Evaluation and management of knee osteoarthritis.

Knee osteoarthritis (KOA) significantly contributes to the global disability burden, with its incidence expected to escalate by 74.9% by 2050. The urgency to comprehend and tackle this condition is critical, necessitating an updated and thorough review of KOA. A systematic review up to February 26, 2024, has elucidated the principal aspects of KOA's pathogenesis, risk factors, clinical manifestations, and contemporary management paradigms. The origins of KOA are intricately linked to mechanical, inflammatory, and metabolic disturbances that impair joint function. Notable risk factors include age, obesity, and previous knee injuries. Diagnosis predominantly relies on clinical assessment, with radiographic evaluation reserved conditionally. The significance of rehabilitation assessments, informed by the International Classification of Functioning, Disability, and Health framework, is highlighted. Treatment strategies are diverse, prioritizing nonpharmacological measures such as patient education, exercise, and weight management, with pharmacological interventions considered adjuncts. Intra-articular injections and surgical options are contemplated for instances where conventional management is inadequate. KOA stands as a predominant disability cause globally, characterized by a complex etiology and profound effects on individuals' quality of life. Early, proactive management focusing on nonpharmacological interventions forms the cornerstone of treatment, aiming to alleviate symptoms and enhance joint function. This comprehensive review underscores the need for early diagnosis, individualized treatment plans, and the integration of rehabilitation assessments to optimize patient outcomes. Further research is needed to refine prevention strategies and improve management outcomes for KOA patients.

A risk prediction model for efficient intubation in the emergency department: A 4-year single-center retrospective analysis.

Objective: To analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms. Methods: This study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs' examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non-intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED. Results: Of 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation. Conclusions: For critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model.

Machine-learning-aided decision-making model for the discontinuation of continuous renal replacement therapy.

BACKGROUND: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Previous research has mostly focused on the univariate and multivariate analysis of factors in CRRT, without the capacity to capture the complexity of the decision-making process. The present study thus developed a dynamic, interpretable decision model for CRRT discontinuation. METHODS: The study adopted a cohort of 1234 adult patients admitted to an intensive care unit in the MIMIC-IV database. We used the extreme gradient boosting (XGBoost) machine learning algorithm to construct dynamic discontinuation decision models across four time points. Shapley additive explanation (SHAP) analysis was conducted to show the contribution of an individual feature to the model output. RESULTS: Of the 1234 included patients with CRRT, 596 (48.3%) successfully discontinued CRRT. The dynamic prediction by the XGBoost model produced an area under the curve of 0.848 and accuracy, sensitivity, and specificity of 0.782, 0.786, and 0.776, respectively. The XGBoost model was thus far superior to other test models. SHAP demonstrated that the features that contributed most to the model results were the sequential organ failure assessment score, serum lactate level, and 24-hour urine output. CONCLUSIONS: Dynamic decision models supported by machine learning are capable of dealing with complex factors in CRRT and effectively predicting the outcome of discontinuation.

Analysis of characteristic aromas of buckwheat with different germplasm using gas chromatography-mass spectrometry combined with chemometrics and multivariate statistical analysis.

In this study, the volatile components in 40 samples of Tartary buckwheat and common buckwheat from 6 major producing areas in China were analyzed. A total of 77 volatile substances were identified, among which aldehydes and hydrocarbons were the main volatile components. Odor activity value analysis revealed 26 aromatic compounds, with aldehydes making a significant contribution to the aroma of buckwheat. Seven key compounds that could be used to distinguish Tartary buckwheat from common buckwheat were identified. The orthogonal partial least squares-discriminant analysis was effectively used to classify Tartary buckwheat and common buckwheat from different producing areas. This study provides valuable information for evaluating buckwheat quality, breeding high-quality varieties, and enhancing rational resource development.

Evaluation of Aromatic Characteristics and Potential Applications of Hemerocallis L. Based on the Analytic Hierarchy Process.

