bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches
Authors: Hsieh Yunli Eric , Tandon Kshitij , Verbruggen Heroen , Nikoloski Zoran
Published: May 2024

Genome-scale metabolic models (GEMs) of microbial communities offer valuable insights into the functional capabilities of their members and facilitate the exploration of microbial interactions. These models are generated using different automated reconstruction tools, each relying on different biochemical databases that may affect the conclusions drawn from the in silico analysis. One way to address this problem is to employ a consensus reconstruction method that combines the outcomes of different reconstruction tools. Here, we conducted a comparative analysis of community models reconstructed from three automated tools, i.e. CarveMe, gapseq, and KBase, alongside a consensus approach, utilizing metagenomics data from two marine bacterial communities. Our analysis revealed that these reconstruction approaches, while based on the same genomes, resulted in GEMs with varying numbers of genes and reactions as well as metabolic functionalities, attributed to the different databases employed. Further, our results indicated that the set of exchanged metabolites was more influenced by the reconstruction approach rather than the specific bacterial community investigated. This observation suggests a potential bias in predicting metabolite interactions using community GEMs. We also showed that consensus models encompassed a larger number of reactions and metabolites while concurrently reducing the presence of dead-end metabolites. Therefore, the usage of consensus models allows making full and unbiased use from aggregating genes from the different reconstructions in assessing the functional potential of microbial communities.
Replicon particle vaccination induces non-neutralizing anti-nucleoprotein antibody-mediated control of Crimean-Congo hemorrhagic fever virus
Authors: Sorvillo Teresa E. , Karaaslan Elif , Scholte Florine E. M. , Welch Stephen R. , Coleman-McCray JoAnn D. , Genzer Sarah C. , Ritter Jana M. , Hayes Heather M. , Jain Shilpi , Pegan Scott D. , Bergeron Éric , Montgomery Joel M. , Spiropoulou Christina F. , Spengler Jessica R.
Published: May 2024

Crimean-Congo hemorrhagic fever virus (CCHFV) can cause severe human disease and is considered a WHO priority pathogen due to the lack of efficacious vaccines and antivirals. A CCHF virus replicon particle (VRP) has previously shown protective efficacy in a lethal Ifnar-/- mouse model when administered as a single dose at least 3 days prior to challenge. Here, we determine that non-specific immune responses are not sufficient to confer short-term protection, since Lassa virus VRP vaccination 3 days prior to CCHFV challenge was not protective. We also investigate how CCHF VRP vaccination confers protective efficacy by examining viral kinetics, histopathology, clinical analytes and immunity early after challenge (3 and 6 days post infection) and compare to unvaccinated controls. We characterize how these effects differ based on vaccination period and correspond to previously reported CCHF VRP-mediated protection. Vaccinating Ifnar-/- mice with CCHF VRP 28, 14, 7, or 3 days prior to challenge, all known to confer complete protection, significantly reduced CCHFV viral load, mucosal shedding, and markers of clinical disease, with greater reductions associated with longer vaccination periods. Interestingly, there were no significant differences in innate immune responses, T cell activation, or antibody titers after challenge between groups of mice vaccinated a week or more before challenge, but higher anti-NP antibody avidity and effector function (ADCD) were positively associated with longer vaccination periods. These findings support the importance of antibody-mediated responses in VRP vaccine-mediated protection against CCHFV infection.
Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves
Authors: Machard Anaïs , Salvati Agnese , P. Tootkaboni Mamak , Gaur Abhishek , Zou Jiwei , Wang Liangzhu Leon , Baba Fuad , Ge Hua , Bre Facundo , Bozonnet Emmanuel , Corrado Vincenzo , Luo Xuan , Levinson Ronnen , Lee Sang Hoon , Hong Tianzhen , Salles Olinger Marcelo , Machado Rayner Maurício e Silva , da Guarda Emeli Lalesca Aparecida , Veiga Rodolfo Kirch , Lamberts Roberto , Afshari Afshin , Ramon Delphine , Ngoc Dung Ngo Hoang , Sengupta Abantika , Breesch Hilde , Heijmans Nicolas , Deltour Jade , Kuborn Xavier , Sayadi Sana , Qian Bin , Zhang Chen , Rahif Ramin , Attia Shady , Stern Philipp , Holzer Peter
Published: May 2024

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.
Effective fabrication and characterization of eco-friendly nano particles composite for adsorption Cd (II) and Cu (II) ions from aqueous solutions using modelling studies
Authors: Hamad Mohammed Taha Moustafa Hussien , Ibrahim Sabah
Published: May 2024

