bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of MIND diet and propolis supplementation on metabolic syndrome indices and cognitive function among patients with metabolic syndrome in Isfahan, Iran, 2024. A rationale and study protocol for randomized controlled trial
Authors: Gholami Zeinab , Maracy Mohammad Reza , Paknahad Zamzam 
Published: August 2024

AbstractMetabolic syndrome (MetS) is the main general and clinical health challenge worldwide. Based on the National Cholesterol Education Program, if the person has three or more indices containing: elevated fasting blood sugar, high levels of triglycerides, hypertension, low levels of high‐density lipoprotein cholesterol, and central obesity, he suffers MetS.The Mediterranean‐Dietary Approaches to Stop Hypertension (DASH) Intervention for Neurodegenerative Delay diet is a novel diet that with the specific aim of safeguarding cognitive function.Propolis is a resinous substance produced by bees from the combination of buds and secretions of plants with saliva and bee enzymes. After propolis supplementation, a significant reduction in fasting plasma glucose levels and lipid profiles has been observed.Considering the importance of chronic diseases like MetS on health, the role of the Mediterranean‐DASH Intervention for Neurodegenerative Delay (MIND) diet and propolis supplement that will improve blood sugar, blood lipid, anthropometric indicators, blood pressure, and cognitive function, and limited contradictory studies, we decided to conduct this study.This study, which is a randomized controlled clinical trial study, will be conducted on adults with MetS who will visit Hazrat Ali Health Center in Isfahan. Participants must provide informed consent before engaging in the study. Demographic data such as age, gender, and medical history will be recorded. Then, anthropometric indices, MetS indices, and cognitive function will be measured in all subjects.The study participants will be divided into three groups and will be controlled for 12 weeks. We will have a MIND diet + placebo group, a MIND diet + propolis supplement group, and a control group that will receive a microcrystalline cellulose placebo and usual dietary advice. At the end of the intervention, all indices will be assessed again.The data obtained in the study will be analyzed at descriptive and analytical levels by the statistical software SPSS26.The present study's protocol was approved by the Iranian Registry of Clinical Trials (www.irct.ir) on 3/28/2023 and a registration reference is IRCT20230105057054N1.
Machine learning-based life cycle assessment for environmental sustainability optimization of a food supply chain
Authors: Nikkhah Amin , Esmaeilpour Mahdi , Kosari-Moghaddam Armaghan , Rohani Abbas , Nikkhah Farima , Ghnimi Sami , Blackstone Nicole Tichenor , Van Haute Sam 
Published: August 2024

Abstract
Effective resource allocation in the agri-food sector is essential in mitigating environmental impacts and moving toward circular food supply chains. The potential of integrating life cycle assessment (LCA) with machine learning has been highlighted in recent studies. This hybrid framework is valuable not only for assessing food supply chains but also for improving them toward a more sustainable system. Yet, an essential step in the optimization process is defining the optimization boundaries, or minimum and maximum quantities for the variables. Usually, the boundaries for optimization variables in these studies are obtained from the minimum and maximum values found through interviews and surveys. A deviation in these ranges can impact the final optimization results. To address this issue, this study applies the Delphi method for identifying variable optimization boundaries. A hybrid environmental assessment framework linking LCA, multilayer perceptron artificial neural network, the Delphi method, and genetic algorithm was used for optimizing the pomegranate production system. The results indicated that the suggested framework holds promise for achieving substantial mitigation in environmental impacts (potential reduction of global warming by 46%) within the explored case study. Inclusion of the Delphi method for variable boundary determination brings novelty to the resource allocation optimization process in the agri-food sector. Integr Environ Assess Manag 2024;20:1759–1769. © 2024 SETAC
Key Points
Integrating life cycle assessment (LCA) with machine learning offers a robust method for optimizing food supply chains. The novel use of the Delphi methodology to define optimization bounds improves the accuracy of environmental impact reduction strategies. Applying a combination of LCA, machine learning, and Delphi can potentially reduce global warming potential (by 46%) in case of pomegranate production.
Multimodal Fusion for Enhanced Semantic Segmentation in Brain Tumor Imaging: Integrating Deep Learning and Guided Filtering Via Advanced 3D Semantic Segmentation Architectures
Authors: Saleh Abbadullah .H , Atila Ümit , Menemencioğlu Oğuzhan 
Published: August 2024

