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Renal replacement therapy (RRT) is a crucial treatment for sepsis-associated acute kidney injury (S-AKI), but it is uncertain which S-AKI patients should receive immediate RRT. Identifying the characteristics of patients who may benefit the most from RRT is an important task. This retrospective study utilized a public database and enrolled S-AKI patients, who were divided into RRT and non-RRT groups. Uplift modeling was used to estimate the individual treatment effect (ITE) of RRT. The validity of different models was compared using a qini curve. After labeling the patients in the validation cohort, we characterized the patients who would benefit the most from RRT and created a nomogram. A total of 8289 patients were assessed, among whom 591 received RRT, and 7698 did not receive RRT. The RRT group had a higher severity of illness than the non-RRT group, with a Sequential Organ Failure Assessment (SOFA) score of 9 (IQR 6,11) vs. 5 (IQR 3,7). The 28-day mortality rate was higher in the RRT group than the non-RRT group (34.83% vs. 14.61%, p < 0.0001). Propensity score matching (PSM) was used to balance baseline characteristics, 458 RRT patients and an equal number of non-RRT patients were enrolled for further research. After PSM, 28-day mortality of RRT and non-RRT groups were 32.3% vs. 39.3%, P = 0.033. Using uplift modeling, we found that urine output, fluid input, mean blood pressure, body temperature, and lactate were the top 5 factors that had the most influence on RRT effect. The area under the uplift curve (AUUC) of the class transformation model was 0.068, the AUUC of SOFA was 0.018, and the AUUC of Kdigo-stage was 0.050. The class transformation model was more efficient in predicting individual treatment effect. A logistic regression model was developed, and a nomogram was drawn to predict whether an S-AKI patient can benefit from RRT. Six factors were taken into account (urine output, creatinine, lactate, white blood cell count, glucose, respiratory rate). Uplift modeling can better predict the ITE of RRT on S-AKI patients than conventional score systems such as Kdigo and SOFA. We also found that white blood cell count is related to the benefits of RRT, suggesting that changes in inflammation levels may be associated with the effects of RRT on S-AKI patients. [ABSTRACT FROM AUTHOR]

Spectroscopy and X-ray diffraction techniques encode ample information on investigated samples. The ability of rapidly and accurately extracting these enhances the means to steer the experiment, as well as the understanding of the underlying processes governing the experiment. It improves the efficiency of the experiment, and maximizes the scientific outcome. To address this, we introduce and validate three frameworks based on self-supervised learning which are capable of classifying 1D spectral curves using data transformations preserving the scientific content and only a small amount of data labeled by domain experts. In particular, in this work we focus on the identification of phase transitions in samples investigated by x-ray powder diffraction. We demonstrate that the three frameworks, based either on relational reasoning, contrastive learning, or a combination of the two, are capable of accurately identifying phase transitions. Furthermore, we discuss in detail the selection of data augmentation techniques, crucial to ensure that scientifically meaningful information is retained. [ABSTRACT FROM AUTHOR]

This study evaluates the use of L-PRF as an autologous scaffold in nerve regeneration, and Schwann cells (SCs) proliferation and secretion of neurotrophic factors and its anti-inflammatory effect on SC Porphyromonas Gingivalis-Lipopolysaccharide (PG-LPS)-induced inflammatory responses in vitro. SEM was done to investigate various features of L-PRF. L-PRF-extracts was used to investigate the release of growth factors and treatment of SCs line. ELISA was applied to examine the release of IGF-1. The proliferative effect of L-PRF on SCs was assessed with CCK-8 assay. The effect of L-PRF on the mRNA and protein expression of SC neurotrophic factors were analyzed by RT-qPCR and ELISA. CCK-8 assay and RT-qPCR were used to determine the required concentration and the action time of PG-LPS before the anti-inflammatory effect of L-PRF was determined by measuring the changes in IL-1β, IL-6, and TNF-a with RT-qPCR and ELISA. There are different features in L-PRF. Fourteen days was sufficient to release adequate GF. The mRNA expressions of the pro-inflammatory cytokines were notably raised by PG-LPS in 3-hours treatment. L-PRF can increase SC proliferation, neurotrophic factors secretion, and suppress SC PG-LPS-induced inflammatory responses in vitro. L-PRF has the potential as an autologous biological additive for peripheral nerve regeneration in the event of nerve inflammation and injuries. [ABSTRACT FROM AUTHOR]

In this study, we present a novel, multiple coefficient of determination (R2M)-based method for parsing SNPs located within the chromosomal neighborhood of a gene into semi-independent families, each of which corresponds to one or more functional variants that regulate transcription of the gene. Specifically, our method utilizes a matrix equation framework to calculate R2M values for SNPs within a chromosome region of interest (ROI) based upon the choices of 1-4 "index" SNPs (iSNPs) that serve as proxies for underlying regulatory variants. Exhaustive testing of sets of 1–4 candidate iSNPs identifies iSNP models that best account for estimated R2 values derived from single-variable linear regression analysis of correlations between mRNA expression and genotypes of individual SNPs. Subsequent genotype-based estimation of pairwise r2 linkage disequilibrium (LD) coefficients between each iSNP and the other ROI SNPs allows the SNPs to be parsed into semi-independent families. Analysis of mRNA expression and genotypes data downloaded from Gene Expression Omnibus (GEO) and database for Genotypes and Phenotypes (dbGAP) demonstrates the usefulness of this method for parsing SNPs based on experimental data. We believe that this method will be widely applicable for the analysis of the genetic basis of mRNA expression and visualizing the contributions of multiple genetic variants to the regulation of individual genes. [ABSTRACT FROM AUTHOR]

Coupling ultrasmall Fe2O3 particles (~4.0 nm) with the MoS2 nanosheets is achieved by a facile method for high-performance anode material for Li-ion battery. MoS2 nanosheets in the composite can serve as scaffolds, efficiently buffering the large volume change of Fe2O3 during charge/discharge process, whereas the ultrasmall Fe2O3 nanoparticles mainly provide the specific capacity. Due to bigger surface area and larger pore volume as well as strong coupling between Fe2O3 particles and MoS2 nanosheets, the composite exhibits superior electrochemical properties to MoS2, Fe2O3 and the physical mixture Fe2O3+MoS2. Typically, after 140 cycles the reversible capacity of the composite does not decay, but increases from 829 mA h g−1 to 864 mA h g−1 at a high current density of 2 A g−1. Thus, the present facile strategy could open a way for development of cost-efficient anode material with high-performance for large-scale energy conversion and storage systems. [ABSTRACT FROM AUTHOR]

RBM10 is an RNA splicing regulator that is frequently mutated in lung adenocarcinoma (LUAD) and has recently been proposed to be a cancer gene. How RBM10 mutations observed in LUAD affect its normal functions, however, remains largely unknown. Here integrative analysis of RBM10 mutation and RNA expression data revealed that LUAD-associated RBM10 mutations exhibit a mutational spectrum similar to that of tumor suppressor genes. In addition, this analysis showed that RBM10 mutations identified in LUAD patients lacking canonical oncogenes are associated with significantly reduced RBM10 expression. To systematically investigate RBM10 mutations, we developed an experimental pipeline for elucidating their functional effects. Among six representative LUAD-associated RBM10 mutations, one nonsense and one frameshift mutation caused loss-of-function as expected, whereas four missense mutations differentially affected RBM10-mediated splicing. Importantly, changes in proliferation rates of LUAD-derived cells caused by these RBM10 missense mutants correlated with alterations in RNA splicing of RBM10 target genes. Together, our data implies that RBM10 mutations contribute to LUAD pathogenesis, at least in large part, by deregulating splicing. The methods described in this study should be useful for analyzing mutations in additional cancer-associated RNA splicing regulators. [ABSTRACT FROM AUTHOR]

