bluuebunny/crossref_metadata_2025 huggingface dataset:
Comprehensive analysis of circRNA expression profile and circRNA-miRNA-mRNA network susceptibility to very early-onset schizophrenia
Authors: Huang Huanhuan , Luo Jie , Qi Yanjie , Wu Yuanzhen , Qi Junhui , Yan Xiuping , Xu Gaoyang , He Fan , Zheng Yi
Published: October 2023

To explore the potential role of circular RNAs (circRNAs) in children developing very early-onset schizophrenia (VEOS). Total RNA was extracted from the plasma samples of 10 VEOS patients and eight healthy controls. Expression profiles of circRNAs, micro RNAs (miRNAs), and messenger RNAs (mRNAs) were analyzed using RNA-seq. The interaction networks between miRNAs and targets were predicted using the miRanda tool. A differentially expressed circRNA-miRNA-mRNA (ceRNA) network was further constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the target mRNAs in the ceRNA network were performed to predict the potential functions of their host genes. The patient group and the control group were also compared on the regulatory patterns of circRNAs on mRNAs. 1934 circRNAs were identified from the samples and reported for the first time in schizophrenia. The circRNA expression levels were lower in the VEOS group than in the healthy control group, and 1889 circRNAs were expressed only in the control group. Differential expression analysis (i.e., log2fold change > 1.5, p 0.05) identified 235 circRNAs (1 up-regulated, 234 down-regulated), 11 miRNAs (7 up-regulated, 4 down-regulated), and 2,308 mRNAs (1906 up-regulated, 402 down-regulated) respectively. In VEOS, a ceRNA network with 10 down-regulated circRNA targets, 6 up-regulated miRNAs, and 47 down-regulated mRNAs was constructed. The target genes were involved in the membrane, the signal transduction, and the cytoskeleton and transport pathways. Finally, different expression correlation patterns of circRNA and mRNA in the network were observed between the patient group and the control group. The current research is the first to reveal the differentially expressed circRNAs in the plasma of VEOS patients. A circRNA-miRNA-mRNA network was also conducted in this study. It may be implied that the circRNAs in this network are potential diagnostic biomarkers for VEOS and they play an important role in the onset and development of VEOS symptoms.
The 10-m cotton maps in Xinjiang, China during 2018–2021
Authors: Kang Xiaoyan , Huang Changping , Chen Jing M. , Lv Xin , Wang Jin , Zhong Tao , Wang Huihan , Fan Xianglong , Ma Yiru , Yi Xiang , Zhang Ze , Zhang Lifu , Tong Qingxi
Published: October 2023

Cotton maps (10 m) of Xinjiang (XJ_COTTON10), which is the largest cotton production region of China, were produced from 2018 to 2021 through supervised classification. A two-step mapping strategy, i.e., cropland mapping followed by cotton extraction, was employed to improve the accuracy and efficiency of cotton mapping for a large region of about 1.66 million km2with high heterogeneity. Additionally, the time-series satellite data related to spectral, textural, structural, and phenological features were combined and used in a supervised random forest classifier. The cotton/non-cotton classification model achieved overall accuracies of about 95% and 90% on the test samples of the same and adjacent years, respectively. The proposed two-step cotton mapping strategy proved promising and effective in producing multi-year and consistent cotton maps. XJ_COTTON10 agreed well with the statistical areas of cotton at the county level (R2 = 0.84–0.94). This is the first cotton mapping for the entire Xinjiang at 10-meter resolution, which can provide a basis for high-precision cotton monitoring and policymaking in China.
Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC
Authors: Heutte Benjamin , Bergner Nora , Beck Ivo , Angot Hélène , Dada Lubna , Quéléver Lauriane L. J. , Laurila Tiia , Boyer Matthew , Brasseur Zoé , Daellenbach Kaspar R. , Henning Silvia , Kuang Chongai , Kulmala Markku , Lampilahti Janne , Lampimäki Markus , Petäjä Tuukka , Shupe Matthew D. , Sipilä Mikko , Uin Janek , Jokinen Tuija , Schmale Julia
Published: October 2023

The Arctic environment is transforming rapidly due to climate change. Aerosols’ abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through direct interaction with solar radiation and indirectly via cloud formation. Importantly, Arctic aerosol properties are also changing in response to climate change. Despite their importance, year-round measurements of their characteristics are sparse in the Arctic and often confined to lower latitudes at Arctic land-based stations and/or short high-latitude summertime campaigns. Here, we present unique aerosol microphysics and chemical composition datasets collected during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, in the central Arctic. These datasets, which include aerosol particle number concentrations, size distributions, cloud condensation nuclei concentrations, fluorescent aerosol concentrations and properties, and aerosol bulk chemical composition (black carbon, sulfate, nitrate, ammonium, chloride, and organics) will serve to improve our understanding of high-Arctic aerosol processes, with relevance towards improved modelling of the future Arctic (and global) climate.
HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data
Authors: Tran Khuong H. , Zhang Xiaoyang , Ye Yongchang , Shen Yu , Gao Shuai , Liu Yuxia , Richardson Andrew
Published: October 2023

Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.
Thermally-robust spatiotemporal parallel reservoir computing by frequency filtering in frustrated magnets
Authors: Kobayashi Kaito , Motome Yukitoshi
Published: October 2023

