Clinical Outcomes of Endoscopic Submucosal Dissection for Early Esophageal Squamous Cell Neoplasms: A Retrospective Single-Center Study in China

Aims. To retrospectively analyze the clinical outcomes for a large number of endoscopic submucosal dissections (ESDs) in early esophageal squamous cell neoplasms (ESCNs) at the First Affiliated Hospital of Nanjing Medical University. Patients and Methods. From January 2010 to February 2014, 296 patients (mean age 61.4 years, range 31–85 years; 202 men) with 307 early ESCNs (79 intramucosal invasive esophageal squamous cell carcinomas (ESCCs) and 228 high-grade intraepithelial neoplasia (HGIN) cases) were included from a total of 519 consecutive patients who were treated by esophageal ESD at our hospital. The primary end points of the study were rates of en bloc resection and complete resection. Secondary end points were complications, residual and recurrence rates, and mortality during follow-up. Results. The en bloc resection rate and complete resection rate were 93.5% and 78.2%, respectively. Complications included strictures (8.4%), perforations (1.0%), and bleedings (0.7%). Twenty-seven (9.1%) patients experienced residual and 18 (6.1%) patients experienced recurrence during a mean follow-up period of 30 months. Thirteen patients died from causes unrelated to ESCC, and no cancer-related death was observed. Conclusions. Our study showed that ESD is a successful and relatively safe treatment for intramucosal invasive ESCC and HGIN, fulfilling the criteria of lymph node negative tumors. This should encourage clinicians to select ESD performed by experienced operators as a potential or even preferred treatment option for lesions amenable to endoscopic treatment

Solar energy investment, technological innovation and carbon emission reduction: Evidence from China

The aim of this paper is to investigate the impact of solar energy investment on carbon emissions. The STIRPAT model, a non-parametric additive regression model, and the vector autoregression model are built to investigate the comprehensive effect of solar energy investment on China’s carbon emissions. Solar energy investment and other factors related to carbon emissions are examined. The empirical study shows that it will take about 8 years for the solar energy investment to promote carbon emission reductions. The moderation analysis indicates that technological innovation has a moderating effect in the facilitation of carbon emission reduction by solar energy investment. The finding of this study has some meaningful policy implications. In order to achieve the goal of carbon emission reduction, China should keep solar energy investment continuous and steady and improve technological innovation

What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning

Visual instruction tuning is an essential approach to improving the zero-shot generalization capability of Multi-modal Large Language Models (MLLMs). A surge of visual instruction datasets with various focuses and characteristics have been proposed recently, enabling MLLMs to achieve surprising results on evaluation benchmarks. To develop more capable MLLMs, in this paper, we aim to investigate a more fundamental question: ``what makes for good visual instructions?''. By conducting a comprehensive empirical study, we find that instructions focused on complex visual reasoning tasks are particularly effective in improving the performance of MLLMs on evaluation benchmarks. Building upon this finding, we design a systematic approach to automatically creating high-quality complex visual reasoning instructions. Our approach employs a synthesis-complication-reformulation paradigm, leveraging multiple stages to gradually increase the complexity of the instructions while guaranteeing quality. Based on this approach, we create the synthetic visual reasoning instruction dataset consisting of 32K examples, namely ComVint, and fine-tune four MLLMs on it. Experimental results demonstrate that our dataset consistently enhances the performance of all the compared MLLMs, e.g., improving the performance of MiniGPT-4 and BLIP-2 on MME-Cognition by 32.6% and 28.8%, respectively. Our code and data are publicly available at the link: https://github.com/RUCAIBox/ComVint.Comment: Work in progres

Effects of Ti/Mg molar ratio on bi-supported SiO2/MgCl2 (ethoxide type)/TiCl4 catalysts in ethylene homopolymerization and ethylene/1-hexene copolymerization