The public health and environment are currently facing significant risks due to the discharge of industrial wastewater, which contains harmful heavy metals and other contaminants. Therefore, there is a pressing need for sustainable and innovative technologies to treat wastewater. The main objective of this research was to develop novel composites known as chitosan, Padina pavonica, Fe(III), and nano MgO incorporated onto pomegranate peel with the specific purpose of removing Cd (II) and Cu (II) ions from aqueous solutions. The characterization of these nanocomposites involved the utilization of several analytical methods, including Fourier-transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, thermal gravimetric analysis, and X-ray photoelectron spectroscopy. The efficiency of these nanocomposites was evaluated through batch mode experiments, investigating the impact of factors such as pH, initial concentration, contact time, and adsorbent dose on the adsorption of Cu(II) ions. The optimum conditions for the removal of ions were pH = 5 for Cu (II) and 6 for Cd (II), contact time: 120 min, adsorbent dosage: 0.2 g, initial metal ion concentration: 50 mg/L for each metal ion for the present study. The MgO@Pp demonstrated the highest removal efficiencies for Cu(II) and Cd(II) at 98.2% and 96.4%, respectively. In contrast, the CS@Fe-PA achieved removal efficiencies of 97.2% for Cu(II) and 89.2% for Cd(II). The modified MgO@Pp exhibited significantly higher total adsorption capacities for Cu(II) and Cd(II) at 333.3 and 200 mg/g, respectively, compared to CS@Fe-PA, which had capacities of 250 and 142 mg/g, respectively. The adsorption of Cd (II) and Cu (II) ions by MgO@Pp was found to be a spontaneous process. The R2 values obtained using the Freundlich and Redlich-Peterson models were the highest for the MgO@Pp composite, with values of 0.99, 0.988, 0.987, and 0.994, respectively, for Cu (II) and Cd (II). The pseudo-second-order equation was determined to be the best-fit kinetic model for this process. Reusability experiments confirmed that the adsorbents can be utilized for up to four regeneration cycles. Based on the findings of this study, MgO @ Pp is the most promising alternative and could be instrumental in developing strategies to address existing environmental pollution through adsorption.
Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
Authors: Kumar Kamlesh , Parihar C. M. , Nayak H. S. , Sena D. R. , Godara Samarth , Dhakar Rajkumar , Patra Kiranmoy , Sarkar Ayan , Bharadwaj Sneha , Ghasal Prakash Chand , L.Meena A. , Reddy K. Srikanth , Das T. K. , Jat S. L. , Sharma D. K. , Saharawat Y. S. , Singh Upendra , Jat M. L. , Gathala M. K.
Published: May 2024

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.
Understanding the impacts of coastal deoxygenation in nitrogen dynamics: an observational analysis
Authors: Farias Laura , de la Maza Lucas
Published: May 2024

Biological production and outgassing of greenhouse gasses (GHG) in Eastern Boundary Upwelling Systems (EBUS) are vital for fishing productivity and climate regulation. This study examines temporal variability of biogeochemical and oceanographic variables, focusing on dissolved oxygen (DO), nitrate, nitrogen deficit (N deficit), nitrous oxide (N2O) and air-sea N2O flux. This analysis is based on monthly observations from 2000 to 2023 in a region of intense seasonal coastal upwelling off central Chile (36°S). Strong correlations are estimated among N2O concentrations and N deficit in the 30–80 m layer, and N2O air-sea fluxes with the proportion of hypoxic water (4 < DO < 89 µmol L−1) in the water column, suggesting that N2O accumulation and its exchange are mainly associated with partial denitrification. Furthermore, we observe interannual variability in concentrations and inventories in the water column of DO, nitrate, N deficit, as well as air-sea N2O fluxes in both downwelling and upwelling seasons. These variabilities are not associated with El Niño-Southern Oscillation (ENSO) indices but are related to interannual differences in upwelling intensity. The time series reveals significant nitrate removal and N2O accumulation in both mid and bottom layers, occurring at rates of 1.5 µmol L−1 and 2.9 nmol L−1 per decade, respectively. Particularly significant is the increase over the past two decades of air-sea N2O fluxes at a rate of 2.9 µmol m−2 d−1 per decade. These observations suggest that changes in the EBUS, such as intensification of upwelling and the prevalence of hypoxic waters may have implications for N2O emissions and fixed nitrogen loss, potentially influencing coastal productivity and climate.
Partial discharge localization in power transformer tanks using machine learning methods
Authors: Khodaveisi Farzin , Karami Hamidreza , Karimpour Matin Zarei , Rubinstein Marcos , Rachidi Farhad
Published: May 2024

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SVM) to more complex approaches like convolutional neural networks (CNN). Multiple case studies are considered, each with different attributes, including sensor position, frequency content of the PD signal, and size of the transformer tank. The paper focuses on predicting the PD location in three-dimensional space using single-sensor electric field measurements. Various aspects of each method are analyzed, such as the input signal, core methodology, correlation coefficient between the predicted location and the actual location, and root mean square error (RMSE). These features are discussed and compared across the different methods. The results indicate that the CNN model exhibits superior performance in terms of location accuracy among the methods considered.
Efficacy and safety of vitamin C supplementation in the treatment of community-acquired pneumonia: a systematic review and meta-analysis with trial sequential analysis
Authors: Sharma Yogesh , Sumanadasa Subodha , Shahi Rashmi , Woodman Richard , Mangoni Arduino A. , Bihari Shailesh , Thompson Campbell
Published: May 2024