Physical reservoir computing is a framework for brain-inspired information processing that utilizes nonlinear and high-dimensional dynamics in non-von-Neumann systems. In recent years, spintronic devices have been proposed for use as physical reservoirs, but their practical application remains a major challenge, mainly because thermal noise prevents them from retaining short-term memory, the essence of neuromorphic computing. Here, we propose a framework for spintronic physical reservoirs that exploits frequency domain dynamics in interacting spins. Through the effective use of frequency filters, we demonstrate, for a model of frustrated magnets, both robustness to thermal fluctuations and feasibility of frequency division multiplexing. This scheme can be coupled with parallelization in spatial domain even down to the level of a single spin, yielding a vast number of spatiotemporal computational units. Furthermore, the nonlinearity via the exchange interaction allows information processing among different frequency threads. Our findings establish a design principle for high-performance spintronic reservoirs with the potential for highly integrated devices.
Potential chemopreventive effects of Broccoli extract supplementation against 7, 12 dimethyl Benz(a)anthracene (DMBA) -induced toxicity in female rats
Authors: Allam Aya M. , AbuBakr Huda O. , Yassin Aya M. , Abdel-Razek Ahmed S. , Khattab Marwa S. , Gouda Eman M. , Mousa Said Z.
Published: October 2023

Dietary components have recently received rapidly expanding attention for their potential to halt or reverse the development of many oxidative stress-mediated diseases after exposure to environmental toxicants. 7, 12 dimethylbenz(a)anthracene (DMBA) is one of the most common environmental pollutants. The present study aimed to evaluate the chemo-preventive effects of broccoli as a nutritional component against DMBA intoxication in rats. A daily dose of aqueous (1 ml/rat) and methanolic (150 mg/kg) broccoli extracts, respectively, was given to 50-day-old female rats for 26 successive weeks after carcinogen intoxication with a single dose of 20 mg/ml of DMBA. DMBA intoxication resulted in a redox imbalance (a decreased GSH level and an increased MDA level) and increased DNA fragmentation in the liver, kidney, and brain. Besides, it affected the level of expression of the bcl2 gene in the liver, kidney, and brain tissue but didn’t affect cfos gene expression accompanied by histopathological changes. The aqueous and methanolic broccoli extract supplements ameliorated the adverse effects by increasing the level of GSH, decreasing the MDA level, and reducing DNA fragmentation. Besides, broccoli extracts decreased the expression of bcl2 in the liver and brain and up-regulated bcl2 expression in the kidney, accompanied by lowering NF-κβ 65 expression in the liver and brain and γ-catenin expression in the liver and kidney. In conclusion, broccoli as a dietary component had a strong chemoprotective effect against oxidative stress, DNA damage, and genotoxicity induced by DMBA intoxication in rats.
Photodynamic reactions using high-intensity red LED promotes gingival wound healing by ROS induction
Authors: Minagawa Emika , Yamauchi Nobuhiro , Taguchi Yoichiro , Umeda Makoto
Published: October 2023

Photodynamic therapy is a treatment that combines a light source with a photosensitizer. LEDs have attracted considerable attention in clinical dentistry because they are inexpensive and safe to use. Although the interaction between photosensitizers and LEDs in dental practice is effective for treating periodontal disease by killing periodontopathic bacteria, little is known about the effects of LEDs on human gingival fibroblasts (HGnFs), which play an important role in gingival wound healing. In this study, we investigated the effects of high-intensity red LED irradiation on HGnFs after the addition of methylene blue (MB), one of the least harmful photosensitizers, on wound healing and reactive oxygen species (ROS) production induced by photodynamic reactions. We found that irradiation of MB with high-intensity red LED at controlled energy levels promoted cell proliferation, migration, and production of wound healing factors. Furthermore, ROS production by a photodynamic reaction enabled the translocation of phosphorylated Grb2-associated binder-1, activating Extracellular signal-regulated kinase 1/2 and c-Jun N-terminal kinase signals. Our findings suggest that proper control of ROS production has a beneficial effect on gingival fibroblasts, which constitute periodontal tissue, from the perspective of gingival wound healing.
Interacting innovation processes
Authors: Aletti Giacomo , Crimaldi Irene , Ghiglietti Andrea
Published: October 2023

In this work, we introduce a general model for a collection of innovation processes in order to model and analyze the interaction among them. We provide theoretical results, analytically proven, and we show how the proposed model fits the behaviors observed in some real data sets (from Reddit and Gutenberg). It is worth mentioning that the given applications are only examples of the potentialities of the proposed model and related results: due to its abstractness and generality, it can be applied to many interacting innovation processes.
Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits
Authors: Dort E. N. , Layne E. , Feau N. , Butyaev A. , Henrissat B. , Martin F. M. , Haridas S. , Salamov A. , Grigoriev I. V. , Blanchette M. , Hamelin R. C.
Published: October 2023

