bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discernible interindividual patterns of global efficiency decline during theoretical brain surgery
Authors: Yueh-Hsin Lin , Dadario Nicholas B. , Tang Si Jie , Crawford Lewis , Tanglay Onur , Dow Hsu-Kang , Young Isabella , Ahsan Syed Ali , Doyen Stephane , Sughrue Michael E. 
Published: June 2024

AbstractThe concept of functional localization within the brain and the associated risk of resecting these areas during removal of infiltrating tumors, such as diffuse gliomas, are well established in neurosurgery. Global efficiency (GE) is a graph theory concept that can be used to simulate connectome disruption following tumor resection. Structural connectivity graphs were created from diffusion tractography obtained from the brains of 80 healthy adults. These graphs were then used to simulate parcellation resection in every gross anatomical region of the cerebrum by identifying every possible combination of adjacent nodes in a graph and then measuring the drop in GE following nodal deletion. Progressive removal of brain parcellations led to patterns of GE decline that were reasonably predictable but had inter-subject differences. Additionally, as expected, there were deletion of some nodes that were worse than others. However, in each lobe examined in every subject, some deletion combinations were worse for GE than removing a greater number of nodes in a different region of the brain. Among certain patients, patterns of common nodes which exhibited worst GE upon removal were identified as “connectotypes”. Given some evidence in the literature linking GE to certain aspects of neuro-cognitive abilities, investigating these connectotypes could potentially mitigate the impact of brain surgery on cognition.
A novel insight into neurological disorders through HDAC6 protein–protein interactions
Authors: Bahram Sangani Nasim , Koetsier Jarno , Mélius Jonathan , Kutmon Martina , Ehrhart Friederike , Evelo Chris T. , Curfs Leopold M. G. , Reutelingsperger Chris P. , Eijssen Lars M. T. 
Published: June 2024

AbstractDue to its involvement in physiological and pathological processes, histone deacetylase 6 (HDAC6) is considered a promising pharmaceutical target for several neurological manifestations. However, the exact regulatory role of HDAC6 in the central nervous system (CNS) is still not fully understood. Hence, using a semi-automated literature screening technique, we systematically collected HDAC6-protein interactions that are experimentally validated and reported in the CNS. The resulting HDAC6 network encompassed 115 HDAC6-protein interactions divided over five subnetworks: (de)acetylation, phosphorylation, protein complexes, regulatory, and aggresome-autophagy subnetworks. In addition, 132 indirect interactions identified through HDAC6 inhibition were collected and categorized. Finally, to display the application of our HDAC6 network, we mapped transcriptomics data of Alzheimer’s disease, Parkinson’s disease, and Amyotrophic Lateral Sclerosis on the network and highlighted that in the case of Alzheimer’s disease, alterations predominantly affect the HDAC6 phosphorylation subnetwork, whereas differential expression within the deacetylation subnetwork is observed across all three neurological disorders. In conclusion, the HDAC6 network created in the present study is a novel and valuable resource for the understanding of the HDAC6 regulatory mechanisms, thereby providing a framework for the integration and interpretation of omics data from neurological disorders and pharmacodynamic assessments.
Production and comparison of structural, thermal and physical characteristics of chitin nanoparticles obtained by different methods
Authors: Farokhi Neda Moshtaghi , Milani Jafar Mohammadzadeh , Amiri Zeinab Raftani 
Published: June 2024

AbstractThis study examined the impact of acid hydrolysis, tempo oxidation, and mechanical grinding on the physical, thermal, and structural properties of α-chitin nanocrystals and nanofibers. The manufacturing methods could influence the diameter, functional groups, and crystal patterns of the resulting nanoparticles. Analysis of the DLS results revealed that the size of acidic nanocrystals were smaller and showed improved dispersibility. The XRD patterns indicated that the chemical and mechanical treatments did not alter the crystalline arrangement of the α-chitin. FT-IR spectra analysis revealed that the chemical and mechanical methods did not affect the functional groups of the nanoparticles. DSC results showed that the nanoparticles had good thermal stability up to 400 °C, and it was found that the nanofibers had better thermal resistance due to their longer length. In the FE-SEM images, the nanoparticles were observed as fiber mats with a length of more than 100 nm. It was also found that the diameter of the nanoparticles was less than 100 nm.
Investigation of the antimycobacterial activity of African medicinal plants combined with chemometric analysis to identify potential leads
Authors: Moyo Phanankosi , Ofori Michael , Bodede Olusola S. , Wooding Madelien , Khorommbi Ndivhuwo Kevin , McGaw Lyndy J. , Danquah Cynthia A. , Maharaj Vinesh J. 
Published: June 2024

