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Objective To establish a nomogram risk predictive model by analyzing the risk factors for postoperative pulmonary complications (PPCs) after total gastrectomy for upper gastric cancer. Methods A retrospective analysis was performed for the clinical data of 197 patients who underwent total gastrectomy for upper gastric cancer in our hospital from June 1, 2020 to September 30, 2021. Univariate and multivariate Logistic regression analyses were used to investigate the risk factors for PPCs, and a nomogram predictive model for PPCs was established. Index of concordance, the receiver operating characteristic (ROC) curve, and the calibration curve were used to evaluate the performance of the predictive model, and the DCA curve was used to evaluate the clinical benefit of the model. Results Among the 197 patients included in the analysis, 71 experienced PPCs, with an incidence rate of 36%.The multivariate Logistic regression analysis showed that age, diabetes mellitus, smoking history, preoperative serum albumin 26 kg/m2 were independent risk factors for PPCs after total gastrectomy for upper gastric cancer. The nomogram prediction model established had an area under the ROC curve of 0.806, suggesting that the model had good prediction performance. The calibration curve showed that the predictive model showed good consistency with the actual incidence rate of complications, and the DCA curve showed obvious positive net benefits, indicating that the predictive model had good clinical benefits. Conclusion The nomogram prediction model established based on independent risk factors has good prediction performance and can provide a basis for predicting PPCs in patients undergoing total gastrectomy for upper gastric cancer.

Photonics inverse design relies on human experts to search for a design topology that satisfies certain optical specifications with their experience and intuitions, which is relatively labor-intensive, slow, and sub-optimal. Machine learning has emerged as a powerful tool to automate this inverse design process. However, supervised or semi-supervised deep learning is unsuitable for this task due to: (1) a severe shortage of available training data due to the high computational complexity of physics-based simulations along with a lack of open-source datasets and/or the need for a pre-trained neural network model; (2) the issue of one-to-many mapping or non-unique solutions; and (3) the inability to perform optimization of the photonic structure beyond inverse designing. Reinforcement Learning (RL) has the potential to overcome the above three challenges. Here, we propose Learning to Design Optical-Resonators (L2DO) to leverage RL that learns to autonomously inverse design nanophotonic laser cavities without any prior knowledge while retrieving unique design solutions. L2DO incorporates two different algorithms – Deep Q-learning and Proximal Policy Optimization. We evaluate L2DO on two laser cavities: a long photonic crystal (PC) nanobeam and a PC nanobeam with an L3 cavity, both popular structures for semiconductor lasers. Trained for less than 152 hours on limited hardware resources, L2DO has improved state-of-the-art results in the literature by over 2 orders of magnitude and obtained 10 times better performance than a human expert working the same task for over a month. L2DO first learned to meet the required maxima of Q-factors (>50 million) and then proceeded to optimize some additional good-to-have features (e.g., resonance frequency, modal volume). Compared with iterative human designs and inverse design via supervised learning, L2DO can achieve over two orders of magnitude higher sample-efficiency without suffering from the three issues above. This work confirms the potential of deep RL algorithms to surpass human designs and marks a solid step towards a fully automated AI framework for photonics inverse design.