Invasive plant pathogenic fungi have a global impact, with devastating economic and environmental effects on crops and forests. Biosurveillance, a critical component of threat mitigation, requires risk prediction based on fungal lifestyles and traits. Recent studies have revealed distinct genomic patterns associated with specific groups of plant pathogenic fungi. We sought to establish whether these phytopathogenic genomic patterns hold across diverse taxonomic and ecological groups from the Ascomycota and Basidiomycota, and furthermore, if those patterns can be used in a predictive capacity for biosurveillance. Using a supervised machine learning approach that integrates phylogenetic and genomic data, we analyzed 387 fungal genomes to test a proof-of-concept for the use of genomic signatures in predicting fungal phytopathogenic lifestyles and traits during biosurveillance activities. Our machine learning feature sets were derived from genome annotation data of carbohydrate-active enzymes (CAZymes), peptidases, secondary metabolite clusters (SMCs), transporters, and transcription factors. We found that machine learning could successfully predict fungal lifestyles and traits across taxonomic groups, with the best predictive performance coming from feature sets comprising CAZyme, peptidase, and SMC data. While phylogeny was an important component in most predictions, the inclusion of genomic data improved prediction performance for every lifestyle and trait tested. Plant pathogenicity was one of the best-predicted traits, showing the promise of predictive genomics for biosurveillance applications. Furthermore, our machine learning approach revealed expansions in the number of genes from specific CAZyme and peptidase families in the genomes of plant pathogens compared to non-phytopathogenic genomes (saprotrophs, endo- and ectomycorrhizal fungi). Such genomic feature profiles give insight into the evolution of fungal phytopathogenicity and could be useful to predict the risks of unknown fungi in future biosurveillance activities.
Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data
Authors: Ditz Jonas C. , Reuter Bernhard , Pfeifer Nico
Published: October 2023

Artificial neural networks show promising performance in detecting correlations within data that are associated with specific outcomes. However, the black-box nature of such models can hinder the knowledge advancement in research fields by obscuring the decision process and preventing scientist to fully conceptualize predicted outcomes. Furthermore, domain experts like healthcare providers need explainable predictions to assess whether a predicted outcome can be trusted in high stakes scenarios and to help them integrating a model into their own routine. Therefore, interpretable models play a crucial role for the incorporation of machine learning into high stakes scenarios like healthcare. In this paper we introduce Convolutional Motif Kernel Networks, a neural network architecture that involves learning a feature representation within a subspace of the reproducing kernel Hilbert space of the position-aware motif kernel function. The resulting model enables to directly interpret and evaluate prediction outcomes by providing a biologically and medically meaningful explanation without the need for additional post-hoc analysis. We show that our model is able to robustly learn on small datasets and reaches state-of-the-art performance on relevant healthcare prediction tasks. Our proposed method can be utilized on DNA and protein sequences. Furthermore, we show that the proposed method learns biologically meaningful concepts directly from data using an end-to-end learning scheme.
The effect of random virus failure following cell entry on infection outcome and the success of antiviral therapy
Authors: Quirouette Christian , Cresta Daniel , Li Jizhou , Wilkie Kathleen P. , Liang Haozhao , Beauchemin Catherine A. A.
Published: October 2023

A virus infection can be initiated with very few or even a single infectious virion, and as such can become extinct, i.e. stochastically fail to take hold or spread significantly. There are many ways that a fully competent infectious virion, having successfully entered a cell, can fail to cause a productive infection, i.e. one that yields infectious virus progeny. Though many stochastic models (SMs) have been developed and used to estimate a virus infection’s establishment probability, these typically neglect infection failure post virus entry. The SM presented herein introduces parameter $$\gamma \in (0,1]$$

γ
∈
(
0
,
1
]

which corresponds to the probability that a virion’s entry into a cell will result in a productive cell infection. We derive an expression for the likelihood of infection establishment in this new SM, and find that prophylactic therapy with an antiviral reducing $$\gamma$$
γ
is at least as good or better at decreasing the establishment probability, compared to antivirals reducing the rates of virus production or virus entry into cells, irrespective of the SM parameters. We investigate the difference in the fraction of cells consumed by so-called extinct versus established virus infections, and find that this distinction becomes biologically meaningless as the probability of establishment approaches zero. We explain why the release of virions continuously over an infectious cell’s lifespan, rather than as a single burst at the end of the cell’s lifespan, does not result in an increased risk of infection extinction. We show, instead, that the number of virus released, not the timing of the release, affects infection establishment and associated critical antiviral efficacy.
The influence of insight on risky decision making and nucleus accumbens activation
Authors: Becker Maxi , Yu Yuhua , Cabeza Roberto
Published: October 2023

During insightful problem solving, the solution appears unexpectedly and is accompanied by the feeling of an AHA!. Research suggests that this affective component of insight can have consequences beyond the solution itself by motivating future behavior, such as risky (high reward and high uncertainty) decision making. Here, we investigate the behavioral and neural support for the motivational role of AHA in decision making involving monetary choices. The positive affect of the AHA! experience has been linked to internal reward. Reward in turn has been linked to dopaminergic signal transmission in the Nucleus Accumbens (NAcc) and risky decision making. Therefore, we hypothesized that insight activates reward-related brain areas, modulating risky decision making. We tested this hypothesis in two studies. First, in a pre-registered online study (Study 1), we demonstrated the behavioral effect of insight-related increase in risky decision making using a visual Mooney identification paradigm. Participants were more likely to choose the riskier monetary payout when they had previously solved the Mooney image with high compared to low accompanied AHA!. Second, in an fMRI study (Study 2), we measured the effects of insight on NAcc activity using a similar Mooney identification paradigm to the one of Study 1. Greater NAcc activity was found when participants solved the Mooney image with high vs low AHA!. Taken together, our results link insight to enhanced NAcc activity and a preference for high but uncertain rewards, suggesting that insight enhances reward-related brain areas possibly via dopaminergic signal transmission, promoting risky decision making.
Pupil response patterns distinguish true from false memories
Authors: Kafkas Alex , Brown Travorn , Olusola Nifemi , Guo Chaodong
Published: October 2023

