bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of NAFLD and bariatric surgery on hepatic and adipose tissue mitochondrial biogenesis and respiration
Authors: Pedersen Julie S. , Rygg Marte O. , Chrøis Karoline , Sustarsic Elahu G. , Gerhart-Hines Zach , Wever Albrechtsen Nicolai J. , Serizawa Reza R. , Kristiansen Viggo B. , Basse Astrid L. , Boilesen Astrid E. B. , Olsen Beth H. , Hansen Torben , Gluud Lise Lotte , Madsbad Sten , Larsen Steen , Bendtsen Flemming , Dela Flemming 
Published: May 2022

AbstractImpaired mitochondrial oxidative phosphorylation (OXPHOS) in liver tissue has been hypothesised to contribute to the development of nonalcoholic steatohepatitis in patients with nonalcoholic fatty liver disease (NAFLD). It is unknown whether OXPHOS capacities in human visceral (VAT) and subcutaneous adipose tissue (SAT) associate with NAFLD severity and how hepatic OXPHOS responds to improvement in NAFLD. In biopsies sampled from 62 patients with obesity undergoing bariatric surgery and nine control subjects without obesity we demonstrate that OXPHOS is reduced in VAT and SAT while increased in the liver in patients with obesity when compared with control subjects without obesity, but this was independent of NAFLD severity. In repeat liver biopsy sampling in 21 patients with obesity 12 months after bariatric surgery we found increased hepatic OXPHOS capacity and mitochondrial DNA/nuclear DNA content compared with baseline. In this work we show that obesity has an opposing association with mitochondrial respiration in adipose- and liver tissue with no overall association with NAFLD severity, however, bariatric surgery increases hepatic OXPHOS and mitochondrial biogenesis.
In-silico synthesis of lowest-pressure high-Tc ternary superhydrides
Authors: Lucrezi Roman , Di Cataldo Simone , von der Linden Wolfgang , Boeri Lilia , Heil Christoph 
Published: May 2022

AbstractWe report the theoretical prediction of two high-performing hydride superconductors BaSiH8 and SrSiH8. They are thermodynamically stable above pressures of 130 and 174 GPa, respectively, and metastable below that. Employing anharmonic phonon calculations, we determine the minimum pressures of dynamical stability to be around 3 GPa for BaSiH8 and 27 GPa for SrSiH8, and using the fully anisotropic Migdal-Eliashberg theory, we predict Tc’s around 71 and 126 K, respectively. We also introduce a method to estimate the lowest pressure of synthesis, based on the calculation of the enthalpy barriers protecting the BaSiH8$$Fm\bar{3}m$$

F
m

3

¯

m

structure from decomposition at various pressures. This kinetic pressure threshold is sensibly higher than the one based on dynamic stability, but gives a much more rigorous limit for synthesizability.
Neuropathic pain caused by miswiring and abnormal end organ targeting
Authors: Gangadharan Vijayan , Zheng Hongwei , Taberner Francisco J. , Landry Jonathan , Nees Timo A. , Pistolic Jelena , Agarwal Nitin , Männich Deepitha , Benes Vladimir , Helmstaedter Moritz , Ommer Björn , Lechner Stefan G. , Kuner Thomas , Kuner Rohini 
Published: May 2022

