Miracle-dz/UniFAR-FTUs huggingface dataset:
A prediction model for in-hospital mortality in intensive care unit patients with metastatic cancer

Aim To identify predictors for in-hospital mortality in patients with metastatic cancer in intensive care units (ICUs) and established a prediction model for in-hospital mortality in those patients. Methods In this cohort study, the data of 2,462 patients with metastatic cancer in ICUs were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to identify the predictors for in-hospital mortality in metastatic cancer patients. Participants were randomly divided into the training set (n = 1,723) and the testing set (n = 739). Patients with metastatic cancer in ICUs from MIMIC-IV were used as the validation set (n = 1,726). The prediction model was constructed in the training set. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were employed for measuring the predictive performance of the model. The predictive performance of the model was validated in the testing set and external validation was performed in the validation set. Results In total, 656 (26.65%) metastatic cancer patients were dead in hospital. Age, respiratory failure, the sequential organ failure assessment (SOFA) score, the Simplified Acute Physiology Score II (SAPS II) score, glucose, red cell distribution width (RDW) and lactate were predictors for the in-hospital mortality in patients with metastatic cancer in ICUs. The equation of the prediction model was ln(P/(1 + P)) = −5.9830 + 0.0174 × age + 1.3686 × respiratory failure + 0.0537 × SAPS II + 0.0312 × SOFA + 0.1278 × lactate − 0.0026 × glucose + 0.0772 × RDW. The AUCs of the prediction model was 0.797 (95% CI,0.776–0.825) in the training set, 0.778 (95% CI, 0.740–0.817) in the testing set and 0.811 (95% CI, 0.789–0.833) in the validation set. The predictive values of the model in lymphoma, myeloma, brain/spinal cord, lung, liver, peritoneum/pleura, enteroncus and other cancer populations were also assessed. Conclusion The prediction model for in-hospital mortality in ICU patients with metastatic cancer exhibited good predictive ability, which might help identify patients with high risk of in-hospital death and provide timely interventions to those patients.
Inhibition of thrombin on endothelium enhances recruitment of regulatory T cells during IRI and when combined with adoptive Treg transfer, significantly protects against acute tissue injury and prolongs allograft survival

Ischemia-reperfusion injury (IRI) amplifies T cell alloimmune responses after transplantation with thrombin playing a key pro-inflammatory role. To explore the influence of thrombin on regulatory T cell recruitment and efficacy we used a well-established model of IRI in the native murine kidney. Administration of the cytotopic thrombin inhibitor PTL060 inhibited IRI, and by skewing expression of chemokines (reducing CCL2 and CCL3 but increasing CCL17 and CCL22) increased the infiltration of M2 macrophages and Tregs. When PTL060 was combined with infusion of additional Tregs, these effects were further amplified. To test the benefits of thrombin inhibition in a transplant model, BALB/c hearts were transplanted into B6 mice with or without perfusion with PTL060 in combination with Tregs. Thrombin inhibition or Treg infusion alone led to small increments in allograft survival. However, the combined therapy led to modest graft prolongation by the same mechanisms as in renal IRI; graft survival was accompanied by increased numbers of Tregs and anti-inflammatory macrophages, and reduced expression of pro-inflammatory cytokines. While the grafts succumbed to rejection associated with the emergence of alloantibody, these data suggest that thrombin inhibition within the transplant vasculature enhances the efficacy of Treg infusion, a therapy that is currently entering the clinic to promote transplant tolerance.
Reprogramming of IL-12 secretion in the PDCD1 locus improves the anti-tumor activity of NY-ESO-1 TCR-T cells