Memory is reconstructive and error-prone, which make memory illusions very common in everyday life. However, studying memory illusions can provide valuable insights into how memory works. Pupil response has emerged, in recent years, as an indicator of memory encoding and retrieval, however its validity as a measure of memory success is debated. In this study, we explored whether pupil response patterns can differentiate true from false memories and whether variations in the temporal dynamics of pupil response can elucidate the mechanisms underlying false memory creation. The Deese-Roediger-McDermott (DRM) paradigm was employed to generate false memories in two separate experiments involving visual and auditory stimuli. Pupil responses effectively differentiated true from false memories based on variations in pupil amplitude at different temporal components. This discrimination remained consistent across both experiments, with slightly stronger effects in the auditory condition, aligning with the more pronounced false memory effects in this condition. Notably, differential pupil responses between true and false memories varied based on the type of memory involved at recognition. These findings provide valuable insights into the cognitive processes underlying memory distortions, with implications for theoretical frameworks and real-world contexts.
Use of pediatric thymus to humanize mice for HIV-1 mucosal transmission
Authors: Roy Chandra N. , Shu Sherry T. , Kline Christopher , Rigatti Lora , Smithgall Thomas E. , Ambrose Zandrea
Published: October 2023

Humanized mice have been used to study human immunodeficiency virus type 1 (HIV-1) transmission, pathogenesis, and treatment. The ability of pediatric thymus tissue implanted either in the leg (Leg PedThy) or under the renal capsule (Renal PedThy) with allogeneic CD34+ hematopoietic cells (HSCs) in NSG mice was evaluated for reconstitution of human immune cells and for rectal transmission of HIV-1. These mice were compared to traditional BLT mice implanted with fetal liver and thymus under the renal capsule and mice injected only with HSCs. Renal PedThy mice had similar immune reconstitution in the blood, spleen and intestine as BLT mice, while Leg PedThy mice had transient detection of immune cells, particularly CD4+ T cells and macrophages, the target cells for HIV-1 infection. Rectal transmission and replication of HIV-1 was efficient in BLT mice but lower and more variable in Renal PedThy mice. HIV-1 was poorly transmitted in HSC mice and not transmitted in Leg PedThy mice, which correlated with the frequencies of target cells in the spleen and intestine. Humanization of NSG mice with pediatric thymus was successful when implanted under the kidney capsule, but led to less efficient HIV-1 rectal transmission and replication compared to BLT mice.
Accessing new avenues of photonic bandgaps using two-dimensional non-Moiré geometries
Authors: Darthy R. Rachel , Venkateswaran C. , Subramanian V. , Ouyang Zhengbiao , Yogesh N.
Published: October 2023

Photonic crystals (PhC) formed by 2-D non-Moiré geometries are realized in this work. Non-Moiré (NM) tiles are the contours of trigonometric functions that generate exciting shapes and geometries. Photonic bandstructure calculations reveal that 2-D NM geometries exhibit new avenues of photonic bandgaps compared to the regular circular rod-based PhCs. The band structures are anisotropic and show, intriguing orientation-dependent partial bandgaps. A few of the orientation-dependent frequency selective properties of the realized NM geometry-based PhCs are demonstrated using full-wave electromagnetic simulations. The proposed geometries are practically realizable, and in this work, we experimentally demonstrate the fabrication process using the 3-D printing technique for microwave frequencies.
Effects of various wet environments on the characteristics of the dust cake deposited on the surface of filter media
Authors: Li Shihang , Lin Yihan , Han Muze , Liu Hao , Shao Jiang , Tan Xiaoyu , Luo Yuchen , Huang Rongting
Published: October 2023

The effect of wet environments on the dust cake of filter media was studied. The collapse angles of dust particles and the collapse angles between dust particles and filter media increase with increasing dust moisture content, relative humidity, and spray rate. The smallest growth rate of collapse was observed under dust moisture content, while the largest growth rate occurred under the spray rate condition. The collapse angles between dust particles and filter media of coated filter media were smaller compared to those of mechanical filter media under different wet environments. The dust cake drag coefficients of both filter media initially increase and then decrease with an increase in the dust moisture content, decrease with the acceleration of the relative humidity, and show a pattern of first decreasing and then increasing as the spray rate increases. The dust loading capacity of both filter media follows an opposite trend to that of the dust cake drag coefficients.
A smart device for non-invasive ADL estimation through multi-environmental sensor fusion
Authors: Kang Homin , Lee Cheolhwan , Kang Soon Ju
Published: October 2023

