Loss of RSR1 function increases the abscisic acid content and improves rice quality performance at high temperature.

Rice starch regulator1 (RSR1) participates in the regulation of starch synthesis in rice, but it's function on starch synthesis and quality formation in response to high temperature is unknown. RSR1 mutation resulted in a significant increase in the abscisic acid (ABA) content in rice grains under both normal and high temperature, and the effect of high temperature on grain filling and quality formation of the rsr1 mutants was significantly reduced. The grain size, 1000-kernels weight, amylose content, gelatinization temperature, and starch viscosity of the rsr1 mutants were less sensitive to high temperature. Loss of RSR1 function increased the expression levels of starch synthesis-related genes and reduced their responses to high temperature to some extent. Besides, the percentage of germinated seeds from rsr1 mutants was significantly lower than that of the wild-type, and the difference was more significant under ABA treatment. The shoot lengths of the rsr1 mutants were remarkably shorter than those of the wild-type, which was further exacerbated by ABA treatment. These results indicated that loss function of RSR1 can improve rice quality performance at high temperature by moderately increasing the ABA content of rice grains, which provides theoretical significance for the cultivation of better-quality rice with high-temperature resistance.

Association between ICW/TBW ratio and cancer prognosis: Subanalysis of a population-based retrospective multicenter study.

BACKGROUND & AIMS: Disease burden is known to alter cellular integrity and water balance. Therefore, the intracellular water/total body water (ICW/TBW) ratio is used as an adjunctive indicator to predict disease severity and prognosis. The ICW/TBW ratio of patients with cancer, who typically present with low muscle mass, poor nutritional status, and high inflammatory response, reportedly differs from that of the healthy population. Herein, we aimed to evaluate the effect of the ICW/TBW ratio on the prognosis of different subgroups of patients with cancer. METHODS: This multicenter cohort study included 2787 patients with malignancies between June 2014 and December 2018. The association between covariates and overall survival (OS) was assessed using restricted cubic spline models. The multivariate Cox regression model included variables demonstrating a statistical significance in the univariate Cox regression analysis (P < 0.05) without multicollinearity. The generated nomogram used the C-index and calibration curves to validate the predictive accuracy of the scoring system. RESULTS: The optimal cut-off value for the ICW/TBW ratio was 0.61. The ICW/TBW ratio was an independent prognostic factor (hazard ratio [HR]: 0.621; 95 % confidence interval [CI]: 0.537-0.719, P < 0.001). Moreover, the ICW/TBW ratio had a greater impact on the prognosis of patients receiving chemoradiotherapy than on those receiving chemotherapy alone (chemoradiotherapy: HR = 0.495, P = 0.005 vs. chemotherapy: HR = 0.646, P < 0.001). Multivariate Cox regression analysis showed that sex, age, tumor stage, body mass index, neutrophil-to-lymphocyte ratio (NLR), and ICW/TBW ratio were associated with OS. Subsequently, a nomogram was developed incorporating these variables and yielded a C-index of 0.743. CONCLUSIONS: The ICW/TBW ratio was associated with muscle mass, nutritional status, and inflammation. A low ICW/TBW ratio is an independent risk factor for poor prognosis in patients with cancer, especially when they are female, have advanced cancer stage, have sarcopenia, and are receiving radiotherapy.

Identification and Characterization of a Nerol Synthase in Fungi.

Nerol, a linear monoterpenoid, is naturally found in essential oils of various plants and is widely used in the fragrance, food, and cosmetic industries. Nerol synthase, essential for nerol biosynthesis, has previously been identified only in plants that use NPP as the precursor. In this study, a novel fungal nerol synthase, named PgfB, was cloned and characterized from Penicillium griseofulvum. In vitro enzymatic assays showed that PgfB could directly convert the substrate GPP into nerol. Furthermore, the successful expression of PgfB and its homologous protein in Saccharomyces cerevisiae resulted in the heterologous production of nerol. Finally, crucial amino acid residues for PgfB's catalytic activity were identified through site-directed mutagenesis. This research broadens our understanding of fungal monoterpene synthases and presents precious gene resources for the industrial production of nerol.