Introduction Although the engineering of T cells to co-express immunostimulatory cytokines has been shown to enhance the therapeutic efficacy of adoptive T cell therapy, the uncontrolled systemic release of potent cytokines can lead to severe adverse effects. To address this, we site-specifically inserted the interleukin-12 (IL-12) gene into the PDCD1 locus in T cells using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based genome editing to achieve T-cell activation-dependent expression of IL-12 while ablating the expression of inhibitory PD-1. Methods New York esophageal squamous cell carcinoma 1(NY-ESO-1)-specific TCR-T cells was investigated as a model system. We generated ΔPD-1-IL-12 -edited NY-ESO-1 TCR-T cells by sequential lentiviral transduction and CRISPR knock-in into activated human primary T cells. Results We showed that the endogenous PDCD1 regulatory elements can tightly control the secretion of recombinant IL-12 in a target cell-dependent manner, at an expression level that is more moderate than that obtained using a synthetic NFAT-responsive promoter. The inducible expression of IL-12 from the PDCD1 locus was sufficient to enhance the effector function of NY-ESO-1 TCR-T cells, as determined by upregulation of effector molecules, increased cytotoxic activity, and enhanced expansion upon repeated antigen stimulation in vitro. Mouse xenograft studies also revealed that PD-1-edited IL-12-secreting NY-ESO-1 TCR-T cells could eliminate established tumors and showed significantly greater in vivo expansion capacity than control TCR-T cells. Discussion Our approach may provide a way to safely harness the therapeutic potential of potent immunostimulatory cytokines for the development of effective adoptive T cell therapies against solid tumors.
Investigating phenotypic relationships in persimmon accessions through integrated proteomic and metabolomic analysis of corresponding fruits

Together with phenological and genomic approaches, gel-based and label-free proteomic as well metabolomic procedures were separately applied to plants to highlight differences between ecotypes, to estimate genetic variability within/between organism populations, or to characterize specific mutants/genetically modified lines at metabolic level. To investigate the possible use of tandem mass tag (TMT)-based quantitative proteomics in the above-mentioned contexts and based on the absence of combined proteo-metabolomic studies on Diospyros kaki cultivars, we here applied integrated proteomic and metabolomic approaches to fruits from Italian persimmon ecotypes with the aim to characterize plant phenotypic diversity at molecular level. We identified 2255 proteins in fruits, assigning 102 differentially represented components between cultivars, including some related to pomological, nutritional and allergenic characteristics. Thirty-three polyphenols were also identified and quantified, which belong to hydroxybenzoic acid, flavanol, hydroxycinnamic acid, flavonol, flavanone and dihydrochalcone sub-classes. Heat-map representation of quantitative proteomic and metabolomic results highlighted compound representation differences in various accessions, whose elaboration through Euclidean distance functions and other linkage methods defined dendrograms establishing phenotypic relationships between cultivars. Principal component analysis of proteomic and metabolomic data provided clear information on phenotypic differences/similarities between persimmon accessions. Coherent cultivar association results were observed between proteomic and metabolomic data, emphasizing the utility of integrating combined omic approaches to identify and validate phenotypic relationships between ecotypes, and to estimate corresponding variability and distance. Accordingly, this study describes an original, combined approach to outline phenotypic signatures in persimmon cultivars, which may be used for a further characterization of other ecotypes of the same species and an improved description of nutritional characteristics of corresponding fruits.
tRNA-derived small RNAs in plant response to biotic and abiotic stresses

tRNA-derived small RNAs (tsRNAs) represent a novel category of small non-coding RNAs and serve as a new regulator of gene expression at both transcriptional and post-transcriptional levels. Growing evidence indicates that tsRNAs can be induced by diverse stimuli and regulate stress-responsive target genes, allowing plants to adapt to unfavorable environments. Here, we discuss the latest developments about the biogenesis and classification of tsRNAs and highlight the expression regulation and potential function of tsRNAs in plant biotic and abiotic stress responses. Of note, we also collect useful bioinformatics tools and resources for tsRNAs study in plants. Finally, we propose current limitations and future directions for plant tsRNAs research. These recent discoveries have refined our understanding of whether and how tsRNAs enhance plant stress tolerance.
Seismological reference earth model in South China (SREM-SC): Crust and uppermost mantle