AbstractThe emergence of drug-resistant Mycobacterium tuberculosis strains is a threat to global health necessitating the discovery of novel chemotherapeutic agents. Natural products drug discovery, which previously led to the discovery of rifamycins, is a valuable approach in this endeavor. Against this backdrop, we set out to investigate the in vitro antimycobacterial properties of medicinal plants from Ghana and South Africa, evaluating 36 extracts and their 252 corresponding solid phase extraction (SPE) generated fractions primarily against the non-pathogenic Mycobacterium smegmatis and Mycobacterium aurum species. The most potent fraction was further evaluated in vitro against infectious M. tuberculosis strain. Crinum asiaticum (bulb) (Amaryllidaceae) emerged as the most potent plant species with specific fractions showing exceptional, near equipotent activity against the non-pathogenic Mycobacterium species (0.39 µg/ml ≤ MIC ≤ 25 µg/ml) with one fraction being moderately active (MIC = 32.6 µg/ml) against M. tuberculosis. Metabolomic analysis led to the identification of eight compounds predicted to be active against M. smegmatis and M. aurum. In conclusion, from our comprehensive study, we generated data which provided an insight into the antimycobacterial properties of Ghanaian and South African plants. Future work will be focused on the isolation and evaluation of the compounds predicted to be active.
Fetal cord plasma herpesviruses and preeclampsia: an observational cohort study
Authors: Häkkinen Inka , Yazgeldi Gunaydin Gamze , Pyöriä Lari , Kojima Shohei , Parrish Nicholas , Perdomo Maria F. , Wedenoja Juho , Hedman Klaus , Heinonen Seppo , Kajantie Eero , Laivuori Hannele , Kere Juha , Katayama Shintaro , Wedenoja Satu 
Published: June 2024

AbstractA previous study suggested that fetal inheritance of chromosomally integrated human herpesvirus 6 (ici-HHV6) is associated with the hypertensive pregnancy disorder preeclampsia (PE). We aimed to study this question utilizing cord plasma samples (n = 1276) of the Finnish Genetics of Preeclampsia Consortium (FINNPEC) cohort: 539 from a pregnancy with PE and 737 without. We studied these samples and 30 placentas from PE pregnancies by a multiplex qPCR for the DNAs of all nine human herpesviruses. To assess the population prevalence of iciHHV-6, we studied whole-genome sequencing data from blood-derived DNA of 3421 biobank subjects. Any herpes viral DNA was detected in only two (0.37%) PE and one (0.14%) control sample (OR 2.74, 95% CI 0.25–30.4). One PE sample contained iciHHV-6B and another HHV-7 DNA. The control’s DNA was of iciHHV-6B; the fetus having growth restriction and preterm birth without PE diagnosis. Placentas showed no herpesviruses. In the biobank data, 3 of 3421 subjects (0.08%) had low level HHV-6B but no iciHHV-6. While iciHHV-6 proved extremely rare, both fetuses with iciHHV-6B were growth-restricted, preterm, and from a pregnancy with maternal hypertension. Our findings suggest that human herpesviruses are not a significant cause of PE, whereas iciHHV-6 may pose some fetal risk.
Exposure to an insecticide formulation alters chemosensory orientation, but not floral scent detection, in buff-tailed bumblebees (Bombus terrestris)
Authors: Kárpáti Zsolt , Szelényi Magdolna Olívia , Tóth Zoltán 
Published: June 2024

