Evaluating Large Language Models on Controlled Generation Tasks

While recent studies have looked into the abilities of large language models in various benchmark tasks, including question generation, reading comprehension, multilingual and etc, there have been few studies looking into the controllability of large language models on generation tasks. We present an extensive analysis of various benchmarks including a sentence planning benchmark with different granularities. After comparing large language models against state-of-the-start finetuned smaller models, we present a spectrum showing large language models falling behind, are comparable, or exceed the ability of smaller models. We conclude that **large language models struggle at meeting fine-grained hard constraints**.Comment: EMNLP 202

Analysis of the mRNA export protein ZC3H11A in HCMV infection and pan-cancer

BackgroundWe have previously reported that human cytomegalovirus (HCMV) infection could promote the progression of glioma. Here we discovered a stress-induced nuclear protein ZC3H11A (ZC3) through high-throughput sequencing after HCMV infection, which has been reported recently by our research group in regulating mRNA export under stress conditions. And also, a thorough analysis of ZC3 in pan-cancer and the omics data of ZC3 are yet to be conducted.MethodsThe transcriptomes of glioma cells after HCMV infection were assessed by RNA sequencing. ZC3 mRNA and protein level following HCMV infection were validated and measured by qRT-PCR and Western-blot. The RNA sequencing and protein expression information of ZC3 across pan-cancer were analyzed and visualized by R packages. The localization of ZC3 protein was assessed by IHC images from HPA. The ZC3 proteomics and transcriptomics data in different cancers were extracted through the CPTAC data portal, and comparisons were conducted with a Python script. The genetic alteration, survival prognosis, immune infiltration analysis of ZC3 in pan-cancer were analyzed by cBioPortal, TCGA, and TIMER2 databases. The protein interaction networks were revealed by STRING, GEPIA2 and TCGA.ResultsGenes in mRNA processing pathways were upregulated after HCMV infection and ZC3 expression in mRNA and protein level was validated. We also discovered that the status of ZC3 were generally at high levels in cancers, although varied among different cancer types. ZC3 protein in tumor cells localized to the nuclear whereas in normal cells it was mainly found in cytoplasmic/membranous. However, from ZC3 proteomics and transcriptomics data in some cancer types, the increase in ZC3 protein was not accompanied by a significant elevation in mRNA level. Additionally, our analysis indicated that elevated ZC3 expression was primarily linked to a negative prognosis in majority cancers but still varied depending on the cancer types. Our annotation analysis suggested that ZC3-related proteins are mainly involved in mRNA processing clusters.ConclusionWe demonstrated that ZC3 significantly impacted by HCMV infection in gliomas. Furthermore, we identified a set of genes exhibiting analogous expression patterns to ZC3H11A in TCGA pan-cancer cohorts, implying a potential functional role for ZC3H11A in mRNA processing. Our study provided valuable insights into the role of a new mRNA export protein ZC3 in HCMV infection and pan-cancer progression. These results lay the foundation for our next research on the regulatory mechanism of ZC3 in virus-infected tumors

novoPathFinder: a webserver of designing novel-pathway with integrating GEM-model

To increase the number of value-added chemicals that can be produced by metabolic engineering and synthetic biology, constructing metabolic space with novel reactions/pathways is crucial. However, with the large number of reactions that existed in the metabolic space and complicated metabolisms within hosts, identifying novel pathways linking two molecules or heterologous pathways when engineering a host to produce a target molecule is an arduous task. Hence, we built a user-friendly web server, novoPathFinder, which has several features: (i) enumerate novel pathways between two specified molecules without considering hosts; (ii) construct heterologous pathways with known or putative reactions for producing target molecule within Escherichia coli or yeast without giving precursor; (iii) estimate novel pathways with considering several categories, including enzyme promiscuity, Synthetic Complex Score (SCScore) and LD50 of intermediates, overall stoichiometric conversions, pathway length, theoretical yields and thermodynamic feasibility. According to the results, novoPathFinder is more capable to recover experimentally validated pathways when comparing other rule-based web server tools. Besides, more efficient pathways with novel reactions could also be retrieved for further experimental exploration. novoPathFinder is available at http://design.rxnfinder.org/novopathfinder/

Analysis of the effect of grouting parameters on pile-soil interaction of grouted piles

Reasonable control of grouting parameters was the key to improving the pile-soil interaction. However, quantitative analysis on the effect of grouting parameters on the pile-soil interaction was still lacking. This article developed an intelligent post-grouting system for precise control and quantitative analysis of grouting parameters. The conventional preparation method for shear tests were improved in this article. By changing the normal stress of the pile-soil interface during grouting, the test sample could simulate the grout distribution of the pile-soil interface at different depths. Through the improved experimental methods, a more accurate analysis of the mechanism for the pile-soil interaction was achieved. And the effectiveness of the intelligent post-grouting system was further verified by the case application. The results indicated that increasing the grout volume could improve the interface shear strength when the normal stress and grouting pressure were constant. This improvement effect caused by increasing grout volume decreased when the normal stress was high. Increasing the grouting pressure increased the interface shear strength when the normal stress and the grout volume remained constant. This improvement effect caused by increasing grouting pressure decreased when the grout volume was small. By appropriately controlling the two grouting parameters, the cohesion and the shear strength of the pile-soil interface were increased by 5.8–18.8 times and 1.16–2.91 times, respectively. The results indicated that the intelligent post-grouting system could accurately control the grouting parameters and effectively improve the pile-soil interaction of bored piles. The intelligent post-grouting system effectively reduced geotechnical engineering risks and improved the bearing capacity of pile

Identification of <em>CHIP</em> as a novel causative gene for autosomal recessive cerebellar ataxia

Autosomal recessive cerebellar ataxias are a group of neurodegenerative disorders that are characterized by complex clinical and genetic heterogeneity. Although more than 20 disease-causing genes have been identified, many patients are still currently without a molecular diagnosis. In a two-generation autosomal recessive cerebellar ataxia family, we mapped a linkage to a minimal candidate region on chromosome 16p13.3 flanked by single-nucleotide polymorphism markers rs11248850 and rs1218762. By combining the defined linkage region with the whole-exome sequencing results, we identified a homozygous mutation (c.493CT) in CHIP (NM_005861) in this family. Using Sanger sequencing, we also identified two compound heterozygous mutations (c.389AT/c.441GT; c.621C>G/c.707GC) in CHIP gene in two additional kindreds. These mutations co-segregated exactly with the disease in these families and were not observed in 500 control subjects with matched ancestry. CHIP colocalized with NR2A, a subunit of the N-methyl-D-aspartate receptor, in the cerebellum, pons, medulla oblongata, hippocampus and cerebral cortex. Wild-type, but not disease-associated mutant CHIPs promoted the degradation of NR2A, which may underlie the pathogenesis of ataxia. In conclusion, using a combination of whole-exome sequencing and linkage analysis, we identified CHIP, encoding a U-box containing ubiquitin E3 ligase, as a novel causative gene for autosomal recessive cerebellar ataxia