bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combining Molecular Quantum Mechanical Modeling and Machine Learning for Accelerated Reaction Screening and Discovery
Authors: Casetti Nicholas , Alfonso‐Ramos Javier E. , Coley Connor W. , Stuyver Thijs 
Published: August 2023

AbstractMolecular quantum mechanical modeling, accelerated by machine learning, has opened the door to high‐throughput screening campaigns of complex properties, such as the activation energies of chemical reactions and absorption/emission spectra of materials and molecules; in silico. Here, we present an overview of the main principles, concepts, and design considerations involved in such hybrid computational quantum chemistry/machine learning screening workflows, with a special emphasis on some recent examples of their successful application. We end with a brief outlook of further advances that will benefit the field.
Climate‐driven shifts in leaf senescence are greater for boreal species than temperate species in the Acadian Forest region in contrast to leaf emergence shifts
Authors: Spafford Lynsay , MacDougall Andrew , Steenberg James 
Published: August 2023

AbstractThe Acadian Forest Region is a temperate‐boreal transitional zone in eastern North America which provides a unique opportunity for understanding the potential effects of climate change on both forest types. Leaf phenology, the timing of leaf life cycle changes, is an important indicator of the biological effects of climate change, which can be observed with stationary timelapse cameras known as phenocams. Using four growing seasons of observations for the species Acer rubrum (red maple), Betula papyrifera (paper/white birch) and Abies balsamea (balsam fir) from the Acadian Phenocam Network as well as multiple growing season observations from the North American PhenoCam Network we parameterized eight leaf emergence and six leaf senescence models for each species which span a range in process and driver representation. With climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) we simulated future leaf emergence, senescence and season length (senescence minus emergence) for these species at sites within the Acadian Phenocam Network. Model performances were similar across models and leaf emergence model RMSE ranged from about 1 to 2 weeks across species and models, while leaf senescence model RMSE ranged from about 2 to 4 weeks. The simulations suggest that by the late 21st century, leaf senescence may become continuously delayed for boreal species like Betula papyrifera and Abies balsamea, though remain relatively stable for temperate species like Acer rubrum. In contrast, the projected advancement in leaf emergence was similar across boreal and temperate species. This has important implications for carbon uptake, nutrient resorption, ecology and ecotourism for the Acadian Forest Region. More work is needed to improve predictions of leaf phenology for the Acadian Forest Region, especially with respect to senescence. Phenocams have the potential to rapidly advance process‐based model development and predictions of leaf phenology in the context of climate change.
Co‐Catalyzed Metal‐Ligand Cooperative Approach for N‐alkylation of Amines and Synthesis of Quinolines via Dehydrogenative Alcohol Functionalization
Authors: Mondal Sucheta , Pal Subhasree , Khanra Subhankar , Chakraborty Santana , Paul Nanda D. 
Published: August 2023

AbstractHerein we report a cobalt‐catalyzed sustainable approach for C−N cross‐coupling reaction between amines and alcohols. Using a well‐defined Co‐catalyst 1 a bearing 2‐(phenyldiazenyl)‐1,10‐phenanthroline ligand, various N‐alkylated amines were synthesized in good yields. 1 a efficiently alkylates diamines producing N, N′‐dialkylated amines in good yields and showed excellent chemoselectivity when oleyl alcohol and β‐citronellol, containing internal carbon‐carbon double bond were used as alkylating agents. 1 a is equally compatible with synthesizing N‐heterocycles via dehydrogenative coupling of amines and alcohols. 1H‐Indole was synthesized via an intramolecular dehydrogenative N‐alkylation reaction, and various substituted quinolines were synthesized by coupling of 2‐aminobenzyl alcohol and secondary alcohols. A few control reactions and spectroscopic experiments were conducted to illuminate the plausible reaction mechanism, indicating that the 1 a‐catalyzed N‐alkylation proceeds through the borrowing hydrogen pathway. The coordinated arylazo ligand participates actively throughout the reaction; the hydrogen eliminated during dehydrogenation of alcohols was set aside in the ligand backbone and subsequently gets transferred in the reductive amination step to imine intermediates yielding N‐alkylated amines. On the other hand, 1 a‐catalyzed quinoline synthesis proceeds through dehydrogenation followed by successive C−C and C−N coupling steps forming H2O2 as a by‐product under air.
Wasserstein‐metric‐based distributionally robust optimization method for unit commitment considering wind turbine uncertainty
Authors: Chen Gengrui , Qi Donglian , Yan Yunfeng , Chen Yulin , Wang Yaxin , Mei Jingcheng 
Published: August 2023

