensive picking techniques can result in food safety issues, like poor taste and fruit rot. In response to the existing challenges of low detection accuracy and slow detection speed in the assessment of strawberry fruit maturity in orchards, a CR-YOLOv9 multi-stage method for strawberry fruit maturity detection was introduced. The composite thinning network, CRNet, is utilized for target fusion, employing multi-branch blocks to enhance images by restoring high-frequency details. To address the issue of low computational efficiency in the multi-head self-attention (MHSA) model due to redundant attention heads, the design concept of CGA is introduced. This concept aligns input feature grouping with the number of attention heads, offering the distinct segmentation of complete features for each attention head, thereby reducing computational redundancy. A hybrid operator, ACmix, is proposed to enhance the efficiency of image classification and target detection. Additionally, the Inner-IoU concept, in conjunction with Shape-IoU, is introduced to replace the original loss function, thereby enhancing the accuracy of detecting small targets in complex scenes. The experimental results demonstrate that CR-YOLOv9 achieves a precision rate of 97.52%, a recall rate of 95.34%, and an mAP@50 of 97.95%. These values are notably higher than those of YOLOv9 by 4.2%, 5.07%, and 3.34%. Furthermore, the detection speed of CR-YOLOv9 is 84, making it suitable for the real-time detection of strawberry ripeness in orchards. The results demonstrate that the CR-YOLOv9 algorithm discussed in this study exhibits high detection accuracy and rapid detection speed. This enables more efficient and automated strawberry picking, meeting the public’s requirements for food safety.
Metabolomic Approaches to Study the Potential Inhibitory Effects of Plantaricin Q7 against Listeria monocytogenes Biofilm
Authors: Liu Yinxue , Liu Yisuo , Hao Linlin , Cao Jiayuan , Jiang Lu , Yi Huaxi
Published: August 2024

Listeria monocytogenes is a serious pathogen and can exacerbate harmful effects through the formation of biofilm. Inhibition of or reduction in L. monocytogenes biofilm is a promising strategy to control L. monocytogenes in the food industry. In our previous study, it was found that plantaricin Q7 produced by Lactiplantibacillus plantarum Q7 could inhibit and reduce L. monocytogenes biofilm, but the specific mechanism remains unclear. In this study, the inhibitive and reduced activity of plantaricin Q7 on L. monocytogenes biofilm was investigated by metabolomics. The results showed that plantaricin Q7 inhibited the synthesis of L. monocytogenes biofilm mainly through purine metabolism and glycerol phospholipid metabolism, and the key differential metabolites included acetylcholine and hypoxanthine with a decrease in abundance from 5.80 to 4.85. In addition, plantaricin Q7 reduced the formed L. monocytogenes biofilm by purine metabolism and arginine biosynthesis, and the main differential metabolites were N-acetylglutamate and D-ribose-1-phosphate with a decrease in abundance from 6.21 to 4.73. It was the first report that purine metabolism and amino acid metabolism were the common metabolic pathway for plantaricin Q7 to inhibit and reduce L. monocytogenes biofilm, which could be potential targets to control L. monocytogenes biofilm. A putative metabolic pathway for L. monocytogenes biofilm inhibition and reduction by plantaricin Q7 was proposed. These findings provided a novel strategy to control L. monocytogenes biofilm in food processing.
The Preharvest Application of Stress Response Elicitors Improves the Content of Bioactive Compounds without Modifying the Sensory Attributes of Butterhead Lettuce (Lactuca sativa var. capitata)
Authors: de la Rosa Laura A. , Moreno-Escamilla Jesus Omar , Martínez-Ruiz Nina del Rocío , Alvarez-Parrilla Emilio , González-Aguilar Gustavo A. , Rodrigo-García Joaquín
Published: August 2024

