Improving aromatic higher alcohol acetates in wines by co-fermentation of Pichia kluyveri and Saccharomyces cerevisiae: growth interaction and amino acid competition.

BACKGROUND: Higher alcohol acetates (HAAs) are potent aroma-active esters that impart desirable fruity and floral aromas. However, the conversion of higher alcohol precursors into HAAs is extremely low in winemaking. To investigate the underlying yeast-yeast interaction on targeted improvement of aromatic HAAs, we evaluated fermentation activity, cell viability, amino acid consumption and HAA production when Pichia kluyveri and Saccharomyces cerevisiae were inoculated concurrently or sequentially. RESULTS: Pichia kluyveri PK-21 possessed the ability to survive and increased HAA level up to 5.2-fold in mixed fermentation. Such an increment may benefit from the efficient conversion of higher alcohol precursors into HAAs (>27-fold higher than S. cerevisiae). During mixed fermentation, the two yeasts exhibited crucial interactions regarding cell growth and amino acid competition. Saccharomyces cerevisiae dominated over the co-inoculated P. kluyveri by efficient uptake of amino acids and biomass production. However, this dominance decreased in sequential fermentation, where P. kluyveri growth increased due to the consumption of preferred amino acids prior to S. cerevisiae. Pearson correlation analysis indicated that phenylalanine and aspartic acid may act as positive amino acids in boosting P. kluyveri growth and HAA production. Laboratory-scale winemaking validated the fermentation performance of P. kluyveri in sequential inoculum, resulting in a balanced aroma profile with enhanced floral and tropical fruity characteristics in the final wines. CONCLUSION: This study proposes a microbial, non-genetically engineered approach for targeted increase of HAA production in winemaking and the findings provide new insights into yeast-yeast interactions. © 2024 Society of Chemical Industry.

Risk assessment of crane operation hazards using modified FMEA approach with Z-number and set pair analysis.

In view of two key deficiencies of failure mode and effects analysis (FMEA) in crane operation hazard risk assessment-information loss and hazard grade lack, a crane operation hazard risk assessment model based on the Z-number and set pair analysis (Z-SPA) is proposed. In this research, the Z-number is used to address the information uncertainty. To reduce the risk losing evaluation information in the conversion of the Z-number into a crisp number, it is translated into an interval number. In this assessment model, the grades of crane operation hazards are determined using grade discrimination rules and a score function of a connection number based on set pair analysis. Two case studies are presented to exemplify the effectiveness of the approach. The first case validates the proposed method, and the second case illustrates the application of the modified FMEA to crane operation hazard risk analysis. Furthermore, the assessment results are analyzed and compared with previous studies to highlight the superiority of the proposed model.

Decoding Polysaccharides from Two Pichia Yeasts and Their Molecular Interaction with Wine Fruity Esters.

This study extensively characterized yeast polysaccharides (YPs) from Pichia fermentans (PF) and Pichia kluyveri (PK), with a specific focus on their structural attributes and their interaction with wine fruity esters in a model wine system. By finely tuning enzymatic reactions based on temperature, pH, and enzyme dosage, an optimal YP yield of 77.37% was achieved, with a specific mass ratio of cellulase, pectinase, and protease set at 3:5:2. There were four YP fractions (YPPF-W, YPPF-N, YPPK-W, and YPPK-N) isolated from the two yeasts. YPPF-N and YPPK-N were identified as glucans based on monosaccharide analysis and Fourier-transform infrared spectroscopy analysis. "Specific degradation-methylation-nuclear magnetic" elucidated YPPF-W's backbone structure as 1,3-linked α-l-Man and 1,6-linked α-d-Glc residues, while YPPK-W displayed a backbone structure of 1,3-linked α-Man residues, indicative of a mannoprotein nature. Isothermal titration calorimetry revealed spontaneous interactions between YPPK-W/YPPF-W and fruity esters across temperatures (25-45 °C), with the strongest interaction observed at 30 °C. However, distinct esters exhibited varying interactions with YPPK-W and YPPF-W, attributed to differences in molecular weights and hydrophobic characteristics. While shedding light on these intricate interactions, further experimental data is essential for a comprehensive understanding of yeast polysaccharides' or mannoproteins' impact on fruity esters. This research significantly contributes to advancing our knowledge of yeast polysaccharides' role in shaping the nuanced sensory attributes of wine.

