The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2 emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2 emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2 emissions decrease

The Effects of the Tractor and Semitrailer Routing Problem on Mitigation of Carbon Dioxide Emissions

The incorporation of CO2 emissions minimization in the vehicle routing problem (VRP) is of critical importance to enterprise practice. Focusing on the tractor and semitrailer routing problem with full truckloads between any two terminals of the network, this paper proposes a mathematical programming model with the objective of minimizing CO2 emissions per ton-kilometer. A simulated annealing (SA) algorithm is given to solve practical-scale problems. To evaluate the performance of the proposed algorithm, a lower bound is developed. Computational experiments on various problems generated randomly and a realistic instance are conducted. The results show that the proposed methods are effective and the algorithm can provide reasonable solutions within an acceptable computational time

A minireview on lipid metabolism and lipid-associated nutritional interventions in childhood cancers

Cancer is a leading cause of mortality in children and results in a significant disease burden. Lipid metabolic reprogramming emerges as a pivotal cancer hallmark, bearing profound implications for understanding tumorigenesis, developing treatment strategies, and improving prognoses. However, research on lipid metabolism and lipid nutritional interventions related to childhood cancers is notably limited compared to adult cancers. This review focused on the current understanding of fatty acid, cholesterol, and phospholipid metabolism in childhood cancers and discussed the correlation between major lipid dietary patterns (such as high-fat, ketogenic, and Mediterranean diets) and the development and progression of childhood cancers. This review also highlighted existing research gaps on the mechanisms of lipid metabolism and the effects of major lipid dietary patterns, and warranted improved research depth, experimental design, and sample size. Therefore, we advocate for future epidemiological, basic science, and multidisciplinary research in the field of childhood cancers to understand more comprehensively and profoundly the role of lipid nutrition in the prevention and treatment of pediatric cancers

A preoperative predictive model based on multi-modal features to predict pathological complete response after neoadjuvant chemoimmunotherapy in esophageal cancer patients

BackgroundThis study aimed to develop a multi-modality model by incorporating pretreatment computed tomography (CT) radiomics and pathomics features along with clinical variables to predict pathologic complete response (pCR) to neoadjuvant chemoimmunotherapy in patients with locally advanced esophageal cancer (EC).MethodA total of 223 EC patients who underwent neoadjuvant chemoimmunotherapy followed by surgical intervention between August 2021 and December 2023 were included in this study. Radiomics features were extracted from contrast-enhanced CT images using PyrRadiomics, while pathomics features were derived from whole-slide images (WSIs) of pathological specimens using a fine-tuned deep learning model (ResNet-50). After feature selection, three single-modality prediction models and a combined multi-modality model integrating two radiomics features, 11 pathomics features, and two clinicopathological features were constructed using the support vector machine (SVM) algorithm. The performance of the models were evaluated using receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA). Shapley values were also utilized to explain the prediction model.ResultsThe predictive capability of the multi-modality model in predicting pCR yielded an area under the curve (AUC) of 0.89 (95% confidence interval [CI], 0.75-1.00), outperforming the radiomics model (AUC 0.70 [95% CI 0.54-0.85]), pathomics model (AUC 0.77 [95% CI 0.53-1.00]), and clinical model (AUC 0.63 [95% CI 0.46-0.80]). Additionally, both the calibration plot and DCA curves support the clinical utility of the integrated multi-modality model.ConclusionsThe combined multi-modality model we propose can better predict the pCR status of esophageal cancer and help inform clinical treatment decisions

Towards a Client-Centered Assessment of LLM Therapists by Client Simulation

Although there is a growing belief that LLMs can be used as therapists, exploring LLMs\u27 capabilities and inefficacy, particularly from the client\u27s perspective, is limited. This work focuses on a client-centered assessment of LLM therapists with the involvement of simulated clients, a standard approach in clinical medical education. However, there are two challenges when applying the approach to assess LLM therapists at scale. Ethically, asking humans to frequently mimic clients and exposing them to potentially harmful LLM outputs can be risky and unsafe. Technically, it can be difficult to consistently compare the performances of different LLM therapists interacting with the same client. To this end, we adopt LLMs to simulate clients and propose ClientCAST, a client-centered approach to assessing LLM therapists by client simulation. Specifically, the simulated client is utilized to interact with LLM therapists and complete questionnaires related to the interaction. Based on the questionnaire results, we assess LLM therapists from three client-centered aspects: session outcome, therapeutic alliance, and self-reported feelings. We conduct experiments to examine the reliability of ClientCAST and use it to evaluate LLMs therapists implemented by Claude-3, GPT-3.5, LLaMA3-70B, and Mixtral 8*7B. Codes are released at https://github.com/wangjs9/ClientCAST

A comparative pharmacological study of three Chinese traditional medicines found Blautia to be the key functional bacterium of Coptis chinensis Franch. and Phellodendri chinensis Cortex against colitis

BackgroundSanhuang refers to the three cold-natured and bitter-flavored traditional Chinese medicines, namely, Scutellaria baicalensis Georgi (HuangQin, HQ), Coptis chinensis Franch. (HuangLian, HL), and Phellodendri chinensis Cortex (HuangBo, HB). Although similar in drug properties, they are traditionally used to treat different dampness-heat syndromes belonging to the Upper Jiao (lung and heart diseases), the Middle Jiao (stomach and intestine diseases), and the Lower Jiao (intestine, kidney, and bladder diseases). The mechanisms behind their differential effects remain unexplored.MethodA model of large intestine dampness-heat syndrome colitis was established through the administration of exogenous hygrothermal conditions combined with lipopolysaccharide (LPS) and Escherichia coli. This model was employed to evaluate the efficacy of Phellodendri Chinensis Cortex, C. chinensis Franch., and S. baicalensis Georgi. Full-length 16S rRNA amplicon sequencing was utilized to assess changes in gut microbiota following drug interventions. Ultimately, the therapeutic effects of key microbial strains on ulcerative colitis were confirmed using a dextran sulfate sodium (DSS)-induced colitis model.ResultsThe results showed that HL and HB exhibited significant remedial effects on large intestine dampness-heat syndrome (LIDHS) colitis, but HQ did not. Gut microbial analysis revealed that HL and HB markedly shifted the overall structure of gut microbiota, while HQ showed little impact. The increase of Blautia sp. was a common sign in both HL- and HB-treated animals, but it was not observed in the HQ group. On the contrary, the abundance of a Lactobacillus-dominant co-abundance gene group (CAG) significantly declined in the HL and HB groups but was similar to the negative control in the HQ group. Additionally, our observations indicate that the enrichment of Blautia is consistent with the difference in drug efficacy. In vivo experiments also demonstrated the anti-colitis efficacy of Blautia producta.ConclusionThis study identifies Blautia as the key bacterium against ulcerative colitis through the establishment of a novel model and a drug comparison

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

Background: The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. // Results: Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic. // Conclusions: Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead