bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lipid complexation reduces rice starch digestibility and boosts short-chain fatty acid production via gut microbiota
Authors: Shen Yi , An Zengxu , Huyan Zongyao , Shu Xiaoli , Wu Dianxing , Zhang Ning , Pellegrini Nicoletta , Rubert Josep 
Published: October 2023

AbstractIn this study, two rice varieties (RS4 and GZ93) with different amylose and lipid contents were studied, and their starch was used to prepare starch-palmitic acid complexes. The RS4 samples showed a significantly higher lipid content in their flour, starch, and complex samples compared to GZ93. The static in vitro digestion highlighted that RS4 samples had significantly lower digestibility than the GZ93 samples. The C∞ of the starch-lipid complex samples was found to be 17.7% and 18.5% lower than that of the starch samples in GZ93 and RS4, respectively. The INFOGEST undigested fractions were subsequently used for in vitro colonic fermentation. Short-chain fatty acids (SCFAs) concentrations, mainly acetate, and propionate were significantly higher in starch-lipid complexes compared to native flour or starch samples. Starch-lipid complexes produced a distinctive microbial composition, which resulted in different gene functions, mainly related to pyruvate, fructose, and mannose metabolism. Using Model-based Integration of Metabolite Observations and Species Abundances 2 (MIMOSA2), SCFA production was predicted and associated with the gut microbiota. These results indicated that incorporating lipids into rice starch promotes SCFA production by modulating the gut microbiota selectively.
Overshooting the critical threshold for the Greenland ice sheet
Authors: Bochow Nils , Poltronieri Anna , Robinson Alexander , Montoya Marisa , Rypdal Martin , Boers Niklas 
Published: October 2023

AbstractMelting of the Greenland ice sheet (GrIS) in response to anthropogenic global warming poses a severe threat in terms of global sea-level rise (SLR)1. Modelling and palaeoclimate evidence suggest that rapidly increasing temperatures in the Arctic can trigger positive feedback mechanisms for the GrIS, leading to self-sustained melting2–4, and the GrIS has been shown to permit several stable states5. Critical transitions are expected when the global mean temperature (GMT) crosses specific thresholds, with substantial hysteresis between the stable states6. Here we use two independent ice-sheet models to investigate the impact of different overshoot scenarios with varying peak and convergence temperatures for a broad range of warming and subsequent cooling rates. Our results show that the maximum GMT and the time span of overshooting given GMT targets are critical in determining GrIS stability. We find a threshold GMT between 1.7 °C and 2.3 °C above preindustrial levels for an abrupt ice-sheet loss. GrIS loss can be substantially mitigated, even for maximum GMTs of 6 °C or more above preindustrial levels, if the GMT is subsequently reduced to less than 1.5 °C above preindustrial levels within a few centuries. However, our results also show that even temporarily overshooting the temperature threshold, without a transition to a new ice-sheet state, still leads to a peak in SLR of up to several metres.
Antiviral type III CRISPR signalling via conjugation of ATP and SAM
Authors: Chi Haotian , Hoikkala Ville , Grüschow Sabine , Graham Shirley , Shirran Sally , White Malcolm F. 
Published: October 2023