Sodium taurocholate co-transporting polypeptide (NTCP) has been identified as an entry receptor for hepatitis B virus (HBV), but the molecular events of the viral post-endocytosis steps remain obscure. In this study, we discovered that manganese (Mn) could strongly inhibit HBV infection in NTCP-reconstituted HepG2 cells without affecting viral replication. We therefore profiled the antiviral effects of Mn2+ in an attempt to elucidate the regulatory mechanisms involved in early HBV infection. Intriguingly, Mn2+ conspicuously stimulated lysosomal activity, as evidenced by hyperactivation of mTORC1 and increased endo/lysosomal acidity. After HBV-triggered internalization, the NTCP receptor was sorted to late endosomal compartments by the ESCRT machinery in concert with the invading virion. The establishment of HBV infection was found to be independent of lysosomal fusion-driven late endosome maturation; Mn2+-induced lysosomal hyperfunction virtually impaired infection, suggesting that virions may gain cytosolic access directly from late endosomes. In contrast, suppression of lysosomal activity substantially enhanced HBV infection. Prolonged mTORC1 inactivation facilitated viral infection by depleting lysosomes and accelerating endocytic transport of virions. Notably, treatment with the natural steroidal alkaloid tomatidine recapitulated the effects of Mn2+ in stimulating lysosomal activity and exhibited potent anti-HBV activity in HepG2-NTCP cells and in proliferating human hepatocyte organoids. These findings provide new insights into the post-endocytosis events of HBV infection. The negative regulation of early HBV infection by endo/lysosomal activity makes it a promising target for antiviral therapies. Author summary: Despite the identification of NTCP as a functional HBV receptor over a decade ago, the later stages of the HBV entry process remain poorly understood. Inspired by a previous publication, we tested the possible effect of manganese (Mn) on HBV infectivity. To our surprise, although Mn2+ did not induce a type I interferon response, it was still able to inhibit HBV infectivity in HepG2-NTCP cells. Using loss-of-function assays with pharmacological inhibitors and RNA interference, we found that after internalization, HBV and the NTCP receptor are co-sorted via the ESCRT machinery into the late endosome, where the virions achieve endosomal escape. Notably, endosome-lysosome fusion is not required for HBV infection. In contrast, lysosomal hyperfunction, induced by Mn2+ or the natural steroidal alkaloid tomatidine, impairs de novo HBV infection, while the use of lysosomal inhibitors facilitates this process. The suppressive impact of lysosomal activity on the early HBV infection renders it a promising target for antiviral therapies. [ABSTRACT FROM AUTHOR]

Background: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable for longitude assessment during anti‐tumor therapy. Purpose: This work aims to develop and validate a noninvasive workflow based on contrast‐enhanced CT (CECT) images to evaluate the CD8+ T‐cell infiltration profiles of GC. Methods: GC patients were retrospectively and consecutively enrolled and randomly assigned to the training (validation) or test cohort at a 7:3 ratio. All patients were binary classified into the CD8‐high (infiltrated proportion ≥ 20%) or CD8‐low group (infiltrated proportion < 20%) group. A total of 1170 radiomics features were extracted from each presurgical CECT series. After feature selection, fifteen radiomics features were transmitted to three independent machine‐learning models for the computation of predictive radiological scores. Multilayer perceptron (MLP) was applied to merge the radiological scores with clinical factors. The predictive efficacy of the radiological scores and of the combined model was evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis in both the training and test cohorts. Results: A total of 210 patients were enrolled in this study (mean age: 63.22 ± 8.74 years, 151 men), and were randomly assigned to the training set (n = 147) or the test set (n = 63). The merged radiological score was correlated with CD8 infiltration in both the training (p = 1.8e−10) and test cohorts (p = 0.00026). The combined model integrating the radiological scores and clinical features achieved an area under the curve (AUC) value of 0.916 (95% CI: 0.872–0.960) in the training set and 0.844 (95% CI: 0.742–0.946) in the test set for classifying CD8‐high GCs. The model was well‐calibrated and exhibited net benefit over "treat‐all" and"treat‐none" strategies in decision curve analysis. Conclusions: Artificial intelligent systems combining radiological features and clinical factors could accurately predict CD8 infiltration levels of GC, which may benefit personalized treatment of GC in the context of immunotherapy. [ABSTRACT FROM AUTHOR]

A prevailing animal model currently used to study severe human diseases like obstructive cholestasis, primary biliary or sclerosing cholangitis, biliary atresia, and acute liver injury is the common bile duct ligation (cBDL). Modifications of this model include ligation of the left hepatic bile duct (pBDL) or ligation of the left bile duct with the corresponding left hepatic artery (pBDL+pAL). Both modifications induce cholestasis only in the left liver lobe. After induction of total or partial cholestasis in mice, the well-being of these animals was evaluated by assessing burrowing behavior, body weight, and a distress score. To compare the pathological features of these animal models, plasma levels of liver enzymes, bile acids, bilirubin, and within the liver tissue, necrosis, fibrosis, inflammation, as well as expression of genes involved in the synthesis or transport of bile acids were assessed. The survival rate of the animals and their well-being was comparable between pBDL+pAL and pBDL. However, surgical intervention by pBDL+pAL caused confluent necrosis and collagen depositions at the edge of necrotic tissue, whereas pBDL caused focal necrosis and fibrosis in between portal areas. Interestingly, pBDL animals had a higher survival rate and their well-being was significantly improved compared to cBDL animals. On day 14 after cBDL liver aspartate, as well as alanine aminotransferase, alkaline phosphatase, glutamate dehydrogenase, bile acids, and bilirubin were significantly elevated, but only glutamate dehydrogenase activity was increased after pBDL. Thus, pBDL may be primarily used to evaluate local features such as inflammation and fibrosis or regulation of genes involved in bile acid synthesis or transport but does not allow to study all systemic features of cholestasis. The pBDL model also has the advantage that fewer mice are needed, because of its high survival rate, and that the well-being of the animals is improved compared to the cBDL animal model. [ABSTRACT FROM AUTHOR]