ABSTRACTBrain tumor segmentation is paramount in medical diagnostics. This study presents a multistage segmentation model consisting of two main steps. First, the fusion of magnetic resonance imaging (MRI) modalities creates new and more effective tumor imaging modalities. Second, the semantic segmentation of the original and fused modalities, utilizing various modified architectures of the U‐Net model. In the first step, a residual network with multi‐scale backbone architecture (Res2Net) and guided filter are employed for pixel‐by‐pixel image fusion tasks without requiring any training or learning process. This method captures both detailed and base elements from the multimodal images to produce better and more informative fused images that significantly enhance the segmentation process. Many fusion scenarios were performed and analyzed, revealing that the best fusion results are attained when combining T2‐weighted (T2) with fluid‐attenuated inversion recovery (FLAIR) and T1‐weighted contrast‐enhanced (T1CE) with FLAIR modalities. In the second step, several models, including the U‐Net and its many modifications (adding attention layers, residual connections, and depthwise separable connections), are trained using both the original and fused modalities. Further, a “Model Selection‐based” fusion of these individual models is also considered for more enhancement. In the preprocessing step, the images are resized by cropping them to decrease the pixel count and minimize background interference. Experiments utilizing the brain tumor segmentation (BraTS) 2020 dataset were performed to verify the efficiency and accuracy of the proposed methodology. The “Model Selection‐based” fusion model achieved an average Dice score of 88.4%, an individual score of 91.1% for the whole tumor (WT) class, an average sensitivity score of 86.26%, and a specificity score of 91.7%. These results prove the robustness and high performance of the proposed methodology compared to other state‐of‐the‐art methods.
Breaking Barriers in Cancer Diagnosis: Super‐Light Compact Convolution Transformer for Colon and Lung Cancer Detection
Authors: Maurya Ritesh , Pandey Nageshwar Nath , Karnati Mohan , Sahu Geet 
Published: August 2024

ABSTRACTAccording to the World Health Organization, lung and colon cancers are known for their high mortality rates which necessitate the diagnosis of these cancers at an early stage. However, the limited availability of data such as histopathology images used for diagnosis of these cancers, poses a significant challenge while developing computer‐aided detection system. This makes it necessary to keep a check on the number of parameters in the artificial intelligence (AI) model used for the detection of these cancers considering the limited availability of the data. In this work, a customised compact and efficient convolution transformer architecture, termed, C3‐Transformer has been proposed for the diagnosis of colon and lung cancers using histopathological images. The proposed C3‐Transformer relies on convolutional tokenisation and sequence pooling approach to keep a check on the number of parameters and to combine the advantage of convolution neural network with the advantages of transformer model. The novelty of the proposed method lies in efficient classification of colon and lung cancers using the proposed C3‐Transformer architecture. The performance of the proposed method has been evaluated on the ‘LC25000’ dataset. Experimental results shows that the proposed method has been able to achieve average classification accuracy, precision and recall value of 99.30%, 0.9941 and 0.9950, in classifying the five different classes of colon and lung cancer with only 0.0316 million parameters. Thus, the present computer‐aided detection system developed using proposed C3‐Transformer can efficiently detect the colon and lung cancers using histopathology images with high detection accuracy.
Optimizing cluster head selection for energy efficiency in wireless sensor networks: A hybrid algorithm combining grey wolf and enhanced sunflower optimization
Authors: Shah Indra Kumar , Rathaur Neha Singh , Dohare Yogendra Singh , Maity Tanmoy 
Published: August 2024