Single-center retrospective study of the diagnostic value of double-balloon enteroscopy in Meckel's diverticulum with bleeding.

BACKGROUND: The study aimed to analyze the characteristic clinical manifestations of patients with intestinal disease Meckel's diverticulum (MD) complicated by digestive tract hemorrhage. Moreover, we aimed to evaluate the value of double-balloon enteroscopy (DBE) in MD diagnosis and the prognosis after laparoscopic diverticula resection. AIM: To evaluate the value of DBE in the diagnosis and the prognosis after laparoscopic diverticula resection for MD with bleeding. METHODS: The study retrospectively analyzed relevant data from 84 MD patients treated between January 2015 and March 2022 and recorded their clinical manifestations, auxiliary examination, and follow-up after laparoscopic resection of diverticula. RESULTS: (1) Among 84 MD patients complicated with hemorrhage, 77 were male, and 7 were female with an average age of 31.31 ± 10.75 years. The incidence was higher in men than in women of different ages; (2) Among the 84 MD patients, 65 (78.40%) had defecated dark red stools, and 50 (58.80%) had no accompanying symptoms during bleeding, indicating that most MD bleeding appeared a dark red stool without accompanying symptoms; (3) The shock index of 71 patients (85.20%) was < 1, suggesting that the blood loss of most MD patients was less than 20%-30%, and only a few patients had a blood loss of > 30%; (4) The DBE-positive rate was 100% (54/54), 99mTc-pertechnetate-positive scanning rate was 78% (35/45) compared with capsule endoscopy (36%) and small intestine computed tomography (19%). These results suggest that DBE and 99mTc-pertechnetate scans had significant advantages in diagnosing MD and bleeding, especially DBE was a highly precise examination method in MD diagnosis; (5) A total of 54 MD patients with hemorrhage underwent DBE examination before surgery. DBE endoscopy revealed many mucosal manifestations including normal appearance, inflammatory changes, ulcerative changes, diverticulum inversion, and nodular hyperplasia, with ulcerative changes being the most common (53.70%). This suggests that diverticular mucosal ulcer was the main cause of MD and bleeding; and (6) Laparoscopic dissection of diverticulae was performed in 76 patients, The patients who underwent postoperative follow-up did not experience any further bleeding. Additionally, follow-up examination of the 8 cases who had declined surgery revealed that 3 of them experienced a recurrence of digestive tract bleeding. These findings indicate that laparoscopic diverticula resection in MD patients complicated by bleeding had a favorable prognosis. CONCLUSION: Bleeding associated with MD was predominantly observed in male adolescents, particularly at a young age. DBE was a highly precise examination method in MD diagnosis. Laparoscopic diverticula resection effectively prevented MD bleeding and had a good prognosis.

Integration of single-cell RNA-seq and bulk RNA-seq data to construct and validate a cancer-associated fibroblast-related prognostic signature for patients with ovarian cancer.

BACKGROUND: To establish a prognostic risk profile for ovarian cancer (OC) patients based on cancer-associated fibroblasts (CAFs) and gain a comprehensive understanding of their role in OC progression, prognosis, and therapeutic efficacy. METHODS: Data on OC single-cell RNA sequencing (scRNA-seq) and total RNA-seq were collected from the GEO and TCGA databases. Seurat R program was used to analyze scRNA-seq data and identify CAFs clusters corresponding to CAFs markers. Differential expression analysis was performed on the TCGA dataset to identify prognostic genes. A CAF-associated risk signature was designed using Lasso regression and combined with clinicopathological variables to develop a nomogram. Functional enrichment and the immune landscape were also analyzed. RESULTS: Five CAFs clusters were identified in OC using scRNA-seq data, and 2 were significantly associated with OC prognosis. Seven genes were selected to develop a CAF-based risk signature, primarily associated with 28 pathways. The signature was a key independent predictor of OC prognosis and relevant in predicting the results of immunotherapy interventions. A novel nomogram combining CAF-based risk and disease stage was developed to predict OC prognosis. CONCLUSION: The study highlights the importance of CAFs in OC progression and suggests potential for innovative treatment strategies. A CAF-based risk signature provides a highly accurate prediction of the prognosis of OC patients, and the developed nomogram shows promising results in predicting the OC prognosis.

