Clinical efficacy of pre-trained large language models through the lens of aphasia.

The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they differ from or relate to the existing language features in aphasia? To what extent can LLMs serve as an interpretable and effective diagnostic and measurement tool in a clinical context? To investigate these questions, we constructed predictive and correlational models, which utilize mean surprisals from LLMs as predictor variables. Using AphasiaBank archived data, we validated our models' efficacy in aphasia diagnosis, measurement, and prediction. Our finding is that LLMs-surprisals can effectively detect the presence of aphasia and different natures of the disorder, LLMs in conjunction with the existing language indices improve models' efficacy in subtyping aphasia, and LLMs-surprisals can capture common agrammatic deficits at both word and sentence level. Overall, LLMs have potential to advance automatic and precise aphasia prediction. A natural language processing pipeline can be greatly benefitted from integrating LLMs, enabling us to refine models of existing language disorders, such as aphasia.

WSSV early protein WSSV004 enhances viral replication by suppressing LDH activity.

White spot syndrome virus (WSSV) is known to upregulate glycolysis to supply biomolecules and energy for the virus's replication. At the viral genome replication stage, lactate dehydrogenase (LDH), a glycolytic enzyme, shows increased activity without any increase in expression. In the present study, yeast 2-hybrid screening was used to identify WSSV proteins that interacted with LvLDH isoform 1 and 2, and these included the WSSV early protein WSSV004. The interaction between WSSV004 and LvLDH1/2 was confirmed by co-immunoprecipitation. Immunofluorescence showed that WSSV004 co-localized with LvLDH1/2 in the cytoplasm. dsRNA silencing experiments showed that WSSV004 was crucial for WSSV replication. However, although WSSV004 silencing led to the suppression of total LvLDH gene expression during the viral late stage, there was nevertheless a significant increase in LvLDH activity at this time. We also used affinity purification-mass spectrometry to identify cellular proteins that interact with WSSV004, and found a total of 108 host proteins and 3 WSSV proteins with which it potentially interacts. Bioinformatics analysis revealed that WSSV004 and its interacting proteins might be responsible for various biological pathways during infection, including vesicular transport machinery and RNA-related functions. Collectively, our study suggests that WSSV004 serves as a multifunctional modulator to facilitate WSSV replication.

Unraveling the pharmacodynamic substances and possible mechanism of Trichosanthis Pericarpium in the treatment of coronary heart disease based on plasma pharmacochemistry, network pharmacology and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Coronary heart disease (CHD) is a chronic disease that seriously threatens people's health and even their lives. Currently, there is no ideal drug without side effects for the treatment of CHD. Trichosanthis Pericarpium (TP) has been used for several years in the treatment of diseases associated with CHD. However, there is still a need for systematic research to unravel the pharmacodynamic substances and possible mechanism of TP in the treatment of coronary heart. AIM OF THE STUDY: The purpose of current study was to explore the pharmacodynamic substances and potential mechanisms of TP in the treatment of CHD via integrating network pharmacology with plasma pharmacochemistry and experimental validation. MATERIALS AND METHODS: The effect of TP intervention in CHD was firstly assessed on high-fat diet combined with isoprenaline-induced CHD rats and H2O2-induced H9c2 cells, respectively. Then, the LC-MS was utilized to identify the absorbed components of TP in the plasma of CHD rats, and this was used to develop a network pharmacology prediction to obtain the possible active components and mechanisms of action. Molecular docking and immunohistochemistry were used to explore the interaction between TP and key targets. Subsequently, the efficacy of the active ingredients was investigated by in vitro cellular experiments, and their metabolic pathways in CHD rats were further analyzed. RESULTS: The effects of TP on amelioration of CHD were verified by in vivo and in vitro experiments. Plasma pharmacochemistry and network pharmacology screened six active components in plasma including apigenin, phenylalanine, quercetin, linoleic acid, luteolin, and tangeretin. The interaction of these compounds with potential key targets AKT1, IL-1ß, IL-6, TNF-α and VEGFA were preliminarily verified by molecular docking. And immunohistochemical results showed that TP reduced the expression of AKT1, IL-1ß, IL-6, TNF-α and VEGFA in CHD rat hearts. Then cellular experiments confirmed that apigenin, phenylalanine, quercetin, linoleic acid, luteolin, and tangeretin were able to reduce the ROS level in H2O2-induced HUVEC cells and promote the migration and tubule formation of HUVEC cells, indicating the pharmacodynamic effects of the active components. Meanwhile, the metabolites of TP in CHD rats suggested that the pharmacological effects of TP might be the result of the combined effects of the active ingredients and their metabolites. CONCLUSION: Our study found that TP intervention in CHD is characterized by multi-component and multi-target regulation. Apigenin, phenylalanine, linoleic acid, quercetin, luteolin, and tangeretin are the main active components of TP. TP could reduce inflammatory response and endothelial damage by regulating AKT1, IL-1ß, IL-6, TNF-α and VEGFA, reduce ROS level to alleviate the oxidative stress situation and improve heart disease by promoting angiogenesis to regulate endothelial function. This study also provides an experimental and scientific basis for the clinical application and rational development of TP.

