Linear Score Research Articles

Abstract 4122763: Health Status Outcomes of Antianginal Therapies in Patients After Coronary Revascularization: Insights From the GREAT Disease Registry Study

Background: The impact of antianginal therapies on the health status of coronary artery disease (CAD) patients who have undergone coronary revascularization has not been extensively researched. This study aimed to investigate the effect of nicorandil on the health status in patients after coronary revascularization, measured by the Seattle Angina Questionnaire (SAQ). Methods: We analyzed data from 1,556 patients enrolled in the GREAT Disease Registry Study (Clinicaltrial No. NCT05050773) between September 2021 and May 2022. Changes in SAQ summary score (SAQ-SS) from baseline to 3, 6, 9, and 12 months were assessed. Statistical methods included a linear mixed-effects model and propensity score matching (PSM) for comparative analysis. Results: Among the 1,038 patients receiving revascularization analyzed (22.7% female; mean age [SD], 59.9 [10.2] years), 648 (62.4%) received nicorandil, while 390 (37.6%) did not. In the linear mixed-effects model analysis, statistically significant improvements were observed with nicorandil in SAQ-SS across all time points ( Table 1 ), indicating beneficial effects of nicorandil on health status outcomes after revascularization. Sensitive analysis was conducted using the PSM method. After PSM adjustment, both groups comprised 321 patients each. The change in SAQ-SS from baseline to 12 months was significantly greater in the nicorandil group (19.2 ± 14.06 points) compared to the non-nicorandil group (14.91 ± 12.9 points, p < 0.001). Conclusions: These findings indicated that nicorandil is associated with improved health status outcomes in CAD patients who have undergone coronary revascularization.

On the Relationship Among Linear Type Traits and Functional Longevity in the Italian Mediterranean Buffalo Using a Weibull Proportional Hazards Model

Weibull proportional hazards model was used to identify the non-genetic effects that affect length of productive life (LPL) of the Italian Mediterranean Buffalo (IMB). Data were provided by the Italian National Association of Buffalo Breeders (ANASB) and included records of reproductive, productive, and linear type traits from 59,943 buffalo with first calving from 2002 to 2019. Data were divided into 4 geographical regions to determine if the relationship between the investigated effects and LPL varied by region. LPL was defined as the number of days from the first calving to culling for those buffaloes that were culled (uncensored) or to the date of the last test-day for those that are still alive (censored). The Weibull model included time-dependent effects of herd-year-season of calving, parity and stage of lactation, production as within-herd deviations, as well as time-independent effects of age at first calving, year of birth, type of reproduction (natural mating vs artificial insemination), classifier and ten linear type traits. The average duration of productive life was 1,604 days. Both year of birth and production level had a significant effect on culling risk. Moreover, culling risk decreased linearly across parities. The reference point for age at first calving relative to other classes was set at 35 months. A significant relationship between linear type traits and relative culling risk was also observed, being highest for buffaloes with the lowest linear scores. The results show that the Weibull model provides consistent and robust risk estimates. Therefore, this model would be recommended for future implementation of the first genetic evaluation of LPL in the Italian Mediterranean Buffalo.

Influence of different types of interclass ability grouping on students’ academic achievement in mathematics: evidence from the Confucian Asian cluster

ABSTRACT Ability grouping has attracted worldwide attention in relation to various subjects among different countries and regions. However, few studies have focused on the relationship between ability grouping and students’ mathematical academic achievement in the Confucian Asian countries. Thus, in this study, we aimed to determine how different types of interclass ability grouping impact students’ academic achievement in mathematics. We analysed PISA2022 data for 34,968 students from 923 schools in six countries and regions, including Hong Kong, Macau, Taipei, Japan, South Korea, and Singapore, using a hierarchical linear model and propensity score matching. We found that overall, multi-level ability grouping reduced students’ mathematics achievement, and this negative effect was particularly significant among high-ability students, while it promoted the mathematics achievement of low-ability students to some extent.