Predicting prognosis, immunotherapy and distinguishing cold and hot tumors in clear cell renal cell carcinoma based on anoikis-related lncRNAs.

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequently occurring malignant tumor within the kidney cancer subtype. It has low sensitivity to traditional radiotherapy and chemotherapy, the optimal treatment for localized ccRCC has been surgical resection, but even with complete resection the tumor will be eventually developed into metastatic disease in up to 40% of localized ccRCC. For this reason, it is crucial to find early diagnostic and treatment markers for ccRCC. Methods: We obtained anoikis-related genes (ANRGs) integrated from Genecards and Harmonizome dataset. The anoikis-related risk model was constructed based on 12 anoikis-related lncRNAs (ARlncRNAs) and verified by principal component analysis (PCA), Receiver operating characteristic (ROC) curves, and T-distributed stochastic neighbor embedding (t-SNE), and the role of the risk score in ccRCC immune cell infiltration, immune checkpoint expression levels, and drug sensitivity was evaluated by various algorithms. Additionally, we divided patients based on ARlncRNAs into cold and hot tumor clusters using the ConsensusClusterPlus (CC) package. Results: The AUC of risk score was the highest among various factors, including age, gender, and stage, indicating that the model we built to predict survival was more accurate than the other clinical features. There was greater sensitivity to targeted drugs like Axitinib, Pazopanib, and Sunitinib in the high-risk group, as well as immunotherapy drugs. This shows that the risk-scoring model can accurately identify candidates for ccRCC immunotherapy and targeted therapy. Furthermore, our results suggest that cluster 1 is equivalent to hot tumors with enhanced sensitivity to immunotherapy drugs. Conclusion: Collectively, we developed a risk score model based on 12 prognostic lncRNAs, expected to become a new tool for evaluating the prognosis of patients with ccRCC, providing different immunotherapy strategies by screening for hot and cold tumors.

Histone acetylation-related IncRNA: Potential biomarkers for predicting prognosis and immune response in lung adenocarcinoma, and distinguishing hot and cold tumours.

Background: Histone acetylation-related lncRNAs (HARlncRNAs) play significant roles in various cancers, but their impact on lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop a new HARlncRNA-based prognostic model for LUAD and to explore its potential biological mechanisms. Methods: We identified 77 histone acetylation genes based on previous studies. HARlncRNAs related to prognosis were screened by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator regression (LASSO). Afterward, a prognostic model was established based on the screened HARlncRNAs. We analysed the relationship between the model and immune cell infiltration characteristics, immune checkpoint molecule expression, drug sensitivity, and tumour mutational burden (TMB). Finally, the entire sample was divided into three clusters to further distinguish between hot and cold tumours. Results: A seven-HARlncRNA-based prognostic model was established for LUAD. The area under the curve (AUC) of the risk score was the highest among all the analysed prognostic factors, indicating the accuracy and robustness of the model. The patients in the high-risk group were predicted to be more sensitive to chemotherapeutic, targeted, and immunotherapeutic drugs. It was worth noting that clusters could effectively identify hot and cold tumours. In our study, clusters 1 and 3 were considered hot tumours that were more sensitive to immunotherapy drugs. Conclusion: We developed a risk-scoring model based on seven prognostic HARlncRNAs that promises to be a new tool for evaluating the prognosis and efficacy of immunotherapy in patients with LUAD.

Prospects and feasibility of synergistic therapy with radiotherapy, immunotherapy, and DNA methyltransferase inhibitors in non-small cell lung cancer.

The morbidity and mortality of lung cancer are increasing, seriously threatening human health and life. Non-small cell lung cancer (NSCLC) has an insidious onset and is not easy to be diagnosed in its early stage. Distant metastasis often occurs and the prognosis is poor. Radiotherapy (RT) combined with immunotherapy, especially with immune checkpoint inhibitors (ICIs), has become the focus of research in NSCLC. The efficacy of immunoradiotherapy (iRT) is promising, but further optimization is necessary. DNA methylation has been involved in immune escape and radioresistance, and becomes a game changer in iRT. In this review, we focused on the regulation of DNA methylation on ICIs treatment resistance and radioresistance in NSCLC and elucidated the potential synergistic effects of DNA methyltransferases inhibitors (DNMTis) with iRT. Taken together, we outlined evidence suggesting that a combination of DNMTis, RT, and immunotherapy could be a promising treatment strategy to improve NSCLC outcomes.