Fusion dsRNA designs incorporating multiple target sequences can enhance the aphid control capacity of an RNAi-based strategy.

BACKGROUND: RNA interference (RNAi) is the sequence-dependent suppression of gene expression by double-stranded RNA (dsRNA). This is a promising strategy for the control of insect pests because dsRNA can be rationally designed to maximize efficacy and biosafety, the latter by using sequences that are found in target pests but are safe for non-target insects. However, this has yet to be optimized in aphids, destructive sap-sucking pests that also transmit plant viruses. We used the green peach aphid (Myzus persicae) as a case study to optimize the efficiency of RNAi by applying a novel fusion dsRNA design. RESULTS: Comparative transcriptomics revealed a number of genes that are induced in feeding aphids, and eight candidate genes were chosen as RNAi targets. To improve RNAi efficiency, our fusion dsRNA design approach combined optimal gene fragments (highly conserved in several aphid species but with less homology in beneficial insects such as the predator ladybeetle Propylea japonica) from three candidate genes. We compared this RNAi-based biological control approach with conventional chemical control using imidacloprid. We found that the fusion dsRNA strategy inhibited the aphid population to a significantly greater extent than single-target RNAi and did not affect ladybeetle fitness, allowing an additive effect between RNAi and natural predation, whereas imidacloprid was harmful to aphids and ladybeetles. CONCLUSION: Our fusion dsRNA design approach enhances the ability of RNAi to control aphids without harming natural predators. © 2024 Society of Chemical Industry.

Fusion dsRNA in targeting salivary protein genes enhance the RNAi-based aphid control.

RNA interference (RNAi) is a promising tool for pest control and relies on sequence-specific gene silencing. Salivary proteins are cooperatively secreted into plants to guarantee the feeding of aphids; thus they have potential to develop as selective targets for RNAi-based pest control strategy. For this purpose, we firstly analyzed 18 salivary proteomes of various aphid species, and these salivary proteins can be mainly categorized into seven functional groups. Secondly, we created a work-flow for fusion dsRNA design that can target multiple genes but were selectively safe to beneficial insects. Based on this approach, seven fusion dsRNAs were designed to feed the green peach aphid, which induced a significant reduction in aphid fitness. Among them, ingestion of dsperoxidase induced the highest mortality in aphids, which was also significantly higher than that of traditional dsRNAs in targeting three peroxidases separately. In addition, dsperoxidase-fed green peach aphids triggered the highest H2O2 content of host plants as well as the attraction to natural enemies (ladybeetle and parasitic wasp) but repellent to other control aphids. Our results indicate that the fusion dsRNA design approach can improve aphid control capacity, and the fusion dsRNA targeting salivary protein-encoding genes can enhance the direct and indirect defenses of host plants, thus providing a new strategy for RNAi-based aphid control.

A method for quantifying relative competitive advantage and the combined effect of co-invasion for two invasive plants.

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Degradation Profiling of Nardosinone at High Temperature and in Simulated Gastric and Intestinal Fluids.

