bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-term hypercaloric carbohydrate loading increases surgical stress resilience by inducing FGF21
Authors: Agius Thomas , Emsley Raffaella , Lyon Arnaud , MacArthur Michael R. , Kiesworo Kevin , Faivre Anna , Stavart Louis , Lambelet Martine , Legouis David , de Seigneux Sophie , Golshayan Déla , Lazeyras Francois , Yeh Heidi , Markmann James F. , Uygun Korkut , Ocampo Alejandro , Mitchell Sarah J. , Allagnat Florent , Déglise Sébastien , Longchamp Alban
Published: February 2024

Dietary restriction promotes resistance to surgical stress in multiple organisms. Counterintuitively, current medical protocols recommend short-term carbohydrate-rich drinks (carbohydrate loading) prior to surgery, part of a multimodal perioperative care pathway designed to enhance surgical recovery. Despite widespread clinical use, preclinical and mechanistic studies on carbohydrate loading in surgical contexts are lacking. Here we demonstrate in ad libitum-fed mice that liquid carbohydrate loading for one week drives reductions in solid food intake, while nearly doubling total caloric intake. Similarly, in humans, simple carbohydrate intake is inversely correlated with dietary protein intake. Carbohydrate loading-induced protein dilution increases expression of hepatic fibroblast growth factor 21 (FGF21) independent of caloric intake, resulting in protection in two models of surgical stress: renal and hepatic ischemia-reperfusion injury. The protection is consistent across male, female, and aged mice. In vivo, amino acid add-back or genetic FGF21 deletion blocks carbohydrate loading-mediated protection from ischemia-reperfusion injury. Finally, carbohydrate loading induction of FGF21 is associated with the induction of the canonical integrated stress response (ATF3/4, NF-kB), and oxidative metabolism (PPARγ). Together, these data support carbohydrate loading drinks prior to surgery and reveal an essential role of protein dilution via FGF21.
Unzipped genome assemblies of polyploid root-knot nematodes reveal unusual and clade-specific telomeric repeats
Authors: Mota Ana Paula Zotta , Koutsovoulos Georgios D. , Perfus-Barbeoch Laetitia , Despot-Slade Evelin , Labadie Karine , Aury Jean-Marc , Robbe-Sermesant Karine , Bailly-Bechet Marc , Belser Caroline , Péré Arthur , Rancurel Corinne , Kozlowski Djampa K. , Hassanaly-Goulamhoussen Rahim , Da Rocha Martine , Noel Benjamin , Meštrović Nevenka , Wincker Patrick , Danchin Etienne G. J.
Published: February 2024

Using long-read sequencing, we assembled and unzipped the polyploid genomes of Meloidogyne incognita, M. javanica and M. arenaria, three of the most devastating plant-parasitic nematodes. We found the canonical nematode telomeric repeat to be missing in these and other Meloidogyne genomes. In addition, we find no evidence for the enzyme telomerase or for orthologs of C. elegans telomere-associated proteins, suggesting alternative lengthening of telomeres. Instead, analyzing our assembled genomes, we identify species-specific composite repeats enriched mostly at one extremity of contigs. These repeats are G-rich, oriented, and transcribed, similarly to canonical telomeric repeats. We confirm them as telomeric using fluorescent in situ hybridization. These repeats are mostly found at one single end of chromosomes in these species. The discovery of unusual and specific complex telomeric repeats opens a plethora of perspectives and highlights the evolutionary diversity of telomeres despite their central roles in senescence, aging, and chromosome integrity.
Rapid exchange cooling with trapped ions
Authors: Fallek Spencer D. , Sandhu Vikram S. , McGill Ryan A. , Gray John M. , Tinkey Holly N. , Clark Craig R. , Brown Kenton R.
Published: February 2024

The trapped-ion quantum charge-coupled device (QCCD) architecture is a leading candidate for advanced quantum information processing. In current QCCD implementations, imperfect ion transport and anomalous heating can excite ion motion during a calculation. To counteract this, intermediate cooling is necessary to maintain high-fidelity gate performance. Cooling the computational ions sympathetically with ions of another species, a commonly employed strategy, creates a significant runtime bottleneck. Here, we demonstrate a different approach we call exchange cooling. Unlike sympathetic cooling, exchange cooling does not require trapping two different atomic species. The protocol introduces a bank of “coolant" ions which are repeatedly laser cooled. A computational ion can then be cooled by transporting a coolant ion into its proximity. We test this concept experimentally with two 40Ca+ ions, executing the necessary transport in 107 μs, an order of magnitude faster than typical sympathetic cooling durations. We remove over 96%, and as many as 102(5) quanta, of axial motional energy from the computational ion. We verify that re-cooling the coolant ion does not decohere the computational ion. This approach validates the feasibility of a single-species QCCD processor, capable of fast quantum simulation and computation.
Strong coupling between a microwave photon and a singlet-triplet qubit
Authors: Ungerer J. H. , Pally A. , Kononov A. , Lehmann S. , Ridderbos J. , Potts P. P. , Thelander C. , Dick K. A. , Maisi V. F. , Scarlino P. , Baumgartner A. , Schönenberger C.
Published: February 2024