Hemerocallis L. possesses abundant germplasm resources and holds significant value in terms of ornamental, edible, and medicinal aspects. However, the quality characteristics vary significantly depending on different varieties. Selection of a high-quality variety with a characteristic aroma can increase the economic value of Hemerocallis flowers. The analytic hierarchy process (AHP) is an effective decision-making method for comparing and evaluating multiple characteristic dimensions. By applying AHP, the aromatic character of 60 varieties of Hemerocallis flowers were analyzed and evaluated in the present study. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) was employed to identify volatile components in Hemerocallis flowers. Thirteen volatile components were found to contribute to the aroma of Hemerocallis flowers, which helps in assessing their potential applications in essential oil, aromatherapy, and medical treatment. These components include 2-phenylethanol, geraniol, linalool, nonanal, decanal, (E)-ß-ocimene, α-farnesene, indole, nerolidol, 3-furanmethanol, 3-carene, benzaldehyde and benzenemethanol. The varieties with better aromatic potential can be selected from a large amount of data using an AHP model. This study provides a comprehensive understanding of the characteristics of the aroma components in Hemerocallis flowers, offers guidance for breeding, and enhances the economic value of Hemerocallis flowers.

Pharmacotherapy for adults with overweight and obesity: a systematic review and network meta-analysis of randomised controlled trials.

BACKGROUND: Pharmacotherapy provides an option for adults with overweight and obesity to reduce their bodyweight if lifestyle modifications fail. We summarised the latest evidence for the benefits and harms of weight-lowering drugs. METHODS: This systematic review and network meta-analysis included searches of PubMed, Embase, and Cochrane Library (CENTRAL) from inception to March 23, 2021, for randomised controlled trials of weight-lowering drugs in adults with overweight and obesity. We performed frequentist random-effect network meta-analyses to summarise the evidence and applied the Grading of Recommendations Assessment, Development, and Evaluation frameworks to rate the certainty of evidence, calculate the absolute effects, categorise interventions, and present the findings. The study was registered with PROSPERO, CRD 42021245678. FINDINGS: 14 605 citations were identified by our search, of which 132 eligible trials enrolled 48 209 participants. All drugs lowered bodyweight compared with lifestyle modification alone; all subsequent numbers refer to comparisons with lifestyle modification. High to moderate certainty evidence established phentermine-topiramate as the most effective in lowering weight (odds ratio [OR] of ≥5% weight reduction 8·02, 95% CI 5·24 to 12·27; mean difference [MD] of percentage bodyweight change -7·98, 95% CI -9·27 to -6·69) followed by GLP-1 receptor agonists (OR 6·33, 95% CI 5·00 to 8·00; MD -5·79, 95% CI -6·34 to -5·25). Naltrexone-bupropion (OR 2·69, 95% CI 2·10 to 3·44), phentermine-topiramate (2·40, 1·68 to 3·44), GLP-1 receptor agonists (2·22, 1·74 to 2·84), and orlistat (1·71, 1·42 to 2·05) were associated with increased adverse events leading to drug discontinuation. In a post-hoc analysis, semaglutide, a GLP-1 receptor agonist, showed substantially larger benefits than other drugs with a similar risk of adverse events as other drugs for both likelihood of weight loss of 5% or more (OR 9·82, 95% CI 7·09 to 13·61) and percentage bodyweight change (MD -11·40, 95% CI -12·51 to -10·29). INTERPRETATION: In adults with overweight and obesity, phentermine-topiramate and GLP-1 receptor agonists proved the best drugs in reducing weight; of the GLP-1 agonists, semaglutide might be the most effective. FUNDING: 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.

Effectiveness of Rehabilitation Interventions in Individuals With Emerging Virtual Respiratory Tract Infectious Disease: A Systematic Review and Meta-Analysis.