AbstractIn this letter, we introduce a novel cluster head selection algorithm namely mixed grey wolf and improved sunflower optimization algorithm (MGWISFO). This algorithm leverages both energy requirements and inter‐node distances to select cluster heads (CH). Within this algorithm, the Grey Wolf Optimizer facilitates exploration, offering a broader search, while the improved Sunflower Optimization focuses on exploitation, delivering a narrower search. This balance between exploration and exploitation leads to the identification of the optimal CH node, thereby enhancing network performance. To validate its effectiveness, the proposed algorithm is benchmarked against existing strategies such as particle swarm optimization (PSO), genetic algorithm (GA), grey wolf optimization (GWO), and sunflower optimization (SFO) across various performance parameters including throughput, the number of live and dead nodes, and residual energy. Simulation results unequivocally establish the unparalleled performance of our proposed algorithm, surpassing the capabilities of existing algorithms.
In silico analysis of endocrine‐disrupting potential of triclosan, bisphenol A, and their analogs and derivatives
Authors: Đurić Larisa , Milanović Maja , Drljača Lero Jovana , Milošević Nataša , Milić Nataša 
Published: August 2024

AbstractOwning to the increasing body of evidence about the ubiquitous exposure to endocrine disruptors (EDCs), particularly bisphenol A (BPA), and associated health effects, BPA has been gradually substituted with insufficiently tested structural analogs. The unmanaged excessive use of antimicrobial agents such as triclosan (TCS) during the COVID‐19 outbreak has also raised concerns about its possible interferences with hormonal functions. The similarity of BPA and estradiol, as well as TCS and non‐steroidal estrogens, imply that endocrine‐disrupting properties of their analogs could be predicted based on the chemical structure. Hence, this study aimed to evaluate the endocrine‐disrupting potential of BPA substitutes as well as TCS derivatives and degradation/biotransformation metabolites, in comparison to BPA and TCS based on their molecular properties, computational predictions of pharmacokinetics and binding affinities to nuclear receptors. Based on the obtained results several under‐researched BPA analogs exhibited higher binding affinities for nuclear receptors than BPA. Notable analogs included compounds detected in receipts (DD‐70, BTUM‐70, TGSA, and BisOPP‐A), along with a flame retardant, BDP. The possible health hazards linked to exposure to TCS and its mono‐hydroxylated metabolites were also found. Further research is needed in order to elucidate the health impacts of these compounds and promote better regulation practices.
Diet restriction enhances the effect of immune checkpoint block by inhibiting the intratumoral mTORC1/B7‐H3 axis
Authors: Xiao Duqing , Liu Tingting , Pan Youguang 
Published: August 2024

AbstractImmune checkpoint blockade therapy has demonstrated significant therapeutic efficacy in certain cancer types; however, the impact of dietary restriction remains scarcely reported in this context. This study aimed to investigate the influence of dietary restriction on anti‐PDL‐1 therapy and the interplay of immune cells within this context. Using an anti‐PDL‐1 regimen combined with dietary restrictions, tumor progression was assessed in LLC‐bearing mice. Flow cytometry was employed to analyze immune cell infiltration and differentiation levels within the tumor microenvironment. The expression of mTORC1/B7‐H3 in tumors subjected to dietary restriction was also examined. LLC tumors with elevated B7‐H3 expression were validated in mice to determine its inhibitory effect on immune cell proliferation and differentiation. A CD3/B7‐H3 chimeric antibody was developed for therapeutic intervention in B7‐H3 overexpressing tumors, with subsequent T cell responses assessed through flow cytometry. Dietary restriction potentiated the effect of anti‐PDL1 therapy by suppressing the intratumorally mTORC1/B7‐H3 axis. In vivo experiments demonstrated that elevated B7‐H3 expression in tumors reduced infiltration and activation of CD8 + T cells within the tumor, while it did not affect tumor‐infiltrating Tregs. In vitro studies revealed that high B7‐H3 expression influenced the proliferation and activation of CD8 + T cells within a Coculture system. The constructed CD3/B7‐H3 chimeric antibody prominently activated TCR within B7‐H3 overexpressing tumors and impeded tumor progression. The findings suggest that dietary restriction enhances the efficacy of immune checkpoint blockade by modulating the intratumoral mTORC1/B7‐H3 axis.
MiR‐494‐3p regulates skin fibroblast activities by mediating fibromodulin production
Authors: Zhao Feng , Wang Linshu , Zhang Yuxin , Tang Siqi , Ji Ping , Xiang Xuerong , Pang Xiaoxiao 
Published: August 2024