AbstractThe penetration of wind turbines in the power grid is increasing rapidly. Still, the wind turbine output power has uncertainty, leading to poor grid reliability, affecting the grid's dispatching plan, and increasing the total cost. Thus, a distributionally robust optimization method for thermal power unit commitment considering the uncertainty of wind power is proposed. For this method, energy storage and interruptible load are added to simulate increasingly complex electricity consumption scenarios. Furthermore, the amount of load cutting reflects the satisfaction level of electricity consumption on the user side. Based on Wasserstein metric, an ambiguity set is established to reflect the probabilistic distribution information of the wind power uncertainty. An ambiguity set preprocessing method is proposed to depict the probability distribution of ambiguity set more clearly, to minimize the operation cost under the condition that the uncertainty of wind turbine output power obeys the extreme probabilistic distribution of the ambiguity set. The test case in a modified version of the IEEE 6‐bus system shows that the proposed method can flexibly adjust the robustness and economy of optimization decisions by controlling the sample size and the confidence of Wasserstein ambiguity set radius. In addition, the proposed ambiguity set preprocessing method can obtain more economical dispatching decisions with a smaller sample size.
Lipidomic analyses of five Carya illinoinensis cultivars
Authors: Zhao Zhe , Wang Fei , Hu Tian , Zhou Chun‐hua 
Published: August 2023

AbstractCarya illinoinensis (Wangenh.) K. Koch, nuts are a renowned health food. However, there are many cultivars of this nut tree, and their mature kernel lipid composition has not been thoroughly studied. Therefore, we used liquid chromatography–mass spectrometry (LC–MS) to analyze the lipid composition of mature nuts of five C. illinoinensis cultivars. In the mature kernels of all cultivars, there were 58 lipid types which were mainly composed of glycerolipids (c. 65%) and phospholipids (>30%). Triacylglycerol (TG) accounted for the largest proportion of mature nuts of all cultivars, exceeding 50%; and diacylglycerol (DG), ceramide (Cer), phosphatidylcholine (PC), and phosphatidylethanolamine (PE) were also relatively high. Additionally, nuts contain fatty acids, mainly oleic, linoleic, and linolenic acids. Our research provides a new perspective for the processing and utilization of plant and edible oils, and for the use of C. illinoinensis kernels in the development of medicine and food science.
The optimal time to buy and hold stock in a reversal
Authors: Han Xuyuan , Liu Zhenya 
Published: August 2023

AbstractInvestors cannot anticipate a return reversal in the stock market. Therefore, choosing the optimal time to buy and hold a stock is vital. This paper formulates a disorder problem using the optimal stopping theory to study the optimal time to buy and hold a stock when a downward trend is about to reverse. The results show that investors should buy a stock when the conditional probability of a return reversal hits an optimal boundary for the first time. The optimal boundary is uniquely determined by the stock return, volatility, and the intensity of return reversal. Moreover, the optimal boundary decreases as the stock volatility and the intensity of return reversal increase. We use the China Securities Index 300 (CSI 300), Standard & Poor's 500 (S&P 500), Dow Jones Industrial Average (DJIA), and Russell 2000 indexes to estimate the parameters and the related optimal boundary. We find that the estimated optimal boundary can be used to time stock buying.
An effective human monkeypox classification using vision transformer
Authors: Aloraini Mohammed 
Published: August 2023