Spatiotemporal changes in snow depth and the influence factors in China from 1979 to 2019.

Snow depth is an important parameter to characterize the characteristics of snow cover, and it is also one of the most sensitive response factors to regional climate change. However, the extent of snow depth variability and its driving mechanisms are still unknown in China. Therefore, in this study, we used the regression analysis, root-mean-square error analysis, anomalous year analysis, and correlation analysis methods to explore the spatiotemporal variation characteristics of snow depth in China from 1979 to 2019 based on the reanalysis snow depth dataset. The results show that (1) the snow distribution in China is obviously spatially heterogeneous, and the southeastern, western, and southern regions of the Qinghai-Tibet Plateau, northern Xinjiang, and northeastern China have high values of snow depth; (2) the high-value regions are also the sensitive regions for anomalous variations in snow depth in China; (3) in the past 41 years, the interannual variability of snow depth in China has shown a significantly decreasing trend, and the linear tendency of snow depth is - 0.093 cm/10 a (p < 0.01) and the snow depth in four seasons showed a decreasing trend (p < 0.05); and (4) the driving factors of snow heterogeneity are dissimilar in different regions and seasons. In temperate zones, average air temperature is the main factor affecting snow depth in cold temperature, mid temperature, and warm temperature zones; the maximum air temperature is the main factor affecting snow depth in mid temperate and warm temperate zones. Both the minimum air temperature and the average land-surface temperature are important factors affecting the snow depth in the cold temperate, mid temperate and warm temperate zones, and all passed the significance test of 0.01.

Two Directions for Clinical Data Generation with Large Language Models: Data-to-Label and Label-to-Data.

Large language models (LLMs) can generate natural language texts for various domains and tasks, but their potential for clinical text mining, a domain with scarce, sensitive, and imbalanced medical data, is under-explored. We investigate whether LLMs can augment clinical data for detecting Alzheimer's Disease (AD)-related signs and symptoms from electronic health records (EHRs), a challenging task that requires high expertise. We create a novel pragmatic taxonomy for AD sign and symptom progression based on expert knowledge and generated three datasets: (1) a gold dataset annotated by human experts on longitudinal EHRs of AD patients; (2) a silver dataset created by the data-to-label method, which labels sentences from a public EHR collection with AD-related signs and symptoms; and (3) a bronze dataset created by the label-to-data method which generates sentences with AD-related signs and symptoms based on the label definition. We train a system to detect AD-related signs and symptoms from EHRs. We find that the silver and bronze datasets improves the system performance, outperforming the system using only the gold dataset. This shows that LLMs can generate synthetic clinical data for a complex task by incorporating expert knowledge, and our label-to-data method can produce datasets that are free of sensitive information, while maintaining acceptable quality.

Baculovirus-derived influenza virus-like particle confers complete protection against lethal H7N9 avian influenza virus challenge in chickens and mice.

Currently, highly pathogenic avian influenza (HPAI) H7N9 viruses still pose a potential pandemic threat. Influenza virus-like particle (VLP) is one of the most promising vaccine strategies to complement traditional egg-dependent vaccines. Here, we generated a H7N9 VLP vaccine candidate by baculovirus expression system and evaluated its efficacy in chickens and mice. The H7N9 VLP was produced through co-infection of Sf9 insect cells with three recombinant baculoviruses expressing individual HA, NA and M1 gene of the HPAI H7N9 virus A/chicken/Guangdong/GD15/2016. Intramuscular immunization of the H7N9 VLP elicited robust antibody immune responses and conferred complete clinical protection against lethal H7N9 virus challenge both in chickens and mice. Meanwhile, H7N9 VLP significantly restrained virus shedding and dramatically alleviated pulmonary lesions caused by H7N9 virus infection in birds and mice. Interestingly, chicken antibodies induced by the H7N9 VLP also had a good cross-reactivity with H7N9 field strains isolated in different years. In addition, vaccination with the H7N9 VLP elicited high T cell immunity in mouse lung, evidenced by significantly upregulated expression of IL-2, IL-4 and IFN-γ. Furthermore, the H7N9 VLP significantly decreased the expression of some key inflammatory cytokines, such as IL6, RANTES and TNF-α in mouse lung, which may partially account for its contribution to alleviate lung pathology. Therefore, our study describes the good efficacy of the HA + NA + M1-containing H7N9 VLP both in chicken and mice models, highlighting the potential of VLP-based vaccine as a critical alternative of traditional egg-based vaccine for control of H7N9 influenza virus in both humans and poultry.