Combining superconducting resonators and quantum dots has triggered tremendous progress in quantum information, however, attempts at coupling a resonator to even charge parity spin qubits have resulted only in weak spin-photon coupling. Here, we integrate a zincblende InAs nanowire double quantum dot with strong spin-orbit interaction in a magnetic-field resilient, high-quality resonator. The quantum confinement in the nanowire is achieved using deterministically grown wurtzite tunnel barriers. Our experiments on even charge parity states and at large magnetic fields, allow us to identify the relevant spin states and to measure the spin decoherence rates and spin-photon coupling strengths. We find an anti-crossing between the resonator mode in the single photon limit and a singlet-triplet qubit with a spin-photon coupling strength of g/2π = 139 ± 4 MHz. This coherent coupling exceeds the resonator decay rate κ/2π = 19.8 ± 0.2 MHz and the qubit dephasing rate γ/2π = 116 ± 7 MHz, putting our system in the strong coupling regime.
Eosinophils preserve bone homeostasis by inhibiting excessive osteoclast formation and activity via eosinophil peroxidase
Authors: Andreev Darja , Kachler Katerina , Liu Mengdan , Chen Zhu , Krishnacoumar Brenda , Ringer Mark , Frey Silke , Krönke Gerhard , Voehringer David , Schett Georg , Bozec Aline
Published: February 2024

Eosinophils are involved in tissue homeostasis. Herein, we unveiled eosinophils as important regulators of bone homeostasis. Eosinophils are localized in proximity to bone-resorbing osteoclasts in the bone marrow. The absence of eosinophils in ΔdblGATA mice results in lower bone mass under steady-state conditions and amplified bone loss upon sex hormone deprivation and inflammatory arthritis. Conversely, increased numbers of eosinophils in IL-5 transgenic mice enhance bone mass under steady-state conditions and protect from hormone- and inflammation- mediated bone loss. Eosinophils strongly inhibit the differentiation and demineralization activity of osteoclasts and lead to profound changes in the transcriptional profile of osteoclasts. This osteoclast-suppressive effect of eosinophils is based on the release of eosinophil peroxidase causing impaired reactive oxygen species and mitogen-activated protein kinase induction in osteoclast precursors. In humans, the number and the activity of eosinophils correlates with bone mass in healthy participants and rheumatoid arthritis patients. Taken together, experimental and human data indicate a regulatory function of eosinophils on bone.
Exploring negative emission potential of biochar to achieve carbon neutrality goal in China
Authors: Deng Xu , Teng Fei , Chen Minpeng , Du Zhangliu , Wang Bin , Li Renqiang , Wang Pan
Published: February 2024

Limiting global warming to within 1.5 °C might require large-scale deployment of premature negative emission technologies with potentially adverse effects on the key sustainable development goals. Biochar has been proposed as an established technology for carbon sequestration with co-benefits in terms of soil quality and crop yield. However, the considerable uncertainties that exist in the potential, cost, and deployment strategies of biochar systems at national level prevent its deployment in China. Here, we conduct a spatially explicit analysis to investigate the negative emission potential, economics, and priority deployment sites of biochar derived from multiple feedstocks in China. Results show that biochar has negative emission potential of up to 0.92 billion tons of CO2 per year with an average net cost of US$90 per ton of CO2 in a sustainable manner, which could satisfy the negative emission demands in most mitigation scenarios compatible with China’s target of carbon neutrality by 2060.
Self-assembled hydrated copper coordination compounds as ionic conductors for room temperature solid-state batteries
Authors: Zhan Xiao , Li Miao , Zhao Xiaolin , Wang Yaning , Li Sha , Wang Weiwei , Lin Jiande , Nan Zi-Ang , Yan Jiawei , Sun Zhefei , Liu Haodong , Wang Fei , Wan Jiayu , Liu Jianjun , Zhang Qiaobao , Zhang Li
Published: February 2024

As the core component of solid-state batteries, neither current inorganic solid-state electrolytes nor solid polymer electrolytes can simultaneously possess satisfactory ionic conductivity, electrode compatibility and processability. By incorporating efficient Li+ diffusion channels found in inorganic solid-state electrolytes and polar functional groups present in solid polymer electrolytes, it is conceivable to design inorganic-organic hybrid solid-state electrolytes to achieve true fusion and synergy in performance. Herein, we demonstrate that traditional metal coordination compounds can serve as exceptional Li+ ion conductors at room temperature through rational structural design. Specifically, we synthesize copper maleate hydrate nanoflakes via bottom-up self-assembly featuring highly-ordered 1D channels that are interconnected by Cu2+/Cu+ nodes and maleic acid ligands, alongside rich COO− groups and structural water within the channels. Benefiting from the combination of ion-hopping and coupling-dissociation mechanisms, Li+ ions can preferably transport through these channels rapidly. Thus, the Li+-implanted copper maleate hydrate solid-state electrolytes shows remarkable ionic conductivity (1.17 × 10−4 S cm−1 at room temperature), high Li+ transference number (0.77), and a 4.7 V-wide operating window. More impressively, Li+-implanted copper maleate hydrate solid-state electrolytes are demonstrated to have exceptional compatibility with both cathode and Li anode, enabling long-term stability of more than 800 cycles. This work brings new insight on exploring superior room-temperature ionic conductors based on metal coordination compounds.
Development of multifunctional membranes via plasma-assisted nonsolvent induced phase separation
Authors: Huang Yueh-Han , Wang Meng-Jiy , Chung Tai-Shung
Published: February 2024

