Dynamic Strategy Chain: Dynamic Zero-Shot CoT for Long Mental Health Support Generation

Long counseling Text Generation for Mental health support (LTGM), an innovative and challenging task, aims to provide help-seekers with mental health support through a comprehensive and more acceptable response. The combination of chain-of-thought (CoT) prompting and Large Language Models (LLMs) is employed and get the SOTA performance on various NLP tasks, especially on text generation tasks. Zero-shot CoT prompting is one of the most common methods in CoT prompting. However, in the LTGM task, Zero-shot CoT prompting can not simulate a counselor or provide personalized strategies without effective mental health counseling strategy prompts. To tackle this challenge, we propose a zero-shot Dynamic Strategy Chain (DSC) prompting method. Firstly, we utilize GPT2 to learn the responses written by mental health counselors and dynamically generate mental health counseling strategies tailored to the help-seekers' needs. Secondly, the Zero-shot DSC prompting is constructed according to mental health counseling strategies and the help-seekers' post. Finally, the Zero-shot DSC prompting is employed to guide LLMs in generating more human-like responses for the help-seekers. Both automatic and manual evaluations demonstrate that Zero-shot DSC prompting can deliver more human-like responses than CoT prompting methods on LTGM tasks

OsAPX4 gene response to several environmental stresses in rice (Oryza sativa L.)

Expression of the gene, OsAPX4, coding for ascorbate peroxidase in leaves and roots of rice were induced by abiotic stresses, such as NaCl, NaHCO3 and Na2CO3, polyethylene glycol (PEG) 6000, H2O2, CuCl2. Yeast (Saccharomyces cerevisiae) over-expressing ascorbate peroxidase exhibited greater tolerance to NaCl and NaHCO3 and transgenic Arabidopsis over-expressing OsAPX4 had a greater salt tolerance than wild-type plants in 1/2 Murashige and Skoog (MS) medium with 150, 200 mM NaCl and 5, 7.5 mM NaHCO3. These results suggest that OsAPX4 plays an important role in multiple environmental stresses.Keywords: Arabidopsis, Oryza sativa, thaliana, carbonic anhydrase ascorbate peroxides, gene expression stressAfrican Journal of Biotechnology Vol. 9(36), pp. 5908-5913, 6 September, 201

Interpreting XML keyword query using hidden Markov model

Pretraživanje ključne riječi na XML bazi podataka privuklo je prilično zanimanja. Kako se XML dokumenti vrlo razlikuju od plošnih (flat) dokumenata, učinkovita pretraga XML dokumenata zahtijeva posebno razmatranje. Tradicionalni model vreće riječi (bag-of-words) ne uzima u obzir uloge ključnih riječi i odnos između ključnih riječi pa prema tome nije pogodan za XML pretragu ključne riječi. U ovom radu predstavljamo novi model, nazvan polu-strukturno pretraživanje ključne riječi (SSQ), koji podrazumijeva pretraživanje ključne riječi na različit način; to se pretraživanje sastoji od nekoliko cjelina pretrage i svaka cjelina predstavlja stanje pretrage (query condition). Za interpretaciju pretrage po tom modelu, potrebna su dva koraka. Prvo, predlažemo probabilistički pristup zasnovan na skrivenom Markovljevom modelu za izračunavanje najboljeg uklapanja traženih ključnih riječi u termine baze podataka, tj. elemenata, atributa i vrijednosti. Drugo, generiramo konstrukcije ključnih riječi (SSQs) na osnovu uklapanja. Eksperimentalni rezultati potvrđuju učinkovitost naših metoda.Keyword search on XML database has attracted a lot of research interests. As XML documents are very different from flat documents, effective search of XML documents needs special considerations. Traditional bag-of-words model does not take the roles of keywords and the relationship between keywords into consideration, and thus is not suited for XML keyword search. In this paper, we present a novel model, called semi-structured keyword query (SSQ), which understands a keyword query in a different way: a keyword query is composed of several query units, where each unit represents query condition. To interpret a keyword query under this model, we take two steps. First, we propose a probabilistic approach based on a Hidden Markov Model for computing the best mapping of the query keywords into the database terms, i.e., elements, attributes and values. Second, we generate SSQs based on the mapping. Experimental results verify the effectiveness of our methods