AbstractNerve injury leads to chronic pain and exaggerated sensitivity to gentle touch (allodynia) as well as a loss of sensation in the areas in which injured and non-injured nerves come together1–3. The mechanisms that disambiguate these mixed and paradoxical symptoms are unknown. Here we longitudinally and non-invasively imaged genetically labelled populations of fibres that sense noxious stimuli (nociceptors) and gentle touch (low-threshold afferents) peripherally in the skin for longer than 10 months after nerve injury, while simultaneously tracking pain-related behaviour in the same mice. Fully denervated areas of skin initially lost sensation, gradually recovered normal sensitivity and developed marked allodynia and aversion to gentle touch several months after injury. This reinnervation-induced neuropathic pain involved nociceptors that sprouted into denervated territories precisely reproducing the initial pattern of innervation, were guided by blood vessels and showed irregular terminal connectivity in the skin and lowered activation thresholds mimicking low-threshold afferents. By contrast, low-threshold afferents—which normally mediate touch sensation as well as allodynia in intact nerve territories after injury4–7—did not reinnervate, leading to an aberrant innervation of tactile end organs such as Meissner corpuscles with nociceptors alone. Genetic ablation of nociceptors fully abrogated reinnervation allodynia. Our results thus reveal the emergence of a form of chronic neuropathic pain that is driven by structural plasticity, abnormal terminal connectivity and malfunction of nociceptors during reinnervation, and provide a mechanistic framework for the paradoxical sensory manifestations that are observed clinically and can impose a heavy burden on patients.
MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses
Authors: Devine Jay , Vidal-García Marta , Liu Wei , Neves Amanda , Lo Vercio Lucas D. , Green Rebecca M. , Richbourg Heather A. , Marchini Marta , Unger Colton M. , Nickle Audrey C. , Radford Bethany , Young Nathan M. , Gonzalez Paula N. , Schuler Robert E. , Bugacov Alejandro , Rolian Campbell , Percival Christopher J. , Williams Trevor , Niswander Lee , Calof Anne L. , Lander Arthur D. , Visel Axel , Jirik Frank R. , Cheverud James M. , Klein Ophir D. , Birnbaum Ramon Y. , Merrill Amy E. , Ackermann Rebecca R. , Graf Daniel , Hemberger Myriam , Dean Wendy , Forkert Nils D. , Murray Stephen A. , Westerberg Henrik , Marcucio Ralph S. , Hallgrímsson Benedikt 
Published: May 2022

AbstractComplex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).
A novel fuzzy framework for technology selection of sustainable wastewater treatment plants based on TODIM methodology in developing urban areas
Authors: Eseoglu Gunes , Yapsakli Kozet , Tozan Hakan , Vayvay Ozalp 
Published: May 2022

AbstractOptimal technology selection of wastewater treatment plants (WWTPs) necessitates the adoption of data-driven scientific approaches that satisfy the sustainability requirements of the urban ecosystem. Such approaches should be able to provide actionable insights to decision makers constrained by factors such as population growth, land scarcity, and loss of functionality of wastewater treatment plants. The framework in this study proposes a hybrid fuzzy multi-criteria decision making (MCDM) model consisting of the analytical hierarchy process (AHP) and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) by using alpha cut series which takes into account the risk aversion of decision makers (DMs) to overcome uncertainties of environmental conditions. The literature to date indicates that the study is the first to presents how a systematic decision-making process is approached by interpreting the interaction of criteria for the selection of wastewater treatment technology through the membership function of Prospect Theory. The proposed methodology reveals that the prominent reference criterion manipulates other sub-criteria according to the function of risk-aversion behavior. The fuzzy sets based on alpha cut series are employed to evaluate both the criteria weight and the rank of the alternatives in the decision-making process to obtain compromise solutions under uncertainty. The dominance degrees of the alternatives are achieved by fuzzy TODIM integrated with the fuzzy analytic hierarchy process (FAHP) which deals with the uncertainty of human judgements. According to the ranking results determined by the dominance degree of alternatives, anaerobic–anoxic–oxic (A2O) without pre-clarification was the most effective process in relation to the sludge disposal cost (C25) calculated as reference criteria. The ranking of four full-scale WWTPs in a metropolitan city of an EMEA country based on 24 sub-criteria listed under the four main criteria, namely the dimensions of sustainability, is used as a case study to verify the usefulness of the fuzzy approach. Motivated by the literature gap related to the failure to consider the psychological behavior of DMs in technology selection problem for wastewater treatment, it is discussed how the proposed hybrid MCDM model can be utilized by reflecting human risk perception in wastewater treatment technology selection for developing urban areas.
Healthcare services relaxing natural selection may contribute to increase of dementia incidence
Authors: You Wenpeng , Henneberg Renata , Henneberg Maciej 
Published: May 2022