AbstractSkin wound healing is a well‐coordinated process in which various cells and factors participate, during which fibroblast exhibits a critical role by exerting its multiple activities, including proliferation, migration, invasion, and differentiation. Previous studies have identified that fibromodulin (FMOD) could enhance dermal wound healing by promoting skin fibroblast activities, but little is known about its upstream regulator. We occasionally found that FMOD expression was downregulated in skin fibroblast by transforming growth factor‐β1 treatment. It was hypothesized that microRNAs (miRNA) in skin fibroblast could downregulate FMOD production and blocking them would increase FMOD expression, as well as promote skin wound healing. Here, by utilizing combined analysis of miRNA microarray from the Gene Expression Omnibus database and miRNA targets prediction, we successfully identified a miRNA, termed miR‐494‐3p, could regulate FMOD production in human skin fibroblast (BJ fibroblast). The functional analysis revealed that miR‐494‐3p mimics could inhibit BJ fibroblast migration and invasion but not proliferation and differentiation, while miR‐494‐3p inhibition markedly promotes migration, invasion, and differentiation of BJ fibroblast. Moreover, we established FMOD overexpression (OE) and knockout BJ fibroblast. We found that FMOD OE could rescue the inhibitory effects of miR‐494‐3p mimics on the migration and invasion of BJ fibroblast. In contrast, the miR‐494‐3p inhibitor transfection could not enhance migration, invasion, and differentiation of FMOD KO BJ fibroblast. Together, our results suggest that miR‐494‐3p may be a potential target for skin wound management via regulating FMOD production.
Comparative anatomy of siphons in tellinoidean clams (Bivalvia, Tellinoidea)
Authors: Batistão Alan R. , Audino Jorge A. , Passos Flávio D. 
Published: August 2024

AbstractSiphons are tubular organs formed by fusion and posterior extension of the marginal mantle folds. They are supposed to have performed key roles in the evolution of bivalves by enabling these animals to occupy several ecological niches. However, anatomical details of these organs are scarce for one of the most diverse lineages of tropical bivalves, the superfamily Tellinoidea. We investigated the siphonal morphology of 15 species, sampling five tellinoidean families, by integrating scanning electron microscopy, confocal microscopy, and histology. The siphons revealed variations in length, pigmentation, tentacles, papillae, and number of nerve cords. Due to the presence of sensorial structures, such as papillae and tentacles, we reclassify the siphons of Tellinoidea from type A to A+. Additional anatomical patterns were identified at family and genus levels. For example, the incurrent siphon shorter than the excurrent and 24 tentacles are putative synapomorphies of Donacidae. We also highlight shared siphonal traits between Donacidae and Solecurtidae as well as between Semelidae and Tellinidae. In addition, our data support the idea of Psammobiidae as a paraphyletic lineage. Overall, we provide an extensive comparative data set on siphonal traits with significant relevance for bivalve taxonomy, functional anatomy, and evolutionary investigations.
Spatiotemporal analysis of compound droughts and heat waves in the Horn of Africa
Authors: Alasow Ahmed Abdiaziz , Hamed Mohammed Magdy , Rady Mohammed , Shahid Shamsuddin 
Published: August 2024