AbstractCRISPR systems are widespread in the prokaryotic world, providing adaptive immunity against mobile genetic elements1,2. Type III CRISPR systems, with the signature gene cas10, use CRISPR RNA to detect non-self RNA, activating the enzymatic Cas10 subunit to defend the cell against mobile genetic elements either directly, via the integral histidine–aspartate (HD) nuclease domain3–5 or indirectly, via synthesis of cyclic oligoadenylate second messengers to activate diverse ancillary effectors6–9. A subset of type III CRISPR systems encode an uncharacterized CorA-family membrane protein and an associated NrN family phosphodiesterase that are predicted to function in antiviral defence. Here we demonstrate that the CorA-associated type III-B (Cmr) CRISPR system from Bacteroides fragilis provides immunity against mobile genetic elements when expressed in Escherichia coli. However, B. fragilis Cmr does not synthesize cyclic oligoadenylate species on activation, instead generating S-adenosyl methionine (SAM)-AMP (SAM is also known as AdoMet) by conjugating ATP to SAM via a phosphodiester bond. Once synthesized, SAM-AMP binds to the CorA effector, presumably leading to cell dormancy or death by disruption of the membrane integrity. SAM-AMP is degraded by CRISPR-associated phosphodiesterases or a SAM-AMP lyase, potentially providing an ‘off switch’ analogous to cyclic oligoadenylate-specific ring nucleases10. SAM-AMP thus represents a new class of second messenger for antiviral signalling, which may function in different roles in diverse cellular contexts.
Clinical trial links oncolytic immunoactivation to survival in glioblastoma
Authors: Ling Alexander L. , Solomon Isaac H. , Landivar Ana Montalvo , Nakashima Hiroshi , Woods Jared K. , Santos Andres , Masud Nafisa , Fell Geoffrey , Mo Xiaokui , Yilmaz Ayse S. , Grant James , Zhang Abigail , Bernstock Joshua D. , Torio Erickson , Ito Hirotaka , Liu Junfeng , Shono Naoyuki , Nowicki Michal O. , Triggs Daniel , Halloran Patrick , Piranlioglu Raziye , Soni Himanshu , Stopa Brittany , Bi Wenya Linda , Peruzzi Pierpaolo , Chen Ethan , Malinowski Seth W. , Prabhu Michael C. , Zeng Yu , Carlisle Anne , Rodig Scott J. , Wen Patrick Y. , Lee Eudocia Quant , Nayak Lakshmi , Chukwueke Ugonma , Gonzalez Castro L. Nicolas , Dumont Sydney D. , Batchelor Tracy , Kittelberger Kara , Tikhonova Ekaterina , Miheecheva Natalia , Tabakov Dmitry , Shin Nara , Gorbacheva Alisa , Shumskiy Artemy , Frenkel Felix , Aguilar-Cordova Estuardo , Aguilar Laura K. , Krisky David , Wechuck James , Manzanera Andrea , Matheny Chris , Tak Paul P. , Barone Francesca , Kovarsky Daniel , Tirosh Itay , Suvà Mario L. , Wucherpfennig Kai W. , Ligon Keith , Reardon David A. , Chiocca E. Antonio 
Published: October 2023

AbstractImmunotherapy failures can result from the highly suppressive tumour microenvironment that characterizes aggressive forms of cancer such as recurrent glioblastoma (rGBM)1,2. Here we report the results of a first-in-human phase I trial in 41 patients with rGBM who were injected with CAN-3110—an oncolytic herpes virus (oHSV)3. In contrast to other clinical oHSVs, CAN-3110 retains the viral neurovirulence ICP34.5 gene transcribed by a nestin promoter; nestin is overexpressed in GBM and other invasive tumours, but not in the adult brain or healthy differentiated tissue4. These modifications confer CAN-3110 with preferential tumour replication. No dose-limiting toxicities were encountered. Positive HSV1 serology was significantly associated with both improved survival and clearance of CAN-3110 from injected tumours. Survival after treatment, particularly in individuals seropositive for HSV1, was significantly associated with (1) changes in tumour/PBMC T cell counts and clonal diversity, (2) peripheral expansion/contraction of specific T cell clonotypes; and (3) tumour transcriptomic signatures of immune activation. These results provide human validation that intralesional oHSV treatment enhances anticancer immune responses even in immunosuppressive tumour microenvironments, particularly in individuals with cognate serology to the injected virus. This provides a biological rationale for use of this oncolytic modality in cancers that are otherwise unresponsive to immunotherapy (ClinicalTrials.gov: NCT03152318).
High-resolution maps show that rubber causes substantial deforestation
Authors: Wang Yunxia , Hollingsworth Peter M. , Zhai Deli , West Christopher D. , Green Jonathan M. H. , Chen Huafang , Hurni Kaspar , Su Yufang , Warren-Thomas Eleanor , Xu Jianchu , Ahrends Antje 
Published: October 2023

