(R)-1-[(S)-(3-Cyano­thio­morpholino)carbon­yl]-2-methyl­propyl­aminium chloride dihydrate

In the title compound, C10H18N3OS+·Cl−·2H2O, the three C atoms of the isopropyl group are disordered and were refined using a split-site mode [occupancy ratio 0.53 (3):0.47 (3)]. In the crystal, the cations, anions and water mol­ecules are connected via O—H⋯O, O—H⋯Cl, N—H⋯Cl and N—H⋯O hydrogen bonding

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation

Diffusion models based on permutation-equivariant networks can learn permutation-invariant distributions for graph data. However, in comparison to their non-invariant counterparts, we have found that these invariant models encounter greater learning challenges since 1) their effective target distributions exhibit more modes; 2) their optimal one-step denoising scores are the score functions of Gaussian mixtures with more components. Motivated by this analysis, we propose a non-invariant diffusion model, called $\textit{SwinGNN}$, which employs an efficient edge-to-edge 2-WL message passing network and utilizes shifted window based self-attention inspired by SwinTransformers. Further, through systematic ablations, we identify several critical training and sampling techniques that significantly improve the sample quality of graph generation. At last, we introduce a simple post-processing trick, $\textit{i.e.}$, randomly permuting the generated graphs, which provably converts any graph generative model to a permutation-invariant one. Extensive experiments on synthetic and real-world protein and molecule datasets show that our SwinGNN achieves state-of-the-art performances. Our code is released at https://github.com/qiyan98/SwinGNN

Claudin7 and moesin in endometrial Adenocarcinoma; a retrospective study of 265 patients

<p>Abstract</p> <p>Background</p> <p>Metastasis is the main cause of death in cancer and is a multistep process. Moesin (MSN), a member of the ezrin-rdixin-moesin family and Claudin7 (CLDN7), a tight junction protein, both play a role in tumor cell metastasis. Previously, we found an over-expression of MSN and under-expression of CLDN7 at the mRNA level in uterine serous carcinoma in comparison to uterine endometrioid adenocarcinoma. The purpose of this study is to determine the protein expression of MSN and CLDN7 in endometrial cancer (EC) and to evaluate their prognostic value. Two hundred sixty-five patients with EC were retrieved from the archives. MSN and CLDN7 immunostaining were performed on the tissue paraffin sections. The expression of each antibody was reported and then correlated with clinicopathological prognostic factors including age, tumor grade, tumor stage, lympho-vascular involvement, depth of myometrial invasion, overall survival (OS), disease free survival (DFS) and death of disease (DOD).</p> <p>Results</p> <p>MSN and CLDN were expressed in 46% and 52% of overall cases. We observed an association between MSN<it>⁺</it>staining and tumor grade, and serous and clear cell carcinoma subtypes (<it>p </it>< 0.001 each). There was an association between CLDN7⁺staining and low tumor grade and endometrioid adenocarcinoma subtype (<it>p </it>< 0.001 and 0.001 respectively). However, no association between MSN and CLDN7 expression and outcome including OS, DOD, and DFS was found.</p> <p>Conclusion</p> <p>A significant prognostic value of MSN and CLDN7 in predicting disease outcomes in patients with EC was not demonstrated. Nevertheless, the high percentage of EC cases with MSN and CLDN7 immunoexpression, and their association with tumor grade and subtypes, suggests that these proteins might play a role in tumorigenesis of endometrial adenocarcinomas. Future studies are needed to shed light on their mechanistic properties in EC cells.</p

Numerička studija izrađena pomoću ChemKin za rasplinjavanje vodene pare ugljene prašine i transformacije žive unutar rasplinjača s vodenom parom

Zero-emission coal (ZEC) technology has been actively studied recently. It aims to achieve zero emission of CO2 and other pollutants and the efficiency of this system can reach no less than 70%. Hydro-gasification of pulverized coal is a core process of ZEC. However, the mechanism of gasification and transformation of mercury speciation in the hydro-gasification is has not been understood precisely up until now. This restrains the ZEC’s commercialization. The purpose of this paper is to study the mechanism of hydro-gasification and mercury speciation transformation for coal in the gasifier with high temperature and pressure. Detailed chemical kinetics mechanism (CKM) has been proposed for hydro-gasification for pulverized coal in an entrained flow hydro-gasifier. The effects have been studied for different reaction conditions on hydro-gasification products and evolution of Hg in terms of the chemical reaction kinetics method. The CKM mechanism includes 130 elementary reactions and is solved with commercially available software, ChemKin. The calculation results are validated against the experimental data from literature and meaningful predictions are finally obtained. In addition, the chemical equilibrium calculation (CEC) is also used for predictions. Although the CEC method assumes all the reactions have reached chemical equilibrium, which is not the case in industrial reality, the calculation results are of value as reference.Tehnologija korištenja ugljena bez emisija (ZEC) se od nedavno aktivno proučava. Njezin cilj je postizanje nulte stope emisija CO2 te ostalih štetnih tvari dok efikasnost sustava mora biti minimalno 70%. Rasplinjavanje ugljene prašine vodenom parom je temeljni proces ZEC-a. Međutim, mehanizam rasplinjavanja i transformacije žive u rasplinjavanju vodenom parom još nije u potpunosti shvaćeno. To ograničava mogućnost komercijalne primjene ZEC-a. Cilj ovog rada je proučavanje mehanizama rasplinjavanja vodenom parom i transformacije žive za rasplinjavanje ugljena u rasplinjaču s visokim temperaturama i tlakom. Predloženi su detaljni kemijski kinetički mehanizmi (CKM) za rasplinjavanje ugljene prašine u fluidiziranom sloju sa zajedničkim tokom tvari. Proučeni su utjecaji raznih uvjeta pod kojim su se odvijale reakcije na produkte rasplinjavanja i evoluciju žive u uvjetima kemijskih reakcija kinetičke metode. CMK mehanizam sadrži 130 elementarnih reakcija i rješava se s komercijalno dostupnim programom, ChemKin. Rezultati simulacije se uspoređuju s eksperimentalnim iz literature te su konačno dobivena smislena predviđanja. Jednadžbe kemijske ravnoteže (CEC) su također korištene za predviđanja. Iako CEC metoda pretpostavlja da su sve reakcije postigle ravnotežu, što nije uvijek slučaj u industriji, rezultati tog proračuna mogu poslužiti kao referenca