Nardosinone, a predominant bioactive product from Nardostachys jatamansi DC, is well-known for its promising therapeutic applications, such as being used as a drug on anti-inflammatory, antidepressant, cardioprotective, anti-neuroinflammatory, anti-arrhythmic, anti-periodontitis, etc. However, its stability under varying environmental conditions and its degradation products remain unclear. In this study, four main degradation products, including two previously undescribed compounds [2-deoxokanshone M (64.23%) and 2-deoxokanshone L (1.10%)] and two known compounds [desoxo-narchinol A (2.17%) and isonardosinone (3.44%)], were firstly afforded from the refluxed products of nardosinone in boiling water; their structures were identified using an analysis of the extensive NMR and X-ray diffraction data and the simulation and comparison of electronic circular dichroism spectra. Compared with nardosinone, 2-deoxokanshone M exhibited potent vasodilatory activity without any of the significant anti-neuroinflammatory activity that nardosinone contains. Secondly, UPLC-PDA and UHPLC-DAD/Q-TOF MS analyses on the degradation patterns of nardosinone revealed that nardosinone degraded more easily under high temperatures and in simulated gastric fluid compared with the simulated intestinal fluid. A plausible degradation pathway of nardosinone was finally proposed using nardosinonediol as the initial intermediate and involved multiple chemical reactions, including peroxy ring-opening, keto-enol tautomerization, oxidation, isopropyl cleavage, and pinacol rearrangement. Our findings may supply certain guidance and scientific evidence for the quality control and reasonable application of nardosinone-related products.

Characterizing and detecting delirium with clinical and computational measures of speech and language disturbance.

BACKGROUND: Delirium is a critically underdiagnosed syndrome of altered mental status affecting more than 50% of older adults admitted to hospital. Few studies have incorporated speech and language disturbance in delirium detection. We sought to describe speech and language disturbances in delirium, and provide a proof of concept for detecting delirium using computational speech and language features. METHODS: Participants underwent delirium assessment and completed language tasks. Speech and language disturbances were rated using standardized clinical scales. Recordings and transcripts were processed using an automated pipeline to extract acoustic and textual features. We used binomial, elastic net, machine learning models to predict delirium status. RESULTS: We included 33 older adults admitted to hospital, of whom 10 met criteria for delirium. The group with delirium scored higher on total language disturbances and incoherence, and lower on category fluency. Both groups scored lower on category fluency than the normative population. Cognitive dysfunction as a continuous measure was correlated with higher total language disturbance, incoherence, loss of goal and lower category fluency. Including computational language features in the model predicting delirium status increased accuracy to 78%. LIMITATIONS: This was a proof-of-concept study with limited sample size, without a set-aside cross-validation sample. Subsequent studies are needed before establishing a generalizable model for detecting delirium. CONCLUSION: Language impairments were elevated among patients with delirium and may also be used to identify subthreshold cognitive disturbances. Computational speech and language features are promising as accurate, noninvasive and efficient biomarkers of delirium.

The 100 most cited papers in nasopharyngeal carcinoma between 2000 and 2019: a bibliometric study.

Background: To identify the 100 most-cited papers that have contributed to the understanding and treatment of nasopharyngeal carcinoma (NPC). Methods: We searched the NPC-related papers between 2000 and 2019 using the Web of Science database on October 12, 2022. Papers were identified in descending order according to the number of citations. The top 100 papers were analyzed. Results: These 100 most cited papers on NPC have been cited for a total of 35,273 times, with a median number of citations of 281 times. There were 84 research papers and 16 review papers. The Journal of Clinical Oncology (n=17), International Journal of Radiation Oncology Biology Physics (n=13), and Cancer Research (n=9) published the most papers. Cancer Epidemiology Biomarkers & Prevention, Lancet, Cancer Cell, Molecular Cancer, and the New England Journal of Medicine had the largest average citations per paper. China contributed the most papers (n=71), followed by USA (n=13), Singapore (n=4) and, France (n=4). There were 55 clinical research papers and 29 laboratory research papers. Intensity-modulated radiation therapy technology (n=13), concurrent chemoradiotherapy (n=9), and neoadjuvant chemoradiotherapy (n=5) were the top three research topics. Epstein-Barr virus-related genes (n=9) and noncoding RNA (n=8) were the research domains in laboratory research papers. The top three contributors were Jun Ma (n=9), Anthony T C Chan (n=8), and Anne Wing-Mui Lee (n=6). Conclusions: This study provides an overview of the major areas of interest in the field of NPC with bibliometric analyses. This analysis recognizes some important contributions in the field of NPC and stimulates future investigations in the scientific community.

Validity and reliability of an Emotional Thermometer tool: an exploratory cross-sectional study.