Single Dose of Bivalent H5 and H7 Influenza Virus-Like Particle Protects Chickens Against Highly Pathogenic H5N1 and H7N9 Avian Influenza Viruses.

Both H5N1 and H7N9 subtype avian influenza viruses cause enormous economic losses and pose considerable threats to public health. Bivalent vaccines against both two subtypes are more effective in control of H5N1 and H7N9 viruses in poultry and novel egg-independent vaccines are needed. Herein, H5 and H7 virus like particle (VLP) were generated in a baculovirus expression system and a bivalent H5+H7 VLP vaccine candidate was prepared by combining these two antigens. Single immunization of the bivalent VLP or commercial inactivated vaccines elicited effective antibody immune responses, including hemagglutination inhibition, virus neutralizing and HA-specific IgG antibodies. All vaccinated birds survived lethal challenge with highly pathogenic H5N1 and H7N9 viruses. Furthermore, the bivalent VLP significantly reduced viral shedding and virus replication in chickens, which was comparable to that observed for the commercial inactivated vaccine. However, the bivalent VLP was better than the commercial vaccine in terms of alleviating pulmonary lesions caused by H7N9 virus infection in chickens. Therefore, our study suggests that the bivalent H5+H7 VLP vaccine candidate can serve as a critical alternative for the traditional egg-based inactivated vaccines against H5N1 and H7N9 avian influenza virus infection in poultry.

H7N9 influenza virus-like particle based on BEVS protects chickens from lethal challenge with highly pathogenic H7N9 avian influenza virus.

H7N9 avian influenza virus poses a dual threat to both poultry industry and public health. Therefore, it is highly urgent to develop an effective vaccine to reduce its pandemic potential. Virus-like particles (VLP) represent an effective approach for pandemic vaccine development. In this study, a recombinant baculovirus co-expressing the HA, NA and M1 genes of the H7N9 virus was constructed for generation of H7N9 VLP. Single immunization of chickens with 15 µg of the VLP or the commercial whole virus inactivated vaccine stimulates high hemagglutination inhibition, virus neutralizing and HA-specific IgY antibodies. Moreover, the antiserum had a good cross-reactivity with H7N9 field strains isolated in different years. Within 14 days after a lethal challenge with highly pathogenic (HP) H7N9 virus, no clinical symptoms and death were observed in the vaccinated chickens, and no virus was recovered from the organs. Compared to the non-vaccinated chickens, H7N9 VLP significantly reduced the proportion of animals shedding virus. Only 30 % of the VLP-vaccinated birds shed virus, whereas virus shedding was detected in 50 % of the chickens immunized with the commercial vaccine. Moreover, both vaccines dramatically alleviated pulmonary lesions caused by HP H7N9 virus, with a greater degree observed for the VLP. Altogether, our results indicated that the H7N9 VLP vaccine candidate confers a complete clinical protection against a lethal challenge with HP H7N9 virus, significantly inhibits virus shedding and abolishes viral replication in chickens. The VLP generated in this study represents a promising alternative strategy for the development of novel H7N9 avian influenza vaccines for chickens.

Role of RASA1 in cancer: A review and update (Review).

Ras p21 protein activator 1 (RASA1) is a regulator of Ras GDP and GTP and is involved in numerous physiological processes such as angiogenesis, cell proliferation, and apoptosis. As a result, RASA1 also contributes to pathological processes in vascular diseases and tumour formation. This review focuses on the role of RASA1 in multiple tumours types in the lung, intestines, liver, and breast. Furthermore, we discuss the potential mechanisms of RASA1 and its downstream effects through Ras/RAF/MEK/ERK or Ras/PI3K/AKT signalling. Moreover, miRNAs are capable of regulating RASA1 and could be a novel targeted treatment strategy for tumours.