The delineation of management zones using soil quality indices for the cultivation of irrigated rice (Oryza sativa L.) in Huila, Colombia

Conventional intensive farming systems can result in degraded soil. It is therefore important to monitor this effect periodically by delineating management zones (MZ) based on soil quality indices (SQI) in order to maintain and improve the soil characteristics in a precision farming environment and obtain homogeneous rice yields. The aim of this study was to determine and spatialise SQI and delineate MZ for cultivating flooded rice in an area of Fluvisols in Huila, Colombia. Forty-one georeferenced soil samples were collected from the 0 to 20 cm layer, and the physical, chemical and biological attributes of the soil were analysed to calculate the Integrated Quality Index (IQI) and the Nemoro Quality Index (NQI) using linear scoring functions. Geostatistical tools were then used to fit semivariogram models of the SQI, and interpolated using ordinary kriging to map the MZ using the QGIS software. The IQI and NQI showed a moderate spatial correlation, which allowed three distinct MZ to be identified and delineated. Attributes, such as bulk density (Bd), total porosity (TP), soil respiration (SR), available water (AW) and soil organic matter (SOM) were significant and can be used as a guide by farmers for restoring the quality of the soil in rice production. The method proved to be effective, and provided an information base to be used in the local management of areas of rice cultivation in the study region.

Does vibrotactile biofeedback for postural control interfere with cognitive processes?

BackgroundDirectional vibrotactile biofeedback for balance control can be instructed in the form of Repulsive (to move in the opposite direction of vibrations) or Attractive (to move in the direction of vibrations) stimulus encodings. However, which of these encodings is less cognitively demanding and poses less interference with high-level cognitive processes of conflict resolution remains unresolved.MethodsIn two between-subject studies with 30 (16 females) and 35 (23 females) healthy young adults, respectively, we investigated the cognitive load of Attractive and Repulsive vibrotactile biofeedback on 1) working memory (Study I) and 2) cognitive conflict resolution (Study II). Both studies also examined the effectiveness of both feedback stimulus encodings on balance control during quiet standing with eyes closed.ResultsBoth Attractive and Repulsive vibrotactile biofeedback increased balance stability (reduced trunk sway variability) in both the working memory and the conflict resolution study (Study I and II, respectively) with a greater increase of stability for the Repulsive encoding during multitasking demanding cognitive conflict resolution (Study II). Cognitive costs, measured in terms of the Linear Integrated Speed-Accuracy Score (LISAS), were greater for the Attractive encoding during multitasking with working memory demands. When cognitive conflict resolution was required as a secondary cognitive task, both stimulus encodings increased cognitive costs equally.ConclusionsThe effects of instructed Repulsive and Attractive stimulus encodings for the response-related interpretation of vibrotactile biofeedback of body sway were contrasted with respect to cognitive processing demands and balance stabilisation benefits. Both encodings improved balance stability but at certain cognitive costs. Regarding interference with specific high-level cognitive processes, however, a distinction has to be made between both encodings. Repulsive feedback encoding seems to cause less cognitive costs on working memory load and slightly greater stabilisation when cognitive conflict resolution is required. These results are discussed in the context of the known benefits of avoidance actions on cognitive control.

Enhancing health assessments with large language models: A methodological approach.

Health assessments have long been a significant research topic within the field of health psychology. By analyzing the results of subject scales, these assessments effectively evaluate physical and mental health status. Traditional methods, based on statistical analysis, are limited in accuracy due to their reliance on linear scoring methods. Meanwhile, machine learning approaches, despite their potential, have not been widely adopted due to their poor interpretability and dependence on large amounts of training data. Recently, large language models (LLMs) have gained widespread attention for their powerful natural language understanding capabilities, offering a viable solution to these issues. This study investigates the application of LLMs in enhancing physical and mental health assessments, introducing ScaleLLM. ScaleLLM employs language and knowledge alignment to turn LLMs into expert evaluators for health psychology scales. Experimental results indicate that ScaleLLM can improve the accuracy and interpretability of health assessments.

Development and validation of the 5-Dimension Comprehensive Assessment Scale (5DCAS) for assessing physical function and health in axial spondyloarthritis.