Community-acquired pneumonia (CAP) poses a significant global health challenge, prompting exploration of innovative treatments. This systematic review and meta-analysis aimed to evaluate the efficacy and safety of vitamin C supplementation in adults undergoing treatment for CAP. A comprehensive search of the MEDLINE, Embase, CINAHL, the Cochrane Central Register of Controlled Trials, and Clinical Trials.gov databases from inception to 17 November 2023 identified six randomized-controlled-trials (RCTs) meeting inclusion criteria. The primary outcome analysis revealed a non-significant trend towards reduced overall mortality in the vitamin C group compared to controls (RR 0.51; 95% CI 0.24 to 1.09; p = 0.052; I2 = 0; p = 0.65). Sensitivity analysis, excluding corona-virus-disease 2019 (COVID-19) studies and considering the route of vitamin C administration, confirmed this trend. Secondary outcomes, including hospital length-of-stay (LOS), intensive-care-unit (ICU) LOS, and mechanical ventilation, exhibited mixed results. Notably, heterogeneity and publication bias were observed in hospital LOS analysis, necessitating cautious interpretation. Adverse effects were minimal, with isolated incidents of nausea, vomiting, hypotension, and tachycardia reported. This meta-analysis suggests potential benefits of vitamin C supplementation in CAP treatment. However, inconclusive findings and methodological limitations warrants cautious interpretation, emphasising the urgency for high-quality trials to elucidate the true impact of vitamin C supplementation in CAP management.
Absence of sympathetic innervation hampers the generation of tertiary lymphoid structures upon acute lung inflammation
Authors: Riffard Clémence , Letaïef Laïla , Azar Safa , Casrouge Armanda , Brunet Isabelle , Teillaud Jean-Luc , Dieu-Nosjean Marie-Caroline
Published: May 2024

Tertiary lymphoid structures (TLS) are lymphoid organs present in inflammatory non-lymphoid tissues. Studies have linked TLS to favorable outcomes for patients with cancers or infectious diseases, but the mechanisms underlying their formation are not fully understood. In particular, secondary lymphoid organs innervation raises the question of sympathetic nerve fibers involvement in TLS organogenesis. We established a model of pulmonary inflammation based on 5 daily intranasal instillations of lipopolysaccharide (LPS) in immunocompetent mice. In this setting, lung lymphoid aggregates formed transiently, evolving toward mature TLS and disappearing when inflammation resolved. Sympathetic nerve fibers were then depleted using 6-hydroxydopamine. TLS quantification by immunohistochemistry showed a decrease in LPS-induced TLS number and surface in denervated mouse lungs. Although a reduction in alveolar space was observed, it did not impair overall pulmonary content of transcripts encoding TNF-α, IL-1β and IFN-γ inflammation molecules whose expression was induced by LPS instillations. Immunofluorescence analysis of immune infiltrates in lungs of LPS-treated mice showed a drop in the proportion of CD23+ naive cells among CD19+ B220+ B cells in denervated mice whereas the proportion of other cell subsets remained unchanged. These data support the existence of neuroimmune crosstalk impacting lung TLS neogenesis and local naive B cell pool.
The association between three prevalent autoimmune disorders and the likelihood of developing prostate cancer: a Mendelian randomization study
Authors: Deng Xiaoqian , Sun Shiwei , Yao Wei , Yue Peng , Guo Fuyu , Wang Yue , Zhang Yangang
Published: May 2024

Numerous studies establish a significant correlation between autoimmune disorders (AIDs) and prostate cancer (PCa). Our Mendelian randomization (MR) analysis investigates the potential connection between rheumatoid arthritis (RA) and PCa, aiming to confirm causal links between systemic lupus erythematosus (SLE), hyperthyroidism, and PCa. Summary statistics from genome-wide association studies provided data on PCa and three AIDs. MR analysis, using IVW as the main approach, assessed causal relationships, validated by sensitivity analysis. IVW revealed a correlation between genetically anticipated RA and PCa, notably in Europeans (OR = 1.03; 95% CI 1.01–1.04, p = 2*10−5). Evidence supported a lower PCa risk in individuals with SLE (OR = 0.94; 95% CI 0.91–0.97, p = 2*10−4) and hyperthyroidism (OR = 0.02; 95% CI 0.001–0.2, p = 2*10−3). Weighted mode and median confirmed these findings. No pleiotropic effects were observed, and MR heterogeneity tests indicated dataset homogeneity. Our study establishes a causal link between RA, SLE, hyperthyroidism, and PCa.
Association between life’s essential 8 and overactive bladder
Authors: Feng Guoliang , Huang Shaoqun , Zhao Weimin , Gong Hongyang
Published: May 2024

Limited research has explored the relationship between overactive bladder (OAB) and cardiovascular health (CVH). We aim to examine the correlation between OAB and CVH in American adults, utilizing the Life’s Essential 8 (LE8). We included 70,190 individuals from the National Health and Nutrition Examination Survey spanning from 2005 to 2018. In our study, the independent variable is LE8 score, where higher scores denote better CVH. The dependent variable is the presence of OAB. We employed multivariable logistic regression along with restricted cubic splines to evaluate the association between LE8 and OAB. Additionally, we performed interaction analyzes on subgroups to validate the findings. There is a significant negative correlation between LE8 scores and OAB. Upon adjusting for all covariates, a 10-point increase in LE8 total score correlated with a 17% decrease in the odds of OAB [0.83 (95% CI 0.78, 0.89)]. Compared to participants with lower LE8 scores, those with higher LE8 scores had a 46% lower probability of developing OAB. Consistent results were also observed in the association between scores of four health behaviors and four health factors and OAB. Furthermore, a notable interaction was observed between LE8 scores and smoking status. This study showed a significant negative correlation between LE8 scores and OAB prevalence.
MieAI: a neural network for calculating optical properties of internally mixed aerosol in atmospheric models
Authors: Kumar Pankaj , Vogel Heike , Bruckert Julia , Muth Lisa Janina , Hoshyaripour Gholam Ali
Published: May 2024