Diagnosis and treatment of venous thromboembolism during pregnancy relate to genetic polymorphism.

OBJECTIVES: Previous research had shown that age, a positive family history, comorbidities, major surgical operations, gestation, and use of several medications could increase the incidence of venous thromboembolism (VTE). With the development of medical and clinical individualized treatment, many people exposed to above risk factors did not develop VTE, suggested that genetic factors are also involved in the development of VTE. In this review, we aim to summarize VTE diagnosis and treatment in pregnancy women related to gene polymorphism. METHODS: A comprehensive electronic search using PubMed, MEDLINE, EMBASE and Web of Science was conducted to find relevant journal articles with key search terms including: "pregnancy OR pregnant," "venous thromboembolism OR VTE," "deep vein thrombosis OR DVT," "pulmonary embolism OR PE," and "genetic OR gene." Prominent publications from establishment of database till present were analysed to achieve a deeper understanding of VTE during pregnancy relate to genetic polymorphism, and the information was then collated to form this review. RESULTS: The literature review revealed that inherited thrombophilia significantly associated with the development of VTE, especially the factor V Leiden (FVL) and prothrombin gene mutation (PGM). Furthermore, the role of methylenetetrahydrofolate reductase (MTHFR) gene mutation in the development of pregnancy-related VTE remains controversial, further study is required. In the present study, Marburg I polymorphism (G511 E), c.1538 G>A and c.1601 G>A in Factor V (FV), JAK2V617 F mutation were reported as an independent risk factor for VTE, there is no sufficient evidence to confirm the gene mutation is related to VTE during pregnancy, these factors appearing as another promising potential diagnostic marker of VTE during pregnancy. Besides, the dosages of heparin in the treatment of VTE during pregnancy need be adjusted according to gene polymorphism of these population, particularly FVL or PGM carriers, and this area is not studied deeply, it is worth further study. CONCLUSION: Inherited thrombophilia significantly associated with the development of VTE, especially the FVL and PGM, however the relation between MTHFR gene mutation and pregnancy-related VTE remains controversial, further study is needed. In addition, the dosages of heparin in the treatment of VTE during pregnancy suggested to adjusted based on gene polymorphism in FVL and PGM, and establish better prediction models is a direction of future research.

Time-Course Transcriptomic Analysis Reveals Molecular Insights into the Inflorescence and Flower Development of Cardiocrinum giganteum.

Cardiocrinum giganteum is an endemic species of east Asia which is famous for its showy inflorescence and medicinal bulbs. Its inflorescence is a determinate raceme and the flowers bloom synchronously. Morphological observation and time-course transcriptomic analysis were combined to study the process of inflorescence and flower development of C. giganteum. The results show that the autonomic pathway, GA pathway, and the vernalization pathway are involved in the flower formation pathway of C. giganteum. A varied ABCDE flowering model was deduced from the main development process. Moreover, it was found that the flowers in different parts of the raceme in C. giganteum gradually synchronized during development, which is highly important for both evolution and ecology. The results obtained in this work improve our understanding of the process and mechanism of inflorescence and flower development and could be useful for the flowering period regulation and breeding of C. giganteum.

KGSCS-a smart care system for elderly with geriatric chronic diseases: a knowledge graph approach.