To describe the development and validation of a novel patient reported scale, which is a comprehensive assessment of the physical function and health specific for patients with axial spondyloarthritis (axSpA). This is a multiphase, mixed methods study. Based on opinion collection and discussions of multidisciplinary consensus meetings and patients, an initial item pool covering all of the ranges of functioning was generated. The item optimization, model fit, response category functioning, differential item functioning, reliability, structure validity, and unidimensionality were tested by confirmatory factor analysis and Rasch measurement theory framework. After the consensus meeting and the two rounds of surveys in patients with axSpA, the initial pool of 135 items was reduced to 25 items formed in five dimensions, which exhibited preferable item reliability, item fit, and person fit to the Rasch model. The Five-Dimensional Comprehensive Assessment Scale (5DCAS) had the best reliability and validity (Kaiser-Meyer-Olkin was 0.919, and the standardized Cronbach's α coefficient was 0.932). The final version of 5DCAS had good unidimensionality, and the Person Separation Index ranged from 0.77 to 0.85. 5DCAS significantly correlated with ASAS-HI, SF-36, BASFI, and disease activity with p values of < 0.001. 5DCAS is a novel patient-reported outcome specific to axSpA, and it forms five dimensions providing a linear sum score of 25 items. 5DCAS comprehensively and significantly represents the physical function and health status of patients with axSpA, although its performance needs further validation in future clinical practices. Key Points • The primary goal in the management of axial spondyloarthritis is to maximize health-related quality of life. Except for the current instruments of ASAS-HI, BASFI, or SF-36, the heterogeneous clinical symptoms and rapid updated treat-to-target concept require a new instrument which can comprehensive and significant evaluate the changes of physical function and health-related quality of life due to disease. • 5DCAS is a novel patient-reported outcome specific to axSpA, and it forms five dimensions providing a linear sum score of 25 items, which contained aspect of pain involvement, spine mobility, global body performance and activity, social participation and environment, and mental health. All of the items were set to a 4-point semantic rating scale measuring severity, frequency, or interference from score 0 to 3. Total 5DCAS score ranges from 0 to 75; higher scores represented greater symptom burden and worse physical function. • 5DCAS is a comprehensive, multidisciplinary, and convenient disease outcome measurement specific for axSpA. It provides a new evaluation instrument in clinical trial and treat-to-target clinical remission for patients and physicians, and also provides a sensitive and accurate assessment standard for optimized health benefits.

Leapfrogging Sycamore: Harnessing 1432 GPUs for 7× faster quantum random circuit sampling

Abstract Random quantum circuit sampling serves as a benchmark to demonstrate quantum computational advantage. Recent progress in classical algorithms, especially those based on tensor network methods, has significantly reduced the classical simulation time and challenged the claim of the first-generation quantum advantage experiments. However, in terms of generating uncorrelated samples, time-to-solution, and energy consumption, previous classical simulation experiments still underperform the Sycamore processor. Here we report an energy-efficient classical simulation algorithm, using 1432 GPUs to simulate quantum random circuit sampling which generates uncorrelated samples with higher linear cross entropy score and is 7 times faster than the Sycamore 53 qubits experiment. We propose a post-processing algorithm to reduce the overall complexity, and integrate state-of-the-art high-performance general-purpose GPU to achieve two orders of lower energy consumption compared to previous works. Our work provides the first unambiguous experimental evidence to refute Sycamore’s claim of quantum advantage, and redefines the boundary of quantum computational advantage using random circuit sampling.

Early prediction of milk yield from Holstein-Friesian cow lactation in Querétaro, Mexico

Objective: To obtain a machine learning (ML) model to predict the milk yield adjusted to 305 d (MY305) from the same lactation period. Design/methodology/approach: A database of test days (TD) was used, made up by 11,892 records of daily milk production from cows with more than 150 days in milk (DIM), from 19 barns in Querétaro, Mexico. The milk production was standardized to specific DIMs (5, 10, 20, 30 and 40) and estimations of MY305 were obtained with these, using ML models. The following were incorporated as explicative variables of the herd: month of birth of the cow, month of start of lactation, number of lactation, number of days for three daily milking events, and the two first linear scores of somatic cells. Results: The best goodness of fit was achieved with ensemble models, obtaining a deviance of 1503584 in the training with 80% of data chosen randomly, while with 20% of the data reserved to evaluate the deviance model it was 1576776. The rate between data observed and predictions of MY305 of the ensemble models had a coefficient of determination of r2 = 0.79 and RMSE of 1256. In the best individual model (deviance of 2281420) of ‘deep learning’ type, the most important variables were daily milk production of 30, 10, 5 and 20 DIM (19.9, 16.6, 16.2 and 12.8%, respectively). Limitations on study/implications: The value of RMSE is high, although the TD databases are generated systematically and usually there are not many barns represented. Findings/conclusions: For the database examined, milk production in the early phase of lactation together with a set of automatic learning models resulted in an adequate prediction of MY305.