AbstractAgeing and genetic traits can only explain the increasing dementia incidence partially. Advanced healthcare services allow dementia patients to survive natural selection and pass their genes onto the next generation. Country-specific estimates of dementia incidence rates (all ages and 15–49 years old), Biological State Index expressing reduced natural selection (Is), ageing indexed by life expectancy e(65), GDP PPP and urbanization were obtained for analysing the global and regional correlations between reduced natural selection and dementia incidence with SPSS v. 27. Worldwide, Is significantly, but inversely, correlates with dementia incidence rates for both all ages and 15–49 years old in bivariate correlations. These relationships remain inversely correlated regardless of the competing contributing effects from ageing, GDP and urbanization in partial correlation model. Results of multiple linear regression (enter) have shown that Is is the significant predictor of dementia incidence among all ages and 15–49 years old. Subsequently, Is was selected as the variable having the greatest influence on dementia incidence in stepwise multiple linear regression. The Is correlated with dementia incidence more strongly in developed population groupings. Worldwide, reduced natural selection may be yet another significant contributor to dementia incidence with special regard to developed populations.
Applications of machine learning in pine nuts classification
Authors: Huang Biaosheng , Liu Jiang , Jiao Junying , Lu Jing , Lv Danjv , Mao Jiawei , Zhao Youjie , Zhang Yan 
Published: May 2022

AbstractPine nuts are not only the important agent of pine reproduction and afforestation, but also the commonly consumed nut with high nutritive values. However, it is difficult to distinguish among pine nuts due to the morphological similarity among species. Therefore, it is important to improve the quality of pine nuts and solve the adulteration problem quickly and non-destructively. In this study, seven pine nuts (Pinus bungeana,Pinus yunnanensis,Pinus thunbergii,Pinus armandii,Pinus massoniana,Pinus elliottiiandPinus taiwanensis) were used as study species. 210 near-infrared (NIR) spectra were collected from the seven species of pine nuts, five machine learning methods (Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Naive Bayes (NB)) were used to identify species of pine nuts. 303 images were used to collect morphological data to construct a classification model based on five convolutional neural network (CNN) models (VGG16, VGG19, Xception, InceptionV3 and ResNet50). The experimental results of NIR spectroscopy show the best classification model is MLP and the accuracy is closed to 0.99. Another experimental result of images shows the best classification model is InceptionV3 and the accuracy is closed to 0.964. Four important range of wavebands, 951–957 nm, 1,147–1,154 nm, 1,907–1,927 nm, 2,227–2,254 nm, were found to be highly related to the classification of pine nuts. This study shows that machine learning is effective for the classification of pine nuts, providing solutions and scientific methods for rapid, non-destructive and accurate classification of different species of pine nuts.
Longer amplicons provide better sensitivity for electrochemical sensing of viral nucleic acid in water samples using PCB electrodes
Authors: Ahuja Shruti , Kumar M. Santhosh , Nandeshwar Ruchira , Kondabagil Kiran , Tallur Siddharth 
Published: May 2022

AbstractThe importance of monitoring environmental samples has gained a lot of prominence since the onset of COVID-19 pandemic, and several surveillance efforts are underway using gold standard, albeit expensive qPCR-based techniques. Electrochemical DNA biosensors could offer a potential cost-effective solution suitable for monitoring of environmental water samples in lower middle income countries. In this work, we demonstrate electrochemical detection of amplicons as long as $${503}\,\hbox {bp}$$

503

bp

obtained from Phi6 bacteriophage (a popular surrogate for SARS-CoV-2) isolated from spiked lake water samples, using ENIG finish PCB electrodes with no surface modification. The electrochemical sensor response is thoroughly characterised for two DNA fragments of different lengths ($${117}\,\hbox {bp}$$