INTRODUCTION: There are a few screening tools to detect psychological symptoms among people with multiple chronic conditions (MCCs) in China. AIM: The aim of this study was to examine the validity and reliability of a translated version of the Emotional Thermometer (ET) tool. MATERIALS AND METHODS: This cross-sectional study consisted of two phases: (1) translation and content validity testing; and (2) assessment of psychometric properties, including internal consistency, test-retest reliability, and construct validity. For the first phase, the authors used a forward-backward translation approach for the Chinese version of the instrument and tested its content validity with a panel of six experts. For the second phase, the data, including the ET tool and demographic characteristics were collected in a convenience sample of 197 Chinese people with MCCs recruited from a university hospital. The first 50 participants participated in the two-week retest. RESULTS: The Chinese version of the ET tool had satisfactory psychometric properties; content validity index (0.83), internal consistency (0.92), and ICC (0.93 to 0.98 [p < 0.01]). Principal component analysis showed that there was only one component with an eigenvalue greater than 1 (value = 3.80), with 76.67% of the variance responding. All items loaded significantly onto this factor and demonstrated strong loadings of > 0.70. CONCLUSION: The Chinese-version of the ET tool is psychometrically sound. It has the potential to be used as a screening tool for psychological symptoms in Chinese people with MCCs. IMPACT STATEMENT: Findings from testing the Chinese translation of the Emotional Thermometer indicate this could be a convenient and useful screening tool to detect psychological symptoms in patients with multiple chronic conditions.

Facility-Level Emissions and Synergistic Control of Energy-Related Air Pollutants and Carbon Dioxide in China.

Boilers involve ∼60% of primary energy consumption in China and emit more air pollutants and CO2 than any other infrastructures. Here, we established a nationwide, facility-level emission data set considering over 185,000 active boilers in China by fusing multiple data sources and jointly using various technical means. The emission uncertainties and spatial allocations were significantly improved. We found that coal-fired power plant boilers were not the most emission-intensive boilers with regard to SO2, NOx, PM, and mercury but emitted the highest CO2. However, biomass- and municipal waste-fired combustion, regarded as zero-carbon technologies, emitted a large fraction of SO2, NOx, and PM. Future biomass or municipal waste mixing in coal-fired power plant boilers can make full use of the advantages of zero-carbon fuel and the pollution control devices of coal-fired power plants. We identified small-size boilers, medium-size boilers using circulating fluidized bed boilers, and large-size boilers located in China's coal mine bases as the main high emitters. Future focuses on high-emitter control can substantially mitigate the emissions of SO2 by 66%, NOx by 49%, PM by 90%, mercury by 51%, and CO2 by 46% at the most. Our study sheds light on other countries wishing to reduce their energy-related emissions and thus the related impacts on humans, ecosystems, and climates.

Latent Factors of Language Disturbance and Relationships to Quantitative Speech Features.

BACKGROUND AND HYPOTHESIS: Quantitative acoustic and textual measures derived from speech ("speech features") may provide valuable biomarkers for psychiatric disorders, particularly schizophrenia spectrum disorders (SSD). We sought to identify cross-diagnostic latent factors for speech disturbance with relevance for SSD and computational modeling. STUDY DESIGN: Clinical ratings for speech disturbance were generated across 14 items for a cross-diagnostic sample (N = 334), including SSD (n = 90). Speech features were quantified using an automated pipeline for brief recorded samples of free speech. Factor models for the clinical ratings were generated using exploratory factor analysis, then tested with confirmatory factor analysis in the cross-diagnostic and SSD groups. The relationships between factor scores and computational speech features were examined for 202 of the participants. STUDY RESULTS: We found a 3-factor model with a good fit in the cross-diagnostic group and an acceptable fit for the SSD subsample. The model identifies an impaired expressivity factor and 2 interrelated disorganized factors for inefficient and incoherent speech. Incoherent speech was specific to psychosis groups, while inefficient speech and impaired expressivity showed intermediate effects in people with nonpsychotic disorders. Each of the 3 factors had significant and distinct relationships with speech features, which differed for the cross-diagnostic vs SSD groups. CONCLUSIONS: We report a cross-diagnostic 3-factor model for speech disturbance which is supported by good statistical measures, intuitive, applicable to SSD, and relatable to linguistic theories. It provides a valuable framework for understanding speech disturbance and appropriate targets for modeling with quantitative speech features.