OBJECTIVE: Assessing rehabilitation effectiveness for persistent symptoms post-infection with emerging viral respiratory diseases. DATA SOURCES: Systematic review of seven databases (MEDLINE, EMBASE, Cochrane Library, PEDro, MedRxiv, CNKI, Wanfang) until 30 December 2023. REVIEW METHODS: Evaluated 101 studies (9593 participants) on respiratory function, exercise capacity, and quality of life. Methodological quality was assessed using the Cochrane Collaboration's Risk of Bias tool for randomized controlled trials (RCTs), the Newcastle-Ottawa Scale (NOS) for observational studies and non-RCTs, and the NIH Quality Assessment Tools for before-after studies. RESULTS: The most common rehabilitation program combined breathing exercises with aerobic exercise or strength training. Rehabilitation interventions significantly enhanced respiratory function, as evidenced by improvements on the Borg Scale (MD, -1.85; 95% CI, -3.00 to -0.70, low certainty), the mMRC Dyspnea Scale (MD, -0.45; 95% CI, -0.72 to -0.18, low certainty), and the Multidimensional Dyspnoea-12 Scale (MD, -4.64; 95% CI, -6.54 to -2.74, moderate certainty). Exercise capacity also improved, demonstrated by results from the Six-Minute Walk Test (MD, 38.18; 95% CI, 25.33-51.03, moderate certainty) and the Sit-to-Stand Test (MD, 3.04; 95% CI, 1.07-5.01, low certainty). CONCLUSION: Rehabilitation interventions are promising for survivors of viral respiratory diseases, yet gaps in research remain. Future investigations should focus on personalizing rehabilitation efforts, utilizing remote technology-assisted programs, improving research quality, and identifying specific subgroups for customized rehabilitation strategies to achieve the best outcomes for survivors.

Advances in balance training to prevent falls in stroke patients: a scoping review.

Objective: To summarize the status and characteristics of the available evidence, research gaps, and future research priorities for preventing falls in stroke patients through balance training. Methods: We used a scoping review framework. A systematic search of PUBMED, Embase, and Cochrane databases for main articles was conducted. Our study only included articles that on balance training and fall-related indicators in stroke patients. Two researchers independently screened the literature according to the inclusion and exclusion criteria. The data of demographic, clinical characteristics, intervention, sample, and outcome indicators were extracted. The characteristics and limitations of the included literature were comprehensively analyzed. Results: Of the 1,058 studies, 31 were included. The methods of balance training include regular balance training, Tai Chi, Yoga, task balance training, visual balance training, multisensory training, aquatic balance training, perturbation-based balance training, cognitive balance training, system-based balance training, and robot-assisted balance training. The commonly used outcome measures include clinical balance test, such as Berg balance scale (BBS), Timed Up-and-Go Test (TUG), Fall Risk Index assessment (FRI), Fall Efficacy Scale score (FES), and instrumented balance tests. Conclusion: This scoping review summarizes the existing primary research on preventing falls in stroke patients by balance training. Based on the summary of the existing evidence, the characteristics of balance training and their relation to falls in stroke patients were found. The future researches should explore how to develop personalized training program, the sound combination of various balance training, to more effectively prevent falls.

Multi-organ spatiotemporal information aware model for sepsis mortality prediction.

BACKGROUND: Sepsis is a syndrome involving multi-organ dysfunction, and the mortality in sepsis patients correlates with the number of lesioned organs. Precise prognosis models play a pivotal role in enabling healthcare practitioners to administer timely and accurate interventions for sepsis, thereby augmenting patient outcomes. Nevertheless, the majority of available models consider the overall physiological attributes of patients, overlooking the asynchronous spatiotemporal interactions among multiple organ systems. These constraints hinder a full application of such models, particularly when dealing with limited clinical data. To surmount these challenges, a comprehensive model, denoted as recurrent Graph Attention Network-multi Gated Recurrent Unit (rGAT-mGRU), was proposed. Taking into account the intricate spatiotemporal interactions among multiple organ systems, the model predicted in-hospital mortality of sepsis using data collected within the 48-hour period post-diagnosis. MATERIAL AND METHODS: Multiple parallel GRU sub-models were formulated to investigate the temporal physiological variations of single organ systems. Meanwhile, a GAT structure featuring a memory unit was constructed to capture spatiotemporal connections among multi-organ systems. Additionally, an attention-injection mechanism was employed to govern the data flowing within the network pertaining to multi-organ systems. The proposed model underwent training and testing using a dataset of 10,181 sepsis cases extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. To evaluate the model's superiority, it was compared with the existing common baseline models. Furthermore, ablation experiments were designed to elucidate the rationale and robustness of the proposed model. RESULTS: Compared with the baseline models for predicting mortality of sepsis, the rGAT-mGRU model demonstrated the largest area under the receiver operating characteristic curve (AUROC) of 0.8777 ± 0.0039 and the maximum area under the precision-recall curve (AUPRC) of 0.5818 ± 0.0071, with sensitivity of 0.8358 ± 0.0302 and specificity of 0.7727 ± 0.0229, respectively. The proposed model was capable of delineating the varying contribution of the involved organ systems at distinct moments, as specifically illustrated by the attention weights. Furthermore, it exhibited consistent performance even in the face of limited clinical data. CONCLUSION: The rGAT-mGRU model has the potential to indicate sepsis prognosis by extracting the dynamic spatiotemporal interplay information inherent in multi-organ systems during critical diseases, thereby providing clinicians with auxiliary decision-making support.