This research paper introduces the Smart Plug Hub (SPH), a non-invasive system designed to accurately estimating a patient’s Activities of Daily Living (ADL). Traditional methods for measuring ADL include interviews, remote video systems, and wearable devices that track behavior. However, these approaches have limitations, such as patient memory dependency, privacy violations, and careless device management. To address these limitations, SPH utilizes sensor fusion to analyze time-series environmental signals and accurately estimate a patient’s ADL. We have effectively optimized the utilization of computing resources through the implementation of “device collaboration” in SPH to receive event data and segments portions of the time-series environmental signal. By segmenting the data into smaller segments, we extracted an analyzable dataset, which was processed by an edge device—SPH. We have conducted several experiments with the SPH, and our research has resulted in a significant 75% accuracy in the classification of patients’ kitchen ADLs and an 85% accuracy in the classification of toilet ADLs. These activities include actions such as eating activities in the kitchen and typical activities performed in the toilet. These findings have substantial implications for the progress of healthcare and patient care, highlighting the potential uses of the SPH technology in the monitoring and improvement of daily living activities.
The presence of wolves leads to spatial differentiation in deer browsing pressure on forest regeneration
Authors: Wójcicki Adam , Borowski Zbigniew
Published: October 2023

With the recent return of large carnivores to forest ecosystems, an important issue for forest owners and managers is how large predators influence the behaviour of their natural prey and, consequently, cervid browsing pressure on forest regeneration. To investigate this issue, we analysed deer pressure on Scots pine and European beech plantations in northern Poland's ecosystems with and without permanent wolf populations. Two characteristics were used to describe deer browsing patterns in plantations: distance from the forest edge (spatial pattern of browsing) and number of saplings browsed (browsing intensity). Beech saplings were more intensively browsed by deer compared to pine saplings. In a forest ecosystem not inhabited by wolves, spatial variation in browsing patterns on small-sized beech plantations was the same between the edge and the center. In contrast, browsing pressure by deer was greater at the edges on large-sized pine plantations. The presence of wolves reduced deer browsing on beech and increased browsing on pine saplings. In addition, deer foraging behaviour changed in large-sized pine plantations, and browsing pressure increased only in the central areas of the plantations. We assume that the presence of wolves in a forest landscape is an important factor that alters browsing pressure on the youngest stands and their spatial pattern, and that this may be a major factor in stand regeneration, especially in small forest patches.
Global termite methane emissions have been affected by climate and land-use changes
Authors: Ito Akihiko
Published: October 2023

Termites with symbiotic methanogens are a known source of atmospheric methane (CH4), but large uncertainties remain regarding the flux magnitude. This study estimated global termite CH4 emissions using a framework similar to previous studies but with contemporary datasets and a biogeochemical model. The global termite emission in 2020 was estimated as 14.8 ± 6.7 Tg CH4 year−1, mainly from tropical and subtropical ecosystems, indicating a major natural source from upland regions. Uncertainties associated with estimation methods were assessed. The emission during the historical period 1901–2021 was estimated to have increased gradually (+ 0.7 Tg CH4 year−1) as a result of combined influences of elevated CO2 (via vegetation productivity), climatic warming, and land-use change. Future projections using climate and land-use scenarios (shared socioeconomic pathways [ssp] 126 and 585) also showed increasing trends (+ 0.5 to 5.9 Tg CH4 year−1 by 2100). These results suggest the importance of termite emissions in the global CH4 budget and, thus, in climatic prediction and mitigation.
Shift in hospital opioid use during the COVID-19 pandemic in Brazil: a time-series analysis of one million prescriptions
Authors: Carvalho Romulo Mendonça , de Magalhães-Barbosa Maria Clara , Bianchi Lucas Monteiro , Rodrigues-Santos Gustavo , da Cunha Antônio José Ledo Alves , Bastos Francisco Inácio , Prata-Barbosa Arnaldo
Published: October 2023

The pronounced change in the profile of hospitalized patients during COVID-19 and the severe respiratory component of this disease, with a great need for mechanical ventilation, led to changes in the consumption pattern of some medicines and supplies. This time-series study analyzed the in-hospital consumption of opioids during the COVID-19 pandemic in 24 Brazilian hospitals compared to the pre-pandemic period. Data included 711,883 adult patients who had opioids prescribed. In 2020, the mean consumption was significantly higher compared to 2019 for parenteral fentanyl, enteral methadone, and parenteral methadone. It was significantly lower for parenteral morphine parenteral sufentanil, and parenteral tramadol. For remifentanil, it did not differ. The number of patients in 2020 was lower but the mean consumption was higher for fentanyl, parenteral methadone, and remifentanil. It was lower for enteral methadone and parenteral sufentanil. The consumption of parenteral morphine and parenteral tramadol was stable. There was a relevant increase in hospital consumption of some potent opioids during the COVID-19 pandemic in Brazil. These results reinforce the concern about epidemiological surveillance of opioid use after periods of increased hospital use since in-hospital consumption can be the gateway to the misuse or other than the prescribed use of opioids after discharge.
Relationship among DDR gene mutations, TMB and PD-L1 in solid tumour genomes identified using clinically actionable biomarker assays
Authors: Wang Danyi , Elenbaas Brian , Murugesan Karthikeyan , Shah Kunal , Montesion Meagan , Gounaris Ioannis , Scheuenpflug Juergen , Locatelli Giuseppe , Feng Zheng
Published: October 2023