Does servitization of industrial structure adversely affect the quality of economic development? Evidence from China.

China is shifting from focusing on speed of economic development to quality development. As the proportion of service industry increases, the impact of servitization of industrial structure on high-quality development urgently needs to be clarified. This paper for the first time uses the panel data of 280 prefecture-level cities ranging from 2003 to 2019 in China, applies the dynamic panel Generalized Method of Moment (GMM) estimation method, employs labor productivity, average wage, and environmental pollution as intermediary variables, and analyzes how servitization of industrial structure affects the quality of economic development. The results show that there is a U-shaped effect for servitization of industrial structure on quality of economic development. The higher the initial level of servitization of industrial structure, the weaker the negative effect for servitization of industrial structure on the quality of economic development. When the initial level of the former is high enough, it can promote the latter. Moreover, the effects differ by region. Furthermore, negative effect of the service-oriented trend of industrial structure on economic development quality is weakened by improving the overall labor productivity and reducing environmental pollution, while it is strengthened by reducing the average wage level. As such, we propose that it is necessary to further promote the rationalization of the industrial structure, promote the optimization of the development of the industrial structure, and to promote the effective allocation of resources.

Clinical and computational speech measures are associated with social cognition in schizophrenia spectrum disorders.

In this study, we compared three domains of social cognition (emotion processing, mentalizing, and attribution bias) to clinical and computational language measures in 63 participants with schizophrenia spectrum disorders. Based on the active inference model for discourse, we hypothesized that emotion processing and mentalizing, but not attribution bias, would be related to language disturbances. Clinical ratings for speech disturbance assessed disorganized and underproductive dimensions. Computational features included speech graph metrics, use of modal verbs, use of first-person pronouns, cosine similarity of adjacent utterances, and measures of sentiment; these were represented by four principal components. We found that higher clinical ratings for disorganized speech were predicted by greater impairments in both emotion processing and mentalizing, and that these relationships remained significant when accounting for demographic variables, overall psychosis symptoms, and verbal ability. Similarly, a computational speech component reflecting insular speech was consistently predicted by impairment in emotion processing. There were notable trends for computational speech components reflecting underproductive speech and decreased content-rich speech predicting mentalizing ability. Exploratory longitudinal analyses in a small subset of participants (n = 17) found that improvements in both emotion processing and mentalizing predicted improvements in disorganized speech. Attribution bias did not demonstrate strong relationships with language measures. Altogether, our findings are consistent with the active inference model of discourse and suggest greater emphasis on treatments that target social cognitive and language systems.

[Analysis of clinical features and EBF3 gene variant in a child with hypotonia, ataxia and developmental delay].

OBJECTIVE: To explore the genetic basis for a child featuring hypotonia, ataxia, and delayed development syndrome (HADDS). METHODS: Whole exome sequencing was carried out for the child. Candidate variant was verified by Sanger sequencing of the child and his parents. RESULTS: The child was found to harbor a de novo heterozygous c.625G>A (p.Arg209Trp) variant of the EBF3 gene, which has caused substitution of Arginine by Tryptophan. The variant may has impaired the binding affinity of EBF3 with DNA and altered its subcellular localization, and ultimately decreased the transcriptional activity of the EBF3 gene. CONCLUSION: The c.625G>A variant of the EBF3 gene probably underlay the pathogenesis of HADDS in this child. Above finding has expanded the spectrum of EBF3 variants and enriched the clinical manifestations of the HADDS.

Case Report: Chinese female patients with a heterozygous pathogenic RPS6KA3 gene variant c.898C>T and distal 22q11.2 microdeletion.