Relit-NeuLF: Efficient Relighting and Novel View Synthesis via Neural 4D Light Field

In this paper, we address the problem of simultaneous relighting and novel view synthesis of a complex scene from multi-view images with a limited number of light sources. We propose an analysis-synthesis approach called Relit-NeuLF. Following the recent neural 4D light field network (NeuLF), Relit-NeuLF first leverages a two-plane light field representation to parameterize each ray in a 4D coordinate system, enabling efficient learning and inference. Then, we recover the spatially-varying bidirectional reflectance distribution function (SVBRDF) of a 3D scene in a self-supervised manner. A DecomposeNet learns to map each ray to its SVBRDF components: albedo, normal, and roughness. Based on the decomposed BRDF components and conditioning light directions, a RenderNet learns to synthesize the color of the ray. To self-supervise the SVBRDF decomposition, we encourage the predicted ray color to be close to the physically-based rendering result using the microfacet model. Comprehensive experiments demonstrate that the proposed method is efficient and effective on both synthetic data and real-world human face data, and outperforms the state-of-the-art results. We publicly released our code on GitHub. You can find it here: https://github.com/oppo-us-research/RelitNeuLFComment: 10 page

Loss of Scribble confers cisplatin resistance during NSCLC chemotherapy via Nox2/ROS and Nrf2/PD-L1 signaling

Background: Cisplatin resistance remains a major clinical obstacle to the successful treatment of non-small cell lung cancer (NSCLC). Scribble contributes to ROS-induced inflammation and cisplatin-elevated toxic reactive oxygen species (ROS) promotes cell death. However, it is unknown whether and how Scribble is involved in the cisplatin-related cell death and the underlying mechanism of Scribble in response to chemotherapies and in the process of oxidative stress in NSCLC. Methods: We used two independent cohorts of NSCLC samples derived from patients treated with platinumcontaining chemotherapy and xenograft modeling in vivo. We analyzed the correlation between Scribble and Nox2 or Nrf2/PD-L1 both in vivo and in vitro, and explored the role of Scribble in cisplatin-induced ROS and apoptosis. Findings: Clinical analysis revealed that Scribble expression positively correlatedwith clinical outcomes and chemotherapeutic sensitivity in NSCLC patients. Scribble protected Nox2 protein from proteasomal degradation. Scribble knockdown induced cisplatin resistance by blocking Nox2/ROS and apoptosis in LRR domaindependent manner. In addition, low levels of Scribble correlated with high levels of PD-L1 via activation of Nrf2 transcription in vivo and in vitro. Interpretations: Our study revealed that polarity protein Scribble increased cisplatin-induced ROS generation and is beneficial to chemotherapeutic outcomes in NSCLC. Although Scribble deficiency tends to lead to cisplatin resistance by Nox2/ROS and Nrf2

Diagnostic and Prognostic Performance of MicroRNA-25, Carbohydrate Antigen 19-9, Carcinoembryonic Antigen, and Carbohydrate Antigen 125 in Pancreatic Ductal Adenocarcinoma

Background: Pancreatic cancer is a malignancy with high mortality due to the difficulties in early detection. We investigated and compared the diagnostic and prognostic performance of several blood biomarkers, including microRNA-25 (miR-25), carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and carbohydrate antigen 125 (CA125). Methods: A retrospective study was conducted at the Chinese People’s Liberation Army General Hospital from May 2014 to September 2018. Serum specimens were collected, and miR-25 expression levels were measured using real-time quantitative polymerase chain reaction. Serum CA19-9, CEA, and CA125 levels were measured using enzyme-linked immunosorbent assay (ELISA). Statistical analyses including nonparametric test, receiver operator characteristic (ROC) curves, Kaplan-Meier analysis, and subsequent log-rank test were performed with PRISM 5.0 software. Univariate and multivariate analyses were performed with the R software. P<0.05 was considered statistically significant.Results: A total of 250 individuals were recruited, including 75 with pancreatic ductal adenocarcinoma (PDAC), 75 with benign lesions, and 100 healthy controls. miR-25, CA19-9, CEA, and CA125 exhibited an area under the curve (AUC) of 0.88, 0.91, 0.81, and 0.76 with a sensitivity of 78.7%, 74.7%, 37.3%, and 35.7% and specificity of 91.5%, 97.0%, 98.2%, and 98.3%, respectively. The combination of miR-25 and CA19-9 further increased the sensitivity to 93.3% with a specificity of 88.5%. Stage-dependent sensitivity was observed with CA19-9, CEA, and CA125. miR-25 levels significantly stratified the prognosis by median level (4,989.97 copies/mL). CA19-9, CEA, and CA125 levels significantly stratified the prognosis by median levels. Univariate and subsequent multivariate analyses identified tumor (T) stage, CA19-9, and CA125 as independent risk factors for PDAC prognosis.Conclusion: The combination of miR-25 and CA19-9 significantly enhanced the detection sensitivity of PDAC. T stage, CA19-9, and CA125 levels were independent risk factors for PDAC prognosis