Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer

Background We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature. Methods This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score. Results We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990–1.000] and 0.822 [95% CI 0.649–0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did. Conclusions The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5

Research on environmental impacts of tourism in China: progress and prospect

With the rapid development of tourism industry in China since 1980, the country has experienced an increasing use of its natural and cultural environment for tourism, resulting in tourism resources being adversely impacted in many tourism destinations. This paper described the research progress in tourism impacts on the environment in the context of China through a review of the growing literature in this field. Specifically, research on tourism impacts on the biophysical and socio-cultural environments, tourism carrying capacity, environmental quality assessment, and measures for the protection and management of tourism resources was reviewed. The review found that the majority of research was qualitative and descriptive in nature, and there was a lack of case studies and theoretical development. Future research should focus on the evaluation of environmental impacts, particularly those gradual cumulative impacts on the tourism environment; examination of the quantitative relationship between the impact and the level of tourism use for different activities; development of methods to estimate the carrying capacity; and understanding of positive impacts of tourism

Development and evaluation of a data-driven integrated management app for perioperative adverse events: protocol for a mixed-design study

Introduction A patient record review study conducted in 2006 in a random sample of 21 Dutch hospitals found that 51%–77% of adverse events are related to perioperative care, while Centers for Disease Control and Prevention data in USA in 2013 estimated that the medical error is the third-leading cause of mortality. To capitalise on the potential of apps to enhance perioperative medical quality, there is a need for interventions developed in consultation with real-world users designed to support integrated management for perioperative adverse events (PAEs). This study aims: (1) to access the knowledge, attitude and practices for PAEs among physicians, nurses and administrators, and to identify the needs of healthcare providers for a mobile-based PAEs tool; (2) to develop a data-driven app for integrated PAE management that meets those needs and (3) to test the usability, clinical efficacy and cost-effectiveness of the developed app.Methods and analysis We will adopt an embedded mixed-methods research technique; qualitative data will be used to assess user needs and app adoption, while quantitative data will provide crucial insights to establish the demand for the app, and measure the app effects. Phase 1 will enrol surgery-related healthcare providers from the West China Hospital and identify their latent demand for mobile-based PAEs management using a self-designed questionnaire underpinned by the knowledge, attitude and practice model, as well as expert interviews. In phase 2, we will develop the app for integrated PAE management and test its effectiveness and sustainability. In phase 3, the effects on the total number and severity of reported PAEs will be evaluated using Poisson regression with interrupted time-series analysis over a 2-year period, while users’ engagement, adherence, process evaluation and cost-effectiveness will be evaluated using quarterly surveys and interviews.Ethics and dissemination The West China Hospital of Sichuan University’s Institutional Review Board authorised this study after approving the study protocol, permission forms and questionnaires (number: 2022-1364). Participants will be provided with study information, and informed written consent will be obtained. Study findings will be disseminated through peer-reviewed publications and conference presentations

Spatial–temporal variation of extreme precipitation in the Yellow–Huai–Hai–Yangtze Basin of China

Abstract Climate warming leads to frequent extreme precipitation events, which is a prominent manifestation of the variation of the global water cycle. In this study, data from 1842 meteorological stations in the Huang–Huai–Hai–Yangtze River Basin and 7 climate models of CMIP6 were used to obtain the historical and future precipitation data using the Anusplin interpolation, BMA method, and a non-stationary deviation correction technique. The temporal and spatial variations of extreme precipitation in the four basins were analysed from 1960 to 2100. The correlation between extreme precipitation indices and their relationship with geographical factors was also analysed. The result of the study indicates that: (1) in the historical period, CDD and R99pTOT showed an upward trend, with growth rates of 14.14% and 4.78%, respectively. PRCPTOT showed a downward trend, with a decreasing rate of 9.72%. Other indices showed minimal change. (2) Based on SSP1-2.6, the intensity, frequency, and duration of extreme precipitation changed by approximately 5% at SSP3-7.0 and 10% at SSP5-8.5. The sensitivity to climate change was found to be highest in spring and autumn. The drought risk decreased, while the flood risk increased in spring. The drought risk increased in autumn and winter, and the flood risk increased in the alpine climate area of the plateau in summer. (3) Extreme precipitation index is significantly correlated with PRCPTOT in the future period. Different atmospheric circulation factors significantly affected different extreme precipitation indices of FMB. (4) CDD, CWD, R95pD, R99pD, and PRCPTOT are affected by latitude. On the other hand, RX1day and RX5day are affected by longitude. The extreme precipitation index is significantly correlated with geographical factors, and areas above 3000 m above sea level are more sensitive to climate change

Genetic Variants of lncRNA GAS5 Contribute to Susceptibility of Ischemic Stroke among Southern Chinese Population

Emerging evidence suggests that the long noncoding RNA (lncRNA) growth arrest special 5 (GAS5) plays crucial roles in the pathogenesis of ischemic stroke (IS). The current research is aimed at assessing the correlation between two functional GAS5 variants (rs145204276 and rs55829688) and susceptibility to IS in a Han Chinese population. This study genotyped the two GAS5 variants in 1086 IS patients as well as 1045 age-matched healthy controls by using an improved multitemperature ligase detection reaction (iMLDR-TM) genotyping technology. We observed a considerable change in the frequencies of the rs145204276 allele and genotype among the IS patients and healthy control group. The del-T haplotype was substantially more prevalent in the IS cases compared to the control individuals. When study participants were stratified according to environmental factors, we found that the rs145204276 del allele was correlated with a higher risk of IS in male, smokers, hypertensive, and those ≥65 years old. Additional stratification conforming to IS subtypes exhibited that individuals carrying the rs145204276 del allele conferred a higher risk of expanding a larger artery atherosclerosis stroke subset. Moreover, there was a significant association between the rs145204276 del allele and elevated expression of GAS5 in IS patients. In contrast, the frequency of the allele related to rs55829688 was not statistically correlated with IS in all analysis. Our study supports a model wherein the rs145204276 variant in the GAS5 lncRNA is associated with IS risk, thus representing a potentially viable biomarker for IS prevention and treatment

Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer

Abstract Background We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature. Methods This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score. Results We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990–1.000] and 0.822 [95% CI 0.649–0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did. Conclusions The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making

Flaxseed Oil Alleviates Chronic HFD-Induced Insulin Resistance through Remodeling Lipid Homeostasis in Obese Adipose Tissue

Emerging evidence suggests that higher circulating long-chain n-3 polyunsaturated fatty acids (n-3PUFA) levels were intimately associated with lower prevalence of obesity and insulin resistance. However, the understanding of bioactivity and potential mechanism of α-linolenic acid-rich flaxseed oil (ALA-FO) against insulin resistance was still limited. This study evaluated the effect of FO on high-fat diet (HFD)-induced insulin resistance in C57BL/6J mice focused on adipose tissue lipolysis. Mice after HFD feeding for 16 weeks (60% fat-derived calories) exhibited systemic insulin resistance, which was greatly attenuated by medium dose of FO (M-FO), paralleling with differential accumulation of ALA and its n-3 derivatives across serum lipid fractions. Moreover, M-FO was sufficient to effectively block the metabolic activation of adipose tissue macrophages (ATMs), thereby improving adipose tissue insulin signaling. Importantly, suppression of hypoxia-inducible factors HIF-1α and HIF-2α were involved in FO-mediated modulation of adipose tissue lipolysis, accompanied by specific reconstitution of n-3PUFA within adipose tissue lipid fractions