BACKGROUND: The increasing aging population has led to a shortage of geriatric chronic disease caregiver, resulting in inadequate care for elderly people. In this global context, many older people rely on nonprofessional family care. The credibility of existing health websites cannot meet the needs of care. Specialized health knowledge bases such as SNOMED-CT and UMLS are also difficult for nonprofessionals to use. Furthermore, professional caregiver in elderly care institutions also face difficulty caring for multiple elderly people at the same time and working handovers. As a solution, we propose a smart care system for the elderly based on a knowledge graph. METHOD: First, we worked with professional caregivers to design a structured questionnaire to collect more than 100 pieces of care-related information for the elderly. Then, in the proposed system, personal information, smart device data, medical knowledge, and nursing knowledge are collected and organized into a dynamic knowledge graph. The system offers report generation, question answering, risk identification and data updating services. To evaluate the effectiveness of the system, we use the expert evaluation method to score the user experience. RESULTS: The results of the study showed that compared to existing tools (health websites, archives and expert team consultation), the system achieved a score of 8 or more for basic information, health support and Dietary information. Some secondary evaluation indicators reached 9 and 10 points. This finding suggested that the system is superior to existing tools. We also present a case study to help the reader understand the role of the system. CONCLUSION: The smart care system provide personalized care guidelines for nonprofessional caregivers. It also makes the job easier for institutional caregivers. In addition, the system provides great convenience for work handover.

La-doped Porous Fe2O3 Nanorods as Advanced Anodes for Lithium/Sodium Ion Batteries and Sulfur Host for Li-Sulfur Batteries.

Transition metal oxides are investigated as electrochemically active anodes for several years due to the merits of high specific capacity, low cost, abundant resources and controllable synthesis. But the poor cycle performances have hindered their further wide application. Herein, porous La-doped FeOOH nanorods have been synthesized through a facile hydrothermal method, which could be transformed into porous La-doped Fe2O3 (Fe2O3-La) via a simple heating process. Compared with the undoped Fe2O3, the Fe2O3-La showed larger surface area, higher specific capacities and more stable cycle performances for lithium/sodium ion batteries. In addition, as an advanced sulfur host for lithium-sulfur batteries, the Fe2O3-La also displayed much more excellent cycle and rate performances than the undoped Fe2O3. The superior electrochemical performances of the Fe2O3-La may could be attributed to the doping of La, which could induce more porous morphology and offer more reactive sites. The positive effects of La-doping for electrochemical performances of porous Fe2O3 nanorods provide novel insights for further applications of rare earth metal doping.

Differences of bacterioplankton communities between the source and upstream regions of the Yangtze River: microbial structure, co-occurrence pattern, and environmental influencing factors.

The source area of the Yangtze River is located in the hinterland of the Qinghai-Tibet Plateau, which is known as the "Earth's third pole." It is the water conservation area and the natural barrier of the ecosystem of the Yangtze River basin. It is also the most sensitive area of the natural ecosystem, and the ecological environment is very fragile. Microorganisms play key roles in the biogeochemical processes of water. In this paper, the bacterioplankton communities in the source and upstream regions of the Yangtze River were studied based on 16S rRNA high-throughput sequencing, and their environmental influencing factors were further analyzed. Results showed that the upstream region had higher richness and diversity than the source region. The predominant bacterial phyla in the source and upstream regions were Proteobacteria, Firmicutes, and Actinobacteriota. The bacterial phyla associated with municipal pollution and opportunistic pathogen, such as Firmicutes and Actinobacteriota, were more abundant in the upstream. By contrast, distinct planktonic bacterial genera associated with mining pollution, such as Acidiphilium and Acidithiobacillus, were more abundant in the source region. The co-occurrence network showed that the interaction of bacterioplankton community is more frequent in the upstream. The bacterioplankton community compositions, richness, and functional profiles were affected by the spatial heterogeneity. Moreover, variation partitioning analysis further confirmed that the amount of variation in the source region independently explained by variables of altitude was the largest, followed by water nutrient. This paper revealed the spatial distribution of planktonic bacterial communities in the source and upstream regions of the Yangtze River and its correlation with environmental factors, providing information support for ensuring the health and safety of aquatic ecosystems in the Yangtze River Basin.