A Bio-Hygromorph Fabricated with Fish Swim Bladder Hydrogel and Wood Flour-Filled Polylactic Acid Scaffold by 3D Printing

Describes a study where researchers constructed a bio-hygromorph using fish swim bladder hydrogel as the hydrophilic material and wood flour-filled polylactic acid (WPLA) scaffold, which was printed with fused deposition modeling (FDM) 3D printing technology (3DP)

Keratin 18 phosphorylation as a progression marker of chronic hepatitis B

BACKGROUND: The intermediate filament proteins keratins 18 (K18) and 8 (K8) polymerize to form the cytoskeletal network in the mature hepatocytes. It has been shown that the phosphorylation of K18 at two serine residues, 33 and 52, correlates with the progression of hepatitis C, but little is known of chronic hepatitis B (CHB). In this study, we examined K18 phosphorylation in relation to CHB. RESULTS: Site-specific phosphorylation of K18 was determined in livers of twelve healthy donors, and non-cirrhosis (n = 40) and cirrhosis (n = 21) patients. On average, progressively higher level of Ser52 phosphorylation was observed in non-cirrhotic and cirrhotic livers, while elevated Ser33 phosphorylation was detected in both livers but no significant difference. Progressive increase of Ser33 and Ser52 phosphorylation correlated with the elevation of both histological lesions and enzymatic activities of alanine aminotransferase in non-cirrhotic livers. In the hepatocytes of an inactive HBV carrier, strong signals of Ser33 phosphorylation were co-localized with viral infection, while only basal level of Ser52 phosphorylation was detected in infected cells. CONCLUSION: Assuming all obtained data, our data suggest that K18 phosphorylation is a progression marker for CHB

ICEberg: a web-based resource for integrative and conjugative elements found in Bacteria

ICEberg (http://db-mml.sjtu.edu.cn/ICEberg/) is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. We propose that ICEberg will facilitate efficient, multi-disciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community

Prognostic Significance of Serum Cysteine-Rich Protein 61 in Patients with Acute Heart Failure

Background/Aims: Cyr61-cysteine-rich protein 61 (CCN1/CYR61) is a multifunctional matricellular protein involved in the regulation of fibrogenesis. Animal experiments have demonstrated that CCN1 can inhibit cardiac fibrosis in cardiac hypertrophy. However, no study has been conducted to assess the relation between serum CCN1 and prognosis of acute heart failure (AHF). Methods: We measured the serum CCN1 levels of 183 patients with AHF, and the patients were followed up for 6 months. The associations between CCN1 levels and some clinical covariates, especially left ventricular ejection fraction (LVEF), estimated glomerular filtration rate (eGFR), atrial fibrillation and age, were estimated. The AHF patients were followed up for 6 months. The endpoint was all-cause mortality. Kaplan-Meier curve analysis and multivariable Cox proportional hazards analysis were employed to evaluate the prognostic ability of CCN1. We used calibration, discrimination and reclassification to assess the mortality risk prediction of adding CCN1. Results: Serum CCN1 concentrations in AHF patients were significantly increased compared with those in individuals without AHF (237 pg/ml vs. 124.8 pg/ml, p< 0.001). CCN1 level was associated with the level of NT-proBNP (r=0.349, p< 0.001) and was not affected by LVEF, eGFR, age or atrial fibrillation in AHF patients. Importantly, Kaplan-Meier curve analysis illustrated that the AHF patients with serum CCN1 level > 260 pg/ ml had a lower survival rate (p< 0.001). Multivariate Cox hazard analysis suggests that CCN1 functions as an independent predictor of mortality for AHF patients (LgCCN1, hazard ratio 5.825, 95% confidence interval: 1.828-18.566, p=0.003). In addition, the inclusion of CCN1 in the model with NT-proBNP significantly improved the C-statistic for predicting death (0.758, p< 0.001). The integrated discrimination index was 0.019 (p< 0.001), and the net reclassification index increased significantly after addition of CCN1 (23.9%, p=0.0179). Conclusions: CCN1 is strongly predictive of 6-month mortality in patients with AHF, suggesting serum CCN1 as a promising candidate prognostic biomarker for AHF patients