AbstractAlthough pesticide-free techniques have been developed in agriculture, pesticides are still routinely used against weeds, pests, and pathogens worldwide. These agrochemicals pollute the environment and can negatively impact human health, biodiversity and ecosystem services. Acetamiprid, an approved neonicotinoid pesticide in the EU, may exert sub-lethal effects on pollinators and other organisms. However, our knowledge on the scope and severity of such effects is still incomplete. Our experiments focused on the effects of the insecticide formulation Mospilan (active ingredient: 20% acetamiprid) on the peripheral olfactory detection of a synthetic floral blend and foraging behaviour of buff-tailed bumblebee (Bombus terrestris) workers. We found that the applied treatment did not affect the antennal detection of the floral blend; however, it induced alterations in their foraging behaviour. Pesticide-treated individuals started foraging later, and the probability of finding the floral blend was lower than that of the control bumblebees. However, exposed bumblebees found the scent source faster than the controls. These results suggest that acetamiprid-containing Mospilan may disrupt the activity and orientation of foraging bumblebees. We hypothesize that the observed effects of pesticide exposure on foraging behaviour could be mediated through neurophysiological and endocrine mechanisms. We propose that future investigations should clarify whether such sub-lethal effects can affect pollinators’ population dynamics and their ecosystem services.
The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance
Authors: Deery Hamish A. , Liang Emma , Di Paolo Robert , Voigt Katharina , Murray Gerard , Siddiqui M. Navyaan , Egan Gary F. , Moran Chris , Jamadar Sharna D. 
Published: June 2024

AbstractRising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of age and insulin resistance to the association of cerebral blood flow and glucose metabolism; both critical process in the supply of energy for the brain. Thirty-four younger (20–42 years) and 41 older (66–86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Lower cerebral blood flow was also associated with worse working memory and slower reaction time in tasks requiring cognitive flexibility and response inhibition. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive correlation. In insulin resistant younger adults, the association showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates of and associations between cerebral blood flow and glucose metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.
Extraction of water bodies from high-resolution remote sensing imagery based on a deep semantic segmentation network
Authors: Sun Dechao , Gao Guang , Huang Lijun , Liu Yunpeng , Liu Dongquan 
Published: June 2024

AbstractThe precise delineation of urban aquatic features is of paramount importance in scrutinizing water resources, monitoring floods, and devising water management strategies. Addressing the challenge of indistinct boundaries and the erroneous classification of shadowed regions as water in high-resolution remote sensing imagery, we introduce WaterDeep, which is a novel deep learning framework inspired by the DeepLabV3 + architecture and an innovative fusion mechanism for high- and low-level features. This methodology first creates a comprehensive dataset of high-resolution remote sensing images, then progresses through the Xception baseline network for low-level feature extraction, and harnesses densely connected Atrous Spatial Pyramid Pooling (ASPP) modules to assimilate multi-scale data into sophisticated high-level features. Subsequently, the network decoder amalgamates the elemental and intricate features and applies dual-line interpolation to the amalgamated dataset to extract aqueous formations from the remote images. Experimental evidence substantiates that WaterDeep outperforms its existing deep learning counterparts, achieving a stellar overall accuracy of 99.284%, FWIoU of 95.58%, precision of 97.562%, recall of 95.486%, and F1 score of 96.513%. It also excels in the precise demarcation of edges and the discernment of shadows cast by urban infrastructure. The superior efficacy of the proposed method in differentiating water bodies in complex urban environments has significant practical applications in real-world contexts.
AI nutrition recommendation using a deep generative model and ChatGPT
Authors: Papastratis Ilias , Konstantinidis Dimitrios , Daras Petros , Dimitropoulos Kosmas 
Published: June 2024