Controlling single-particle wave functions in single semiconductor quantum dots is in demand to implement solid-state quantum information processing and spintronics. Normally, particle wave functions can be tuned transversely by an perpendicular magnetic field. We report a longitudinal wave function control in single quantum dots with a magnetic field. For a pure InAs quantum dot with a shape of pyramid or truncated pyramid, the hole wave function always occupies the base because of the less confinement at base, which induces a permanent dipole oriented from base to apex. With applying magnetic field along the base-apex direction, the hole wave function shrinks in the base plane. Because of the linear changing of the confinement for hole wave function from base to apex, the center of effective mass moves up during shrinking process. Due to the uniform confine potential for electrons, the center of effective mass of electrons does not move much, which results in a permanent dipole moment change and an inverted electron-hole alignment along the magnetic field direction. Manipulating the wave function longitudinally not only provides an alternative way to control the charge distribution with magnetic field but also a new method to tune electron-hole interaction in single quantum dots. [ABSTRACT FROM AUTHOR]

Accurately estimating large-area crop yields, especially for soybeans, is essential for addressing global food security challenges. This study introduces a deep learning framework that focuses on precise county-level soybean yield estimation in the United States. It utilizes a wide range of multi-variable remote sensing data. The model used in this study is a state-of-the-art CNN-BiGRU model, which is enhanced by the GOA and a novel attention mechanism (GCBA). This model excels in handling intricate time series and diverse remote sensing datasets. Compared to five leading machine learning and deep learning models, our GCBA model demonstrates superior performance, particularly in the 2019 and 2020 evaluations, achieving remarkable R 2 , RMSE, MAE and MAPE values. This sets a new benchmark in yield estimation accuracy. Importantly, the study highlights the significance of integrating multi-source remote sensing data. It reveals that synthesizing information from various sensors and incorporating photosynthesis-related parameters significantly enhances yield estimation precision. These advancements not only provide transformative insights for precision agricultural management but also establish a solid scientific foundation for informed decision-making in global agricultural production and food security., (© 2024. The Author(s).)

Autophagy is essential for eukaryotic cell homeostasis and can perform both anti-viral and pro-viral roles depending on the kinds of viruses, cell types and cell environment. Severe fever with thrombocytopenia syndrome phlebovirus (SFTSV) is a newly discovered tick-borne virus in the Phenuiviridae family that causes a severe hemorrhagic fever disease in East Asia. In this study we determined interactions between SFTSV and autophagy. Our results showed that LC3-II (microtubule associated protein 1 light chain 3-II) protein accumulated from 4 h to 24 h after SFTSV infection compared to mock-infected Vero cells, and the use of E64d and pepstatin A did not affect the expression of LC3-II protein, which indicated that the increased LC3-II may be the result of inhibition of autophagic degradation caused by SFTSV infection. However, knockdown of LC3B promotes SFTSV replication, which indicated a negative role of LC3B protein in SFTSV replication. We also detected co-localization of SFTSV non-structure (NSs) protein with LC3B, p62 and Lamp2b respectively in SFTSV infected Vero cells, which indicated the possibility of selective autophagy or chaperone-mediated autophagy involving in SFTSV infection. Our results indicated that SFTSV infection promotes LC3 accumulation and several proteins of the autophagy pathway co-localize with NSs protein during SFTSV infection.

Coupling ultrasmall Fe 2 O 3 particles (~4.0 nm) with the MoS 2 nanosheets is achieved by a facile method for high-performance anode material for Li-ion battery. MoS 2 nanosheets in the composite can serve as scaffolds, efficiently buffering the large volume change of Fe 2 O 3 during charge/discharge process, whereas the ultrasmall Fe 2 O 3 nanoparticles mainly provide the specific capacity. Due to bigger surface area and larger pore volume as well as strong coupling between Fe 2 O 3 particles and MoS 2 nanosheets, the composite exhibits superior electrochemical properties to MoS 2 , Fe 2 O 3 and the physical mixture Fe 2 O 3 +MoS 2 . Typically, after 140 cycles the reversible capacity of the composite does not decay, but increases from 829 mA h g -1 to 864 mA h g -1 at a high current density of 2 A g -1 . Thus, the present facile strategy could open a way for development of cost-efficient anode material with high-performance for large-scale energy conversion and storage systems.

