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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]

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]

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.