Bimodal transit design with heterogeneous demand elasticity under different fare structures

The study develops a new optimisation model to design a bimodal transit system from a microeconomic view to maximise the profit of a transit agency considering heterogeneous demand elasticity and different fare structures. Bimodal transit network parameters are optimized to better serve passenger demand. An elastic demand function is devised to include various time components and incorporate flat, distance-based, and hybrid fares. A nested iterative procedure is developed to find a near-optimal solution. Numerical experiments reveal the following interesting findings. First, the increase in elasticity parameters has a knock-on effect on the financial performance, consequently leading to a net profit reduction. Second, a distance-based fare scheme brings in the least actual demand but makes the most profit, compared with the flat and hybrid fare schemes. Third, passengers prefer using a rail-bus system to a BRT-bus system, especially at a higher demand level

Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions

Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education. This study evaluated the capabilities of leading LLMs, including GPT-4, GPT-3.5, PaLM2, Claude2, and SenseNova, in answering conceptual biology questions. The models were tested on a 108-question multiple-choice exam covering biology topics in molecular biology, biological techniques, metabolic engineering, and synthetic biology. Among the models, GPT-4 achieved the highest average score of 90 and demonstrated the greatest consistency across trials with different prompts. The results indicated GPT-4's proficiency in logical reasoning and its potential to aid biology research through capabilities like data analysis, hypothesis generation, and knowledge integration. However, further development and validation are still required before the promise of LLMs in accelerating biological discovery can be realized

Orsay virus CP-δ adopts a novel β-bracelet structural fold and incorporates into virions as a head fiber

Fiber proteins are commonly found in eukaryotic and prokaryotic viruses, where they play important roles in mediating viral attachment and host cell entry. They typically form trimeric structures and are incorporated into virions via noncovalent interactions. Orsay virus, a small RNA virus which specifically infects the laboratory model nematod

An in vitro vesicle formation assay reveals cargo clients and factors that mediate vesicular trafficking

The fidelity of protein transport in the secretory pathway relies on the accurate sorting of proteins to their correct destinations. To deepen our understanding of the underlying molecular mechanisms, it is important to develop a robust approach to systematically reveal cargo proteins that depend on specific sorting machinery to be enriched into transport vesicles. Here, we used an in vitro assay that reconstitutes packaging of human cargo proteins into vesicles to quantify cargo capture. Quantitative mass spectrometry (MS) analyses of the isolated vesicles revealed cytosolic proteins that are associated with vesicle membranes in a GTP-dependent manner. We found that two of them, FAM84B (also known as LRAT domain containing 2 or LRATD2) and PRRC1, contain proline-rich domains and regulate anterograde trafficking. Further analyses revealed that PRRC1 is recruited to endoplasmic reticulum (ER) exit sites, interacts with the inner COPII coat, and its absence increases membrane association of COPII. In addition, we uncovered cargo proteins that depend on GTP hydrolysis to be captured into vesicles. Comparing control cells with cells depleted of the cargo receptors, SURF4 or ERGIC53, we revealed specific clients of each of these two export adaptors. Our results indicate that the vesicle formation assay in combination with quantitative MS analysis is a robust and powerful tool to uncover novel factors that mediate vesicular trafficking and to uncover cargo clients of specific cellular factors.</p

Enhanced transcriptomic resilience following increased alternative splicing and differential isoform production between air pollution conurbations

Adversehealth outcomes caused by ambient particulate matter (PM) pollution occur in a 16progressive process, with neutrophils eliciting inflammation or pathogenesis. We investigated the 17toxico-transcriptomic mechanisms of PM in real-life settings by comparing healthy residents living 18in Beijing and Chengde, the opposing ends of a well-recognised air pollution (AP) corridor in China. 19Beijing recruits (BRs) uniquelyexpressed ~12,000 alternativesplicing (AS)-derived transcripts, 20largely elevating the proportion of transcripts significantly correlated with PM concentration. BRs 21expressed PM-associated isoforms (PMAIs) of PFKFB3and LDHA,encoding enzymes responsible 22for stimulatingand maintaining glycolysis. PMAIsof PFKFB3featured different COOH-terminals, 23targeting PFKFB3 to different sub-cellular functional compartments and stimulating glycolysis. 24PMAIs of LDHAhavelonger 3’UTRs relative to those expressed in Chengderecruits (CRs),allowing 25glycolysis maintenance by enhancing LDHAmRNA stability and translational efficiency. PMAIs 26weredirectly regulated by different HIF-1Aand HIF-1Bisoforms. BRs expressed more non-func-27tional Fasisoforms and a resultant reduction of intact Fasproportion is expectedto inhibit the trans-28mission of apoptotic signals and prolong neutrophil lifespan. BRs expressed both membrane-bound 29and soluble IL-6Risoforms insteadof only one in CRs. The presence of both IL-6Risoforms sug-30gested a higher migration capacity of neutrophils in BRs. PMAIs of HIF-1Aand PFKFB3were down-31regulated inChronic Obstructive Pulmonary Disease patients compared with BRs, implying HIF-1 32mediated defective glycolysis may mediate neutrophil dysfunction. PMAIs could explain large var-33iances of different phenotypes, highlighting their potential application as biomarkers and therapeu-34tic targets in PM-induced diseases, which remain poorly elucidated