Demands on superhydrophobic, self-cleaning and piezoelectric membranes have gained significantly due to their potential to overcome global shortages in clean water and energy. In this study, we have discovered a novel plasma-assisted nonsolvent induced phase separation (PANIPS) method to prepare superhydrophobic, self-cleaning and piezoelectric poly(vinylidene difluoride) (PVDF) membranes without additional chemical modifications or post-treatments. The PANIPS membranes exhibit water contact angles ranging from 151.2° to 166.4° and sliding angles between 6.7° and 29.7°. They also show a high piezoelectric coefficient (d33) of 10.5 pC N−1 and can generate a high output voltage of 10 Vpp. The PANIPS membranes can effectively recover pure water from various waste solutions containing Rose Bengal dye, humic acid, or sodium dodecyl sulfate via direct contact membrane distillation (DCMD). This study may provide valuable insights to fabricate PANIPS membranes and open up new avenues to molecularly design advanced superhydrophobic, self-cleaning, and piezoelectric membranes in the fields of clean water production, motion sensor, and piezoelectric nanogenerator.
Collectively enhanced Ramsey readout by cavity sub- to superradiant transition
Authors: Bohr Eliot A. , Kristensen Sofus L. , Hotter Christoph , Schäffer Stefan A. , Robinson-Tait Julian , Thomsen Jan W. , Zelevinsky Tanya , Ritsch Helmut , Müller Jörg H.
Published: February 2024

When an inverted ensemble of atoms is tightly packed on the scale of its emission wavelength or when the atoms are collectively strongly coupled to a single cavity mode, their dipoles will align and decay rapidly via a superradiant burst. However, a spread-out dipole phase distribution theory predicts a required minimum threshold of atomic excitation for superradiance to occur. Here we experimentally confirm this predicted threshold for superradiant emission on a narrow optical transition when exciting the atoms transversely and show how to take advantage of the resulting sub- to superradiant transition. A π/2-pulse places the atoms in a subradiant state, protected from collective cavity decay, which we exploit during the free evolution period in a corresponding Ramsey pulse sequence. The final excited state population is read out via superradiant emission from the inverted atomic ensemble after a second π/2-pulse, and with minimal heating this allows for multiple Ramsey sequences within one experimental cycle. Our scheme is an innovative approach to atomic state readout characterized by its speed, simplicity, and highly directional emission of signal photons. It demonstrates the potential of sensors using collective effects in cavity-coupled quantum emitters.
Isolation and characterization of a pangolin-borne HKU4-related coronavirus that potentially infects human-DPP4-transgenic mice
Authors: Xia Luo-Yuan , Wang Zhen-Fei , Cui Xiao-Ming , Li Yuan-Guo , Ye Run-Ze , Zhu Dai-Yun , Li Fang-Xu , Zhang Jie , Wang Wen-Hao , Zhang Ming-Zhu , Gao Wan-Ying , Li Lian-Feng , Que Teng-Cheng , Wang Tie-Cheng , Jia Na , Jiang Jia-Fu , Gao Yu-Wei , Cao Wu-Chun
Published: February 2024

We recently detected a HKU4-related coronavirus in subgenus Merbecovirus (named pangolin-CoV-HKU4-P251T) from a Malayan pangolin1. Here we report isolation and characterization of pangolin-CoV-HKU4-P251T, the genome sequence of which is closest to that of a coronavirus from the greater bamboo bat (Tylonycteris robustula) in Yunnan Province, China, with a 94.3% nucleotide identity. Pangolin-CoV-HKU4-P251T is able to infect human cell lines, and replicates more efficiently in cells that express human-dipeptidyl-peptidase-4 (hDPP4)-expressing and pangolin-DPP4-expressing cells than in bat-DPP4-expressing cells. After intranasal inoculation with pangolin-CoV-HKU4-P251, hDPP4-transgenic female mice are likely infected, showing persistent viral RNA copy numbers in the lungs. Progressive interstitial pneumonia developed in the infected mice, characterized by the accumulation of macrophages, and increase of antiviral cytokines, proinflammatory cytokines, and chemokines in lung tissues. These findings suggest that the pangolin-borne HKU4-related coronavirus has a potential for emerging as a human pathogen by using hDPP4.
Mechanically resilient hybrid aerogels containing fibers of dual-scale sizes and knotty networks for tissue regeneration
Authors: Shahriar S. M. Shatil , McCarthy Alec D. , Andrabi Syed Muntazir , Su Yajuan , Polavoram Navatha Shree , John Johnson V. , Matis Mitchell P. , Zhu Wuqiang , Xie Jingwei
Published: February 2024