Effect of Different Approaches of Nutrient Application on Soil Quality Index Under Maize-Wheat Cropping System in Mollisol Region of Uttarakhand

ABSTRACT A field experiment was conducted at GBPUA&T, Pantnagar, to study the effect of different approaches of nutrient application on soil fertility and soil quality under maize-wheat cropping system. Nine treatment combinations were compared namely, Recommended Doses of Fertilizers (RDF), Soil Test Crop Response (STCR), and various combinations of organic and inorganic fertilizers. This paper aims to develop Soil Quality Index (SQI) based on Minimum Data Set (MDS) using Principal Component Analysis (PCA). Different indicators were employed to formulate the SQI, derived from surface soil layer measurements (0–15 cm). Each MDS indicator was then converted into a dimensionless score using linear scoring function and then integrated into SQI. Results showed that the key soil quality indicators identified as MDS using PCA under maize-wheat cropping system were Water Holding Capacity, organic carbon, available N and dehydrogenase activity. These soil quality indicators were found to be best for monitoring soil health status. After rabi wheat 2019–2020, SQI varied from 1.22 to 2.21 across the treatments whereas, after rabi wheat 2020–2021, SQI varied from 1.13 to 2.23 across the treatments. Among different approaches of nutrient application, STCR-based use of fertilizers along with FYM (T4) helped in maintaining better soil physical, chemical and biological properties and ultimately sustaining soil quality, which was followed by the treatment receiving 75% STCR dose of N (inorganic mode) + full P and K (T5). Integration of organics with inorganic fertilizers maintained soil quality, environmental health and reduced greater dependency on chemical fertilizers.

Empathy Unmasked: Patient Perception of Physician Empathy in an Oncologic Emergency Setting. A Randomized Controlled Trial Comparing Personal Protective Equipment Wear versus Unmasked Video Communication

BackgroundAmidst the COVID-19 pandemic, telemedicine emerged as an important option that supports and facilitates clinical practice, however, its usefulness in emergency settings that treat patients with cancer is unclear. ObjectiveTo evaluate patient perception of physician empathy in an emergency oncology setting, comparing video interaction to an in-person with personal protective equipment (PPE) approach. MethodsIn this single-center, prospective, cross-sectional, survey-based randomized controlled trial, patients were randomized 1:1 for the concluding conversation done in-person which included either interacting with physicians wearing PPE or video interaction with physicians without PPE (virtual). Patients’ perceptions of the physicians’ relational empathy were assessed and compared for each group by using the Consultation and Relational Empathy (CARE) Measure and the Perception of Physician Compassion measure. ResultsPatients (n=106) in both the PPE and virtual arms provided favorable responses to all questions. The mean overall CARE scores for the PPE and virtual arms were 45.02 and 44.43, respectively (difference, 0.58 [95% CI: -2.10, 3.30]). Regarding the linear physician compassion scores, patients in the virtual arm appeared to consider physicians to be warmer (difference, -0.42 [95% CI: -0.87, 0.04]) but less pleasant (difference, 0.33 [95% CI: -0.40, 1.10]) than did patients in the PPE arm. ConclusionsCancer patients presenting to the emergency department perceive empathy and compassion equally when approached by physicians virtually without PPE or in person while wearing PPE. Virtual services for specific aspects of clinical practice during emergency department visits in an oncology setting can be implemented to ensure safer interactions between patients and physicians without compromising the physician-patient relationship.

Rumen-protected methionine supplementation during the transition period under artificially induced heat stress: Effects on cow-calf performance

