Assessing and Optimizing Large Language Models on Spondyloarthritis Multi-Choice Question Answering: Protocol for Enhancement and Assessment.

Background: Spondyloarthritis (SpA), a chronic inflammatory disorder, predominantly impacts the sacroiliac joints and spine, significantly escalating the risk of disability. SpA's complexity, as evidenced by its diverse clinical presentations and symptoms that often mimic other diseases, presents substantial challenges in its accurate diagnosis and differentiation. This complexity becomes even more pronounced in nonspecialist health care environments due to limited resources, resulting in delayed referrals, increased misdiagnosis rates, and exacerbated disability outcomes for patients with SpA.

CEG 2.0: an updated database of clusters of essential genes including eukaryotic organisms.

Essential genes are key elements for organisms to maintain their living. Building databases that store essential genes in the form of homologous clusters, rather than storing them as a singleton, can provide more enlightening information such as the general essentiality of homologous genes in multiple organisms. In 2013, the first database to store prokaryotic essential genes in clusters, CEG (Clusters of Essential Genes), was constructed.

Various approaches of laparoscopic common bile duct exploration plus primary duct closure for choledocholithiasis: A systematic review and meta-analysis.

Background: Common bile duct (CBD) stones may occur in up to 3%-14.7% of all patients with cholecystectomy. Various approaches of laparoscopic CBD exploration plus primary duct closure (PDC) are the most commonly used and the best methods to treat CBD stone.

Identification and analysis of genomic islands in Burkholderia cenocepacia AU 1054 with emphasis on pathogenicity islands.

Background: Genomic islands (GIs) are genomic regions that reveal evidence of horizontal DNA transfer. They can code for many functions and may augment a bacterium's adaptation to its host or environment. GIs have been identified in strain J2315 of Burkholderia cenocepacia, whereas in strain AU 1054 there has been no published works on such regions according to our text mining and keyword search in Medline.

Identifying Bacterial Essential Genes Based on a Feature-Integrated Method.

Essential genes are those genes of an organism that are considered to be crucial for its survival. Identification of essential genes is therefore of great significance to advance our understanding of the principles of cellular life. We have developed a novel computational method, which can effectively predict bacterial essential genes by extracting and integrating homologous features, protein domain feature, gene intrinsic features, and network topological features.

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes.

Combining pseudo dinucleotide composition with the Z curve method to improve the accuracy of predicting DNA elements: a case study in recombination spots.

Pseudo dinucleotide composition (PseDNC) and Z curve showed excellent performance in the classification issues of nucleotide sequences in bioinformatics. Inspired by the principle of Z curve theory, we improved PseDNC to give the phase-specific PseDNC (psPseDNC). In this study, we used the prediction of recombination spots as a case to illustrate the capability of psPseDNC and also PseDNC fused with Z curve theory based on a novel machine learning method named large margin distribution machine (LDM).

Multiple Factors Drive Replicating Strand Composition Bias in Bacterial Genomes.

Composition bias from Chargaff's second parity rule (PR2) has long been found in sequenced genomes, and is believed to relate strongly with the replication process in microbial genomes. However, some disagreement on the underlying reason for strand composition bias remains. We performed an integrative analysis of various genomic features that might influence composition bias using a large-scale dataset of 1111 genomes.

Enzymatic liquefaction and saccharification of pretreated corn stover at high-solids concentrations in a horizontal rotating bioreactor.

A self-designed horizontal rotating bioreactor (HRR) was applied for enzymatic hydrolysis of pretreated corn stover to improve the process economics of ethanol production. The mixing principle was based on gravity and free fall employed with tank-rotating. The liquefaction performances using the HRR and the vertical stirred-tank reactor (VSTR) with a helical impeller were compared and analyzed by measuring rheological properties of the slurry.