AbstractMonkeypox virus has become a popular disease as many people have been recently infected with this virus around the world. This virus causes fears of another global pandemic similar to COVID‐19 pandemic. Therefore, it is important to determine infected people at an early stage to reduce the spread of this virus. Creating an automatic approach to detect monkeypox virus is a challenging problem due to the similar appearance between skin infections. Currently, deep convolutional neural network approaches have been used in detecting and classifying skin infections. However, these approaches sever from certain challenges such as being unable to capture the global context and low accuracy rate. In this paper, we propose a novel approach based on vision transformer to automatically detect monkeypox virus in skin images. We fine‐tune vision transformer for the human monkeypox classification problems. This fine‐tuned vision transformer splits an image into image patches and then these patches are used as input to the transformer in a sequence structure, followed by added layers to detect monkeypox virus. The experimental results show that the proposed approach achieves excellent detection accuracy using a public dataset.
Differential proteomics argues against a general role for CD9, CD81 or CD63 in the sorting of proteins into extracellular vesicles
Authors: Fan Yé , Pionneau Cédric , Cocozza Federico , Boëlle Pierre‐Yves , Chardonnet Solenne , Charrin Stéphanie , Théry Clotilde , Zimmermann Pascale , Rubinstein Eric 
Published: August 2023

AbstractThe tetraspanins CD9, CD81 and CD63 are major components of extracellular vesicles (EVs). Yet, their impact on EV composition remains under‐investigated. In the MCF7 breast cancer cell line CD63 was as expected predominantly intracellular. In contrast CD9 and CD81 strongly colocalized at the plasma membrane, albeit with different ratios at different sites, which may explain a higher enrichment of CD81 in EVs. Absence of these tetraspanins had little impact on the EV protein composition as analysed by quantitative mass spectrometry. We also analysed the effect of concomitant knock‐out of CD9 and CD81 because these two tetraspanins play similar roles in several cellular processes and associate directly with two Ig domain proteins, CD9P‐1/EWI‐F/PTGFRN and EWI‐2/IGSF8. These were the sole proteins significantly decreased in the EVs of double CD9‐ and CD81‐deficient cells. In the case of EWI‐2, this is primarily a consequence of a decreased cell expression level. In conclusion, this study shows that CD9, CD81 and CD63, commonly used as EV protein markers, play a marginal role in determining the protein composition of EVs released by MCF7 cells and highlights a regulation of the expression level and/or trafficking of CD9P‐1 and EWI‐2 by CD9 and CD81.
TP53 mutations correlate with the non‐coding RNA content of small extracellular vesicles in melanoma
Authors: Labbé Maureen , Menoret Estelle , Letourneur Franck , Saint‐Pierre Benjamin , de Beaurepaire Laurence , Veziers Joëlle , Dreno Brigitte , Denis Marc G. , Blanquart Christophe , Boisgerault Nicolas , Fonteneau Jean‐François , Fradin Delphine 
Published: August 2023

AbstractNon‐coding RNAs (ncRNAs) are important regulators of gene expression. They are expressed not only in cells, but also in cell‐derived extracellular vesicles (EVs). The mechanisms controlling their loading and sorting remain poorly understood. Here, we investigated the impact of TP53 mutations on the non‐coding RNA content of small melanoma EVs. After purification of small EVs from six different patient‐derived melanoma cell lines, we characterized them by small RNA sequencing and lncRNA microarray analysis. We found that TP53 mutations are associated with a specific micro and long non‐coding RNA content in small EVs. Then, we showed that long and small non‐coding RNAs enriched in TP53 mutant small EVs share a common sequence motif, highly similar to the RNA‐binding motif of Sam68, a protein interacting with hnRNP proteins. This protein thus may be an interesting partner of p53, involved in the expression and loading of the ncRNAs. To conclude, our data support the existence of cellular mechanisms associate with TP53 mutations which control the ncRNA content of small EVs in melanoma.
Social capital effects on resilience to food insecurity: Evidence from Kyrgyzstan
Authors: Egamberdiev Bekhzod 
Published: August 2023