This study aimed to evaluate the effects of rumen-protected Met on lactation performance, inflammation and immune response, and liver glutathione of lactating dairy cows during a subclinical mastitis challenge (SMC). Thirty-two Holstein cows (145 ± 51 DIM) were enrolled in a randomized complete block design. At -21 d relative to the SMC, cows were assigned to dietary treatments, and data were collected before and during the SMC. Cows were blocked according to parity, DIM, and milk yield and received a basal diet (17.4% CP; Lys 7.01% MP and Met 2.14% MP) plus 100 g/d of ground corn (CON; n = 16) or a basal diet plus 100 g/d of ground corn and rumen-protected Met (SM, Smartamine M at 0.09% of dietary DM; n = 16), fed as a top-dress. At 0 d, the mammary gland's rear right quarter was infused with 100,000 cfu of Streptococcus uberis (O140J). Milk yield was recorded twice daily from 0 until 3 d relative to SMC. Milk samples were collected during each milking from 0 to 3 d relative to SMC, blood samples were collected at 0, 6, 12, 24, 48, and 72 h relative to SMC. The mTOR pathway activation was assessed in immune cells in blood and milk samples by measuring quantity and phosphorylation status of mTOR-related proteins, including AKT, S6RP, and 4EBP1. For the ratio of phosphorylated to total AKT, S6RP, and 4EBP1, blood samples were collected at 0, 12, and 24 h, and milk samples at 24 h relative to SMC. Liver biopsies were performed at -10 d and 24 h relative to SMC for measurement of glutathione. Linear mixed models with repeated measures were used to analyze the results. There was a trend for greater milk yield per milking (+ 0.8 kg) and per day (+1.7 kg) after SMC in SM cows compared with CON. The DMI was not affected by dietary treatments. Reactive oxygen metabolites (ROM) were lower in SM cows than in CON. Milk somatic cell linear score was not affected by dietary treatments, and a score >4 at 24 h confirmed subclinical mastitis. The SM cows had greater milk fat percentage at 24 and 36 h post SMC, resulting in overall greater milk fat. Milk protein tended to be greater in SM cows than in CON. We observed greater liver glutathione in SM cows than in CON. Among inflammation biomarkers, ceruloplasmin was lower for SM cows compared with CON. In milk, greater pAKT:AKT and pS6RP:S6RP ratios were observed in immune cell populations from SM cows compared with CON. Blood neutrophils had a greater p4EBP1:4EBP1 ratio in SM cows compared with CON. Overall, our results show that Met supplementation during an SMC positively affected milk performance, lowered the risk of oxidative stress, and attenuated inflammation partially by increasing liver glutathione and immune cells' protein synthesis via mTOR signaling.

Humoral immune responses primed by the alteration of gut microbiota were associated with galactose-deficient IgA1 production in IgA nephropathy.

Galactose-deficient IgA1 (GdIgA1) is critical in the formation of immunodeposits in IgA nephropathy (IgAN), whereas the origin of GdIgA1 is unknown. We focused on the immune response to fecal microbiota in patients with IgAN. By running 16S ribosomal RNA gene sequencing, we compared IgAN samples to the control samples from household-matched or non-related individuals. Levels of plasma GdIgA1 and poly-IgA complexes were measured, and candidate microbes that can either incite IgA-directed antibody response or degrade IgA through specific IgA protease activities were identified. The IgAN group showed a distinct composition of fecal microbiota as compared to healthy controls. Particularly, high abundance of Escherichia-Shigella was associated with the disease group based on analyses using receiver operating characteristic (area under curve, 0.837; 95% CI, 0.738-0.914), principle coordinates, and the linear discriminant analysis effect size algorithm (linear discriminant analysis score, 4.56; p < 0.001). Accordingly, the bacterial levels directly correlated with high titers of plasma GdIgA1(r = 0.36, p < 0.001), and patients had higher IgA1 against stx2(2.88 ± 0.46 IU/mL vs. 1.34 ± 0.35 IU/mL, p = 0.03), the main antigen of Escherichia-Shigella. Conversely, the healthy controls showed relatively higher abundance of the commensal bacteria that produce IgA-degrading proteases. Particularly, the abundance of some intestinal bacteria expressing IgA proteases showed an inverse correlation with the levels of plasma GdIgA1 in IgAN. Our data suggest that mucosal IgA production, including those of GdIgA1, is potentially linked to the humoral response to gut Escherichia-Shigella as one of the sources of plasma GdIgA1. Conversely, the IgA protease-producing microbiota in the gut are suppressed in patients with IgAN.

Linear Logistic Scoring Equations for Latent Class and Latent Profile Models: A Simple Method for Classifying New Cases

Researchers are often interested in using latent class or latent profile parameter estimates to obtain posterior class membership probabilities for observations other than those of the original sample. In this paper, we demonstrate that these probabilities typically take on the form of linear logistic equations with coefficients which are functions of the original model parameters. In other words, the posterior class membership probabilities can be computed with a prediction formula similar to that of a multinomial logistic regression model. We derive the scoring equations for nominal, ordinal, count, and continuous indicators, as well as investigate models with missing values on class indicators, local dependencies, covariates, or multiple latent variables. In addition to the mathematical derivations of the scoring equations, we describe how either exact or approximate scoring equations can be obtained by estimating a multinomial regression model using a weighted data set.