The South China Block is located on the eastern margin of the Eurasian Plate and the western margin of the Pacific Plate. The South China Block is currently in a tectonically compressed environment, while the Tibetan Plateau is moving eastward and the Philippine Sea Plate is moving westward from geodetic observations. The South China Block is an ideal place to revisit tectonic history from the Archean to Cenozoic, where its information could be well preserved in the crust. In this study, we aim to build the crustal and uppermost mantle component of the Seismological Reference Earth Model in South China (SREM-SC) to provide a background velocity model for geological interpretations and fine-scale velocity inversion. The S-wave velocity model comes from combining models inverted by ambient noise tomography and surface wave tomography. The P-wave velocity model is obtained from converted S-wave velocity and joint inversion tomography. The density model is inferred from an empirical relationship with P-wave velocity. The Moho depth is obtained by a weighted averaging scheme of previously published receiver function results. The P-wave and S-wave velocity models have a grid interval of 0.5 ° in both latitude and longitude, and with a vertical sampling interval of 5 km down to the 60 km depth. This work provides the 3-D crust and uppermost mantle structures and a representative reference model beneath South China.
Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Malnutrition results in enormous socio-economic costs to the individual, their community, and the nation’s economy. The evidence suggests an overall negative impact of climate change on the agricultural productivity and nutritional quality of food crops. Producing more food with better nutritional quality, which is feasible, should be prioritized in crop improvement programs. Biofortification refers to developing micronutrient -dense cultivars through crossbreeding or genetic engineering. This review provides updates on nutrient acquisition, transport, and storage in plant organs; the cross-talk between macro- and micronutrients transport and signaling; nutrient profiling and spatial and temporal distribution; the putative and functionally characterized genes/single-nucleotide polymorphisms associated with Fe, Zn, and β-carotene; and global efforts to breed nutrient-dense crops and map adoption of such crops globally. This article also includes an overview on the bioavailability, bioaccessibility, and bioactivity of nutrients as well as the molecular basis of nutrient transport and absorption in human. Over 400 minerals (Fe, Zn) and provitamin A-rich cultivars have been released in the Global South. Approximately 4.6 million households currently cultivate Zn-rich rice and wheat, while ~3 million households in sub-Saharan Africa and Latin America benefit from Fe-rich beans, and 2.6 million people in sub-Saharan Africa and Brazil eat provitamin A-rich cassava. Furthermore, nutrient profiles can be improved through genetic engineering in an agronomically acceptable genetic background. The development of “Golden Rice” and provitamin A-rich dessert bananas and subsequent transfer of this trait into locally adapted cultivars are evident, with no significant change in nutritional profile, except for the trait incorporated. A greater understanding of nutrient transport and absorption may lead to the development of diet therapy for the betterment of human health.
Journal of Quantitative Analysis in Sports Cruel and Unusual Punishment ? An Analysis of Point Deduction in European Association Football Leagues

We present a methodology to assess the effect of point deductions, which are widely applied as punishments to teams in European association football (soccer) leagues. In particular we outline a method to estimate the increased probability of relegation and the decreased probability of promotion that are associated with a certain penalty for a given team in a particular league. We illustrate our method in the context of two case studies involving points deductions: the relegation of Luton Town from English League Two in 2008--9, and the promotion of Juventus from Italian Serie B in 2006--7. By adapting the parameterisation of our model, we extend our analysis to the more challenging objective of designing standardised point deductions, and discuss how prior knowledge on performance influences the likely severity of any given punishment. We also investigate the relationship between the magnitude of any point deduction and the financial implications for the penalised team. Our techniques allow unambiguous quantification of the consequences of a form of punishment that has been widely, but not necessarily scientifically, implemented by a number of governing bodies in European association football.
Editorial: Offshore wind energy: Modeling and measurements

The global offshore wind industry is growing with unprecedented speed. The Global Wind Energy Council has raised its outlook for 2030 to a total of 316 GW installed for offshore wind (Lee and Zhao, 2022). Over the sea basins, we see wind farms and clusters getting increasingly larger, turbines becoming taller, and floating wind turbines moving from the demonstration phase to the pre-commercial phase and being installed in deeper waters. The increase in size raises a series of challenges to the fundamental science and technologies that have been calibrated and applied to smaller turbines, small wind farms, and simpler systems. Thus, for the modeling of wind turbine and farm wake effects, we are facing the challenge of having both high fidelity and large coverage. For modeling turbulence, we need to break through the classical boundary layer turbulence theories by considering large-scale atmospheric variability. For grid integration and system control, we need to advance our tools to handle big data. For floating turbines and farms, we need to take the complicated sea and ocean conditions into account, as well as the multiscale atmospheric flow effects. Additionally, we need to understand how the new seascape in the presence of wind farms affects the overall offshore environment. The rapid success of the offshore wind industry leaves us little time to identify knowledge gaps, speed up relevant research, and catch up technologically to accommodate efficient, effective, and healthy offshore wind development.
Collecting wild potato species (Solanum sect. Petota) in Peru to enhance genetic representation and fill gaps in ex situ collections

