A Bibliometric Review of Large Language Models Research from 2017 to 2023

Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their ability to generate human-like language and their potential to revolutionize science and technology. In this study, we conduct bibliometric and discourse analyses of scholarly literature on LLMs. Synthesizing over 5,000 publications, this paper serves as a roadmap for researchers, practitioners, and policymakers to navigate the current landscape of LLMs research. We present the research trends from 2017 to early 2023, identifying patterns in research paradigms and collaborations. We start with analyzing the core algorithm developments and NLP tasks that are fundamental in LLMs research. We then investigate the applications of LLMs in various fields and domains including medicine, engineering, social science, and humanities. Our review also reveals the dynamic, fast-paced evolution of LLMs research. Overall, this paper offers valuable insights into the current state, impact, and potential of LLMs research and its applications.Comment: 36 pages, 9 figures, and 4 table

High atmospheric carbon dioxide-dependent alleviation of salt stress is linked to RESPIRATORY BURST OXIDASE 1 (RBOH1)-dependent H2O2 production in tomato (Solanum lycopersicum)

Plants acclimate rapidly to stressful environmental conditions. Increasing atmospheric CO2 levels are predicted to influence tolerance to stresses such as soil salinity but the mechanisms are poorly understood. To resolve this issue, tomato (Solanum lycopersicum) plants were grown under ambient (380 μmol mol–1) or high (760 μmol mol–1) CO2 in the absence or presence of sodium chloride (100 mM). The higher atmospheric CO2 level induced the expression of RESPIRATORY BURST OXIDASE 1 (SlRBOH1) and enhanced H2O2 accumulation in the vascular cells of roots, stems, leaf petioles, and the leaf apoplast. Plants grown with higher CO2 levels showed improved salt tolerance, together with decreased leaf transpiration rates and lower sodium concentrations in the xylem sap, vascular tissues, and leaves. Silencing SlRBOH1 abolished high CO2 -induced salt tolerance and increased leaf transpiration rates, as well as enhancing Na+ accumulation in the plants. The higher atmospheric CO2 level increased the abundance of a subset of transcripts involved in Na+ homeostasis in the controls but not in the SlRBOH1-silenced plants. It is concluded that high atmospheric CO2 concentrations increase salt stress tolerance in an apoplastic H2O2 dependent manner, by suppressing transpiration and hence Na+ delivery from the roots to the shoots, leading to decreased leaf Na+ accumulation

Pilot Safety Evaluation of a Novel Strain of Bacteroides ovatus

Bacteroides ovatus ELH-B2 is considered as a potential next-generation probiotic due to its preventive effects on lipopolysaccharides-associated inflammation and intestinal microbiota disorders in mice. To study safety issues associated with B. ovatus ELH-B2, we conducted comprehensive and systematic experiments, including in vitro genetic assessments of potential virulence and antimicrobial resistance genes, and an in vivo acute toxicity study of both immunocompetent and immunosuppressed mice via cyclophosphamide treatment. The results indicated that this novel strain is non-toxigenic, fragilysin is not expressed, and most of potential virulence genes are correlated with cellular structures such as capsular polysaccharide and polysaccharide utilizations. The antibiotic resistance features are unlikely be transferred to other intestinal microorganisms as no plasmids nor related genomic islands were identified. Side effects were not observed in mice. B. ovatus ELH-B2 also alleviated the damages caused by cyclophosphamide injection

Chronic Hepatitis B Virus Infection and Risk of Stroke Types: A Prospective Cohort Study of 500 000 Chinese Adults

BACKGROUND: Stroke is a leading cause of mortality and permanent disability in China, with large and unexplained geographic variations in rates of different stroke types. Chronic hepatitis B virus infection is prevalent among Chinese adults and may play a role in stroke cause. // METHODS: The prospective China Kadoorie Biobank included >500 000 adults aged 30 to 79 years who were recruited from 10 (5 urban and 5 rural) geographically diverse areas of China from 2004 to 2008, with determination of hepatitis B surface antigen (HBsAg) positivity at baseline. During 11 years of follow-up, a total of 59 117 incident stroke cases occurred, including 11 318 intracerebral hemorrhage (ICH), 49 971 ischemic stroke, 995 subarachnoid hemorrhage, and 3036 other/unspecified stroke. Cox regression models were used to estimate adjusted hazard ratios (HRs) for risk of stroke types associated with HBsAg positivity. In a subset of 17 833 participants, liver enzymes and lipids levels were measured and compared by HBsAg status. // RESULTS: Overall, 3.0% of participants were positive for HBsAg. HBsAg positivity was associated with an increased risk of ICH (adjusted HR, 1.29 [95% CI, 1.16–1.44]), similarly for fatal (n=5982; adjusted HR, 1.36 [95% CI, 1.16–1.59]) and nonfatal (n=5336; adjusted HR, 1.23 [95% CI, 1.06–1.44]) ICH. There were no significant associations of HBsAg positivity with risks of ischemic stroke (adjusted HR, 0.97 [95% CI, 0.92–1.03]), subarachnoid hemorrhage (adjusted HR, 0.87 [95% CI, 0.57–1.33]), or other/unspecified stroke (adjusted HR, 1.12 [95% CI, 0.89–1.42]). Compared with HBsAg-negative counterparts, HBsAg-positive individuals had lower lipid and albumin levels and higher liver enzyme levels. After adjustment for liver enzymes and albumin, the association with ICH from HBsAg positivity attenuated to 1.15 (0.90–1.48), suggesting possible mediation by abnormal liver function. // CONCLUSIONS: Among Chinese adults, chronic hepatitis B virus infection is associated with an increased risk of ICH but not other stroke types, which may be mediated through liver dysfunction and altered lipid metabolism