Background: Coffin-Lowry syndrome (CLS) [OMIM#303600] is a rare X-linked dominant syndrome. CLS is caused by highly heterogeneous loss-of-function mutations in the RPS6KA3 gene (OMIM*300,075). CLS is characterized by intellectual disability (ID), short stature, tapered fingers, characteristic facial features, and progressive skeletal changes. Distal 22q11.2 microdeletion syndrome (OMIM#611867) is an autosomal dominant and recurrent genomic disorder. It mainly includes three types [distal type I (D-E/F), type II (E-F), and type III (F-G)] and exhibits variable clinical phenotypes (mild, moderate, or even normal): preterm birth, pre- and/or postnatal growth restriction, development delay, ID, behavioral problems, cardiovascular defects, skeletal anomalies, and dysmorphic facial features. We investigated the genetic etiology of a Chinese pedigree with ID, short stature, digit abnormalities, facial dysmorphism, and menstrual disorder. A heterozygous RPS6KA3 gene variant c.898C>T (p.R300X) was identified in this familial case. Two female CLS patients with distal 22q11.2 microdeletion presented with more severe clinical phenotypes. We provided clinical characteristics of these Chinese female CLS patients. Case presentation: We described a Chinese family with three affected females (the mother, the elder sister, and the proband). The mother and the elder sister had more severe clinical phenotypes (moderate facial dysmorphism, more severe cognitive impairment, and shorter stature). The common characteristic phenotypes are ID, short stature, facial dysmorphism, irregular menstruation, and cardiovascular disorders. Peripheral blood samples were collected from the pedigree. Whole-exome sequencing (WES) identified a heterozygous nonsense RPS6KA3 gene variant c.898C>T (p.R300X). It was verified by Sanger sequencing. Copy number variation sequencing (CNV-seq) showed that both the mother and the elder sister carried a CNVseq [hg19] del (22) (q11.22-q11.23) (22997582-23637176)×0.5. RNA from peripheral blood samples was used for measuring the relative quantification of mRNA (expressed by exon 14 of RPS6KA3). The levels of mRNA relative expressions were significantly lower in the mother's and the elder sister's blood samples. The levels of mRNA relative expressions were significantly higher in the proband's blood sample. X-chromosome inactivation (XCI) studies demonstrated that the proband showed extremely skewed XCI, and the XCI pattern of the elder sister was random. Conclusion: Herein, we reported three Chinese female patients with a heterozygous nonsense RPS6KA3 gene variant c.898C>T. Further genetic studies were performed. To our knowledge, Chinese patients with this variant have not been previously reported in the literature. The three female patients presented with variable degrees of severity. The clinical characteristics of these Chinese female CLS patients could expand the phenotypic spectrum of CLS. We helped physicians to understand the genotype-phenotype correlation further.

A novel 16-gene alternative mRNA splicing signature predicts tumor relapse and indicates immune activity in stage I-III hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a lethal disease with high relapse and dismal survival rates. Alternative splicing (AS) plays a crucial role in tumor progression. Herein, we aim to integratedly analyze the relapse-associated AS events and construct a signature predicting tumor relapse in stage I-III HCC. Methods: AS events of stage I-III HCC with tumor relapse or long-term relapse-free survival were profiled to identify the relapse-associated AS events. A splicing network was set up to analyze the correlation between the relapse-associated AS events and splicing factors. Cox regression analysis and receiver operating characteristic curve were performed to develop and validate the relapse-predictive AS signature. Single-sample gene set enrichment analysis (ssGSEA) and the ESTIMATE algorithm were used to assess the immune infiltration status of the HCC microenvironment between different risk subgroups. Unsupervised cluster analysis was conducted to assess the relationship between molecular subtypes and local immune status and clinicopathological features. Results: In total, 2441 ASs derived from 1634 mRNA were identified as relapse-associated AS events. By analyzing the proteins involved in the relapse-associated AS events, 1573 proteins with 11590 interactions were included in the protein-protein interaction (PPI) network. In total, 16 splicing factors and 61 relapse-associated AS events with 85 interactions were involved in the splicing network. The relevant genes involved in the PPI network and splicing network were also analyzed by Gene Ontology enrichment analysis. Finally, we established a robust 16-gene AS signature for predicting tumor relapse in stage I-III HCC with considerable AUC values in all of the training cohort, testing cohort, and entire cohort. The ssGSEA and ESTIMATE analyses showed that the AS signature was significantly associated with the immune status of the HCC microenvironment. Moreover, four molecular subgroups with distinguishing tumor relapse modes and local immune status were also revealed. Conclusion: Our study built a novel 16-gene AS signature that robustly predicts tumor relapse and indicates immune activity in stage I-III HCC, which may facilitate the deep mining of the mechanisms associated with tumor relapse and tumor immunity and the development of novel individualized treatment targets for HCC.