The structure and design flexibility of aerogels make them promising for soft tissue engineering, though they tend to come with brittleness and low elasticity. While increasing crosslinking density may improve mechanics, it also imparts brittleness. In soft tissue engineering, resilience against mechanical loads from mobile tissues is paramount. We report a hybrid aerogel that consists of self-reinforcing networks of micro- and nanofibers. Nanofiber segments physically entangle microfiber pillars, allowing efficient stress distribution through the intertwined fiber networks. We show that optimized hybrid aerogels have high specific tensile moduli (~1961.3 MPa cm3 g−1) and fracture energies (~7448.8 J m−2), while exhibiting super-elastic properties with rapid shape recovery (~1.8 s). We demonstrate that these aerogels induce rapid tissue ingrowth, extracellular matrix deposition, and neovascularization after subcutaneous implants in rats. Furthermore, we can apply them for engineering soft tissues via minimally invasive procedures, and hybrid aerogels can extend their versatility to become magnetically responsive or electrically conductive, enabling pressure sensing and actuation.
Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition
Authors: Guzman Ulises H. , Martinez-Val Ana , Ye Zilu , Damoc Eugen , Arrey Tabiwang N. , Pashkova Anna , Renuse Santosh , Denisov Eduard , Petzoldt Johannes , Peterson Amelia C. , Harking Florian , Østergaard Ole , Rydbirk Rasmus , Aznar Susana , Stewart Hamish , Xuan Yue , Hermanson Daniel , Horning Stevan , Hock Christian , Makarov Alexander , Zabrouskov Vlad , Olsen Jesper V.
Published: February 2024

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run.
Correcting PCR amplification errors in unique molecular identifiers to generate accurate numbers of sequencing molecules
Authors: Sun Jianfeng , Philpott Martin , Loi Danson , Li Shuang , Monteagudo-Mesas Pablo , Hoffman Gabriela , Robson Jonathan , Mehta Neelam , Gamble Vicki , Brown Tom , Brown Tom , Canzar Stefan , Oppermann Udo , Cribbs Adam P.
Published: February 2024

Unique molecular identifiers are random oligonucleotide sequences that remove PCR amplification biases. However, the impact that PCR associated sequencing errors have on the accuracy of generating absolute counts of RNA molecules is underappreciated. We show that PCR errors are a source of inaccuracy in both bulk and single-cell sequencing data, and synthesizing unique molecular identifiers using homotrimeric nucleotide blocks provides an error-correcting solution that allows absolute counting of sequenced molecules.
Development of Groundwater Levels Dataset for Chile since 1970
Authors: Venegas-Quiñones Héctor Leopoldo , Valdés-Pineda Rodrigo , García-Chevesich Pablo , Valdés Juan B. , Gupta Hoshin V. , Whitaker Martha P. L. , Ferré Ty P. A.
Published: February 2024

Access to accurate spatio-temporal groundwater level data is crucial for sustainable water management in Chile. Despite this importance, a lack of unified, quality-controlled datasets have hindered large-scale groundwater studies. Our objective was to establish a comprehensive, reliable nationwide groundwater dataset. We curated over 120,000 records from 640 wells, spanning 1970-2021, provided by the General Water Resources Directorate. One notable enhancement to our dataset is the incorporation of elevation data. This addition allows for a more comprehensive estimation of groundwater elevation. Rigorous data quality analysis was executed through a classification scheme applied to raw groundwater level records. This resource is invaluable for researchers, decision-makers, and stakeholders, offering insights into groundwater trends to support informed, sustainable water management. Our study bridges a crucial gap by providing a dependable dataset for expansive studies, aiding water management strategies in Chile.
Chia seeds ameliorate cardiac disease risk factors via alleviating oxidative stress and inflammation in rats fed high-fat diet
Authors: Aref Mohamed , FaragAllah Eman Mahmoud , Goda Nehal I. A. , Abu-Alghayth Mohammed H. , Abomughaid Mosleh M. , Mahboub Heba H. , Alwutayd Khairiah Mubarak , Elsherbini Hadeel A.
Published: February 2024

Obesity upsurges the risk of developing cardiovascular disease, primarily heart failure and coronary heart disease. Chia seeds have a high concentration of dietary fiber and increased concentrations of anti-inflammatoryand antioxidant compounds. They are used for weight loss plus enhancing blood glucose and lipid profile. The current perspective was commenced to examine the protective influence of chia seeds ingestion on cardiovascular disease risk factors in high-fat diet-fed rats. Forty male albino rats (with an initial body weight of 180–200 g) were used in this study. Rats were randomly and equally divided into 4 groups: Group I was the control group and group II was a control group with chia seeds supplementation. Group III was a high-fat diet group (HFD) that received HFD for 10 weeks and group IV was fed on HFD plus chia seeds for 10 weeks. In all groups Echocardiographic measurements were performed, initial and final BMI, serum glucose, AC/TC ratio, lipid profile, insulin (with a computed HOMA-IR), creatinine phosphokinase-muscle/brain (CPK-MB), CRP, and cardiac troponin I (cTnI) and MAP were estimated. Whole heart weight (WHW) was calculated, and then WHW/body weight (BW) ratio was estimated. Eventually, a histopathological picture of cardiac tissues was performed to assess the changes in the structure of the heart under Haematoxylin and Eosin and Crossmon’s trichrome stain. Ingestion of a high diet for 10 weeks induced a clear elevation in BMI, AC/ TC, insulin resistance, hyperlipidemia, CRP, CPK-MB, and cTnI in all HFD groups. Moreover, there was a significant increase in MAP, left ventricular end diastolic diameter (LVEDD), and left ventricular end systolic diameter (LVESD). Furthermore, histological cardiac examination showed structural alteration of the normal structure of the heart tissue with an increase in collagen deposition. Also, the Bcl-2 expression in the heart muscle was significantly lower, but Bax expression was significantly higher. Chia seeds ingestion combined with HFD noticeably ameliorated the previously-recorded biochemical biomarkers, hemodynamic and echocardiography measures, and histopathological changes. Outcomes of this report reveal that obesity is a hazard factor for cardiovascular disease and chia seeds could be a good candidate for cardiovascular system protection.
Elevated body temperature is associated with depressive symptoms: results from the TemPredict Study
Authors: Mason Ashley E. , Kasl Patrick , Soltani Severine , Green Abigail , Hartogensis Wendy , Dilchert Stephan , Chowdhary Anoushka , Pandya Leena S. , Siwik Chelsea J. , Foster Simmie L. , Nyer Maren , Lowry Christopher A. , Raison Charles L. , Hecht Frederick M. , Smarr Benjamin L.
Published: February 2024