The MindMoves Trial: Cross-Sectional Analyses of Baseline Vascular Risk and Cognition in Older Women with Cardiovascular Disease.

Vascular diseases, including atherosclerotic cardiovascular disease (ASCVD) and stroke, increase the risk of Alzheimer's disease and cognitive impairment. Serum biomarkers, such as brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and insulin-like growth factor 1 (IGF-1), may be indicators of cognitive health. We examined whether vascular risk was associated with levels of cognition and serum biomarkers in older women with cardiovascular disease (CVD). Baseline data from a lifestyle trial in older women (n = 253) with CVD (NCT04556305) were analyzed. Vascular risk scores were calculated for ASCVD (ASCVD risk estimator) and stroke (CHA2DS2-VASc) based on published criteria. Cognition-related serum biomarkers included BDNF, VEGF, and IGF-1. Cognition was based on a battery of neuropsychological tests that assessed episodic memory, semantic memory, working memory, and executive function. A series of separate linear regression models were used to evaluate associations of vascular risk scores with outcomes of cognition and serum biomarkers. All models were adjusted for age, education level, and racial and ethnic background. In separate linear regression models, both ASCVD and CHA2DS2-VASc scores were inversely associated with semantic memory (β= -0.22, p = 0.007 and β= -0.15, p = 0.022, respectively), with no significant findings for the other cognitive domains. There were no significant associations between vascular risk scores and serum biomarkers. Future studies should prospectively examine associations between vascular risk and cognition in other populations and additionally consider other serum biomarkers that may be related to vascular risk and cognition.

Study on the protection of gingival epithelial barrier by interleukin-22 through regulating microbiota and E-cadherin expression

Objective: To investigate the regulatory effect and mechanism of interleukin-22 (IL-22) on the gingival epithelial barrier in the context of periodontal inflammation. Methods: IL-22 knockout (IL-22 KO) mice were constructed, and periodontitis mice models were established through oral gavage with polymicrobial inoculation. DNAs were extracted from the oral plaques of IL-22 KO periodontitis mice group (n=7) and their wild-type littermates periodontitis group (n=7) to establish a periodontitis-related oral microbiota database"PD-RiskMicroDB", determining the relationship between changes in oral microbiota and microbial function in two groups using 16S rRNA sequencing results. Gingival epithelial cells (GEC) were cultured by modified trypsinization method, and were stimulated with 100 μg/L IL-22, Porphyromonas gingivalis (Pg) (multiplicity of infection:100), separately or together for 3 and 12 hours. The experimental groups were as follows: control group (no stimulation), IL-22 group, Pg group and Pg+IL-22 group. The expression of barrier protein E-cadherin in each group at 3 h was detected by immunofluorescence, real-time fluorescence quantitative PCR (RT-qPCR) and Western blotting. Fluorescein isothiocyanate-dextran-mediated epithelial cell permeability experiment was conducted to clarify the changes in permeability of GEC in each group at 3 and 12 h. The mRNA expressions of E-cadherin in the gingival epithelium of wild-type littermates periodontitis group and IL-22 KO periodontitis group were detected by RT-qPCR. Fifteen C57BL/6 wild-type mice were randomly divided into control group (n=5), periodontitis group (n=5) and periodontitis+IL-22 treatment group (n=5). RT-qPCR and immunohistochemistry (IHC) staining were used to detect the expression level of E-cadherin in the gingival epithelium of each group. Results: 16S rRNA sequencing results showed that the composition of oral microbiota changed in IL-22 KO periodontitis group, of which the abundance of bacterial genera related to periodontal tissue invasion was significantly increased (linear discriminant analysis score: 2.22, P=0.009), compared with wild-type littermates periodontitis group. In vitro cell experiments showed that after Pg infection for 3 hours, the cell connections of GEC in Pg group were interrupted, and the fluorescence intensity of E-cadherin was reduced in Pg group compared with the control group. Meanwhile, the mRNA and protein expression levels of E-cadherin (mRNA: 0.69±0.12; protein: 0.60±0.12) were downregulated compared with the control group [mRNA: 1.00±0.00 (P=0.043); protein: 1.04±0.08 (P=0.003)], respectively. The fluorescence intensity of E-cadherin in the Pg+IL-22 group was enhanced compared with Pg group, and expression levels of E-cadherin mRNA (1.16±0.10) and protein (0.98±0.07) in Pg+IL-22 group showed a significant increase compared with Pg group [mRNA: 0.69±0.12 (P=0.005); protein: 0.60±0.12 (P=0.007)]. The result of epithelial permeability test showed that there was no statistical difference in epithelial permeability among control group, Pg group, IL-22 group and Pg+IL-22 group with treatment for 3 hours (F=0.20, P=0.893). While when the treatment time turned to be 12 hours, the epithelial barrier permeability showed a significant increase in Pg group (1.39±0.15) compared with control group (1.00±0.00, P=0.027), and a decrease in Pg+IL-22 group (1.02±0.18) compared with Pg group (1.39±0.15, P=0.034). In vivo, the mRNA expression of E-cadherin in the gingival epithelium of IL-22 KO periodontitis group decreased significantly (0.32±0.21) compared with wild-type littermates periodontitis group (1.01±0.01) (t=5.70, P=0.005). Moreover, RT-qPCR and IHC staining results showed that the mRNA expression level of E-cadherin (0.40±0.07) and absorbance value of E-cadherin positive expression (0.02±0.00) in gingival epithelial tissue of periodontitis group were both significantly down-regulated compared with control group [mRNA: 1.00±0.00 (P=0.005); absorbance value of E-cadherin positive expression: 0.04±0.01 (P=0.006)]. Meanwhile, the mRNA expression level of E-cadherin (1.06±0.24) and the absorbance value of E-cadherin positive expression (0.03±0.01) were both observed increase in periodontitis+IL-22 treatment group compared with periodontitis group (P=0.003, P=0.039). Conclusions: IL-22 may exert a protective effect on the gingival epithelial barrier in an inflammatory environment by regulating the invasiveness of oral microbiota and the expression of host barrier protein.