User-Centered Evaluation and Design Recommendations for an Internal Medicine Resident Competency Assessment Dashboard.

OBJECTIVES: Clinical Competency Committee (CCC) members employ varied approaches to the review process. This makes the design of a competency assessment dashboard that fits the needs of all members difficult. This work details a user-centered evaluation of a dashboard currently utilized by the Internal Medicine Clinical Competency Committee (IM CCC) at the University of Cincinnati College of Medicine and generated design recommendations. METHODS: Eleven members of the IM CCC participated in semistructured interviews with the research team. These interviews were recorded and transcribed for analysis. The three design research methods used in this study included process mapping (workflow diagrams), affinity diagramming, and a ranking experiment. RESULTS: Through affinity diagramming, the research team identified and organized opportunities for improvement about the current system expressed by study participants. These areas include a time-consuming preprocessing step, lack of integration of data from multiple sources, and different workflows for each step in the review process. Finally, the research team categorized nine dashboard components based on rankings provided by the participants. CONCLUSION: We successfully conducted user-centered evaluation of an IM CCC dashboard and generated four recommendations. Programs should integrate quantitative and qualitative feedback, create multiple views to display these data based on user roles, work with designers to create a usable, interpretable dashboard, and develop a strong informatics pipeline to manage the system. To our knowledge, this type of user-centered evaluation has rarely been attempted in the medical education domain. Therefore, this study provides best practices for other residency programs to evaluate current competency assessment tools and to develop new ones.

Effect of the telemedicine-supported multicomponent exercise therapy in patients with knee osteoarthritis: study protocol for a randomized controlled trial.

INTRODUCTION: The rising prevalence of knee osteoarthritis is placing a considerable strain on the global healthcare system. To address this issue, telemedicine-supported multicomponent exercise therapy has emerged as a promising approach. This therapy combines exercise, patient education, and health coaching to empower knee osteoarthritis patients to manage their condition from the comfort of their homes. Nevertheless, there are some existing limitations in the current research on this approach, including challenges related to patient compliance and the absence of objective evaluation methods. METHODS AND ANALYSIS: Patients diagnosed with knee osteoarthritis, who have not undergone knee surgery in the past year, will be recruited for a randomized controlled trial. The trial will include an intervention group and a control group. The intervention group will receive an mHealth app-based multicomponent exercise therapy, consisting of exercise therapy, patient education, and health coaching. Meanwhile, the control group will receive usual care, involving drug therapy and patient education. The primary outcome of the trial will be the measurement of pain intensity, assessed using a visual analog scale at baseline and at 4, 8, and 12 weeks of the post-intervention. To analyze the data, a two-factor, four-level repeated measures ANOVA will be used if the assumptions of homogeneity of variance and sphericity are met. If not, a mixed effects model will be employed. DISCUSSION: The aim of the study is to evaluate the effectiveness of multicomponent exercise therapy aimed at enhancing pain self-management for knee osteoarthritis patients in the comfort of their own homes. The intervention incorporate wearable devices equipped with advanced deep learning systems to monitor patients' adherence to the prescribed at-home exercise regimen, as well as to track changes in outcomes before and after the exercise sessions. The findings from this trial have the potential to enhance both the accessibility and quality of care provided to knee osteoarthritis patients, offering valuable insights for future improvements in their treatment and management. TRIAL REGISTRATION: Chinese Clinical Trials Registry, ChiCTR2300073688. Registered on 19 July 2023, https://www.chictr.org.cn/bin/project/edit?pid=199707 . World Health Organization International Clinical Trials Registry Platform, https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2300073688 .