SiO2/MgCl2 (ethoxide type)/TiCl4 Ziegler-Natta catalysts for use in ethylene polymerization and ethylene/1-hexene copolymerization have been prepared using silica with a supported layer of magnesium ethoxide (Mg(OEt)2) as a catalyst precursor, followed by treating with TiCl4 at different Ti/Mg molar ratios, which showed significant effects on the active centers and pore structures of the catalysts. The formation amount of β-MgCl2 carrier increased to a maximum with increasing the Ti/Mg molar ratio from 1.50 to 2.25, and then decreased with the further increasing of Ti/Mg molar to 2.50. When the Ti/Mg molar ratio reached 2.25, the catalyst showed the best performance of polymerization, which could be attributed to the most active centers, high surface area and loose surface structure, mainly owing to the high conversion of Mg(OEt)2 to β-MgCl2. The polymers obtained showed medium and high molecular weight (Mw) with medium molecular weight distribution (MWD). In contrast to the conventional Mg(OEt)2-based ZN catalysts, the sphericity of particles was easy to control in this bi-supported catalyst. Furthermore, the prepared catalysts exhibited rather high activity, good copolymerization ability and hydrogen response

Introduction of titanium species into fluorine-modified SiO2- supported Cr-V bimetallic catalyst for ethylene polymerization and ethylene/1-hexene copolymerization

Chromium-vanadium (Cr-V) bimetallic catalysts are prepared by the introduction of vanadium into the Phillips catalyst which is one of the most significant industrial ethylene polymerization catalysts for tuning the Phillips catalyst performances and improving polyethylene properties. In the present work, titanium species were introduced into the fluorine-modified chromium-vanadium bimetallic catalysts (Cr-V-F) and the prepared catalysts were systematically explored. The element content results of multi-component catalysts showed that a competitive inhibition interaction existed between chromium and vanadium, whereas chromium was more preferable to attach to the Ti-SiO2 than vanadium. In addition, ethylene homopolymerization and ethylene/1-hexene copolymerization were carried out and examined with different catalysts. The introduction of titanium into fluorine-modified bimetallic catalysts enhanced the molecular weight (MW) and broadened the molecular weight distribution (MWD) of polyethylene. The MW of the titanium- and fluorine-modified bimetallic catalysts (Cr-V-F/Ti) firstly rose up and then dropped down with the increasing of the Al/Cr molar ratio. The Cr-V-F/Ti catalysts showed slightly depressed hydrogen response and incorporation of 1-hexene. The short-chain branch distribution (SCBD) results, which were characterized by TREF/SSA, showed that the introduction of the titanium species increased the SCB content in low MW fractions and decreased the SCB content in the high Mw fractions of ethylene/1-hexene copolymers obtained from (Cr-V-F/3Ti)600 in contrast to that from (Cr-V-F)600

Diagnostic and prognostic role of circRNAs in pancreatic cancer: a meta-analysis

BackgroundCircular RNAs (circRNAs) are types of endogenous noncoding RNAs produced by selective splicing that are expressed highly specifically in various organisms and tissues and have numerous clinical implications in the regulation of cancer development and progression. Since circRNA is resistant to digestion by ribonucleases and has a long half-life, there is increasing evidence that circRNA can be used as an ideal candidate biomarker for the early diagnosis and prognosis of tumors. In this study, we aimed to reveal the diagnostic and prognostic value of circRNA in human pancreatic cancer (PC).MethodsA systematic search for publications from inception to 22 July 2022 was conducted on Embase, PubMed, Web of Science (WOS), and the Cochrane Library databases. Available studies that correlated circRNA expression in tissue or serum with the clinicopathological, diagnostic, and prognostic values of PC patients were enrolled. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were used to evaluate clinical pathological characteristics. Area under the curve (AUC), sensitivity, and specificity were adopted to assess diagnostic value. Hazard ratios (HRs) were utilized to assess disease-free survival (DFS) and overall survival (OS).ResultsThis meta-analysis enrolled 32 eligible studies, including six on diagnosis and 21 on prognosis, which accounted for 2,396 cases from 245 references. For clinical parameters, high expression of carcinogenic circRNA was significantly associated with degree of differentiation (OR = 1.85, 95% CI = 1.47–2.34), TNM stage (OR = 0.46, 95% CI = 0.35–0.62), lymph node metastasis (OR = 0.39, 95% CI = 0.32–0.48), and distant metastasis (OR = 0.26, 95% CI = 0.13–0.51). As for clinical diagnostic utility, circRNA could discriminate patients with pancreatic cancer from controls, with an AUC of 0.86 (95% CI: 0.82–0.88), a relatively high sensitivity of 84%, and a specificity of 80% in tissue. In terms of prognostic significance, carcinogenic circRNA was correlated with poor OS (HR = 2.00, 95% CI: 1.76–2.26) and DFS (HR = 1.96, 95% CI: 1.47–2.62).ConclusionIn summary, this study demonstrated that circRNA may act as a significant diagnostic and prognostic biomarker for pancreatic cancer

TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World

To facilitate the research on intelligent and human-like chatbots with multi-modal context, we introduce a new video-based multi-modal dialogue dataset, called TikTalk. We collect 38K videos from a popular video-sharing platform, along with 367K conversations posted by users beneath them. Users engage in spontaneous conversations based on their multi-modal experiences from watching videos, which helps recreate real-world chitchat context. Compared to previous multi-modal dialogue datasets, the richer context types in TikTalk lead to more diverse conversations, but also increase the difficulty in capturing human interests from intricate multi-modal information to generate personalized responses. Moreover, external knowledge is more frequently evoked in our dataset. These facts reveal new challenges for multi-modal dialogue models. We quantitatively demonstrate the characteristics of TikTalk, propose a video-based multi-modal chitchat task, and evaluate several dialogue baselines. Experimental results indicate that the models incorporating large language models (LLM) can generate more diverse responses, while the model utilizing knowledge graphs to introduce external knowledge performs the best overall. Furthermore, no existing model can solve all the above challenges well. There is still a large room for future improvements, even for LLM with visual extensions. Our dataset is available at \url{https://ruc-aimind.github.io/projects/TikTalk/}.Comment: Accepted to ACM Multimedia 202

Multimodal Predictions of Super-Refractory Status Epilepticus and Outcome in Status Epilepticus Due to Acute Encephalitis

Objective: Status epilepticus (SE) is one of the most critical symptoms of encephalitis. Studies on early predictions of progression to super-refractory status epilepticus (SRSE) and poor outcome in SE due to acute encephalitis are scarce. We aimed to investigate the values of neuroimaging and continuous electroencephalogram (EEG) in the multimodal prediction.Methods: Consecutive patients with convulsive SE due to acute encephalitis were included in this study. Demographics, clinical features, neuro-imaging characteristics, medical interventions, and anti-epileptic treatment responses were collected. All the patients had EEG monitoring for at least 24 h. We determined the early predictors of SRSE and prognostic factors of 3-month outcome using multivariate logistic regression analyses.Results: From March 2008 to February 2018, 570 patients with acute encephalitis were admitted to neurological intensive care unit (N-ICU) of Xijing hospital. Among them, a total of 94 patients with SE were included in this study. The percentage of non-SRSE and SRSE were 76.6 and 23.4%. Cortical or hippocampal abnormality on neuroimaging (p = 0.002, OR 20.55, 95% CI 3.16–133.46) and END-IT score (p < 0.001, OR 4.07, 95% CI 1.91–8.67) were independent predictors of the progression to SRSE. At 3 months after N-ICU discharge, 56 (59.6%) patients attained good outcomes, and 38 (40.4%) patients had poor outcomes. The recurrence of clinical or EEG seizures within 2 h after the infusion rate of a single anesthetic drug >50% proposed maximal dose (p = 0.044, OR 4.52, 95% CI 1.04–19.68), tracheal intubation (p = 0.011, OR 4.99, 95% CI 1.37–11.69) and emergency resuscitation (p = 0.040, OR 9.80, 95% 1.11–86.47) predicted poor functional outcome.Interpretation: Initial neuro-imaging findings assist early identification of the progression to SRSE. Continuous EEG monitoring contributes to outcome prediction in SE due to acute encephalitis