Crop wild relatives (CWRs) are important sources of novel genes, due to their high variability of response to biotic and abiotic stresses, which can be invaluable for crop genetic improvement programs. Recent studies have shown that CWRs are threatened by several factors, including changes in land-use and climate change. A large proportion of CWRs are underrepresented in genebanks, making it necessary to take action to ensure their long-term ex situ conservation. With this aim, 18 targeted collecting trips were conducted during 2017/2018 in the center of origin of potato (Solanum tuberosum L.), targeting 17 diverse ecological regions of Peru. This was the first comprehensive wild potato collection in Peru in at least 20 years and encompassed most of the unique habitats of potato CWRs in the country. A total of 322 wild potato accessions were collected as seed, tubers, and whole plants for ex situ storage and conservation. They belonged to 36 wild potato species including one accession of S. ayacuchense that was not conserved previously in any genebank. Most accessions required regeneration in the greenhouse prior to long-term conservation as seed. The collected accessions help reduce genetic gaps in ex situ conserved germplasm and will allow further research questions on potato genetic improvement and conservation strategies to be addressed. These potato CWRs are available by request for research, training, and breeding purposes under the terms of the International Treaty for Plant Genetic Resources for Food and Agriculture (ITPGRFA) from the Instituto Nacional de Innovacion Agraria (INIA) and the International Potato Center (CIP) in Lima-Peru.
Cartilage organoids for cartilage development and cartilage-associated disease modeling

Cartilage organoids have emerged as powerful modelling technology for recapitulation of joint embryonic events, and cartilage regeneration, as well as pathophysiology of cartilage-associated diseases. Recent breakthroughs have uncovered “mini-joint” models comprising of multicellular components and extracellular matrices of joint cartilage for development of novel disease-modifying strategies for personalized therapeutics of cartilage-associated diseases. Here, we hypothesized that LGR5-expressing embryonic joint chondroprogenitor cells are ideal stem cells for the generation of cartilage organoids as “mini-joints” ex vivo “in a dish” for embryonic joint development, cartilage repair, and cartilage-associated disease modelling as essential research models of drug screening for further personalized regenerative therapy. The pilot research data suggested that LGR5-GFP-expressing embryonic joint progenitor cells are promising for generation of cartilage organoids through gel embedding method, which may exert various preclinical and clinical applications for realization of personalized regenerative therapy in the future.
A new way to improve the robustness of complex communication networks by allocating redundancy links

We investigate the robustness of complex communication networks on allocating redundancy links. The protecting key nodes (PKN) strategy is proposed to improve the robustness of complex communication networks against intentional attack. Our numerical simulations show that allocating a few redundant links among key nodes using the PKN strategy will significantly increase the robustness of scale-free complex networks. We have also theoretically proved and demonstrated the effectiveness of the PKN strategy. We expect that our work will help achieve a better understanding of communication networks.
A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems

A new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters. Fourier series expansion (FSE) is introduced to deal with the problem of uncertain time-varying parameters. The bound of the expanded remaining items is unknown. A typical convergent series is used to deal with the unknown bound in the design process of the controller. The adaptive iterative learning synchronization controller and parameter update laws are designed. Two different chaotic systems are synchronized asymptotically according to different proportional functions on a finite time interval by Lyapunov stability analysis. The simulation example proves the feasibility and effectiveness of the proposed method.
Genetic diversity and structure of Brycon henni in regulated and non-regulated water flow rivers of the Colombian Andes

The sabaleta, Brycon henni, is a medium-size fish species found in the Andean range of the Magdalena-Cauca river basin in Colombia, where it is a fishery resource. Recruitment of sabaleta has affected construction of dams with unknown consequences on its genetic diversity and structure. Understanding the current genetic architecture in the dam-influenced areas compared to non-regulated water flow systems is crucial to diagnose the impact of human interventions and formulate proper management strategies. In this study, we evaluated the genetic structure and diversity of B. henni by using a set of microsatellites in individuals from 14 localities to identify the number of distinct genetic pools. We used various approaches to compare populations between regulated and non-regulated areas in the Magdalena-Cauca basin, and identified eleven well-differentiated and highly diverse population groups with marked genetic structures at local and regional levels. Genetic diversity of B. henni was very similar among non-regulated and dam-regulated water flow areas; however, one of the populations in non-regulated areas showed evidence of a founder effect associated with recent introductions. The effect of dams on the genetic structure of B. henni in the Magdalena-Cauca basin was negligible, probably due to their recent construction. Future reduction of genetic diversity and the loss of unique populations is expected due to the combined effect of geographic isolation and population declines. Thus, monitoring programs are necessary to detect changes in the genetic structure of fish populations to develop useful conservation actions.