Synthesis of a novel monomer "DDTU-IDI" for the development of low-shrinkage dental resin composites.

OBJECTIVE: The current dental resin composites often suffer from polymerization shrinkage, which can lead to microleakage and potentially result in recurring tooth decay. This study presents the synthesis of a novel monomer, (3,9-diethyl-1,5,7,11-tetraoxaspiro[5,5]undecane-3,9-diyl)bis(methylene) bis((2-(3-(prop-1-en-2-yl)phenyl)propan-2-yl)carbamate) (DDTU-IDI), and evaluates its effect in the formulation of low-shrinkage dental resin composites. METHODS: DDTU-IDI was synthesized through a two-step reaction route, with the initial synthesis of the required raw material monomer 3,9-diethyl-3,9-dihydroxymethyl-1,5,7,11-tetraoxaspiro-[5,5] undecane (DDTU). The structures were confirmed using Fourier-transform infrared (FT-IR) spectroscopy and hydrogen nuclear magnetic resonance (1HNMR) spectroscopy. Subsequently, DDTU-IDI was incorporated into Bis-GMA-based composites at varying weight percentages (5, 10, 15, and 20 wt%). The polymerization reaction, degree of conversion, polymerization shrinkage, mechanical properties, physicochemical properties and biocompatibility of the low-shrinkage composites were thoroughly evaluated. Furthermore, the mechanical properties were assessed after a thermal cycling test with 10,000 cycles to determine the stability. RESULTS: The addition of DDTU-IDI at 10, 15, and 20 wt% significantly reduced the polymerization volumetric shrinkage of the experimental resin composites, without compromising the degree of conversion, mechanical and physicochemical properties. Remarkably, at a monomer content of 20 wt%, the polymerization shrinkage was reduced to 1.83 ± 0.53%. Composites containing 10, 15, and 20 wt% DDTU-IDI exhibited lower water sorption and higher contact angle. Following thermal cycling, the composites exhibited no significant decrease in mechanical properties, except for the flexural properties. SIGNIFICANCE: DDTU-IDI has favorable potential as a component which could produce volume expansion and increase rigidity in the development of low-shrinkage dental resin composites. The development of low-shrinkage composites containing DDTU-IDI appears to be a promising strategy for reducing polymerization shrinkage, thereby potentially enhancing the longevity of dental restorations.

CT-Based Radiomics Analysis of Different Machine Learning Models for Discriminating the Risk Stratification of Pheochromocytoma and Paraganglioma: A Multicenter Study.

RATIONALE AND OBJECTIVES: Using different machine learning models CT-based radiomics to integrate clinical radiological features to discriminating the risk stratification of pheochromocytoma/paragangliomas (PPGLs). MATERIALS AND METHODS: The present study included 201 patients with PPGLs from three hospitals (training set: n = 125; external validation set: n = 45; external test set: n = 31). Patients were divided into low-risk and high-risk groups using a staging system for adrenal pheochromocytoma and paraganglioma (GAPP). We extracted and selected CT radiomics features, and built radiomics models using support vector machines (SVM), k-nearest neighbors, random forests, and multilayer perceptrons. Using receiver operating characteristic curve analysis to select the optimal radiomics model, a combined model was built using the output of the optimal radiomics model and clinical radiological features, and its accuracy and clinical applicability were evaluated using calibration curves and clinical decision curve analysis (DCA). RESULTS: Finally, 13 radiomics features were selected to construct machine learning models. In the radiomics model, the SVM model demonstrated higher accuracy and stability, with an AUC value of 0.915 in the training set, 0.846 in external validation set, and 0.857 in external test set. Combining the outputs of SVM models with two clinical radiological features, a combined model constructed has demonstrated optimal risk stratification ability for PPGLs with an AUC of 0.926 for the training set, 0.883 for the external validation set, and 0.899 for the external test set. The calibration curve and DCA show good calibration accuracy and clinical effectiveness for the combined model. CONCLUSION: Combined model that integrates radiomics and clinical radiological features can discriminate the risk stratification of PPGLs.