Using stress elicitors in fruits and vegetables is considered a good strategy to increase the content of bioactive compounds in plant foods. However, bioactive compounds can affect the sensory characteristics of food products, and little is known about their shelf-life stability in fresh produce treated with elicitors. In the present work, carotenoids and polyphenols were quantified by spectrophotometric methods in red and green butterhead lettuce treated with elicitors that had previously been demonstrated to increase bioactive compounds: arachidonic acid (AA), methyl jasmonate (MJ), and Harpin protein (HP). The bioactive compounds were determined immediately and during three weeks after harvest. A descriptive sensory analysis was carried out, which included odor, taste, tactile, and visual attributes of control and elicitor-treated lettuce. Carotenoids showed greater shelf-life stability than polyphenols, and both were more stable in red than in green lettuce during the first two weeks of storage. The best elicitor was MJ, which increased phenolic compounds (red and green lettuce), anthocyanins, and carotenoids (red lettuce) through the storage period. Color intensity, crispness, wettability, and bitter taste were some of the primary sensory attributes in butterhead lettuce and were not affected by any treatment. Other organoleptic properties were also not affected by the elicitors. These results suggest that elicitation could improve the content of bioactive compounds, which is stable through the shelf-life of butterhead lettuce, without any adverse effect on the sensory properties.
Black Mulberries (Morus nigra L.) Modulate Oxidative Stress and Beta-Amyloid-Induced Toxicity, Becoming a Potential Neuroprotective Functional Food
Authors: Cásedas Guillermo , Moliner Cristina , Abad-Longas Alba , Núñez Sonia , Gómez-Rincón Carlota , Maggi Filippo , López Víctor
Published: August 2024

Black mulberry (Morus nigra L.) is a common edible fruit from the Moraceae family with a wide variety of nutritional and medicinal applications, mainly due to its antioxidant and anti-inflammatory properties. The purpose of this work was to investigate the cytoprotective and neuroprotective capacity of a hydrophilic black mulberry solvent-free extract rich in polyphenols, including the antioxidant, antiradical, and enzymatic mechanisms that would explain these effects. Its neuroprotective potential was evaluated in vitro using the Neuro-2a cell line and in vivo through the Caenorhabditis elegans organism model. Neuro-2a cells were treated at different concentrations of the extract (25–500 µg/mL) and hydrogen peroxide (300 µM) as an oxidant agent, simultaneously. From these treatments, redox status (intracellular ROS production) and cellular activity (MTT) were also quantified in Neuro-2a. Regarding the C. elegans assay, the protection of the extract against β-amyloid toxicity was measured against the CL4176 strain, which is a model of Alzheimer disease. As a complementary neuroprotective assay, its potential to inhibit the monoamine oxidase A (MAO-A) enzyme was measured. In addition, an Artemia salina bioassay was performed for preliminary toxicity screening. And its antioxidant properties were evaluated by means of the FRAP assay. The results confirm its neuroprotective potential and its ability to scavenge free radicals and decrease ROS production, also acting as a moderate MAO-A inhibitor. Moreover, the polyphenolic extract alleviates the toxicity induced by β-amyloid accumulation in C. elegans. Concluding, Morus nigra can be considered a functional food with bioactive compounds that may prevent the onset of neurodegenerative diseases.
Olive Oil (Royal Cultivar) from Mill Obtained by Short Time Malaxation and Early Ripening Stage
Authors: Peralta Raúl , Espínola Francisco , Vidal Alfonso M. , Moya Manuel
Published: August 2024

The olive oil from the Royal cultivar has not been studied in depth, especially its relationship between analytical and sensory parameters. Currently, it is a minority cultivar, but due to its excellent organoleptic properties, it is constantly growing. The research objective is to obtain excellent-quality olive oil from the Royal cultivar at an industrial extraction plant and characterize the oil sensory and analytically. For this purpose, three important factors were set: very early olives; very low-time olive paste malaxation; and environmental temperature. The analytical parameters studied were volatile and phenolic compounds, fatty acids, photosynthetic pigments, and other quality parameters. Fourteen phenolic compounds were identified and found in significantly higher concentrations in Royal olive oil, including the oleacein compound. Moreover, volatile compounds from the LOX pathway, such as hexenal, (E)-2-hexenal, and (Z)-3-hexen-1-ol, had significantly higher concentrations, which were related to organoleptic characteristics: very fruity, not very spicy, and very low bitterness. The highest values obtained were 74.98% extraction efficiency at 30 min; 71.31 mg/kg chlorophyll content at 30 min; 156.38 mg/kg phenolic compound at 30 min; 18.98 mg/kg volatile compounds at 15 min; and better organoleptic characteristics at 15 min. The oil extraction efficiency was lower than that of other olive cultivars; nevertheless, the content of volatile compounds is higher.