Aerosols influence weather and climate by interacting with radiation through absorption and scattering. These effects heavily rely on the optical properties of aerosols, which are mainly governed by attributes such as morphology, size distribution, and chemical composition. These attributes undergo continuous changes due to chemical reactions and aerosol micro-physics, resulting in significant spatio-temporal variations. Most atmospheric models struggle to incorporate this variability because they use pre-calculated tables to handle aerosol optics. This offline approach often leads to substantial errors in estimating the radiative impacts of aerosols along with posing significant computational burdens. To address this challenge, we introduce a computationally efficient and robust machine learning approach called MieAI. It allows for relatively inexpensive calculation of the optical properties of internally mixed aerosols with a log-normal size distribution. Importantly, MieAI fully incorporates the variability in aerosol chemistry and microphysics. Our evaluation of MieAI against traditional Mie calculations, using number concentrations from the ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases (ICON-ART) simulations, demonstrates that MieAI exhibits excellent predictive accuracy for aerosol optical properties. MieAI achieves this with errors well within 10%, and it operates more than 1000 times faster than the benchmark approach of Mie calculations. Due to its generalized nature, the MieAI approach can be implemented in any chemistry transport model which represents aerosol size distribution in the form of log-normally distributed internally mixed modes. This advancement has the potential to replace frequently employed look-up tables and plays a substantial role in the ongoing attempts to reduce uncertainties in estimating aerosol radiative forcing.
Basin-dependent response of Northern Hemisphere winter blocking frequency to CO2 removal
Authors: Hwang Jaeyoung , Son Seok-Woo , Martineau Patrick , Sung Mi-Kyung , Barriopedro David , An Soon-Il , Yeh Sang-Wook , Min Seung-Ki , Kug Jong-Seong , Shin Jongsoo
Published: May 2024

Atmospheric blocking has been identified as one of the key elements of the extratropical atmospheric variabilities, controlling extreme weather events in mid-latitudes. Future projections indicate that Northern Hemisphere winter blocking frequency may decrease as CO2 concentrations increase. Here, we show that such changes may not be reversed when CO2 concentrations return to the current levels. Blocking frequency instead exhibits basin-dependent changes in response to CO2 removal. While the North Atlantic blocking frequency recovers gradually from the CO2-induced eastward shift, the North Pacific blocking frequency under the CO2 removal remains lower than its initial state. These basin-dependent blocking frequency changes result from background flow changes and their interactions with high-frequency eddies. Both high-frequency eddy and background flow changes determine North Atlantic blocking changes, whereas high-frequency eddy changes dominate the slow recovery of North Pacific blocking. Our results indicate that blocking-related extreme events in the Northern Hemisphere winter may not monotonically respond to CO2 removal.
Early adverse physiological event detection using commercial wearables: challenges and opportunities
Authors: Phipps Jesse , Passage Bryant , Sel Kaan , Martinez Jonathan , Saadat Milad , Koker Teddy , Damaso Natalie , Davis Shakti , Palmer Jeffrey , Claypool Kajal , Kiley Christopher , Pettigrew Roderic I. , Jafari Roozbeh
Published: May 2024

Data from commercial off-the-shelf (COTS) wearables leveraged with machine learning algorithms provide an unprecedented potential for the early detection of adverse physiological events. However, several challenges inhibit this potential, including (1) heterogeneity among and within participants that make scaling detection algorithms to a general population less precise, (2) confounders that lead to incorrect assumptions regarding a participant’s healthy state, (3) noise in the data at the sensor level that limits the sensitivity of detection algorithms, and (4) imprecision in self-reported labels that misrepresent the true data values associated with a given physiological event. The goal of this study was two-fold: (1) to characterize the performance of such algorithms in the presence of these challenges and provide insights to researchers on limitations and opportunities, and (2) to subsequently devise algorithms to address each challenge and offer insights on future opportunities for advancement. Our proposed algorithms include techniques that build on determining suitable baselines for each participant to capture important physiological changes and label correction techniques as it pertains to participant-reported identifiers. Our work is validated on potentially one of the largest datasets available, obtained with 8000+ participants and 1.3+ million hours of wearable data captured from Oura smart rings. Leveraging this extensive dataset, we achieve pre-symptomatic detection of COVID-19 with a performance receiver operator characteristic (ROC) area under the curve (AUC) of 0.725 without correction techniques, 0.739 with baseline correction, 0.740 with baseline correction and label correction on the training set, and 0.777 with baseline correction and label correction on both the training and the test set. Using the same respective paradigms, we achieve ROC AUCs of 0.919, 0.938, 0.943 and 0.994 for the detection of self-reported fever, and 0.574, 0.611, 0.601, and 0.635 for detection of self-reported shortness of breath. These techniques offer improvements across almost all metrics and events, including PR AUC, sensitivity at 75% specificity, and precision at 75% recall. The ring allows continuous monitoring for detection of event onset, and we further demonstrate an improvement in the early detection of COVID-19 from an average of 3.5 days to an average of 4.1 days before a reported positive test result.
The integration of metabolic and proteomic data uncovers an augmentation of the sphingolipid biosynthesis pathway during T-cell differentiation
Authors: Kanno Toshio , Konno Ryo , Sato Masaru , Kurabayashi Atsushi , Miyako Keisuke , Nakajima Takahiro , Yokoyama Satoru , Sasamoto Shigemi , Asou Hikari K. , Ohzeki Junichiro , Hasegawa Yoshinori , Ikeda Kazutaka , Kawashima Yusuke , Ohara Osamu , Endo Yusuke
Published: May 2024