Correlations between altered body temperature and depression have been reported in small samples; greater confidence in these associations would provide a rationale for further examining potential mechanisms of depression related to body temperature regulation. We sought to test the hypotheses that greater depression symptom severity is associated with (1) higher body temperature, (2) smaller differences between body temperature when awake versus asleep, and (3) lower diurnal body temperature amplitude. Data collected included both self-reported body temperature (using standard thermometers), wearable sensor-assessed distal body temperature (using an off-the-shelf wearable sensor that collected minute-level physiological data), and self-reported depressive symptoms from > 20,000 participants over the course of ~ 7 months as part of the TemPredict Study. Higher self-reported and wearable sensor-assessed body temperatures when awake were associated with greater depression symptom severity. Lower diurnal body temperature amplitude, computed using wearable sensor-assessed distal body temperature data, tended to be associated with greater depression symptom severity, though this association did not achieve statistical significance. These findings, drawn from a large sample, replicate and expand upon prior data pointing to body temperature alterations as potentially relevant factors in depression etiology and may hold implications for development of novel approaches to the treatment of major depressive disorder.
An observation of a negative effect of social cohesion on creativity in musical improvisation
Authors: Kempf Adrian , Benedek Mathias , Schiavio Andrea
Published: February 2024

Although various social factors can significantly impact creative performance, it is still unclear how social cohesion (i.e., how close we feel to others) influences creativity. We therefore conducted two studies exploring the association between social cohesion and creativity within the domain of musical improvisation, a prime example of creative performance, which usually plays out in social contexts. The first study (n = 58 musical novices) showed that music-induced synchrony facilitates social cohesion. In our second study (n = 18 musical novices), we found that in two out of three experimental conditions, increased social cohesion is associated with less creative musical outcomes, as rated by nine expert musicians. In our subsequent analysis we related measures of social cohesion and creativity. This approach highlights how, within a musical setting, creativity unfolds in the context of social contingencies as social cohesion and related factors.
Biochar and conservation tillage affect the agronomic performance and fatty acid composition of Nigella sativa L. under both irrigated and dryland conditions
Authors: Kiani Hawre , Khalesro Shiva , Mokhatssi-Bidgoli Ali , Sharifi Zahed
Published: February 2024

Soils in arid and semi-arid regions like Iran have suffered greatly from low organic matter content and low water availability. Traditional tillage and the overuse of chemical fertilizers are accelerating the problems in the region. So, sensible and sustainable strategies such as conservation tillage and natural organic inputs are becoming increasingly important to enhance organic matter and humidity in the soil and grow high-quality crops in agroecosystems. Thus, in 2019 and 2020, a split-split plot arrangement within a randomized complete block design was conducted in Iran to assess the effects of irrigated conditions, tillage systems, and biochar on the aforementioned traits. There were two irrigation conditions (irrigated and dryland) as the main plots, three tillage methods (conventional, minimum, and no-tillage) as sub-plots, and two application rates for biochar (0 and 15 ton ha−1) as sub-sub plots. The findings indicated that biochar application enhanced grain yield across all tillage methods under both irrigation conditions. Biochar with minimum tillage improved oil yield by 23% and 29% compared to those that did not use biochar under the dryland and irrigated conditions, respectively. Moreover, oil yield was higher in 2020 than in 2019 for all tillage systems and biochar rates. The main components of Nigella sativa L. oil belong to linoleic, oleic, and palmitic acids. Minimum tillage with biochar under irrigated conditions in 2020 and no-tillage without biochar under dryland conditions in 2019 had the most (59%) and the least linoleic acid (53%), respectively. Conventional, minimum, and no-tillage with biochar in dryland conditions significantly increased linoleic acid by 2%, 3%, and 5% compared to those without biochar in 2020, respectively. In general, adopting biochar with minimum tillage produced the best outcomes for Nigella sativa L. yield, and grain oil quality under both irrigation conditions. It is recommended that farmers incorporate these practices to produce high-quality Nigella sativa L. in sustainable agricultural systems.
The use of deep learning integrating image recognition in language analysis technology in secondary school education
Authors: Chu Liqing , Liu Yanlan , Zhai Yixi , Wang Dandan , Wu Yufei
Published: February 2024