Percutaneous radiofrequency ablation is superior to hepatic resection in patients with small hepatocellular carcinoma.

BACKGROUND: It is not known whether percutaneous radiofrequency ablation (PRFA) has the same treatment efficacy and fewer complications than laparoscopic resection in patients with small centrally located hepatocellular carcinoma (HCC). AIM: To compare the effectiveness of PRFA with classical laparoscopic resection in patients with small HCC and document the safety parameters. METHODS: In this retrospective study, 85 patients treated with hepatic resection (HR) and 90 PRFA-treated patients were enrolled in our hospital from July 2016 to July 2019. Treatment outcomes, including major complications and survival data, were evaluated. RESULTS: The results showed that minor differences existed in the baseline characteristics between the patients in the two groups. PRFA significantly increased cumulative recurrence-free survival (hazard ratio 1.048, 95%CI: 0.265-3.268) and overall survival (hazard ratio 0.126, 95%CI: 0.025-0.973); PRFA had a lower rate of major complications than HR (7.78% vs 20.0%, P < 0.05), and hospital stay was shorter in the PRFA group than in the HR group (7.8 ± 0.2 d vs 9.5 ± 0.3 d, P < 0.001). CONCLUSION: Based on the data obtained, we conclude that PRFA was superior to HR and may reduce complications and hospital stay in patients with small HCC.

MetaMT, a Meta Learning Method Leveraging Multiple Domain Data for Low Resource Machine Translation.

Neural machine translation (NMT) models have achieved state-of-the-art translation quality with a large quantity of parallel corpora available. However, their performance suffers significantly when it comes to domain-specific translations, in which training data are usually scarce. In this paper, we present a novel NMT model with a new word embedding transition technique for fast domain adaption. We propose to split parameters in the model into two groups: model parameters and meta parameters. The former are used to model the translation while the latter are used to adjust the representational space to generalize the model to different domains. We mimic the domain adaptation of the machine translation model to low-resource domains using multiple translation tasks on different domains. A new training strategy based on meta-learning is developed along with the proposed model to update the model parameters and meta parameters alternately. Experiments on datasets of different domains showed substantial improvements of NMT performances on a limited amount of data.

IL­37 expression is decreased in patients with hyperhomocysteinemia and protects cells from inflammatory injury by homocysteine.

As a novel anti­inflammatory cytokine of the interleukin (IL)­1 family, IL­37 protects the human body from diseases characterized by excessive inflammation. The pathologic process of hyperhomocysteinemia (hHcy) is accompanied by persistent inflammation. However, little is known regarding the role of IL­37 in hHcy. In the present study, the levels of cytokines including IL­37, IL­1ß, IL­6 and tumor necrosis factor­α in the supernatant were detected by ELISA. mRNA and protein expression were detected by Reverse transcription­quantitative PCR and western blotting, respectively. LDH level was determined by ELISA and the cell viability was detected through CCK­8 kit. In the present study, mean serum IL­37 levels of patients with hHcy were 32.3% lower than those of controls (P<0.01). In peripheral blood mononuclear cells (PBMCs) from patients with hHcy, mean IL­37 mRNA expression was 73.5% lower (P<0.01) and IL­37 protein expression was 77.7% lower compared with that of healthy controls (P<0.01). Furthermore, the results demonstrated that exogenous homocysteine (Hcy) stimulation markedly downregulated the mRNA and protein expression levels of IL­37 in PBMCs in vitro. In 293T cells, overexpression of IL­37 restored the cell viability impaired by Hcy, and reduced the release of lactate dehydrogenase and the proinflammatory cytokines IL­1ß, IL­6 and tumor necrosis factor­α. In conclusion, IL­37 was downregulated by Hcy in vivo and in vitro, and IL­37 exhibited a protective role against cell injury induced by Hcy.

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach.