AbstractUnderstanding the effects of cash crop expansion on natural forest is of fundamental importance. However, for most crops there are no remotely sensed global maps1, and global deforestation impacts are estimated using models and extrapolations. Natural rubber is an example of a principal commodity for which deforestation impacts have been highly uncertain, with estimates differing more than fivefold1–4. Here we harnessed Earth observation satellite data and cloud computing5 to produce high-resolution maps of rubber (10 m pixel size) and associated deforestation (30 m pixel size) for Southeast Asia. Our maps indicate that rubber-related forest loss has been substantially underestimated in policy, by the public and in recent reports6–8. Our direct remotely sensed observations show that deforestation for rubber is at least twofold to threefold higher than suggested by figures now widely used for setting policy4. With more than 4 million hectares of forest loss for rubber since 1993 (at least 2 million hectares since 2000) and more than 1 million hectares of rubber plantations established in Key Biodiversity Areas, the effects of rubber on biodiversity and ecosystem services in Southeast Asia could be extensive. Thus, rubber deserves more attention in domestic policy, within trade agreements and in incoming due-diligence legislation.
Hydrological model-based streamflow reconstruction for Indian sub-continental river basins, 1951–2021
Authors: Chuphal Dipesh Singh , Mishra Vimal 
Published: October 2023

AbstractStreamflow is a vital component of the global water cycle. Long-term streamflow observations are required for water resources planning and management, hydroclimatic extremes analysis, and ecological assessment. However, long-term streamflow observations for the Indian-Subcontinental (ISC) river basins are lacking. Using meteorological observations, state-of-the-art hydrological model, and river routing model, we developed hydrological model-simulated monthly streamflow from 1951–2021 for the ISC river basins. We used high-resolution vector-based routing model (mizuRoute) to generate streamflow at 9579 stream reaches in the sub-continental river basins. The model-simulated streamflow showed good performance against the observed flow with coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) above 0.70 for more than 60% of the gauge stations. The dataset was used to examine the variability in low, average, and high flow across the streams. Long-term changes in streamflow showed a significant decline in flow in the Ganga basin while an increase in the semi-arid western India and Indus basin. Long-term streamflow can be used for planning water management and climate change adaptation in the Indian sub-continent.
A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
Authors: Ricci Lara María Agustina , Rodríguez Kowalczuk María Victoria , Lisa Eliceche Maite , Ferraresso María Guillermina , Luna Daniel Roberto , Benitez Sonia Elizabeth , Mazzuoccolo Luis Daniel 
Published: October 2023

AbstractIn recent years, numerous dermatological image databases have been published to make possible the development and validation of artificial intelligence-based technologies to support healthcare professionals in the diagnosis of skin diseases. However, the generation of these datasets confined to certain countries as well as the lack of demographic information accompanying the images, prevents having a real knowledge of in which populations these models could be used. Consequently, this hinders the translation of the models to the clinical setting. This has led the scientific community to encourage the detailed and transparent reporting of the databases used for artificial intelligence developments, as well as to promote the formation of genuinely international databases that can be representative of the world population. Through this work, we seek to provide details of the processing stages of the first public database of dermoscopy and clinical images created in a hospital in Argentina. The dataset comprises 1,616 images corresponding to 1,246 unique lesions collected from 623 patients.
Infection prediction in swine populations with machine learning
Authors: Halev Avishai , Martínez-López Beatriz , Clavijo Maria , Gonzalez-Crespo Carlos , Kim Jeonghoon , Huang Chao , Krantz Seth , Robbins Rebecca , Liu Xin 
Published: October 2023

AbstractThe pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model’s ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of $$85.3\%$$