AbstractIn recent years, major advances in artificial intelligence (AI) have led to the development of powerful AI systems for use in the field of nutrition in order to enhance personalized dietary recommendations and improve overall health and well-being. However, the lack of guidelines from nutritional experts has raised questions on the accuracy and trustworthiness of the nutritional advice provided by such AI systems. This paper aims to address this issue by introducing a novel AI-based nutrition recommendation method that leverages the speed and explainability of a deep generative network and the use of novel sophisticated loss functions to align the network with established nutritional guidelines. The use of a variational autoencoder to robustly model the anthropometric measurements and medical condition of users in a descriptive latent space, as well as the use of an optimizer to adjust meal quantities based on users’ energy requirements enable the proposed method to generate highly accurate, nutritious and personalized weekly meal plans. Coupled with the ability of ChatGPT to provide an unparalleled pool of meals from various cuisines, the proposed method can achieve increased meal variety, accuracy and generalization capabilities. Extensive experiments on 3000 virtual user profiles and 84000 daily meal plans, as well as 1000 real profiles and 7000 daily meal plans, demonstrate the exceptional accuracy of the proposed diet recommendation method in generating weekly meal plans that are appropriate for the users in terms of energy intake and nutritional requirements, as well as the easiness with which it can be integrated into future diet recommendation systems.
Cardiovascular and cardiorespiratory effects of high-intensity interval training in body fat responders and non-responders
Authors: Domaradzki Jarosław , Koźlenia Dawid 
Published: June 2024

AbstractThis study aimed to investigate cardiovascular and cardiorespiratory adaptations to exercise intervention among participants who showed higher (responders–RsBFP) and lower (non-responders–NRsBFP) levels of body fat percentage (BFP) responsiveness. Adolescents (42.5% males) participated in a ten-week school-based high-intensity interval training (HIIT), followed by a comparison of BFP, blood pressure (BP), and cardiorespiratory fitness (CRF). RsBFP age of 16.15 ± 0.36 years, body height 170.82 ± 8.16 cm, weight 61.23 ± 12.80 kg, and BMI 20.86 ± 3.29 kg/m2. Meanwhile, NRsBFP age of 16.04 ± 0.36 years, body height 168.17 ± 8.64 cm, weight 57.94 ± 8.62 kg, and BMI 20.47 ± 2.24 kg/m2. HIIT intervention impacted BFP, with a higher decrease in the RsBFP than the NRsBFP (ΔBFPRs = − 2.30 ± 3.51(10.34%) vs. ΔBFPNRs = 1.51 ± 1.54(6.96%) p < 0.001). The primary comparison showed a statistically significant interaction effect in relation to CRF (F(1,71) = 14.12; p < 0.001). Detailed comparisons showed large and significant CRF changes in RsBFP (7.52%; d = 0.86; p < 0.001) but not in NRsBFP (2.01%; d = 0.11; p = 0.576). In addition, RsBFP and NRsBFP benefited equally in SBP (5.49%, d = 0.75; p < 0.001; 4.95%, d = 0.74; p < 0.001, respectively). These findings highlight that exercise benefits on body fat may be mainly related to gains in CRF. Due to substantial intra-individual variability in adaptation, there is a need for personalized intervention tailored for those with different reaction thresholds in body mass components.
Starch vs. tannin as biodegradable reagents for ultrafine hematite depression
Authors: Kordloo Mehrdad , Rahmanian Ahmad , Mohammadzadeh Amirhossein , Tohry Arash , Rezaei Ali , Chehreh Chelgani Saeed 
Published: June 2024

AbstractEnrichment of ultrafine liberated valuable minerals from their associated gangue phases is one of the emerging investigation topics within mineral processing and recycling. Using green flotation reagents and turning processes into eco-friendly systems is also one of the challenges in the green transition of ore beneficiation plants. Starch and Tanin as biodegradable depressants for hematite depression have been commercially used in various iron ore processing plants. However, their depression effects on ultrafine particles were not systemically assessed and compared. To fill this gap, this investigation examined the effects of starch, tannin, their mixtures (different ratios), and their different conditioning sequence on the floatability of ultrafine quartz and hematite (− 15 µm). Since the macromolecular polymer of these biodegradable depressants can bind particles together and flocculate them, turbidity analyses were used to assess their optimum ratio for hematite depression without affecting quartz floatability. Turbidity analyses provided a mixture of tannin and starch might enhance the flotation separation of quartz from hematite. Starch could flocculate ultrafine hematite particles, while tannin could disperse ultrafine quartz particles. Floatability experiments indicated that starch had the highest performance in hematite depression (lowest effect on quartz particles) compared to other conditions. Surface analyses (zeta potential and FTIR) proved floatability outcomes and highlighted starch had stronger adsorption on the hematite surface than tannin.
Negative association between higher maternal pre-pregnancy body mass index and breastfeeding outcomes is not mediated by DNA methylation
Authors: Elliott Hannah R. , Bennett Chloe L. , Caramaschi Doretta , English Sinead 
Published: June 2024