Human error risk prioritization in crane operations based on CPT and ICWGT.

Human error plays a significant role in crane safety. To increase the accuracy and rationality of human error risk prioritization for crane operations, this study proposes a risk prioritization model for human errors in crane operations based on the cumulative prospect theory (CPT) and the improved combination weighting model of game theory (ICWGT). The ICWGT integrates the risk-factor weights obtained via subjective and objective methods. Trapezoidal fuzzy numbers are used to describe experts' uncertainty information. Then, the CPT is applied to handle the assessment of experts' risk attitudes in the decision process. The human error risk ranking of crane operations is obtained according to the overall prospect values calculated using the CPT. A case study of human error in overhead crane operations was conducted, and sensitivity and comparison analyses confirmed the feasibility of the proposed model. The proposed ranking mechanism for human error risk priority in crane operations is helpful for crane risk management.

Safe Disposal of Accident Wastewater in Chemical Industrial Parks Using Non-Thermal Plasma with ZnO-Fe3O4 Composites.

Chemical wastewater has a high concentration of toxic and hazardous antibiotic pollutants, which not only devastates the ecological environment and disrupts the ecological balance, but also endangers human health. This research proposed a non-thermal plasma (NTP) combined with a ZnO-Fe3O4 nano-catalyst system to achieve the efficient degradation of ciprofloxacin (CIP) in chemical wastewater. Firstly, ZnO-Fe3O4 composite materials were prepared using hydrothermal method and characterized with scanning electron microscopy (SEM), transmission electron microscope (TEM), X-ray diffractometer (XRD), X-ray photoelectron spectroscopy (XPS), etc. With the sole NTP, NTP/ZnO, and NTP/ZnO-Fe3O4 systems, the removal efficiency of CIP can reach 80.1%, 88.2%, and 99.6%, respectively. The optimal doping amount of Fe3O4 is 14%. Secondly, the capture agent experiment verified that ·OH, ·O2-, and 1O2 all have a certain effect on CIP degradation. Then, liquid chromatography-mass spectrometry (LC-MS) was used to detect the intermediate and speculate its degradation pathway, which mainly included hydroxyl addition, hydroxyl substitution, and piperazine ring destruction. After treatment with the NTP/ZnO-Fe3O4 system, the overall toxicity of the product was reduced. Finally, a cyclic experiment was conducted, and it was found that the prepared ZnO-Fe3O4 catalyst has good reusability. The NTP/ZnO-Fe3O4 was also applied in practical pharmaceutical wastewater treatment and has practical applicability.

WD repeat domain 5 promotes the development of late-onset preeclampsia by activating nuclear factor kappa B.

PURPOSE: Over-activation of nuclear factor kappa B (NF-κB) was proven to be involved in the pathogenesis of preeclampsia. However, its regulation mechanism is not clear yet. This paper explored the role of WD repeat domain 5 (WDR5) in the development of late-onset preeclampsia and its relationship with NF-κB. METHODS: WDR5 expression was detected in normal placentas and placentas from late-onset preeclampsia patients. CCK-8 and colony formation assays were conducted to appraise the proliferative ability of trophoblast. Migration and invasion were observed by wound healing and transwell assays. The interaction between WDR5 and NF-κB inhibitor I-kappa-B-alpha (IkBa) was verified by Co-immunoprecipitation analysis. Immunofluorescence was used to analyze the activation of NF-κB. Finally, we tested the role of WDR5 using the mice late-onset preeclampsia model. RESULTS: WDR5 was highly expressed in the placentas of late-onset preeclampsia patients. WDR5 overexpression suppressed cell proliferation, migration, and invasion in trophoblast. WDR5 could interact with IkBa to activate NF-κB. Knockdown of NF-κB counteracted the anti-proliferative and anti-metastatic effects of WDR5 overexpression in trophoblast. In-vivo studies suggested that targeting WDR5 combated late-onset preeclampsia development. CONCLUSIONS: Our finding provides new insights into the role of WDR5 in late-onset preeclampsia development.