85.3
%

on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of $$58.5\%$$

58.5
%

, $$58.7\%$$

58.7
%

, $$72.8\%$$

72.8
%

and $$74.8\%$$

74.8
%

on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.
Untargeted lipidomics reveal association of elevated plasma C18 ceramide levels with reduced survival in metastatic castration-resistant prostate cancer patients
Authors: Cattrini Carlo , Manfredi Marcello , Barboro Paola , Ghirimoldi Marco , Mennitto Alessia , Martini Veronica , Battioni Alessio , Le Van Marco , Gobbato Simone , Branni Carmen , Ayed Rahma Ben , Pinato David James , Catalano Fabio , Zanardi Elisa , Boccardo Francesco , Gennari Alessandra 
Published: October 2023

AbstractEmerging evidence highlights the potential prognostic relevance of circulating lipids in metastatic castration-resistant prostate cancer (mCRPC), with a proposed 3-lipid signature. This study aims to analyze the lipidomic profiles of individuals with mCRPC to identify lipid species that could serve as predictive indicators of prognosis and therapeutic response. Plasma samples were collected from mCRPC patients initiating first-line treatment (1 L) (n = 29) and those previously treated with at least two lines of therapy (> 2 L) (n = 19), including an androgen-receptor signaling inhibitor and a taxane. Employing an untargeted lipidomic approach, lipids were extracted from the plasma samples and subjected to analysis. A comprehensive identification and quantification of 789 plasma lipids was achieved. Notably, 75 species displayed significant dysregulation in > 2 L patients in comparison to the 1 L group. Among these, 63 species exhibited elevated levels, while 12 were reduced. Patients included in > 2 L cohort showed elevated levels of acylcarnitines (CAR), diacylglycerols (DG), phosphatidylethanolamines (PE), triacylglycerols (TG), and ceramides (Cer). Notably, some upregulated lipids, including CAR 14:0, CAR 24:1, Cer d18:1/16:0, Cer d18:1/18:0 (C18 Cer), Cer d18:2/18:0, Cer d18:1/24:1, and Cer d20:1/24:1, showed significant associations with overall survival (OS) in univariate models. Specifically, increased levels of C18 Cer remained significantly associated with poorer OS in the multivariate model, even after adjusting for treatment line and PSA levels (Hazard Ratio: 3.59 [95% Confidence Interval 1.51–8.52], p = 0.004). Employing quantitative mass spectrometry, our findings underscore the independent prognostic significance of C18 Cer in individuals with mCRPC. This discovery opens avenues for further studies within this field.
Improving the quality of image generation in art with top-k training and cyclic generative methods
Authors: Vela Laura , Fuentes-Hurtado Félix , Colomer Adrián 
Published: October 2023

AbstractThe creation of artistic images through the use of Artificial Intelligence is an area that has been gaining interest in recent years. In particular, the ability of Neural Networks to separate and subsequently recombine the style of different images, generating a new artistic image with the desired style, has been a source of study and attraction for the academic and industrial community. This work addresses the challenge of generating artistic images that are framed in the style of pictorial Impressionism and, specifically, that imitate the style of one of its greatest exponents, the painter Claude Monet. After having analysed several theoretical approaches, the Cycle Generative Adversarial Networks are chosen as base model. From this point, a new training methodology which has not been applied to cyclical systems so far, the top-kapproach, is implemented. The proposed system is characterised by using in each iteration of the training thosekimages that, in the previous iteration, have been able to better imitate the artist’s style. To evaluate the performance of the proposed methods, the results obtained with both methodologies, basic and top-k, have been analysed from both a quantitative and qualitative perspective. Both evaluation methods demonstrate that the proposed top-kapproach recreates the author’s style in a more successful manner and, at the same time, also demonstrate the ability of Artificial Intelligence to generate something as creative as impressionist paintings.
Assessment of key parameters of normal uterus in women of reproductive age
Authors: Chen Fang , Gong Yingxin , Xie Yu , Zhu Lei , Chen Limei , Xiao Jingjing , Jiang Ninghong , Sun Li , Sui Long 
Published: October 2023