This work aims to investigate the application of advanced deep learning algorithms and image recognition technologies to enhance language analysis tools in secondary education, with the goal of providing educators with more effective resources and support. Based on artificial intelligence, this work integrates data mining techniques related to deep learning to analyze and study language behavior in secondary school education. Initially, a framework for analyzing language behavior in secondary school education is constructed. This involves evaluating the current state of language behavior, establishing a framework based on evaluation comments, and defining indicators for analyzing language behavior in online secondary school education. Subsequently, data mining technology and image and character recognition technology are employed to conduct data mining for online courses in secondary schools, encompassing the processing of teaching video images and character recognition. Finally, an experiment is designed to validate the proposed framework for analyzing language behavior in secondary school education. The results indicate specific differences among the grouped evaluation scores for each analysis indicator. The significance p values for the online classroom discourse’s speaking rate, speech intelligibility, average sentence length, and content similarity are −0.56, −0.71, −0.71, and −0.74, respectively. The aim is to identify the most effective teaching behaviors for learners and enhance the support for online course instruction.
Fuzzy PID control of permanent magnet synchronous motor electric steering engine by improved beetle antennae search algorithm
Authors: Zhang Bu , Niu Pingjuan , Guo Xitong , He Jiyan
Published: February 2024

The accuracy of control in permanent magnet synchronous motor system significantly affects overall mechanical structure safety. To satisfy high-performance control for the position servo of the electric steering engine, this study selects a suitable vector control model for permanent magnet synchronous motor. Additionally, an enhanced beetle antennae search algorithm is designed and employed to optimize the fuzzy proportional–integral–derivative controller. The hybrid fuzzy proportional-integral-derivative controller is then implemented in the control model of the permanent magnet synchronous motor, resulting in the establishment of a novel control model for the electric steering engine driven by the permanent magnet synchronous motor. The test results showed that root-mean-square error of this control model was 0.03 mm and 0.02 mm respectively under the conditions of sinusoidal response, square wave response and step response, which was obviously shorter than all the selected control models. In addition, the standard deviation of the control model designed in this study accounted for less than 4% of root-mean-square error of electric steering engine position under the sinusoidal response condition, so the calculation stability was high. The research results show that the designed control model has a certain reference value for improving servo control performance of permanent magnet synchronous motor.
A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring
Authors: Bajcz Alex W. , Glisson Wesley J. , Doser Jeffrey W. , Larkin Daniel J. , Fieberg John R.
Published: February 2024

To efficiently detect aquatic invasive species early in an invasion when control may still be possible, predictions about which locations are likeliest to be occupied are needed at fine scales but are rarely available. Occupancy modeling could provide such predictions given data of sufficient quality and quantity. We assembled a data set for the macroalga starry stonewort (Nitellopsis obtusa) across Minnesota and Wisconsin, USA, where it is a new and high-priority invader. We used these data to construct a multi-season, single-species spatial occupancy model that included biotic, abiotic, and movement-related predictors. Distance to the nearest access was an important occurrence predictor, highlighting the likely role boats play in spreading starry stonewort. Fetch and water depth also predicted occupancy. We estimated an average detection probability of 63% at sites with mean non-N. obtusa plant cover, declining to ~ 38% at sites with abundant plant cover, especially that of other Characeae. We recommend that surveyors preferentially search for starry stonewort in areas of shallow depth and high fetch close to boat accesses. We also recommend searching during late summer/early fall when detection is likelier. This study illustrates the utility of fine-scale occupancy modeling for predicting the locations of nascent populations of difficult-to-detect species.
Deep-WET: a deep learning-based approach for predicting DNA-binding proteins using word embedding techniques with weighted features
Authors: Mahmud S. M. Hasan , Goh Kah Ong Michael , Hosen Md. Faruk , Nandi Dip , Shoombuatong Watshara
Published: February 2024

DNA-binding proteins (DBPs) play a significant role in all phases of genetic processes, including DNA recombination, repair, and modification. They are often utilized in drug discovery as fundamental elements of steroids, antibiotics, and anticancer drugs. Predicting them poses the most challenging task in proteomics research. Conventional experimental methods for DBP identification are costly and sometimes biased toward prediction. Therefore, developing powerful computational methods that can accurately and rapidly identify DBPs from sequence information is an urgent need. In this study, we propose a novel deep learning-based method called Deep-WET to accurately identify DBPs from primary sequence information. In Deep-WET, we employed three powerful feature encoding schemes containing Global Vectors, Word2Vec, and fastText to encode the protein sequence. Subsequently, these three features were sequentially combined and weighted using the weights obtained from the elements learned through the differential evolution (DE) algorithm. To enhance the predictive performance of Deep-WET, we applied the SHapley Additive exPlanations approach to remove irrelevant features. Finally, the optimal feature subset was input into convolutional neural networks to construct the Deep-WET predictor. Both cross-validation and independent tests indicated that Deep-WET achieved superior predictive performance compared to conventional machine learning classifiers. In addition, in extensive independent test, Deep-WET was effective and outperformed than several state-of-the-art methods for DBP prediction, with accuracy of 78.08%, MCC of 0.559, and AUC of 0.805. This superior performance shows that Deep-WET has a tremendous predictive capacity to predict DBPs. The web server of Deep-WET and curated datasets in this study are available athttps://deepwet-dna.monarcatechnical.com/. The proposed Deep-WET is anticipated to serve the community-wide effort for large-scale identification of potential DBPs.
Effect of ginger supplementation on the fecal microbiome in subjects with prior colorectal adenoma
Authors: Prakash Ajay , Rubin Nathan , Staley Christopher , Onyeaghala Guillaume , Wen Ya-Feng , Shaukat Aasma , Milne Ginger , Straka Robert J. , Church Timothy R. , Prizment Anna
Published: February 2024