Recent studies have highlighted the significance of cellular metabolism in the initiation of clonal expansion and effector differentiation of T cells. Upon exposure to antigens, naïve CD4+ T cells undergo metabolic reprogramming to meet their metabolic requirements. However, only few studies have simultaneously evaluated the changes in protein and metabolite levels during T cell differentiation. Our research seeks to fill the gap by conducting a comprehensive analysis of changes in levels of metabolites, including sugars, amino acids, intermediates of the TCA cycle, fatty acids, and lipids. By integrating metabolomics and proteomics data, we discovered that the quantity and composition of cellular lipids underwent significant changes in different effector Th cell subsets. Especially, we found that the sphingolipid biosynthesis pathway was commonly activated in Th1, Th2, Th17, and iTreg cells and that inhibition of this pathway led to the suppression of Th17 and iTreg cells differentiation. Additionally, we discovered that Th17 and iTreg cells enhance glycosphingolipid metabolism, and inhibition of this pathway also results in the suppression of Th17 and iTreg cell generation. These findings demonstrate that the utility of our combined metabolomics and proteomics analysis in furthering the understanding of metabolic transition during Th cell differentiation.
Potential roles of sex-linked differences in obesity and cancer immunotherapy: revisiting the obesity paradox
Authors: Vick Logan V. , Rosario Spencer , Riess Jonathan W. , Canter Robert J. , Mukherjee Sarbajit , Monjazeb Arta M. , Murphy William J.
Published: May 2024

Obesity, a condition of excess adiposity usually defined by a BMI > 30, can have profound effects on both metabolism and immunity, connecting the condition with a broad range of diseases, including cancer and negative outcomes. Obesity and cancer have been associated with increased incidence, progression, and poorer outcomes of multiple cancer types in part due to the pro-inflammatory state that arises. Surprisingly, obesity has also recently been demonstrated in both preclinical models and clinical outcomes to be associated with improved response to immune checkpoint inhibition (ICI). These observations have laid the foundation for what has been termed the “obesity paradox”. The mechanisms underlying these augmented immunotherapy responses are still unclear given the pleiotropic effects obesity exerts on cells and tissues. Other important variables such as age and sex are being examined as further affecting the obesity effect. Sex-linked factors exert significant influences on obesity biology, metabolism as well as differential effects of different immune cell-types. Age can be another confounding factor contributing to the effects on both sex-linked changes, immune status, and obesity. This review aims to revisit the current body of literature describing the immune and metabolic changes mediated by obesity, the role of obesity on cancer immunotherapy, and to highlight questions on how sex-linked differences may influence obesity and immunotherapy outcome.
Encapsulation of a small-molecule drug based on substituted 2-aminothiophenes in calcium carbonate carriers for therapy of melanoma
Authors: Karpov Timofey E. , Rogova Anna , Akhmetova Darya R. , Tishchenko Yulia A. , Chinakova Anastasia V. , Lipin Dmitriy V. , Gavrilova Nina V. , Gorbunova Irina A. , Shipilovskikh Sergei A. , Timin Alexander S.
Published: May 2024

Encapsulation of 2-aminothiophenes in calcium carbonate particles leads to improved antitumor activity against melanoma.
Carbohydrate-active enzyme (CAZyme) discovery and engineering via (Ultra)high-throughput screening
Authors: Wardman Jacob F. , Withers Stephen G.
Published: May 2024

(Ultra)high-throughput screening is an important methodology for the identification of new and improved CAZymes. Herein, we detail how new technologies and understandings of enzyme mechanisms have been applied towards innovative screening approaches.
Total synthesis of (−)-securingine G
Authors: Youn Taesik , Kim Taewan , Han Sunkyu
Published: May 2024

In this study, we present the first total synthesis of (−)-securingine G.
Harnessing a simple ratiometric fluorescent probe for albumin recognition and beyond
Authors: Xu Zhongyong , Deng Weihua , Li Na , Lv Taoyuze , Wang Lei , Chen Xiaoqiang , Li Mingle , Zhang Wenxing , Liu Bin , Peng Xiaojun
Published: May 2024