AbstractThis paper investigates the role of social capital in terms of trust and group membership in building household resilience to food insecurity. Using detailed ‘Life in Kyrgyzstan’ multi‐topic panel data, the research estimates resilience to food insecurity through the Resilience Index Measurement and Analysis (RIMA) approach, including different pillars and a resilience capacity index. The impact of social capital on resilience pillars and capacity is estimated using IV models for multiple endogenous variables. The results suggest that both trust and group membership positively affect resilience pillars and capacity.
Mechanical stress and inflammation have opposite effects on Wnt signaling in human chondrocytes
Authors: Timmermans Ritchie G. M. , Blom Arjen B. , Nelissen Rob G. H. H. , Broekhuis Demiën , van der Kraan Peter M. , Meulenbelt Ingrid , van den Bosch Martijn H. J. , Ramos Yolande F. M. 
Published: August 2023

AbstractDysregulation of Wingless and Int‐1 (Wnt) signaling has been strongly associated with development and progression of osteoarthritis (OA). Here, we set out to investigate the independent effects of either mechanical stress (MS) or inflammation on Wnt signaling in human neocartilage pellets, and to relate this Wnt signaling to OA pathophysiology. OA synovium‐conditioned media (OAS‐CM) was collected after incubating synovium from human end‐stage OA joints for 24 h in medium. Cytokine levels in the OAS‐CM were determined with a multiplex immunoassay (Luminex). Human neocartilage pellets were exposed to 20% MS, 2% OAS‐CM or 1 ng/mL Interleukin‐1β (IL‐1β). Effects on expression levels of Wnt signaling members were determined by reverse transcription‐quantitative polymerase chain reaction. Additionally, the expression of these members in articular cartilage from human OA joints was analyzed in association with joint space narrowing (JSN) and osteophyte scores. Protein levels of IL‐1β, IL‐6, IL‐8, IL‐10, tumor necrosis factor α, and granulocyte‐macrophage colony‐stimulating factor positively correlated with each other. MS increased noncanonical WNT5A and FOS expression. In contrast, these genes were downregulated upon stimulation with OAS‐CM or IL‐1β. Furthermore, Wnt inhibitors DKK1 and FRZB decreased in response to OAS‐CM or IL‐1β exposure. Finally, expression of WNT5A in OA articular cartilage was associated with increased JSN scores, but not osteophyte scores. Our results demonstrate that MS and inflammatory stimuli have opposite effects on canonical and noncanonical Wnt signaling in human neocartilage. Considering the extent to which MS and inflammation contribute to OA in individual patients, we hypothesize that targeting specific Wnt pathways offers a more effective, individualized approach.
Parvovirus in dermatology: A review
Authors: Pudasaini Prajwal , Das Kinnor , Gorai Suraljit , Paudel Sushil , G.C. Sagar , Adhikari Sadiksha , Thapa Bibechan , Kurien Ann John 
Published: August 2023

AbstractParvovirus B19 is a small nonenveloped single‐stranded DNA virus belonging to the parvoviridae family. The dermatological manifestations are varied ranging from infective to inflammatory, but the most common among infective etiologies is erythema infectiosum, also known as the fifth disease or ‘slapped cheek’ disease, which is mildly contagious. Clinical corroboration of symptoms and signs with serum antibody levels has been seen in acute and persistent parvoviral infections. Other dermatological manifestations of parvovirus B19 infections include erythema multiforme, vasculitis, reticular erythema, maculopapular eruptions, pustular eruptions, papular‐purpuric gloves and socks syndrome (PPGSS) and Gianotti‐Crosti syndrome. Skin lesions are quite characteristic and begin with oedema and erythema symmetrically localized to the hands and feet. Subsequently, petechial and purpuric changes appear varying from a few millimetres in diameter to larger, confluent patches. The primary target of parvovirus B19 is the hematopoietic‐erythroid cell line, specifically near the pronormoblast stage and the vulnerability to cellular damage increases along the differentiation lineage. There's multimodal clinical phenotypic presentation seen in parvoviral infections. Among the clinical expression of HPV B19 infections, the most common is dermatologic, however other manifestations such as rheumatologic and hematologic are not uncommon. However, some infections can be asymptomatic, especially in immunocompetent hosts, whereas in others with haematological abnormalities, these can lead to aplastic cellular crises.
Applications of multi‐omics analysis in human diseases
Authors: Chen Chongyang , Wang Jing , Pan Donghui , Wang Xinyu , Xu Yuping , Yan Junjie , Wang Lizhen , Yang Xifei , Yang Min , Liu Gong‐Ping 
Published: August 2023