Government Subsidies and IPO Firms’ Short-Term Excess Returns: Evidence from China

AbstractAs an important tool for local governments to intervene in the listing process in their jurisdiction, the implementation effect of government subsidy has been quite controversial. This study examines the pricing mechanism of Initial Public Offerings (IPO) within China’s macro institutional environment. The period from April 2012 to December 2015 was selected as the sample observation period, with companies listed on Growth Enterprise Market (GEM) as the study objects. By focusing on IPO firms’ short-term excess returns, the multiple linear regression model and propensity score matching method (PSM) were applied to evaluate the actual impact of local government intervention through financial subsidies during the listing process. The results show that government subsidies improve IPO firm’s short-term excess returns. This promotion effect is more significant in state-owned enterprises rather than in private enterprises. Moreover, the implicit window guidance weakens the promotion effect of government subsidies on the short-term excess returns. Further, the more government subsidies the IPO firms receive, the worse their long-term performance will be. The findings demonstrate that local governments employ financial subsidies to expedite the listing process within their jurisdiction, thereby facilitating IPO companies in generating short-term excessive returns while simultaneously impeding the normal production and operation. The conclusion enhances theoretical understanding regarding high underpricing, while also offering investors a novel approach to interpreting government subsidy information and assessing IPO firm’s earnings sustainability.

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning.

Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehensive diagnostic model that investigates the diagnostic markers distinguishing between cirrhosis and HCC. Based on multiple GEO datasets containing cirrhosis and HCC samples, we used lasso regression, random forest (RF)-recursive feature elimination (RFE) and receiver operator characteristic analysis to screen for characteristic genes. Subsequently, we integrated these genes into a multivariable logistic regression model and validated the linear prediction scores in both training and validation cohorts. The ssGSEA algorithm was used to estimate the fraction of infiltrating immune cells in the samples. Finally, molecular typing for patients with cirrhosis was performed using the CCP algorithm. The study identified 137 differentially expressed genes (DEGs) and selected five significant genes (CXCL14, CAP2, FCN2, CCBE1 and UBE2C) to construct a diagnostic model. In both the training and validation cohorts, the model exhibited an area under the curve (AUC) greater than 0.9 and a kappa value of approximately 0.9. Additionally, the calibration curve demonstrated excellent concordance between observed and predicted incidence rates. Comparatively, HCC displayed overall downregulation of infiltrating immune cells compared to cirrhosis. Notably, CCBE1 showed strong correlations with the tumour immune microenvironment as well as genes associated with cell death and cellular ageing processes. Furthermore, cirrhosis subtypes with high linear predictive scores were enriched in multiple cancer-related pathways. In conclusion, we successfully identified diagnostic markers distinguishing between cirrhosis and hepatocellular carcinoma and developed a novel diagnostic model for discriminating the two conditions. CCBE1 might exert a pivotal role in regulating the tumour microenvironment, cell death and senescence.