This paper attempts to investigate the effect of various parameters on the axial compressive behavior of nano-silica concrete-filled angle steel reinforced GFRP tubular columns. The proposed new composite column consists of three parts: the outer GFRP tube, the inner angle section steel and the nano-silica concrete filled between GFRP tube and angle section steel. Twenty-seven specimens with different nano-silica concrete compressive strength (20MPa, 30MPa and 40MPa), diameter-to-thickness ratio of GFRP tube (20, 25 and 40) and steel ratio (0.008, 0.022 and 0.034) were tested under axial load. The main purpose of this study is to examine the effect of the three parameters on the following: failure modes, deformation capacity, load bearing capacity, ductility and initial stiffness of the new composite column under axial load. It was found that the load bearing capacity and initial stiffness increased as the nano-silica concrete compressive strength of the specimens increased. But the specimens with higher nano-silica concrete compressive strength showed lower deformation capacity than that of the specimens with lower nano-silica concrete compressive strength. The varieties of the steel ratio have no significant effect on the specimens’ axial deformation behavior. Experimental results also showed that both load bearing capacity and deformation capacity increased with the decrease of diameter-to-thickness ratio of GFRP tube. However, diameter-to-thickness ratio of GFRP tube has no significant effect on the initial stiffness of specimens. The confinement coefficient was proposed to better evaluate the confinement effect of GFRP tube on the inner angle section steel reinforced core nano-silica concrete. The confinement effect of GFRP tube on lower strength concrete was better, and the confinement effect reduced as the diameter-to-thickness ratio of GFRP tube increased. The design formulas for the load bearing capacity of the nano-silica concrete-filled angle steel reinforced GFRP tubular columns under axial load were proposed.

In purely organic room‐temperature phosphorescence (RTP) materials, fluorescence radiative transitions generally compete against inter‐system crossing (ISC) transitions to give fluorescence/phosphorescence dual emission. In order to achieve pure phosphorescence in RTP organic light‐emitting diodes (OLEDs), extended π‐conjugation is introduced into Se‐containing donors to suppress the fluorescence radiative transitions by the symmetry excited state orbitals in the introduced π–π* transitions that cancel the overlap of the orbitals, and two novel nonaromatic amine donor containing orange RTP emitters namely 2‐(benzo[c]phenoxaselenin‐10‐yl)‐4,6‐diphenyl‐1,3,5‐triazine (BPXSeDRZ) and 2‐(dibenzo[a,c]phenoxaselenin‐11‐yl)‐4,6‐diphenyl‐1,3,5‐triazine (DBPXSeDRZ) are developed, both of which exhibit efficient orange pure phosphorescence in doped films thanks to the sufficient ISC transitions. As a result, high external quantum efficiencies of 17.2% and 17.9% are respectively achieved for the orange RTP‐OLEDs based on BPXSeDRZ and DBPXSeDRZ for the first time, and they also exhibit stable pure electro‐phosphorescence spectra in a wide driving voltage. Moreover, by adopting DBPXSeDRZ as a sensitizer to harvest the triplet excitons and tetraphenyldibenzoperiflanthene as a conventional fluorescent emitter, the external quantum efficiency of the sensitized red fluorescent OLED can be elevated to 10.1%, which greatly expands the potential applications of the metal‐free phosphors in OLEDs. [ABSTRACT FROM AUTHOR]