Association between Sleep Duration and Left Ventricular Hypertrophy for Patients with Type 2 Diabetes Mellitus.

Objective: In this study, we aimed to estimate the impact of sleep duration on left ventricular hypertrophy (LVH) in type 2 diabetes mellitus (T2DM). Methods: Consecutive patients with T2DM undergoing transthoracic echocardiography (TTE) in our center from October 2017 to February 2021 were analyzed. The association of the risk of LVH in T2DM patients was evaluated using univariable and multivariable logistic regression analyses. Results: This study finally included 2689 adult patients (mean age 51.8 ± 12.5 years, 56.2% men, mean sleep duration 7.6 ± 1.4 hours per day). Of all patients, 655 (24.4%) patients were diagnosed with LVH and 2034 did not have LVH. All patients were adults and were diagnosed with T2DM. In the univariate and multivariate regression analyses, gender, sleep duration, body mass index (BMI), waist, hemoglobin (Hb), blood creatinine (Cr), and high-density lipoprotein cholesterol (HDL-c) were associated with LVH. In the restricted cubic spline (RCS) model, the cut-off points of sleep duration given refer to the group of patients with T2DM and LVH were 8 hours per day. With the cut-off points, the multivariable analysis demonstrated that, for diabetic patients, LVH was significantly correlated with a sleep duration of 8 hours per day, hemoglobin, blood urea nitrogen (BUN), and HDL-c. Conclusion: For patients with T2DM, long sleep duration (>8 hours per day), hemoglobin, BUN, and HDL-c were independently associated with LVH. This trial is registered with NCT03811470.

Potential Schizophrenia Disease-Related Genes Prediction Using Metagraph Representations Based on a Protein-Protein Interaction Keyword Network: Framework Development and Validation.

BACKGROUND: Schizophrenia is a serious mental disease. With increased research funding for this disease, schizophrenia has become one of the key areas of focus in the medical field. Searching for associations between diseases and genes is an effective approach to study complex diseases, which may enhance research on schizophrenia pathology and lead to the identification of new treatment targets. OBJECTIVE: The aim of this study was to identify potential schizophrenia risk genes by employing machine learning methods to extract topological characteristics of proteins and their functional roles in a protein-protein interaction (PPI)-keywords (PPIK) network and understand the complex disease-causing property. Consequently, a PPIK-based metagraph representation approach is proposed. METHODS: To enrich the PPI network, we integrated keywords describing protein properties and constructed a PPIK network. We extracted features that describe the topology of this network through metagraphs. We further transformed these metagraphs into vectors and represented proteins with a series of vectors. We then trained and optimized our model using random forest (RF), extreme gradient boosting, light gradient boosting machine, and logistic regression models. RESULTS: Comprehensive experiments demonstrated the good performance of our proposed method with an area under the receiver operating characteristic curve (AUC) value between 0.72 and 0.76. Our model also outperformed baseline methods for overall disease protein prediction, including the random walk with restart, average commute time, and Katz models. Compared with the PPI network constructed from the baseline models, complementation of keywords in the PPIK network improved the performance (AUC) by 0.08 on average, and the metagraph-based method improved the AUC by 0.30 on average compared with that of the baseline methods. According to the comprehensive performance of the four models, RF was selected as the best model for disease protein prediction, with precision, recall, F1-score, and AUC values of 0.76, 0.73, 0.72, and 0.76, respectively. We transformed these proteins to their encoding gene IDs and identified the top 20 genes as the most probable schizophrenia-risk genes, including the EYA3, CNTN4, HSPA8, LRRK2, and AFP genes. We further validated these outcomes against metagraph features and evidence from the literature, performed a features analysis, and exploited evidence from the literature to interpret the correlation between the predicted genes and diseases. CONCLUSIONS: The metagraph representation based on the PPIK network framework was found to be effective for potential schizophrenia risk genes identification. The results are quite reliable as evidence can be found in the literature to support our prediction. Our approach can provide more biological insights into the pathogenesis of schizophrenia.