AbstractMulti‐omics usually refers to the crossover application of multiple high‐throughput screening technologies represented by genomics, transcriptomics, single‐cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi‐omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi‐omics. This review outlines the existing technical categories of multi‐omics, cautions for experimental design, focuses on the integrated analysis methods of multi‐omics, especially the approach of machine learning and deep learning in multi‐omics data integration and the corresponding tools, and the application of multi‐omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open‐source analysis tools and databases, and finally, discusses the challenges and future directions of multi‐omics integration and application in precision medicine. With the development of high‐throughput technologies and data integration algorithms, as important directions of multi‐omics for future disease research, single‐cell multi‐omics and spatial multi‐omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi‐omics medical research.
Noonan syndrome: rhGH treatment and PTPN11 mutation
Authors: Wu Xian , Wu Jiali , Yuan Yi , Yang Li , Yu Lirong 
Published: August 2023

AbstractObjectiveTo analyze the clinical data and genetic characteristics of Noonan syndrome, both the effect and side effects of recombinant human growth hormone (rhGH) treatment.MethodsWe collected clinical data from 8 children with Noonan syndrome diagnosed from November 2017 to June 2021. The diagnosis was clarified by exome second‐generation sequencing and parental PCR‐NGS validation and interpretation of the preceding evidence, and growth hormone therapy was administered. Of the cases, four males and four females were seen for slow height growth and the median age at diagnosis was 8 years 7 months (1 year 7 months to 12 years 6 months).ResultsHere, 7 children were treated with rhGH. Compared to the pre‐treatment period, the growth rate increased after rhGH treatment [3.7 ± 0.5 cm/year before treatment and 8.0 ± 1.0 cm/year after treatment, p < 0.01], with the maximum growth rate between 3 and 6 months of treatment and decreasing with the duration of treatment thereafter. The growth hormone treatment was discontinued and the orthopedic consultation was ordered with regular follow‐up, which was considered to be related to the PTPN11 mutation.ConclusionNoonan syndrome is characterized by slow growth, short stature, mental retardation, peculiar facial features, structural heart abnormalities and abnormal bone metabolism. and osteochondroma was found after case 2 rhGH treatment. Genetic examination is mostly caused by PTPN11 mutation. It is recommended to pay attention to bone metabolism abnormalities before growth hormone treatment, especially in children with PTPN11 mutations.
Micronutrients in High‐Fat Diet Modify Insulin Resistance and Its Regulatory Genes in Adult Male Mice
Authors: Yang Zeyu , Kubant Ruslan , Cho Clara E. , Kranenburg Eva , Beaudry Jacqueline , Bottiglieri Teodoro , Anderson G. Harvey 
Published: August 2023

ScopeObesity and insulin resistance (IR) are associated with epigenetic changes of gene expression. However, the relationship between micronutrients, epigenetic regulation of gene expression, and IR during development of diet‐induced obesity has yet to be defined. Our objective is to describe the effect of micronutrient addition to diets on IR and its related genes during obesity development.Methods and resultsMale C57BL/6J mice are fed a high‐fat (HFD) or low‐fat (LFD) diets with or without a multi‐vitamin mineral mix (MVM) addition containing vitamins A, B1, B6, B12, and Zn, and Se for 9 weeks. Compared to LFD mice, HFD mice have higher body weight, IR, fasting glucose, insulin, C‐peptide, leptin, and hepatic triglyceride concentrations, and dysregulated gene expression in liver, muscle, pancreas, and fat tissues (p < 0.05). The addition of MVM reduces these HFD‐induced effects. HFD downregulates 27 genes associated with insulin regulation and adipose tissue function across all tissues by an average of 47% and upregulates five genes by 230% (p < 0.001). Adding MVM downregulates five genes and upregulates one in HFD‐fed mice. Both HFD and MVM alter one‐carbon metabolites.ConclusionAddition of micronutrients to the HFD decreases IR and modifies associated gene expression in obese and lean mice.