117

bp

and $${503}\,\hbox {bp}$$

503

bp

), and the impact of salt in PCR master mix on methylene blue (MB)-DNA interactions is studied. Our findings establish that length of the DNA fragment significantly determines electrochemical sensitivity, and the ability to detect long amplicons without gel purification of PCR products demonstrated in this work bodes well for realisation of fully-automated solutions for in situ measurement of viral load in water samples.
Evolutionary game analysis of opportunistic behavior of Sponge City PPP projects: a perceived value perspective
Authors: Zhao Hui , Liu Xin , Wang Yiting 
Published: May 2022

AbstractSponge City Public Private Partnership (PPP) project is a significant step to promote the construction of resilient city and sustainable development. Private companies take advantage of information asymmetry and regulatory loopholes to take opportunistic behavior, which affects the project delivery quality and public interests. In order to reveal the decision-making mechanism of the main stakeholders, this paper constructs an evolutionary game model of private companies, citizens and the government from a fresh perspective of perceived value. First, the traditional payoff matrix is modified by combining Prospect Theory and Mental Accounting. Next, this paper analyzes the strategic evolution law and stability conditions of game players by replicated dynamic equation. Finally, Nanganqu project is used for empirical simulation to verify the effectiveness of this model. Results indicate that, (1) due to the complexity of the project and the bounded rationality of the participants, there is no evolutionary stable strategy in this game system. (2) The behavioral decision of participants is affected by perceived incomes and perceived costs. (3) Government punishment and reputation loss can effectively curb the opportunistic behavior. All above studies are expected to improve the management of Sponge City PPP projects, providing theoretical guidance for the government to make scientific decisions.
A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data
Authors: Nguyen T. V. , Dakka M. A. , Diakiw S. M. , VerMilyea M. D. , Perugini M. , Hall J. M. M. , Perugini D. 
Published: May 2022

AbstractTraining on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI training. Data-centric, cross-silo federated learning represents a pathway forward for training on distributed medical datasets. Existing approaches typically require updates to a training model to be transferred to a central server, potentially breaching data privacy laws unless the updates are sufficiently disguised or abstracted to prevent reconstruction of the dataset. Here we present a completely decentralized federated learning approach, using knowledge distillation, ensuring data privacy and protection. Each node operates independently without needing to access external data. AI accuracy using this approach is found to be comparable to centralized training, and when nodes comprise poor-quality data, which is common in healthcare, AI accuracy can exceed the performance of traditional centralized training.
Functional optical design of thickness-optimized transparent conductive dielectric-metal-dielectric plasmonic structure
Authors: Çetinkaya Çağlar , Çokduygulular Erman , Güzelçimen Feyza , Kınacı Barış 
Published: May 2022

AbstractDielectric/metal/dielectric plasmonic transparent structures play an important role in tailoring the high-optical performance of various optoelectronic devices. Though these structures are in significant demand in applications, including modification of the optical properties, average visible transmittance (AVT) and colour render index (CRI) and correlated colour temperature (CCT), obtaining optimal ones require precise thickness optimization. The overall objective of this study is the estimation of the optimal design concept of MoO3/Ag/WO3 (10/dAg/dWO3 nm) plasmonic structure. To explore the proper use in optoelectronic devices, we are motivated to conduct a rigorous optical evaluation on the thickness of layers. Having calculated optical characteristics and achieved the highest AVT of 97.3% for dAg = 4 nm and dWO3 = 6 nm by the transfer matrix method, it is quite possible to offer the potential of the structure acting as a transparent contact. Notably, the colour coordinates of the structure are x = 0.3110 and y = 0.3271, namely, it attributes very close to the Planckian locus. This superior colour performance displays that MoO3/Ag/WO3 shall undergo rapid development in neutral-colour windows and LED technologies. Structure with dAg = 6 nm and dWO3 = 16 nm exhibits the highest CRI of 98.58, thus identifying an optimal structure that can be integrated into LED lighting applications and imaging technologies. Besides the colour of structure with dAg = 4 nm and dWO3 = 8 nm is equal for D65 Standard Illuminant, the study reports that the range of CCTs are between 5000 and 6500 K. This optimization makes the structure employable as a near-daylight broadband illuminant. The study emphasizes that optimal MoO3/Ag/WO3 plasmonic structures can be used effectively to boost optoelectronic devices' performance.
Facile access to fused 2D/3D rings via intermolecular cascade dearomative [2 + 2] cycloaddition/rearrangement reactions of quinolines with alkenes
Authors: Ma Jiajia , Chen Shuming , Bellotti Peter , Wagener Tobias , Daniliuc Constantin , Houk Kendall N. , Glorius Frank 
Published: May 2022