A commercially available naphthalene fluorophore serves as a ratiometric indicator for albumin, showcasing its applications in albumin-based supramolecular recognition.
Reactivity of surface oxygen vacancy sites and frustrated Lewis acid–base pairs of In2O3 catalysts in CO2 hydrogenation
Authors: Wei Zhangqian , Li Shenggang , Gao Peng
Published: May 2024

The effects of VO formation energies and surface frustrated Lewis acid–base pairs on CO2 hydrogenation over In2O3 catalysts were studied using DFT calculations.
Hydrothermal and anion exchange synthesis of Mn(v)-doped Ba5(PO4)3Cl nano-apatite toward NIR-II temperature sensing
Authors: Huang Wenjing , Zhang Jiahui , Zheng Yuchuan , Zeng Linyun , Liu Wei , Umar Zafari , Xie Mubiao , Bokshyts Yuliya , Pan Jialiang , Zhang Xinguo
Published: May 2024

Mn5+-doped Ba5(PO4)3Cl nano-apatite with NIR-II luminescence is made by a two-step (hydrothermal and anion exchange) method. This nanophosphor can serve as a nanothermometer in the NIR-II window with high sensitivity.
Probing assembly/disassembly of ordered molecular hydrogels
Authors: Ramalhete Susana M. , Nartowski Karol P. , Green Hayley , Angulo Jesús , Iuga Dinu , Fábián László , Lloyd Gareth O. , Khimyak Yaroslav Z.
Published: May 2024

Using multicomponent gels based on Phe and amino-l-phenylalanine (NH2-Phe), we explore the trends of assembly and disassembly of the gels depending on their compositions and patterns of intermolecular interactions in the gel fibres and at the fibre/solution interfaces.
Enhancing direct hydroxylation of benzene to phenol on Fe1/PMA single-atom catalyst: a comparative study of H2O2vs.O2-assisted reactions
Authors: Bashir Beenish , Talib Shamraiz Hussain , Khan Muhammad Ajmal , Mohamed Sharmarke , Qurashi Ahsanulhaq , Xiao Hai , Li Jun
Published: May 2024

This study enhances benzene oxidation to phenol using Fe1/PMA catalyst under ambient conditions, providing insights for sustainable catalytic processes, especially regarding selection of oxidant.
Surface-enhanced optical-mid-infrared photothermal microscopy using shortened colloidal silver nanowires: a noble approach for mid-infrared surface sensing
Authors: Baden Naoki , Watanabe Hirohmi , Aoyagi Masaru , Ujii Hiroshi , Fujita Yasuhiko
Published: May 2024

This paper presents a novel approach to optical-mid-infrared photothermal (MIP) microscopy that enables surface sensing of polymer top surfaces with a depth resolution below 20 nm.
Total synthesis and structure–antifouling activity relationship of scabrolide F
Authors: Takamura Hiroyoshi , Sugitani Yuki , Morishita Ryohei , Yorisue Takefumi , Kadota Isao
Published: May 2024

The details of our total synthesis of scabrolide F are described. The synthetic scabrolide F and its synthetic intermediates exhibited antifouling activity without toxicity.
Chiral amino acids: evolution in atroposelective C–H activation
Authors: Parmar Diksha , Kumar Rohit , Sharma Upendra
Published: May 2024

This review covers the journey of chiral amino acids as ligands in atroposelective C–H bond activation/functionalization via transition metal catalysis.
Heliphyrin: a ring open porphyrinoid with helical chirality
Authors: Schrage Briana R. , Gaire Sanjay , Mamattah Kirsty , Nevonen Dustin E. , Nemykin Victor N. , Ziegler Christopher J.
Published: May 2024

We report the template-based synthesis of a new series of ring-open phthalocyanine analogs that exhibit helical chirality. These conjugated helical porphyrinoids also strongly absorb across the entire visible spectrum.
Copper-catalyzed remote nucleophilic substitution of 5-ethynylthiophene esters
Authors: Li Xiang , Qian Hao-Dong , Qiao Xinying , Zhao Chunhui , Lu Yuepeng , Zhu Cuiju , Xu Hao
Published: May 2024

Here we demonstrate a strategy for the copper-catalyzed remote nucleophilic substitution of 5-ethynylthiophene esters at the η-position.
Emulsions in microfluidic channels with asymmetric boundary conditions and directional surface roughness: stress and rheology
Authors: Pelusi Francesca , Filippi Daniele , Derzsi Ladislav , Pierno Matteo , Sbragaglia Mauro
Published: May 2024

Numerical simulations help in elaborating a validated protocol for reconstructing stress profiles in channels with asymmetric boundary conditions and directional roughness, which is crucial for investigating rheological responses near the rough wall.
Heterostructures stacked with X2SY (X = In, Ga; Y = Se, Te) and g-C2N monolayers for high power conversion efficiency solar cells: insight from electronic properties and nonadiabatic dynamics
Authors: Wan Xue-Qing , Yang Chuan-Lu , Li Xiao-Hu , Liu Yu-Liang , Zhao Wen-Kai
Published: May 2024