Superconductivity (SC) with the suppression of long-range antiferromagnetic (AFM) order is observed in the parent compounds of both iron-based and cuprate superconductors. The AFM wave vectors are bicollinear (π, 0) in the parent compound FeTe different from the collinear AFM order (π, π) in most iron pnictides. Study of the phase diagram of Fe1+yTe1-xSex is the most direct way to investigate the competition between bicollinear AFM and SC. However, presence of interstitial Fe affects both magnetism and SC of Fe1+yTe1-xSex, which hinders the establishment of the real phase diagram. Here, we report the comparison of doping-temperature (x-T) phase diagrams for Fe1+yTe1-xSex (0 ≤ x ≤ 0.43) single crystals before and after removing interstitial Fe. Without interstitial Fe, the AFM state survives only for x < 0.05, and bulk SC emerges from x = 0.05, and does not coexist with the AFM state. The previously reported spin glass state, and the coexistence of AFM and SC may be originated from the effect of the interstitial Fe. The phase diagram of Fe1+yTe1-xSex is found to be similar to the case of the "1111" system such as LaFeAsO1-xFx, and is different from that of the "122" system.

T follicular helper (Tfh) cells provide help for antigen-specific B cells. We have previously shown that Tfh cell frequency was increased and associated with auto-antibodies in patients with rheumatoid arthritis (RA), suggesting a possible involvement of Tfh cells in its pathogenesis. Mesenchymal stem cells (MSCs) represent a promising alternative cell therapy for RA by modulating T and B cell activation and proliferation. However, it remains unknown whether MSCs have immunoregulation on Tfh cells. In this paper, we have demonstrated that allogeneic MSCs could suppress Tfh cell differentiation in RA patients partly via the production of indoleamine 2,3-dioxygenase (IDO). IFNγ generated from Tfh cell differentiation system induced IDO expression on MSCs. MSCs transplantation (MSCT) into collagen-induced arthritis (CIA) mice prevented arthritis progression by inhibiting both the number and function of Tfh cells in vivo. These findings reveal a novel suppressive function of MSCs in Tfh cells, which has implication in understanding the underlying mechanisms of the immunotherapeutic effects of MSCs on RA patients.

Protein misfolding and aggregation are associated with more than twenty diseases, such as neurodegenerative diseases and metabolic diseases. The amyloid oligomers and fibrils may induce cell membrane disruption and lead to cell apoptosis. A great number of studies have focused on discovery of amyloid inhibitors which may prevent or treat amyloidosis diseases. Polyphenols have been extensively studied as a class of amyloid inhibitors, with several polyphenols under clinical trials as anti-neurodegenerative drugs. As oxidative intermediates of natural polyphenols, quinones widely exist in medicinal plants or food. In this study, we used insulin as an amyloid model to test the anti-amyloid effects of four simple quinones and four natural anthraquinone derivatives from rhubarb, a traditional herbal medicine used for treating Alzheimer's disease. Our results demonstrated that all eight quinones show inhibitory effects to different extent on insulin oligomerization, especially for 1,4-benzoquinone and 1,4-naphthoquinone. Significantly attenuated oligomerization, reduced amount of amyloid fibrils and reduced hemolysis levels were found after quinones treatments, indicating quinones may inhibit insulin from forming toxic oligomeric species. The results suggest a potential action of native anthraquinone derivatives in preventing protein misfolding diseases, the quinone skeleton may thus be further explored for designing effective anti-amyloidosis compounds.