A pyroptosis-related gene signature for prognosis prediction in hepatocellular carcinoma

IntroductionHepatocellular carcinoma (HCC) is one of the most invasive cancers with a low 5-year survival rate. Pyroptosis, a specialized form of cell death, has shown its association with cancer progression. However, its role in the prognosis of HCC has not been fully understood.MethodsIn our study, clinical information and mRNA expression for 1076 patients with HCC were obtained from the five public cohorts. Pyroptotic clusters were generated by unsupervised clustering based on 40 pyroptosis-related genes (PRGs) in the TCGA and ICGC cohort. A pyroptosis-related signature was constructed using least absolute shrinkage and selection operator (LASSO) regression according to differentially expressed genes (DEGs) of pyroptotic clusters. The signature was then tested in the validation cohorts (GES10142 and GSE14520) and subsequently validated in the CPTAC cohort (n=159) at both mRNA and protein levels. Response to sorafenib was explored in GSE109211.ResultsThree clusters were identified based on the 40 PRGs in the TCGA cohort. A total of 24 genes were selected based on DEGs of the above three pyroptotic clusters to construct the pyroptotic risk score. Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28). The predictive ability of the risk score was further confirmed in the CPTAC cohort at both mRNAs (P<0.001; HR, 2.99; 95% CI, 1.67-5.36) and protein levels (P<0.001; HR, 2.97; 95% CI 1.66-5.31). The expression of the model genes was correlated with immune cell infiltration, angiogenesis-related genes, and sensitivity to antiangiogenic therapy (P<0.05).DiscussionIn conclusion, we established a prognostic signature of 24 genes based on pyroptosis clusters for HCC patients, providing insight into the risk stratification of HCC

Leveraging “Guilt-free Pleasure” concept in developing healthful snack products

Doctor of PhilosophyDepartment of Food, Nutrition, Dietetics and HealthKadri KoppelConsumers are seeking greater healthy and ethical living globally nowadays. The goal of this dissertation is to gain insights on promoting healthy and sustainable eating behaviors through exploring the effect of guilt on food choice and eating behaviors. In the first phase, consumer-based characteristics of food that might aid in identifying the different levels of guilt perceptions were investigated by using a qualitative approach. Product grouping patterns were identified with Sorting method based on different levels of guilt perceptions the consumers have had with 18 food and beverage products. Four categories of 45 factors were identified that could elicit guilt perceptions, including intrinsic product characteristics, extrinsic product characteristics, situational factors, and social-cultural factors, indicating its complexity and multidimensionality. Consumers' guilt tendency concerning food in the context of daily life was recognized as an essential characteristic that could influence consumers' food choices, eating behavior, purchase decisions, and lifestyle. Moreover, the product representation map implied the potential of using guilt related perceptions for product differentiation. White space of snack products that could deliver "Guilt-free pleasure" was identified, providing new opportunities for healthy snack products' development. In the second phase, a Food Consumer Guilt Scale for measuring consumers' guilt tendencies to foods was developed. A preliminary questionnaire was constructed and validated in terms of the total scale score distribution, reliability, internal validity, and discriminating ability. The updated scale with 16 items was found to be a reliable measurement instrument that showed high internal consistency, discrimination power, and was cross-validated with a new sample of consumers. Factor analysis was conducted to uncover the underlying structure of the scale, which included three aspects: (1) consumers' eating behavior, including perceived unhealthiness of food and less unhealthy eating style; (2) the naturalness of the food and its packaging; (3) a sustainable and healthy lifestyle. Consumers were identified with three different guilt tendencies related to food. They had diverse preference patterns and distinct potential eating frequency on products tested. These findings suggested that the Food Consumer Guilt Scale could be a useful segmentation tool to understand consumers' food choices and eating behaviors, therefore, helpful in providing guidance promoting healthy and sustainable eating behaviors. In the third phase, a Food Product Guilt Scale was developed to measure how product characteristics affect on products' guilt perception. A preliminary questionnaire was constructed and tested through an online survey. Reliability, discriminating ability, and correlation with the product's guilt perception was evaluated to refine the items. A final 14-item measure was found to be a reliable measurement instrument possessing discrimination power and was cross-validated with a new sample of consumers. Moreover, it was found that there was no clear relationship between guilt rating and perceived liking of the products. Regretful, Irresponsible, Lazy, Unproductive, Bloated, Heavy, Gross and Terrible were identified positively related to guilt, whereas, Healthy, Natural, Good, Balanced, Energized, Refreshed, Energetic, Productive and Sustained were negatively correlated. Product representation showed that intrinsic product characteristics of nutritional values were the main contributors to tested products' guilt perception

High Nursing Staff Turnover In Nursing Homes Offers Important Quality Information.

Nursing staff turnover has long been considered an important indicator of nursing home quality. However, turnover has never been reported on the Nursing Home Compare website, likely because of the lack of adequate data. On July 1, 2016, the Centers for Medicare and Medicaid Services began collecting auditable payroll-based daily staffing data for US nursing homes. We used 492 million nurse shifts from these data to calculate a novel turnover metric representing the percentage of hours of nursing staff care that turned over annually at each of 15,645 facilities. Mean and median annual turnover rates for total nursing staff were roughly 128 percent and 94 percent, respectively. Turnover rates were correlated with facility location, for-profit status, chain ownership, Medicaid patient census, and star ratings. Disseminating facilities' nursing staff turnover rates on Nursing Home Compare could provide important quality information for policy makers, payers, and consumers, and it may incentivize efforts to reduce turnover