AbstractClimate change has increased the frequency and severity of weather extremes, including droughts, heat waves and compound drought and heatwave (CDHW) events. CDHW events profoundly impact water availability, agriculture, public health and energy production, particularly in the Horn of Africa (HOA). This study examined the historical spatiotemporal patterns of CDHW periods in the HOA during three periods (1951–1980, 1971–2000 and 1991–2020) using the ERA5 reanalysis dataset. This study utilized monthly Standardized Precipitation Evapotranspiration Index (SPEI) data to detect droughts and daily maximum temperature data to identify heatwaves for characterizing the duration, severity and magnitude of CDHW events. The results show a substantial increase in the duration of CDHW events in recent years, with durations reaching up to 25 days. The average duration of heat waves also increased from 7 days before 1993 to 18 days by 2011, culminating in a record‐breaking 43‐day heat wave in 2019. Most areas experienced a significant increase in heatwave duration by more than 12 days from the early period of 1951–1980 to the late period of 1991–2020. Although around 76% and 69% of the HOA exhibited insignificant heatwave trends in the first two periods, Ethiopia and Kenya experienced substantial increases of more than 18 days during the most recent period, with some durations exceeding 25 days in recent decades. The magnitude of CDHW events generally decreased as drought duration intensified, but specific areas, particularly southwest Kenya and Eritrea, exhibited higher CDHW values in the last period. These findings underscore the urgent need to understand and address CDHW events in the HOA. Targeted interventions for disaster risk reduction and resilience‐building are needed to mitigate the adverse effects of these events in this vulnerable region. This study provides a basis for future research and policy formulation in the HOA.
Delay in diagnosis is associated with decreased treatment effectiveness in children with rumination syndrome
Authors: Jia Margaret R. , Lu Peter L. , Khoo Janice S. , Sabella Julia , Yang Dennis M. , Puri Neetu B. , Vaz Karla , Yacob Desale , Di Lorenzo Carlo , Kroon Van Diest Ashley M. 
Published: August 2024

AbstractObjectivesRumination syndrome (RS) is challenging to diagnose, which can lead to diagnostic delays. Our objective was to evaluate the length of time from RS symptom onset to diagnosis in patients referred to our institution and to examine whether this duration predicts treatment outcomes.MethodsWe conducted a review of patients with RS evaluated at our institution. Data were collected from chart review and patient/family reported questionnaires. We evaluated the time from symptom onset to diagnosis over time and whether it was associated with symptom resolution.ResultsWe included 247 patients with RS (60% female, median age of 14 years, interquartile range [IQR]: 9–16 years). The median age at symptom onset was 11 years (IQR: 5–14 years) and median age at diagnosis was 13 years (IQR: 9–15 years) for a median duration of 1 year (IQR: 0–3 years) between symptom onset and diagnosis. Length of time between symptom onset and diagnosis did not change significantly at our institution from 2016 to 2022. Among the 164 children with outcome data, 47 (29%) met criteria for symptom resolution after treatment. A longer time to diagnosis was associated with a lower likelihood of symptom resolution after treatment (p = 0.01).ConclusionIn our experience, the time to RS diagnosis after symptom onset is shorter than previously described. A longer delay in diagnosis is associated with lower likelihood of symptom resolution after treatment, emphasizing the importance of a prompt recognition of rumination symptoms and a timely diagnosis.
The inhibitory effects of free and bound phenolics from Phyllanthus emblica Linn. on α‐amylase: a comparison study
Authors: Xing Mingxia , Xie Fan , Wang Guangqiang , Yuan Chunmei , Huang Siyan , Zhou Tingrun , Song Zibo , Ai Lianzhong 
Published: August 2024

AbstractBACKGROUNDPhyllanthus emblica Linn. (PE) is rich in polyphenols, which can be categorized into free and bound phenolics (PEFP and PEBP). This study evaluated the inhibitory effect of PEFB and PEBP on α‐amylase for the first time. The mechanism of the inhibition effect of PEFP and PEBP on α‐amylase was investigated by enzyme inhibition kinetics, multispectral analysis, thermodynamics, and molecular docking.RESULTSFree and bound phenolics inhibited α‐amylase activity effectively in a mixed type of inhibition. Fluorescence quenching and thermodynamic analyses showed that the binding of PEFP and PEBP to α‐amylase occurred through a static quenching process (Kq = 6.94 × 10¹² and 5.74 × 10¹² L mol−1 s−1), which was accompanied by a redshift (λem from 343 to 347 nm), leading to a change in the microenvironment. This process was found to be a spontaneous exothermic reaction (ΔG < 0). Circular dichroism (CD) analysis confirms that the secondary structure of α‐amylase was altered, in particular a decrease in α‐helixes and an increase in random coils. Molecular docking studies showed that PEFP and PEBP interacted with α‐amylase through hydrogen bonding and hydrophobic interactions.CONCLUSIONThe present study provides valuable insights into the mechanism of action of PEFP and PEBP on α‐amylase, which will provide a theoretical basis for their possible use as novel natural α‐amylase inhibitors. © 2024 Society of Chemical Industry.