Exploring the Origin of High Dechlorination Activity in Polar Materials M₂B₅O₉Cl (M = Ca, Sr, Ba, Pb) with Built-In Electric Field

Polar photocatalyst materials usually exhibit ferroelectric characteristics giving rise to spontaneous polarization behavior which works as a driving force for the separation of photogenerated electrons and holes and mitigates the effect of charge recombination. This study shows that the surface potential changes for a polar phtotocatalyst before and after photoirradiation can be used to predict the photocatalytic activities among different phtotocatalysts. We systematically investigated the correlation among the surface properties, crystal structure, electronic band structure, photocatalytic activity, and stability of four B–O and alkaline earth cations containing photocatalysts, M₂B₅O₉Cl (M = Ca, Sr, Ba, Pb). Among the four studied photocatalysts, Ba₂B₅O₉Cl exhibits the greatest changes in the surface potential after photoirradiation and also shows the highest photocatalytic activity for dechlorination of chlorophenols under UV light irradiation. Its photocatalytic activity is about 1.3, 2.8, 4.4, and 15 times those of Ca₂B₅O₉Cl, Sr₂B₅O₉Cl, Pb₂B₅O₉Cl, and P25 samples, respectively. The results support that the photocatalytic activity of the four photocatalysts strongly depends on the spontaneous polarization power. Overall, these findings demonstrate the utility of Kelvin probe force microscopy that can screen for a highly efficient photodegradation materials in the field of photocatalysis

Development of a nomogram for the prediction of acute kidney injury after liver transplantation: a model based on clinical parameters and postoperative cystatin C level

Acute kidney injury (AKI) is common after liver transplantation (LT). We developed a nomogram model to predict post-LT AKI. A total of 120 patients were eligible for inclusion in the study. Clinical information was extracted from the institutional electronic medical record system. Blood samples were collected prior to surgery and immediately after surgery. Univariable and multivariate logistic regression were used to identify independent risk factors. Finally, a nomogram was developed based on the final multivariable logistic regression model. In total, 58 (48.3%) patients developed AKI. Multivariable logistic regression revealed four independent risk factors for post-LT AKI: operation duration [odds ratio (OR) = 1.728, 95% confidence interval (CI) = 1.121–2.663, p = 0.013], intraoperative hypotension (OR = 3.235, 95% CI = 1.316–7.952, p = 0.011), postoperative cystatin C level (OR = 1.002, 95% CI = 1.001–1.004, p = 0.005) and shock (OR = 4.002, 95% CI = 0.893–17.945, p = 0.070). Receiver operating characteristic curve analysis was used to evaluate model discrimination. The area under the curve value was 0.815 (95% CI = 0.737–0.894). The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance for post-LT AKI than the model based on clinical parameters or postoperative cystatin C level alone. Additionally, we developed an easy-to-use nomogram based on the final model, which could aid in the early detection of AKI and improve the prognosis of patients after LT. Acute kidney injury (AKI) is one of the most common and important complications after liver transplantation (LT).We developed a nomogram model to predict post-LT AKI based on clinical parameters and postoperative cystatin C level.The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance, which could aid in the early detection of AKI and improve the prognosis of patients after LT. Acute kidney injury (AKI) is one of the most common and important complications after liver transplantation (LT). We developed a nomogram model to predict post-LT AKI based on clinical parameters and postoperative cystatin C level. The model based on combinations of clinical parameters and postoperative cystatin C levels had a higher predictive performance, which could aid in the early detection of AKI and improve the prognosis of patients after LT.</p

Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios

In the face of low-resource reaction training samples, we construct a chemical platform for addressing small-scale reaction prediction problems. Using a self-supervised pretraining strategy called MAsked Sequence to Sequence (MASS), the Transformer model can absorb the chemical information of about 1 billion molecules and then fine-tune on a small-scale reaction prediction. To further strengthen the predictive performance of our model, we combine MASS with the reaction transfer learning strategy. Here, we show that the average improved accuracies of the Transformer model can reach 14.07, 24.26, 40.31, and 57.69% in predicting the Baeyer–Villiger, Heck, C–C bond formation, and functional group interconversion reaction data sets, respectively, marking an important step to low-resource reaction prediction

Discovery of Sovleplenib, a Selective Inhibitor of Syk in Clinical Development for Autoimmune Diseases and Cancers

Herein we describe the medicinal chemistry efforts that led to the discovery of the clinical-staged Syk inhibitor sovleplenib (41) via a structure–activity relationship investigation and pharmacokinetics (PK) optimization of a pyrido[3,4-b]pyrazine scaffold. Sovleplenib is a potent and selective Syk inhibitor with favorable preclinical PK profiles and robust anti-inflammation efficacy in a preclinical collagen-induced arthritis model. Sovleplenib is now being developed for treating autoimmune diseases such as immune thrombocytopenic purpura and warm antibody hemolytic anemia as well as hematological malignancies

Cell proliferation and invasion of PRAME siRNA-treated cells.

<p>RT-PCR(A) and western blot (B) show that PRAME siRNA transfected PC9 and A549 cells exhibited decreased PRAME and E-cadherin expression. Actin serves the loading control in western blot experiments. (C) MTT assay of PC9 and A549 cells after PRAME and control siRNA transfection. (D) Pictures and bar graphs show the increased invasion of lung cancer cells after PRAME knockdown. * p<0.05, ** p<0.001.</p

MMP1 correlates with the clinical features of lung cancer.

<p>(A) Increased expression of MMP1 is observed in lung adenocarcinoma compared with normal lung tissue. (B) Higher expression of MMP1 in Stage II than in Stage I adenocarcinoma. Increased recurrence (C) and deaths at 5 years (D) correlate with higher expression of MMP1. (E) Survival probability is increased in patients with low MMP1 expression.</p

RNA-seq profiling of PC9 cells after PRAME knockdown.

<p>(A) RNA-seq analysis of 3 samples of PC9 cell transfected with PRAME siRNA and control siRNA. Heatmap represents the differentially expressed genes after the knockdown of PRAME. Each column represents one sample, and each row refers to one gene. Top-left is the color legend with the green color indicating the upregulated genes. (B) GO analysis of the differentially expressed genes for the cellular function characterization of these genes. (C) List of the top 65 genes significantly altered after the knockdown of PRAME, which are closely related to cell migration.</p

PRAME shows similar expression pattern with E-cadherin in the bone metastasis mouse model.

<p>(A) Representative images showing the luminescence signal in xenografted mice after PC9 cells inoculation. (B) X-ray photographs show the osteolytic lesion produced by PRAME siRNA transfected PC9 cells. (c) Histological staining of tibias shows the control siRNA and PRAME siRNA treated tumor cells metastasized to tibial bone.</p

PRAME is down-regulated in the human lung cancer and metastases.

<p>RT-PCR (A) and western blot (B) shows that PRAME and E-cadherin are downregulated in lung cancer and lung bone metastasis. Actin serve as the loading control. * p<0.05, *** p<0.0001.</p