A Multilabel Text Classifier of Cancer Literature at the Publication Level: Methods Study of Medical Text Classification.

BACKGROUND: Given the threat posed by cancer to human health, there is a rapid growth in the volume of data in the cancer field and interdisciplinary and collaborative research is becoming increasingly important for fine-grained classification. The low-resolution classifier of reported studies at the journal level fails to satisfy advanced searching demands, and a single label does not adequately characterize the literature originated from interdisciplinary research results. There is thus a need to establish a multilabel classifier with higher resolution to support literature retrieval for cancer research and reduce the burden of screening papers for clinical relevance. OBJECTIVE: The primary objective of this research was to address the low-resolution issue of cancer literature classification due to the ambiguity of the existing journal-level classifier in order to support gaining high-relevance evidence for clinical consideration and all-sided results for literature retrieval. METHODS: We trained a multilabel classifier with scalability for classifying the literature on cancer research directly at the publication level to assign proper content-derived labels based on the "Bidirectional Encoder Representation from Transformers (BERT) + X" model and obtain the best option for X. First, a corpus of 70,599 cancer publications retrieved from the Dimensions database was divided into a training and a testing set in a ratio of 7:3. Second, using the classification terminology of International Cancer Research Partnership cancer types, we compared the performance of classifiers developed using BERT and 5 classical deep learning models, such as the text recurrent neural network (TextRNN) and FastText, followed by metrics analysis. RESULTS: After comparing various combined deep learning models, we obtained a classifier based on the optimal combination "BERT + TextRNN," with a precision of 93.09%, a recall of 87.75%, and an F1-score of 90.34%. Moreover, we quantified the distinctive characteristics in the text structure and multilabel distribution in order to generalize the model to other fields with similar characteristics. CONCLUSIONS: The "BERT + TextRNN" model was trained for high-resolution classification of cancer literature at the publication level to support accurate retrieval and academic statistics. The model automatically assigns 1 or more labels to each cancer paper, as required. Quantitative comparison verified that the "BERT + TextRNN" model is the best fit for multilabel classification of cancer literature compared to other models. More data from diverse fields will be collected to testify the scalability and extensibility of the proposed model in the future.

Time Perspective, Dietary Behavior, and Glycemic Control in Patients With Type 2 Diabetes.

BACKGROUND: Dietary behavior is a key component in the self-management of patients with Type 2 diabetes (T2DM), as it is essential for glycemic control and preventing diabetic complications. However, it is challenging for patients with diabetes to make sustainable dietary behavior changes and achieve long-term optimal glycemic control. OBJECTIVES: Dietary behavior changes involve present efforts to achieve future benefits. The primary aim of this study was to investigate the relationships among time perspective, dietary behaviors, and health outcomes in patients with T2DM. Based on the temporal self-regulation theory and previous research, the secondary aim of the study was to explore how time perspective influences dietary behaviors. METHODS: Following convenient sampling ( N = 329), a cross-sectional study was conducted in patients with T2DM between November 2021 and October 2022. Data were collected using self-reported questionnaires and the retrieval of clinical information from medical records. Hierarchical regression and path analysis were used to explore the relationships among study variables. RESULTS: Our analyses showed that a future-oriented time perspective was associated with better dietary behavior but was not significantly related to hemoglobin A1c. Hierarchical regression analysis also demonstrated that having a more future-oriented time perspective was associated with healthier dietary behavior after controlling covariates. Based on the theory and path analysis, there was an indirect effect of future time perspective on dietary behavior through self-control capacity and intention. DISCUSSION: The study reveals that a future-oriented time perspective can promote healthier dietary behavior when providing care for patients with T2DM. As a theoretical framework, the temporal self-regulation theory offers references for researchers and clinicians to take into consideration patients' time perspectives and their intentions and self-control capacity when developing interventional programs to improve dietary behaviors.