AbstractHybrid fused two-dimensional/three-dimensional (2D/3D) rings are important pharmacophores in drugs owing to their unique structural and physicochemical properties. Preparation of these strained ring systems often requires elaborate synthetic effort and exhibits low efficiency, thus representing a limiting factor in drug discovery. Here, we report two types of energy-transfer-mediated cascade dearomative [2 + 2] cycloaddition/rearrangement reactions of quinoline derivatives with alkenes, which provide a straightforward avenue to 2D/3D pyridine-fused 6−5−4−3- and 6−4−6-membered ring systems. Notably, this energy-transfer-mediated strategy features excellent diastereoselectivity that bypasses the general reactivity and selectivity issues of photochemical [2 + 2] cycloaddition of various other aromatics. Tuning the aza-arene substitutions enabled selective diversion of the iridium photocatalysed energy transfer manifold towards either cyclopropanation or cyclobutane-rearrangement products. Density functional theory calculations revealed a cascade energy transfer scenario to be operative.
IDH mutation and cancer stem cell
Authors: Zhang Yang , Liu Yang , Lang Fengchao , Yang Chunzhang 
Published: May 2022

Abstract
Cancer stem cells (CSCs) are a small population of cells in human malignancies that resemble the biology of human pluripotent stem cells. CSCs are closely related to the critical hallmarks in human cancers, ranging from oncogenesis to disease progression, therapeutic resistance, and overall outcome. Mutations in isocitrate dehydrogenase (IDH) were recently identified as founder mutations for human cancers. An increasing amount of evidence indicates that IDH mutations are closely related to the establishment and maintenance of CSCs. Biosynthesis of oncometabolite, metabolic reprogramming, and epigenetic shifts establish distinctive molecular signatures in IDH-mutated CSCs. Additionally, IDH mutation and IDH-related pathways could be valuable molecular targets to impact the CSC components in human cancers and to improve the disease outcome.
Allied Health Professionals' Views on the Use of 3D Food Printing to Improve the Mealtime Quality of Life for People With Dysphagia: Impact, Cost, Practicality, and Potential
Authors: Smith Rebecca , Bryant Lucy , Hemsley Bronwyn 
Published: May 2022

Purpose:
Much is promised in relation to the use of three-dimensional (3D) food printing to create visually appealing texture-modified foods for people with dysphagia, but little is known of its feasibility. This study aimed to explore the perspective of allied health professionals on the feasibility of using 3D food printing to improve quality of life for people with dysphagia.

Method:
Fifteen allied health professionals engaged in one of four 2-hr online focus groups to discuss 3D food printing for people with dysphagia. They discussed the need to address the visual appeal of texture-modified foods and watched a video of 3D food printing to inform their discussions on its feasibility. Focus group data were transcribed verbatim, de-identified, and analyzed using thematic content analysis. Participants verified summaries of the researchers' interpretation of the themes in the data.

Results:
Participants suggested that 3D food printing could improve the mealtime experience for people with dysphagia but noted several barriers to its feasibility, including the time and effort involved in printing the food and in cleaning the printer. They were not convinced that 3D-printed food held higher visual appeal or looked enough like the “real food” it represented.

Conclusions:
Allied health professionals considered that 3D food printing could benefit people with dysphagia by reducing the negative impacts of poorly presented texture-modified foods. However, they also considered that feasibility barriers could impede uptake and use of 3D food printers. Further research should consider the views of people with dysphagia and address barriers reported in this study.