BACKGROUND: Bleeding events are common and critical and may cause significant morbidity and mortality. High incidences of bleeding events are associated with cardiovascular disease in patients on anticoagulant therapy. Prompt and accurate detection of bleeding events is essential to prevent serious consequences. As bleeding events are often described in clinical notes, automatic detection of bleeding events from electronic health record (EHR) notes may improve drug-safety surveillance and pharmacovigilance. OBJECTIVE: We aimed to develop a natural language processing (NLP) system to automatically classify whether an EHR note sentence contains a bleeding event. METHODS: We expert annotated 878 EHR notes (76,577 sentences and 562,630 word-tokens) to identify bleeding events at the sentence level. This annotated corpus was used to train and validate our NLP systems. We developed an innovative hybrid convolutional neural network (CNN) and long short-term memory (LSTM) autoencoder (HCLA) model that integrates a CNN architecture with a bidirectional LSTM (BiLSTM) autoencoder model to leverage large unlabeled EHR data. RESULTS: HCLA achieved the best area under the receiver operating characteristic curve (0.957) and F1 score (0.938) to identify whether a sentence contains a bleeding event, thereby surpassing the strong baseline support vector machines and other CNN and autoencoder models. CONCLUSIONS: By incorporating a supervised CNN model and a pretrained unsupervised BiLSTM autoencoder, the HCLA achieved high performance in detecting bleeding events.

Recombinant baculovirus vaccine expressing hemagglutinin of H7N9 avian influenza virus confers full protection against lethal highly pathogenic H7N9 virus infection in chickens.

The emergent highly pathogenic avian influenza A (H7N9) (HPAI) virus is a major public concern in China. Therefore, it is crucially important to develop an effective vaccine against this virus. In this study, we constructed a baculovirus vaccine expressing the hemagglutinin (HA) of H7N9 strain A/Chicken/Jiaxing/148/2014 (JX148). The recombinant baculovirus (rBac-JX148HA) generated in this study showed good growth in insect cells and good safety, and it stably expressed the HA protein. We compared the immunogenicity and efficacy of the inactivated whole-virus vaccine JX148 and rBac-JX148HA. One chicken in the JX148-treated group died on day 4 post-challenge, and three chickens had typical clinical symptoms (survival rate, 90%; morbidity, 40%). However, no chickens immunized with rBac-JX148HA showed clinical signs during the 14-day observation period. An analysis of viral shedding and viral replication demonstrated that rBac-JX148HA more efficiently inhibited viral shedding and viral replication than the inactivated whole-virus vaccine. Taken together, these results indicate that the inactivated recombinant baculovirus vaccine induces a high hemagglutination inhibition antibody titer, provides complete protection against challenge with the highly pathogenic H7N9 virus, and effectively inhibits viral shedding. Therefore, the candidate vaccine has potential utility in the prevention and control of H7N9 avian influenza and is also appropriate for veterinary vaccines using cell suspension culture technology.

Tripterygium wilfordii Glycosides Upregulate the New Anti-Inflammatory Cytokine IL-37 through ERK1/2 and p38 MAPK Signal Pathways.

As a Chinese traditional patent medicine, Tripterygium wilfordii glycosides (TWG) have been approved by the China State Food and Drug Administration (Z32021007) for autoimmune and inflammatory diseases. Application of TWG leads to significant decrease of the inflammatory cytokines, such as IL-6, IL-1ß, and TNF-α. However, little is known whether TWG could regulate the anti-inflammatory cytokines and what the mechanism is. Here, we found that TWG could induce the upregulation of IL-37 which is a new anti-inflammatory cytokine. Furthermore, the inhibitors of ERK1/2 and/or p38 MAPK pathways suppressed IL-37 expression induced by TWG, indicating that the two pathways took part in this process. In conclusion, TWG could upregulate the anti-inflammatory cytokine IL-37 and ERK1/2 and p38 MAPK signal pathways were involved in the upregulation of IL-37 induced by TWG. The results showed that TWG had a potent activity on promoting the expression of IL-37, a new anti-inflammatory cytokine, which help further understanding the anti-inflammatory mechanism for the clinical application of TWG in therapy of diseases.