Ginger has been associated with a decreased incidence of colorectal cancer (CRC) through reduction in inflammatory pathways and inhibition of tumor growth. Recent pre-clinical models have implicated changes in the gut microbiome as a possible mediator of the ginger effect on CRC. We hypothesized that, in adults previously diagnosed with a colorectal adenoma, ginger supplementation would alter the fecal microbiome in the direction consistent with its CRC-inhibitory effect. Sixty-eight adults were randomized to take either ginger or placebo daily for 6 weeks, with a 6-week washout and longitudinal stool collection throughout. We performed 16S rRNA sequencing and evaluated changes in overall microbial diversity and the relative abundances of pre-specified CRC-associated taxa using mixed-effects logistic regression. Ginger supplementation showed no significant effect on microbial community structure through alpha or beta diversity. Of 10 pre-specified CRC-associated taxa, there were significant decreases in the relative abundances of the genera Akkermansia (p < 0.001), Bacteroides (p = 0.018), and Ruminococcus (p = 0.013) after 6-week treatment with ginger compared to placebo. Ginger supplementation led to decreased abundances of Akkermansia and Bacteroides, which suggests that ginger may have an inhibitory effect on CRC-associated taxa. Overall, ginger supplementation appears to have a limited effect on gut microbiome in patients with colorectal adenomas.
Dynamic phenotypic reprogramming and chemoresistance induced by lung fibroblasts in small cell lung cancer
Authors: Lu Yuanhua , Li Hui , Zhao Peiyan , Tian Lin , Liu Yan , Sun XiaoDan , Cheng Ying
Published: February 2024

Small cell lung cancer (SCLC) is heterogenous in phenotype and microenvironment. Dynamic phenotypic reprogramming, leading to heterogeneity, is prevalent in SCLC, while the mechanisms remain incompletely understood. Cancer-associated fibroblasts (CAFs) possess comprehensive roles in cancer progression, while their function in phenotypic reprogramming of SCLC remain elusive. Here, we obtained transcriptome data of SCLC tissues from publicly available databases, subsequently estimated abundance of CAFs. We found CAF-abundant SCLC exhibited non-neuroendocrine (Non-NE) characteristics. Supporting this, the positive correlation of expression level of α-SMA, the CAF marker, and expression level of REST, protein typically expressed in Non-NE type SCLC, was identified in SCLC tissue arrays. Moreover, we revealed that fibroblasts inhibited NE markers expression and cell proliferation of SCLC cells in the co-culture system comprising lung fibroblasts and SCLC cells, indicating a phenotypic reprogramming from NE to Non-NE. During this process, fibroblast-derived IL-6 activated the JAK2/STAT3 signaling, upregulated c-MYC expression, and subsequently activated the NOTCH pathway, driving phenotypic reprogramming. Moreover, CAF-enriched SCLC exhibited increased immune cell infiltration, elevated expression of immune activation-related signatures, and checkpoint molecules. Our data also highlighted the chemoresistance induced by fibroblasts in SCLC cells, which was effectively reversed by JAK inhibitor. In conclusion, fibroblasts induced phenotypic reprogramming of SCLC cells from NE to Non-NE, likely contributes to inflamed immune microenvironment and chemoresistance. These findings provide novel insights into the clinical implications of CAFs in SCLC.
Prenatal alcohol exposure is associated with changes in placental gene co-expression networks
Authors: Deyssenroth Maya A. , Williams Randy P. , Lesseur Corina , Jacobson Sandra W. , Jacobson Joseph L. , Cheng Haoxiang , Bose Promita , Li Qian , Wainwright Helen , Meintjes Ernesta M. , Hao Ke , Chen Jia , Carter R. Colin
Published: February 2024

Alcohol consumption during pregnancy can result in a range of adverse postnatal outcomes among exposed children. However, identifying at-risk children is challenging given the difficulty to confirm prenatal alcohol exposure and the lack of early diagnostic tools. Placental surveys present an important opportunity to uncover early biomarkers to identify those at risk. Here, we report the first transcriptome-wide evaluation to comprehensively evaluate human placental pathways altered by fetal alcohol exposure. In a prospective longitudinal birth cohort in Cape Town, South Africa, we performed bulk tissue RNAseq in placenta samples from 32 women reporting heavy drinking during pregnancy and 30 abstainers/light drinkers. Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis were performed to assess associations between fetal alcohol exposure and placental gene expression patterns at a network-wide and single gene level, respectively. The results revealed altered expression in genes related to erythropoiesis and angiogenesis, which are implicated in established postnatal phenotypes related to alcohol exposure, including disruptions in iron homeostasis, growth, and neurodevelopment. The reported findings provide insights into the molecular pathways affected by prenatal alcohol exposure and highlight the potential of placental biomarkers for detecting and understanding the effects of alcohol on fetal development.
MouseVUER: video based open-source system for laboratory mouse home-cage monitoring
Authors: Salem Ghadi , Cope Niall , Garmendia Marcial , Pu Alex , Somenhalli Abhishek , Krynitsky Jonathan , Cubert Noah , Jones Thomas , Dold George , Fletcher Anthony , Kravitz Alexxai , Pohida Thomas , Dennis John
Published: February 2024