AbstractCurrently, the precise and detailed anatomical data of the normal uterus, especially the myometrium thickness in various parts of the uterus, are lacking. This study aims to provide normal references for uterine size in healthy reproductive-aged Chinese women to facilitate the application of hysteroscopic surgery. A total of 298 women of reproductive age with normal uterine were included. Parity was significantly correlated with uterine measurements (P < 0.05), and age impacted several measurements (P < 0.05). At each uterine site examined, the myometrium was thinner in nulliparous women than in parous or primiparous women (P < 0.001). Similarly, the extrauterine measurements for parous or primiparous women were larger than those for nulliparous women. Weight affected some external measurements but not myometrial thicknesses, while height did not affect uterine measurements (P > 0.05). There was a positive correlation between body mass index (BMI) and extrauterine measurements as well as myometrial thickness (P < 0.05). The mathematical model of the uterine size for women of reproductive age was constructed stratified by parity. The study is the first to provide a detailed statistical description of the accurate anatomical parameters of the uterus in Chinese reproductive-aged women and has great significance for improving the safety and effectiveness of hysteroscopic surgery for patients.
Depression and anxiety mediate the relationship between the retrospectively measured symptoms of premenstrual disorders and negative but not positive psychotic-like experiences
Authors: Antosz-Rekucka Rachela , Prochwicz Katarzyna 
Published: October 2023

AbstractThe aim of this study was to examine the relationship between retrospectively measured premenstrual symptoms and subclinical forms of positive and negative psychotic symptoms (psychotic-like experiences; PLEs). It was hypothesised that subjective intensity of the symptoms of premenstrual disorders predicts PLEs frequency and that this relationship is mediated by anxiety and depression. The study sample comprised 108 non-clinical subjects. Study variables were assessed with self-report questionnaires: the Premenstrual Symptoms Screening Tool (PSST); the Beck Depression Inventory Second Edition (BDI-II); the State-Trait Anxiety Inventory (STAI; trait sub-scale); the Community Assessment of Psychic Experiences (CAPE). Regression and mediation analyses were performed. The PSST scores were significantly and positively associated with psychotic-like experiences frequency. The relation was stronger for positive PLEs. Anxiety and depression partially mediated the relationship between premenstrual symptoms and negative PLEs, but not between premenstrual symptoms and positive PLEs. Although the design of the study does not allow to infer causality, it demonstrates strong, positive relationship between the symptoms of premenstrual disorders and psychotic-like experiences. The relationship between premenstrual disorders and negative PLEs seems to be partially based on a general psychopathological factor. Further longitudinal studies are needed to test whether premenstrual disturbances increase risk of psychotic symptoms.
Cuproptosis-related gene SLC31A1: prognosis values and potential biological functions in cancer
Authors: Qi Yue , Yao Qingqing , Li Xuanyan , Li Xinyu , Zhang Wenwen , Qu Pengpeng 
Published: October 2023

AbstractCuproptosis is a unique type of cell death that may influence tumour formation by targeting lipoylated tricarboxylic acid cycle proteins. Solute carrier family 31 member 1 (SLC31A1), an important copper transporter, influences dietary copper absorption in the cell membrane. However, various SLC31A1 properties in pan-cancer profiles remain unknown. This study investigated the role of SLC31A1 in human malignancies and analysed its prognostic value. Raw data were obtained from The Cancer Genome Atlas database and processed using numerous internet databases, including UALCAN, GEPIA, cBioPortal, TIMER2.0, and Human Protein Atlas. SLC31A1 expression was found to be elevated in cervical, endometrial, and breast cancers compared to that in normal tissues, but reduced in clear cell renal cell carcinoma, liver hepatocellular carcinoma, and lung adenocarcinoma. Furthermore, SLC31A1 expression was strongly associated with overall survival and disease-free survival in several cancers. SLC31A1 gene mutations and methylations were identified in 33 cancers. SLC31A1 expression was positively correlated with immune cells in immune infiltration data. Single-cell sequencing revealed that SLC31A1 may play key roles in DNA repair, DNA damage, and proliferation. These findings may lead to better understanding of SLC31A1 in pan-cancer profiles and suggest that SLC31A1 could be a viable predictive biomarker, particularly in gynaecological cancers.