The DNA damage response (DDR) pathway regulates DNA repair and cell survival, and inactivating mutations in DDR genes can increase tumour mutational burden (TMB), a predictive biomarker of treatment benefit from anti-PD-1/PD-L1 immunotherapies. However, a better understanding of the relationship among specific DDR mutations, TMB and PD-L1 expression is needed to improve translational strategies. Here, we determined genomic alteration frequencies in selected DDR genes that are clinically actionable biomarkers and investigated their association with TMB and PD-L1 in bladder, colorectal, non-small cell lung, ovarian and prostate cancers using the FoundationInsights® web portal. Our results not only confirm known associations, such as mismatch repair and POLE gene mutations with high TMB, but also identify significant associations between mutations in the SWI/SNF chromatin remodelling genes ARID1A and SMARCA4 and high TMB in multiple tumour types. Mutations in the ATR gene were associated with high TMB in colorectal and prostate cancers; however, associations between individual DDR mutations and high PD-L1 expression were uncommon and tumour-type specific. Finally, we found that high TMB and high PD-L1 expression were poorly associated, emphasising their independence as predictive biomarkers for immune checkpoint inhibitor use.
Chemoresistant fibroblasts dictate neoadjuvant chemotherapeutic response of head and neck cancer via TGFα-EGFR paracrine signaling
Authors: Su Liangping , Wu Sangqing , Huang Cheng , Zhuo Xianhua , Chen Jiali , Jiang Xue , Kong Xiangzhan , Lv Cui , Xu Qiuping , Han Ping , Huang Xiaoming , Wong Ping-Pui
Published: October 2023

Conventional chemotherapy targets malignant cells without evaluating counter protection from the tumor microenvironment that often causes treatment failure. Herein, we establish chemoresistant fibroblasts (rCAFs) as regulators of neoadjuvant chemotherapeutic (NACT) response in head and neck squamous cell carcinoma (HNSCC). Clinically, high expression of CAF-related gene signature correlates with worse prognosis and chemotherapeutic response in multiple cancers, while the population of CAFs in the residual tumors of chemoresistant HNSCC patients remains unchanged after NACT treatment, compared to chemosensitive patients. Using a murine cancer model or patient-derived organoid, and primary CAFs isolated from chemo-sensitive (sCAFs) or -resistant patients, we show that rCAFs, but not sCAFs, are resistant to chemotherapy-induced apoptosis while reducing HNSCC cell chemosensitivity via paracrine signals. Combined multi-omics and biochemical analyses indicate an elevated PI3K/AKT/p65 driven cell survival and cytokine production in rCAFs, while rCAF-secreted TGFα promotes cancer cell chemoresistance by activating EGFR/Src/STAT3 survival signaling axis. Treatment with anti-EGFR cetuximab restores the chemosensitivity of tumors derived from co-injection of cancer cells and rCAFs in vivo, while the serum level of TGFα determines NACT response in HNSCC patients. Overall, our findings uncover a novel insight whereby the crosstalk between tumor cell and rCAF determines chemotherapeutic response and prognosis in cancer patients.
Stress-induced brain responses are associated with BMI in women
Authors: Kühnel Anne , Hagenberg Jonas , Knauer-Arloth Janine , Ködel Maik , Czisch Michael , Sämann Philipp G. ,   BeCOME working group, Brückl Tanja , Spoormaker Victor I. , Erhardt Angelika , Grandi Norma C. , Ziebula Julius , Elbau Immanuel G. , Lucae Susanne , Binder Elisabeth B. , Kroemer Nils B.
Published: October 2023

Overweight and obesity are associated with altered stress reactivity and increased inflammation. However, it is not known whether stress-induced changes in brain function scale with BMI and if such associations are driven by peripheral cytokines. Here, we investigate multimodal stress responses in a large transdiagnostic sample using predictive modeling based on spatio-temporal profiles of stress-induced changes in activation and functional connectivity. BMI is associated with increased brain responses as well as greater negative affect after stress and individual response profiles are associated with BMI in females (pperm < 0.001), but not males. Although stress-induced changes reflecting BMI are associated with baseline cortisol, there is no robust association with peripheral cytokines. To conclude, alterations in body weight and energy metabolism might scale acute brain responses to stress more strongly in females compared to males, echoing observational studies. Our findings highlight sex-dependent associations of stress with differences in endocrine markers, largely independent of peripheral inflammation.
Femtosecond multimodal imaging with a laser-driven X-ray source
Authors: Doherty Adam , Fourmaux Sylvain , Astolfo Alberto , Ziesche Ralf , Wood Jonathan , Finlay Oliver , Stolp Wiebe , Batey Darren , Manke Ingo , Légaré François , Boone Matthieu , Symes Dan , Najmudin Zulfikar , Endrizzi Marco , Olivo Alessandro , Cipiccia Silvia
Published: October 2023

Laser-plasma accelerators are compact linear accelerators based on the interaction of high-power lasers with plasma to form accelerating structures up to 1000 times smaller than standard radiofrequency cavities, and they come with an embedded X-ray source, namely betatron source, with unique properties: small source size and femtosecond pulse duration. A still unexplored possibility to exploit the betatron source comes from combining it with imaging methods able to encode multiple information like transmission and phase into a single-shot acquisition approach. In this work, we combine edge illumination-beam tracking (EI-BT) with a betatron X-ray source and present the demonstration of multimodal imaging (transmission, refraction, and scattering) with a compact light source down to the femtosecond timescale. The advantage of EI-BT is that it allows multimodal X-ray imaging technique, granting access to transmission, refraction and scattering signals from standard low-coherence laboratory X-ray sources in a single shot.
The future landscape of large language models in medicine
Authors: Clusmann Jan , Kolbinger Fiona R. , Muti Hannah Sophie , Carrero Zunamys I. , Eckardt Jan-Niklas , Laleh Narmin Ghaffari , Löffler Chiara Maria Lavinia , Schwarzkopf Sophie-Caroline , Unger Michaela , Veldhuizen Gregory P. , Wagner Sophia J. , Kather Jakob Nikolas
Published: October 2023

Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and generate text. LLMs attracted substantial public attention after OpenAI’s ChatGPT was made publicly available in November 2022. LLMs can often answer questions, summarize, paraphrase and translate text on a level that is nearly indistinguishable from human capabilities. The possibility to actively interact with models like ChatGPT makes LLMs attractive tools in various fields, including medicine. While these models have the potential to democratize medical knowledge and facilitate access to healthcare, they could equally distribute misinformation and exacerbate scientific misconduct due to a lack of accountability and transparency. In this article, we provide a systematic and comprehensive overview of the potentials and limitations of LLMs in clinical practice, medical research and medical education.
Surfactant-based Potentiometric Sensors for Surfactant Determination
Authors: Coldibeli Bruna , Clemente Marco Aurelio Jeanegitz , Sartori Elen Romão
Published: October 2023

Surfactant-based ion-selective electrodes (ISEs) offer a simple, sensitive, and reliable alternative for surfactant concentration determination in various industrial applications. This review presents the literature between 2014 and 2022 on liquid- or solid-contact ISEs based on surfactant developed for the determination of surfactants in different sample types, as well as the analytical features of each. Selectivity and stability (lifetime) are also considered.
Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods
Authors: Harb Hassan , Elliott Sarah N. , Ward Logan , Foster Ian T. , Klippenstein Stephen J. , Curtiss Larry A. , Assary Rajeev Surendran
Published: October 2023

We present a comprehensive, in silico-based discovery approach to identifying novel liquid organic hydrogen carrier (LOHC) candidates using cheminformatics methods and quantum chemical calculations.
Emerging investigator series: post-synthesis modification of reverse osmosis membranes for the enhanced separation of small neutral molecules
Authors: Habib Shahriar , Wilkins Madison A. , Weinman Steven T.
Published: October 2023

Diamine modification of polyamide reverse osmosis membranes using carbodiimide chemistry and heat treatment improves the removal of small neutral molecules.
Degradation of imidacloprid by Phanerodontia chrysosporium on wood chips for stormwater treatment
Authors: Weaver Leah M. M. , Alexander Nancy Lee , Cubeta Marc A. , Knappe Detlef R. U. , Aziz Tarek N.
Published: October 2023

The white-rot fungus Phanerodontia chrysosporium degraded more than 50% of imidacloprid in synthetic stormwater in one week, demonstrating the potential of fungal bioremediation for improved contaminant removal in stormwater infrastructure.
Dehydration induced selective ion trapping by topology constrained atomically thin graphene-crown membranes
Authors: Sahu Pooja , Ali Sk. Musharaf
Published: October 2023

Inspired by the host–guest recognition of crown ethers, the current era is evolving around the graphene-crown-based atomically thin membranes that will profoundly impact diverse fields of science and engineering.
Conductive and antibacterial dual-network hydrogel for soft bioelectronics
Authors: Sun Huiqi , Wang Sai , Yang Fan , Tan Mingyi , Bai Ling , Wang Peipei , Feng Yingying , Liu Wenbo , Wang Rongguo , He Xiaodong
Published: October 2023

An antibacterial, strong wet-tissue adhesive and biocompatible conductive hydrogel is proposed for next-generation bioelectronic materials in human healthcare.
High-sensitivity and ultralow-hysteresis fluorine-rich ionogel strain sensors for multi-environment contact and contactless sensing
Authors: Hu Faqi , Huang Zhenkai , Luo Chuan , Yue Kan
Published: October 2023

Encapsulation-free strain sensors are realized using fluorine-rich ionogels with abundant ion–dipole interactions, which feature multi-environment tolerance, high sensitivity, ultralow hysteresis, and enable contact or contactless sensing underwater.
Sheet-like silicalite-1 single crystals with embedded macropores displaying superior catalytic performance
Authors: Zhang Yanfei , Qi Liang , Zhang Xiaomin , Jiang Qike , Lu Peng , Xu Lei , Bell Alexis T.
Published: October 2023

Dry-gel synthesis of sheet-like Silicalite-1 single crystals featuring intracrystalline macropores and short b-axis dimension.
Luminescence detection of CH2Cl2 by varying Cu⋯Cu interactions in a flexible porous coordination polymer
Authors: Zhang Wei-Jie , Chen Wan-Tao , Li Chen-Hui , Sun Wen-Zhu , Ye Jia-Wen , Chen Ling , Wang Hai-Ping , Chen Xiao-Ming
Published: October 2023

A flexible Cu(i) coordination polymer is reported as the luminescence sensor for the detection of CH2Cl2. The adsorption of guest molecules lengthens the Cu⋯Cu distance, resulting in luminescent blue shifts and higher emission energy.
Theoretical progress of MXenes as electrocatalysts for the hydrogen evolution reaction
Authors: Wan Pifang , Tang Qing
Published: October 2023