Video monitoring of mice in the home-cage reveals behavior profiles without the disruptions caused by specialized test setups and makes it possible to quantify changes in behavior patterns continually over long time frames. Several commercial home-cage monitoring systems are available with varying costs and capabilities; however there are currently no open-source systems for home-cage monitoring. We present an open-source system for top-down video monitoring of research mice in a slightly modified home-cage. The system is designed for integration with Allentown NexGen ventilated racks and allows unobstructed view of up to three mice, but can also be operated outside the rack. The system has an easy to duplicate and assemble home-cage design along with a video acquisition solution. The system utilizes a depth video camera, and we demonstrate the robustness of depth video for home-cage mice monitoring. For researchers without access to Allentown NexGen ventilated racks, we provide designs and assembly instructions for a standalone non-ventilated rack solution that holds three systems for more compact and efficient housing. We make all the design files, along with detailed assembly and installation instructions, available on the project webpage (https://github.com/NIH-CIT-OIR-SPIS/MouseVUER).
Female tilapia, Oreochromis sp. mobilised energy differently for growth and reproduction according to living environment
Authors: Razali Ros Suhaida , Rahmah Sharifah , Shirly-Lim Yu Ling , Ghaffar Mazlan Abd , Mazelan Suhairi , Jalilah Mohamad , Lim Leong-Seng , Chang Yu Mei , Liang Li Qun , Chen Young-Mao , Liew Hon Jung
Published: February 2024

This study was conducted to investigate the energy mobilisation preference and ionoregulation pattern of female tilapia, Oreochromis sp. living in different environments. Three different treatments of tilapia as physiology compromising model were compared; tilapia cultured in recirculating aquaculture system (RAS as Treatment I—RAS), tilapia cultured in open water cage (Treatment II—Cage) and tilapia transferred from cage and cultured in RAS (Treatment III—Compensation). Results revealed that tilapia from Treatment I and III mobilised lipid to support gonadogenesis, whilst Treatment II tilapia mobilised glycogen as primary energy for daily exercise activity and reserved protein for growth. The gills and kidney Na+/K+ ATPase (NKA) activities remained relatively stable to maintain homeostasis with a stable Na+ and K+ levels. As a remark, this study revealed that tilapia strategized their energy mobilisation preference in accessing glycogen as an easy energy to support exercise metabolism and protein somatogenesis in cage culture condition, while tilapia cultured in RAS mobilised lipid for gonadagenesis purposes.
Predicting outcomes following lower extremity open revascularization using machine learning
Authors: Li Ben , Verma Raj , Beaton Derek , Tamim Hani , Hussain Mohamad A. , Hoballah Jamal J. , Lee Douglas S. , Wijeysundera Duminda N. , de Mestral Charles , Mamdani Muhammad , Al-Omran Mohammed
Published: February 2024

Lower extremity open revascularization is a treatment option for peripheral artery disease that carries significant peri-operative risks; however, outcome prediction tools remain limited. Using machine learning (ML), we developed automated algorithms that predict 30-day outcomes following lower extremity open revascularization. The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity open revascularization for chronic atherosclerotic disease between 2011 and 2021. Input features included 37 pre-operative demographic/clinical variables. The primary outcome was 30-day major adverse limb event (MALE; composite of untreated loss of patency, major reintervention, or major amputation) or death. Our data were split into training (70%) and test (30%) sets. Using tenfold cross-validation, we trained 6 ML models. Overall, 24,309 patients were included. The primary outcome of 30-day MALE or death occurred in 2349 (9.3%) patients. Our best performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve (95% CI) of 0.93 (0.92–0.94). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.08. Our ML algorithm has potential for important utility in guiding risk mitigation strategies for patients being considered for lower extremity open revascularization to improve outcomes.
Evaluating the Bayesian causal inference model of intentional binding through computational modeling
Authors: Tanaka Takumi
Published: February 2024

Intentional binding refers to the subjective compression of the time interval between an action and its consequence. While intentional binding has been widely used as a proxy for the sense of agency, its underlying mechanism has been largely veiled. Bayesian causal inference (BCI) has gained attention as a potential explanation, but currently lacks sufficient empirical support. Thus, this study implemented various computational models to describe the possible mechanisms of intentional binding, fitted them to individual observed data, and quantitatively evaluated their performance. The BCI models successfully isolated the parameters that potentially contributed to intentional binding (i.e., causal belief and temporal prediction) and generally better explained an observer’s time estimation than traditional models such as maximum likelihood estimation. The estimated parameter values suggested that the time compression resulted from an expectation that the actions would immediately cause sensory outcomes. Furthermore, I investigated the algorithm that realized this BCI and found probability-matching to be a plausible candidate; people might heuristically reconstruct event timing depending on causal uncertainty rather than optimally integrating causal and temporal posteriors. The evidence demonstrated the utility of computational modeling to investigate how humans infer the causal and temporal structures of events and individual differences in that process.