Soil Quality Assessment and Its Spatial Variability in an Intensively Cultivated Area in India

Intensive agricultural practices lead to a deterioration in soil quality, causing a decline in farm productivity and quality, and disturbing the ecosystem balance in command areas. To achieve sustainable production and implement effective soil management strategies, understanding the state and spatial variability of soil quality is essential. The study aims to enhance the understanding of soil quality variability and provide actionable insights for sustainable soil management. In this regard, principal component analysis (PCA) and digital soil mapping were used to assess and map the spatial variability of the soil quality index (SQI) in the Cauvery command area, Mandya district, Karnataka, India. A total of 145 georeferenced soil samples were drawn at 0–15 cm depth and analyzed for physico-chemical properties. PCA was used to reduce the dataset into a minimum dataset as eight important soil indicators and to determine relative weightage factors, which were used for assessing SQI with linear and non-linear scoring methods. For spatial assessment of SQI, the random forest algorithm with environmental covariates was used to map eight soil indicators selected in the minimum dataset. The soil property maps were subjected to linear and non-linear scoring, followed by multiplying with corresponding weightage factors and summation to produce SQI maps. Results reveal that values of SQI calculated using linear scoring, range from 0.10 to 0.64, with a mean of 0.39, while non-linear scoring exhibits a wider range of 0.12 to 0.78 and a mean of 0.48. With a slight higher sensitivity index of 6.5, non-linear scoring proved to be the better scoring method compared to linear scoring. Spatial assessment shows that the R2 and LCC between the calculated and predicted SQI were higher for non-linear scoring (0.66 and 0.66) compared to linear scoring (0.60 and 0.65). The SQI maps reveal high spatial variability with more than 40 percent of soils classified as moderate-to-low index. The soils with low SQI were distributed in eastern parts, whereas western parts exhibited high-to-very-high soil quality. To achieve production goals and improve soil quality in the eastern region, sustainable soil and crop management strategies must be developed, and their effects on soil quality should be assessed.

The crosstalk between metabolic reprogramming and epithelial-mesenchymal transition and their synergistic roles in distant metastasis in breast cancer.

Metabolic reprogramming (MR) and epithelial-mesenchymal transition (EMT) are crucial phenomena involved in the distant metastasis of breast cancer (BRCA). This study aims to assess the risk of distant metastasis in BRCA patients based on MR and EMT processes and investigate their underlying mechanisms. Gene sets related to EMT and MR were downloaded. MR-related genes (MRG) and EMT-related genes (ERG) were obtained. Principal Component Analysis method was used to define the EMT Potential Index (EPI) and MR Potential Index (MPI) to quantify the EMT and MR levels in each tumor tissue. A linear scoring model, the Metastasis Score, was derived using the union of MRGs and ERGs to evaluate the risk of distant metastasis/recurrence in BRCA. The Metastasis Score was then validated in multiple datasets. Additionally, our study explored the underlying mechanism of the Metastasis Score and its association with tumor immunity, focusing on HPRT1 gene expression in breast cancer tissues of transfer and untransferred groups using experimental methods. A total of 59 MRGs and 30 ERGs were identified in the present study. Stratifying the dataset based on EPI and MPI revealed significantly lower survival rates (P < .05) in the MPI_high and EPI_high groups. Kaplan-Meier analysis indicated the lowest survival rate in the EPI-high + MPI-high group. The Metastasis Score demonstrated its ability to distinguish prognoses in GSE2034, GSE17705, and TCGA-BRCA datasets. Additionally, differences in mutated genes were found between the high- and the low-Metastasis Score groups, displaying significant associations with immune cell infiltration and anti-tumor immune status. Notably, the 13 genes included in the Metastasis Score showed a strong association with prognosis and tumor immunity. Immunohistochemistry and western blot results revealed high expression of the HPRT1 gene in the transfer group. This study established the Metastasis Score as a reliable tool for evaluating the risk of distant metastasis/recurrence in BRCA patients. Additionally, we identified key genes involved in MR and EMT crosstalk, offering valuable insights into their roles in tumor immunity and other relevant aspects.