We reviewed recent theoretical progress in MXenes as HER electrocatalysts, covering structural and electronic properties, terminal group tunability, heteroatom doping, crucial activity descriptors, and advances in theoretical computational methods.
Controllable 1D, 2D and 3D supramolecular assemblies of Ir(iii) complexes
Authors: Lin Yifan , Chen Yan , Cai Rui , Zhang Hao , Liu Chun
Published: October 2023

Size-controllable supramolecular assemblies of 1D nanofibers, 2D nanosheets and 3D nanoblocks were successfully constructed via seeded self-assembly of Ir(iii) complexes.
Metal porphyrins and metal phthalocyanines as designable molecular model electrocatalysts
Authors: Feng Ya-Chen , Wang Xiang , Wang Dong
Published: October 2023

The application of metal porphyrins and metal phthalocyanines as model catalysts in electrocatalytic reactions provides important insights into understanding the catalytic mechanism and structure–activity relationship.
Organo-catalyzed C2,3–H aminochalcogenation of indoles with secondary (aliphatic) amines
Authors: Zhang Xiaoxiang , Liu Chenrui , Zhang Yingying , Shen Fang , Wei Wanxing , Zhang Zhuan , Liang Taoyuan
Published: October 2023

A direct C2,3–H difunctionalization of indoles with unactivated amines facilitated by the organo-chalconium catalyst generated through the reaction of iodine and chalconium reagents has been developed.
Generation and application of carbodiimide anions: efficient construction of 2-aminopyrimidines via a cascade [4 + 2] annulation/aromatization sequence
Authors: Wang Chuan-Chuan , Wang Xin-Lu , Wang Qing-Long , Gong Yi-Zhi , Hou Xue-Hui , Liu Jun-Tao , Chen Ya-Jing
Published: October 2023

This work disclosed an unprecedented carbodiimide anion participated cascade [4 + 2] annulation/aromatization reaction, affording an efficient method for synthesizing 2-aminopyrimidines.
Evaluation of the biological responses of silver nanoparticles synthesized using Pelargonium x hortorum extract
Authors: Lopez-Ayuso Christian Andrea , Garcia-Contreras Rene , Manisekaran Ravichandran , Figueroa Mario , Arenas-Arrocena Ma. Concepción , Hernandez-Padron Genoveva , Pozos-Guillén Amaury , Acosta-Torres Laura Susana
Published: October 2023

Silver nanoparticle synthesis mediated using Pelargonium x hortorum and its biological assays.
Antibacterial activity and DNA interaction of triazine iron and ruthenium complexes: spectroscopic, voltammetric and theoretical studies
Authors: Albaqami Faisal F. , Sahib Ameer S. , Alharthy Khalid M. , Altharawi Ali , Alshahrani Mohammad Y. , Jawad Mohammed Abed , Suliman Muath , Ahmad Irfan
Published: October 2023

Two complexes of [Ru(μ-tptz)2]Cl2 and [Fe(μ-tptz)2]Cl2 are synthesized, and their DNA binding, molecular docking and antibacterial activity are investigated.
Sporothioethers: deactivated alkyl citrates from the fungus Hypomontagnella monticulosa
Authors: Heinemann Henrike , Becker Kevin , Schrey Hedda , Zeng Haoxuan , Stadler Marc , Cox Russell J.
Published: October 2023

Two new thioether specialised metabolites isolated from the fungus Hypomontagnella monticulosa show attenuated antifungal properties, but retain biofilm inhibition activity.
Rapid detection of Candida albicans in urine by an Electrochemical Impedance Spectroscopy (EIS)-based biosensor
Authors: D'Aponte Tina , De Luca Maria , Sakač Nikola , Schibeci Martina , Arciello Angela , Roscetto Emanuela , Catania Maria Rosaria , Iannotti Vincenzo , Velotta Raffaele , Della Ventura Bartolomeo
Published: October 2023

Candida albicans is a fungal organism commonly found in the human body, including the genitourinary tract.
A self-discharging reaction mediated by imide salt enables the prevention of explosive thermal runaway in high-Ni material/graphite full cells
Authors: Shin Yongho , Ahn Kyungho , Lee Chulhaeng , Kang Byoungwoo
Published: October 2023

A novel strategy for preventing battery thermal runaway has been proposed. A self-discharge reaction which spontaneously occurs above 100 °C can improve phase stability of the delithiated high Ni cathode via LixS-induced lithiation.
One pot synthesis of hydrogen and glucaric acid via glucose electrolysis
Authors: Mehta Daisy , Kaur Sukhjot , Thakur Neha , Nagaiah Tharamani C.
Published: October 2023

Energy efficient glucose assisted hydrogen production over NiMn(x : y)On/OCNT with a selective formation of glucaric acid with 62.8% F.E. at 1.3 V vs. RHE.
Towards large area production: stretchability, flexibility, and stability of efficient printed organic tandem solar cells
Authors: Raïssi Mahfoudh , Wageh S. , Al-Ghamdi Ahmed A. , Rousseau Didier
Published: October 2023

Scaling up organic tandem solar cells from laboratory to large-scale production.
Flexible electrochemical sensor for highly sensitive and selective non-enzymatic detection of creatinine via electrodeposited copper over polymelamine formaldehyde
Authors: Mehta Daisy , Kafle Alankar , Nagaiah Tharamani C.
Published: October 2023

A non-enzymatic flexible electrochemical biosensor was developed for highly sensitive detection of creatinine using copper nanoparticles supported over polymelamine formaldehyde.