A g-C2N/In2STe heterostructure with high power conversion efficiency (10.01%) and carrier utilization efficiency was screened from 114 different configurations based on its electronic properties and nonadiabatic molecular dynamics.
A green oxidizer based on 1,2,3-triazole with a high oxygen balance of +23.3%: a promising replacement of ammonium perchlorate in solid propellants
Authors: Zhao Pinxu , Chen Long , Zhang Qingzhong , Ling Yifei , Lin Qiuhan , Huang Haifeng , Yang Jun
Published: May 2024

A triazole compound (JY-23) with the largest number of nitro groups (seven nitro groups) was designed and synthesized.
Interfacial defect passivation via imidazolium bromide for efficient, stable perovskite solar cells
Authors: Chen Zijing , Jiang Shiyu , Liu Zhenghao , Li Yiming , Shi Jiangjian , Wu Huijue , Luo Yanhong , Li Dongmei , Meng Qingbo
Published: May 2024

1-Methyl-3-benzyl-imidazolium bromide is introduced to passivate the FAPbI3/spiro-OMeTAD interface for efficient and stable PSCs. The champion device achieves a PCE of 25.3% with negligible hysteresis and excellent operational stability.
Giant piezoelectricity and ferroelectricity in two-dimensional ThOTe monolayers
Authors: Zhao Hongbo , Wei Tan , Ren Na , Ding Longhua , Yu Xin , Wang Aizhu , Peng Jingyang , Zhao Mingwen , Liu Hong
Published: May 2024

ThOTe monolayers, through strain engineering, exhibit exceptional piezoelectric and ferroelectric properties with a high coefficient (d11 = 354.95 pm V−1 at 14% strain). This material offers a promising basis for advanced electronic devices.
Distributed angle‐only orbit determination algorithm for non‐cooperative spacecraft based on factor graph
Authors: Zhang Zhixun , Zhang Keke , Shu Leizheng , Zhu Zhencai , Zhou Meijiang
Published: May 2024

Bayesian filtering provides an effective approach for the orbit determination of a non‐cooperative target using angle measurements from multiple CubeSats. However, existing methods face challenges such as low reliability and limited estimation accuracy. Two distributed filtering algorithms based on factor graphs employed in the sub‐parent and distributed cluster spacecraft architectures are proposed. Two appropriate factor graphs representing different cluster spacecraft structures are designed and implement distributed Bayesian filtering within these models. The Gaussian messages transmitted between nodes and the probability distributions of variable nodes are calculated using the derived non‐linear Gaussian belief propagation algorithm. Gaussian messages propagate from the deputy spacecraft to the chief spacecraft in the sub‐parent spacecraft architecture, demonstrating that the estimation accuracy converges to the centralised extended Kalman filter (EKF). Simulation results indicate that the algorithm enhances system robustness in observation node failures without compromising accuracy. In the distributed spacecraft architecture, neighbouring spacecraft iteratively exchanges Gaussian messages. The accuracy of the algorithm can rapidly approach the centralised EKF, benefiting from the efficient and unbiased transmission of observational information. Compared to existing distributed consensus filtering algorithms, the proposed algorithm improves estimation accuracy and reduces the number of iterations needed to achieve consensus.
Optimisation of energy efficiency of ambient backscatter communication and reconfigurable intelligent surfaces in non‐orthogonal multiple access downlink
Authors: Gao Ruiman , Li Suoping , Yang Nana , Yang Sa , Yang Qian
Published: May 2024

The authors study the energy efficiency (EE) of ambient backscatter communication (AmBC) device‐assisted and reconfigurable intelligent surfaces (RIS)‐assisted non‐orthogonal multiple access (NOMA) downlinks. The authors establish two optimisation problems based on the two collaborative devices (AmBC devices, RIS) with the objective of maximising the EE of the system, taking into account the requirements of power limitation and rate limitation, etc. and also obtain the solutions of two problems by optimising the relevant performance metrics based on the alternating optimisation algorithm. For the backscatter device (BD)‐aided downlink NOMA network, the problem is first decoupled into three subproblems, where the power allocation optimisation subproblem is solved by using the quadratic transformation method and the subgradient algorithm. The maximum EE is obtained by iterating according to the Dinkelbach's algorithm. For the RIS‐aided downlink NOMA network, the power allocation problem is solved by the same method as above and the phase optimisation problem is solved by the successive convex approximation method. Numerical results show that the proposed algorithm can achieve convergence after several iterations, and the EE of systems with BD‐assisted and RIS‐assisted have different levels of sensitivity to different influencing factors.
“Forbidden” stars in the eROSITA all-sky survey: X-ray emission from very late-type giants
Authors: Schmitt J. H. M. M. , Hünsch M. , Schneider P. C. , Freund S. , Czesla S. , Robrade J. , Schwope A.
Published: May 2024