AbstractThe benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.
The zebrafish gut microbiome influences benzo[a]pyrene developmental neurobehavioral toxicity
Authors: Stagaman Keaton , Alexiev Alexandra , Sieler Michael J. , Hammer Austin , Kasschau Kristin D. , Truong Lisa , Tanguay Robyn L. , Sharpton Thomas J. 
Published: June 2024

AbstractEarly-life exposure to environmental toxicants like Benzo[a]pyrene (BaP) is associated with several health consequences in vertebrates (i.e., impaired or altered neurophysiological and behavioral development). Although toxicant impacts were initially studied relative to host physiology, recent studies suggest that the gut microbiome is a possible target and/or mediator of behavioral responses to chemical exposure in organisms, via the gut-brain axis. However, the connection between BaP exposure, gut microbiota, and developmental neurotoxicity remains understudied. Using a zebrafish model, we determined whether the gut microbiome influences BaP impacts on behavior development. Embryonic zebrafish were treated with increasing concentrations of BaP and allowed to grow to the larval life stage, during which they underwent behavioral testing and intestinal dissection for gut microbiome profiling via high-throughput sequencing. We found that exposure affected larval zebrafish microbiome diversity and composition in a manner tied to behavioral development: increasing concentrations of BaP were associated with increased taxonomic diversity, exposure was associated with unweighted UniFrac distance, and microbiome diversity and exposure predicted larval behavior. Further, a gnotobiotic zebrafish experiment clarified whether microbiome presence was associated with BaP exposure response and behavioral changes. We found that gut microbiome state altered the relationship between BaP exposure concentration and behavioral response. These results support the idea that the zebrafish gut microbiome is a determinant of the developmental neurotoxicity that results from chemical exposure.
Identification and characterization of plasma proteins associated with intra-amniotic inflammation and/or infection in women with preterm labor
Authors: Cho Hee Young , Lee Ji Eun , Park Kyo Hoon , Choi Bo Young , Lee Min Jung , Jeong Da Eun , Shin Sue 
Published: June 2024

AbstractThis study aimed to identify plasma proteins that could serve as potential biomarkers for microbial invasion of the amniotic cavity (MIAC) or intra-amniotic inflammation (IAI) in women with preterm labor (PTL). A retrospective cohort comprised singleton pregnant women with PTL (24–34 weeks) who underwent amniocentesis. Pooled plasma samples were analyzed by label-free liquid chromatography-tandem mass spectrometry for proteome profiling in a nested case–control study (concomitant MIAC/IAI cases vs. non-MIAC/IAI controls [n = 10 per group]). Eight target proteins associated with MIAC/IAI were further verified by immunoassays in a large cohort (n = 230). Shotgun proteomic analysis revealed 133 differentially expressed proteins (fold change > 1.5, P < 0.05) in the plasma of MIAC/IAI cases. Further quantification confirmed that the levels of AFP were higher and those of kallistatin and TGFBI were lower in the plasma of women with MIAC and that the levels of kallistatin and TGFBI were lower in the plasma of women with IAI than in those without these conditions. The area under the curves of plasma AFP, kallistatin, and TGFBI ranged within 0.67–0.81 with respect to each endpoint. In summary, plasma AFP, kallistatin, and TGFBI may represent valuable non-invasive biomarkers for predicting MIAC or IAI in women with PTL.