A Single Vaccination of Chimeric Bivalent Virus-Like Particle Vaccine Confers Protection Against H9N2 and H3N2 Avian Influenza in Commercial Broilers and Allows a Strategy of Differentiating Infected from Vaccinated Animals.

H9N2 and H3N2 are the two most important subtypes of low pathogenic avian influenza viruses (LPAIV) because of their ongoing threat to the global poultry industry and public health. Although commercially available inactivated H9N2 vaccines are widely used in the affected countries, endemic H9N2 avian influenza remains uncontrolled. In addition, there is no available avian H3N2 vaccine. Influenza virus-like particles (VLPs) are one of the most promising vaccine alternatives to traditional egg-based vaccines. In this study, to increase the immunogenic content of VLPs to reduce production costs, we developed chimeric bivalent VLPs (cbVLPs) co-displaying hemagglutinin (HA) and neuraminidase (NA) of H9N2 and H3N2 viruses with the Gag protein of bovine immunodeficiency virus (BIV) as the inner core using the Bac-to-Bac baculovirus expression system. The results showed that a single immunization of chickens with 40µg/0.3mL cbVLPs elicited an effective immune response and provided complete protection against H9N2 and H3N2 viruses. More importantly, cbVLPs with accompanying serological assays can successfully accomplish the strategy of differentiating infected animals from vaccinated animals (DIVA), making virus surveillance easier. Therefore, this cbVLP vaccine candidate would be a promising alternative to conventional vaccines, showing great potential for commercial development.

Who does what to whom? graph representations of action-predication in speech relate to psychopathological dimensions of psychosis.

Graphical representations of speech generate powerful computational measures related to psychosis. Previous studies have mostly relied on structural relations between words as the basis of graph formation, i.e., connecting each word to the next in a sequence of words. Here, we introduced a method of graph formation grounded in semantic relationships by identifying elements that act upon each other (action relation) and the contents of those actions (predication relation). Speech from picture descriptions and open-ended narrative tasks were collected from a cross-diagnostic group of healthy volunteers and people with psychotic or non-psychotic disorders. Recordings were transcribed and underwent automated language processing, including semantic role labeling to identify action and predication relations. Structural and semantic graph features were computed using static and dynamic (moving-window) techniques. Compared to structural graphs, semantic graphs were more strongly correlated with dimensional psychosis symptoms. Dynamic features also outperformed static features, and samples from picture descriptions yielded larger effect sizes than narrative responses for psychosis diagnoses and symptom dimensions. Overall, semantic graphs captured unique and clinically meaningful information about psychosis and related symptom dimensions. These features, particularly when derived from semi-structured tasks using dynamic measurement, are meaningful additions to the repertoire of computational linguistic methods in psychiatry.

Application of Extracorporeal Membrane Oxygenation in Patients With Severe Acute Respiratory Distress Syndrome Caused by Pneumocystis jirovecii Pneumonia Following Kidney Transplantation: A Case Series.

Objective: To investigate the application effect of extracorporeal membrane oxygenation (ECMO) in patients with severe acute respiratory distress syndrome (ARDS) caused by Pneumocystis jirovecii pneumonia (PJP) after kidney transplantation. Methods: This is a case series on 10 kidney transplant recipients with severe ARDS caused by PJP at the People's Hospital of Zhengzhou, who were enrolled as the case group. A total of 17 cases of PJP diagnosed with severe ARDS without ECMO were selected as the control group. The timing and mode of ECMO support and treatment complications were summarized. The primary aim of this study was mortality and secondary was imaging and complications. Results: The enrolled patients' oxygenation index before the start of ECMO ranged from 25 to 92, and the time from admission to the start of ECMO was 1-17 days, with an average of 5.56 days. In the case group, one patient died of hemorrhagic shock due to abdominal hemorrhage, but the other nine patients were successfully weaned from ECMO. Of these patients, one died due to sepsis following weaning. The survival rate in the case group was 80.0% (8/10), and the survival rate in the control group was 35.29% (6/17). The vein-vein ECMO support time in the nine successfully weaned patients in the case group ranged from 131 to 288 h, with an average of 215.5 h. Of the eight patients who survived, deterioration of renal function after transplantation occurred in two patients, but no fatal complications occurred. Conclusion: Overall, Patients with severe ARDS caused by postoperative PJP infection following kidney transplantation have a poor prognosis. The mortality was lower in patients who were treated with ECMO compared to standard care.