We present the results of the first X-ray all-sky survey (eRASS1) performed by the eROSITA instrument aboard the Spectrum-Roentgen-Gamma (SRG) mission on X-ray emitting red giants and supergiants. Focusing on stars positioned at high galactic latitudes above 20°, we constructed a complete sample of such objects using the Gaia DR3 catalog and identified a sample 96 stars that appear as bona fide entries in the eRASS1 source catalog. By again restricting the sample to objects nearer than 1300 pc and eliminating all catalog entries that are due to optical contamination, we ended up with a sample of 16 genuine red giant or supergiant X-ray sources, most of which represent new X-ray detections. We present a low signal-to-noise X-ray spectrum of the nearby low-activity giant Arcturus obtained from a pointed observation with the XMM-Newton satellite and give a detailed account of our data analysis. We show that Arcturus-like X-ray emission cannot be the explanation for the X-ray emissions observed by eROSITA and provide a discussion of the possible nature of the detected X-ray sources.
The behaviour of eccentric sub-pc massive black hole binaries embedded in massive discs
Authors: Franchini Alessia , Prato Alessandra , Longarini Cristiano , Sesana Alberto
Published: May 2024

Using the 3D smoothed-particle hydrodynamics code PHANTOM, we investigated the evolution of the orbital properties of massive black hole binaries embedded in massive discs where gravitational instabilities (GIs) triggered by the disc’s self-gravity are the only significant source of angular momentum transport. In particular, we investigated the evolution of binaries with different initial eccentricities of e0 = 0.05, 0.5, 0.8 and mass ratios of q = 0.1, 0.3, 0.9. Previous studies indicate an equilibrium eccentricity of around 0.6 < e < 0.8, where the binary tidal torques and disc self-gravity torque are in dynamical balance. Our simulations suggest that there might not be a universal value of critical eccentricity. We find that binaries that are initially more eccentric attain higher asymptotic eccentricity than more circular ones do. This implies that there is a range of critical eccentricity values that depend on the initial condition and microphysics (initial eccentricity, mass ratio, cooling) of the system. In particular, we find the width of this range to be narrower for more unequal binaries. We furthermore measured preferential accretion on one of the binary components, only finding more accretion onto the primary for the mass ratio q = 0.3 and eccentricity e = 0.8. We discuss how this might have implications for the amplitude of the gravitational wave background detected by pulsar timing array (PTA) experiments. We finally measure the corresponding value of the viscosity parameter α due to GIs in our simulations and discuss how this depends on the binary properties.
Numerous bidirectionally propagating plasma blobs near the reconnection site of a solar eruption
Authors: Hou Zhenyong , Tian Hui , Madjarska Maria S. , Chen Hechao , Samanta Tanmoy , Bai Xianyong , Li Zhentong , Su Yang , Chen Wei , Deng Yuanyong
Published: May 2024

A current sheet is a common structure involved in solar eruptions. However, it is observed in a minority of the events, and the physical properties of its fine structures during a solar eruption are rarely investigated. Here, we report an on-disk observation that displays 108 compact, circular, or elliptic bright structures, presumably plasma blobs, propagating bidirectionally along a flare current sheet during a period of ∼24 min. Using extreme ultraviolet images, we investigated the temporal variation of the blob number around the flare’s peak time. The current sheet connects the flare loops and the erupting filament. The width, duration, projected velocity, temperature, and density of these blobs are ∼1.7 ± 0.5 Mm, ∼79 ± 57 s, ∼191 ± 81 km s−1, ∼106.4 ± 0.1 K, and ∼1010.1 ± 0.3 cm−3, respectively. The reconnection site rises with a velocity of ≤69 km s−1. The observational results suggest that plasmoid instability plays an important role in the energy-release process of solar eruptions.
Proton polytropic behavior of periodic density structures in the solar wind
Authors: Katsavrias C. , Nicolaou G. , Di Matteo S. , Kepko L. , Viall N. M. , Aminalragia-Giamini S. , Livadiotis G.
Published: May 2024

Context. In recent years, mesoscales have gained scientific interest because they have been determined to be important in a broad range of phenomena throughout heliophysics. The solar wind mesoscale structures include periodic density structures (PDSs), which are quasi-periodic increases in the density of the solar wind that range from a few minutes to a few hours. These structures have been extensively observed in remote-sensing observations of the solar corona and in in situ observations out to 1 AU, where they manifest as radial length scales greater than or equal to the size of the Earth’s dayside magnetosphere, that is, from tens to hundreds of Earth radii (RE). While the precise mechanisms that form PDSs are still debated, recent studies confirmed that most PDSs are of solar origin and do not form through dynamics during their propagation in the interplanetary space.

Aims. We further investigate the origin of PDSs by exploring the thermodynamic signature of these structures. To do this, we estimate the values of the effective polytropic index (Y) and the entropy of protons, which in turn are compared with the corresponding values found for the solar wind.

Methods. We used an extensive list of PDS events spanning more than two solar cycles of Wind measurements (the entire Wind dataset from 1995 to 2022) to investigate the thermodynamic signatures of PDSs. With the use of wavelet methods, we classified these PDSs as coherent or incoherent, based on the shared periodic behavior between proton density and alpha-to-proton ratio, and we derive the proton polytropic index.

Results. Our results indicate that the coherent PDSs exhibit lower Y values
(Ῡ≈1.54)
on average and a higher entropy than the values in the entire Wind dataset
(Ῡ≈1.79), but also exhibit similarities with the magnetic cloud of an interplanetary coronal mass ejection. In contrast, incoherent PDSs exhibit the same Y values as those of the entire Wind dataset.