Chinese guidelines for the rehabilitation treatment of knee osteoarthritis: An CSPMR evidence-based practice guideline.

BACKGROUND: Knee osteoarthritis (KOA) is the most common degenerative joint disease in China, causing a huge economic burden on patients, families, and society. Standardized KOA rehabilitation treatment is an important means to prevent and treat the disease and promote the development of high-quality medical services. This guideline is updated on the basis of the 2016 and 2019 editions. METHODS: Clinical questions regarding rehabilitation assessment and treatment were selected through clinical questions screening and deconstruction, and multiple rounds of Delphi questionnaire consultation. The International Classification of Functioning, Disability and Health (ICF) was used as the theoretical framework, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to grade the quality of evidence and recommendations. RESULTS: The reporting of this guideline followed the standard of Reporting Items for Practice Guidelines in Healthcare (RIGHT). Taking into account patients' preferences and values and the needs of Chinese clinical practice, a total of 11 clinical questions and 28 recommendations were established. The clinical questions were grouped into two categories: KOA assessment (body function, body structure, activity and participation, quality of life, and environmental factors and clinical outcomes assessment, resulting in 9 recommendations) and KOA treatment (health education, therapeutic exercise, therapeutic modalities, occupational therapy, assistive devices, and regenerative rehabilitation approaches, resulting in 19 recommendations). CONCLUSION: This is the first evidence-based guideline for KOA rehabilitation in China utilizing the ICF framework. This guideline provides key guidance for developing systematic, standardized, and precise rehabilitation protocols for KOA across various healthcare settings.

Low-frequency whole-body vibration can enhance cartilage degradation with slight changes in subchondral bone in mice with knee osteoarthritis and does not have any morphologic effect on normal joints.

PURPOSES: To evaluate the effects of low frequency whole-body vibration (WBV) on degeneration of articular cartilage and subchondral bone in mice with destabilization of the medial meniscus (DMM)induced osteoarthritis(OA) and mice with normal knee. METHODS: Ten-week-old C57BL/6J male mice received DMM on right knees, while the left knees performed sham operation. There were six groups: DMM, SHAM DMM, DMM+WBV,SHAM DMM+WBV, DMM+ NON-WBV and SHAM DMM+NON-WBV. After four weeks, the knees were harvested from the DMM and SHAM DMM group. The remaining groups were treated with WBV (10 Hz) or NON-WBV. Four weeks later, the knees were harvested. Genes, containing Aggrecan(Acan) and CollagenⅡ(Col2a1), Matrix Metalloproteinases 3 and 13(MMP3,13), TNFα and IL6, were measured and staining was also performed. OA was graded with OARSI scores, and tibial plateaubone volume to tissue volume ratio(BV/TV), bone surface area to bone volume ratio (BS/BV), trabecular number(Tb.N) and trabecular thickness separation(TS) between groups were analyzed. RESULTS: Increased OARSI scores and cartilage degradation were observed after WBV. BV/TV, Tb.N and TS were not significant between the groups. Significant reductions were observed in MMP3, MMP13, Col2a1, Acan, TNFα and IL6 in the DMM+WBV compared to SHAM DMM+WBV group. BV/TV, BS/BV, Tb.N, TS and OARSI scores were not significantly changed in the left knees. IL6 expression in the SHAM DMM+WBV group was significantly increased compared with the SHAM DMM+ NON-WBV group, while Col2a1, Acan and MMP13 expression decreased. CONCLUSION: WBV accelerated cartilage degeneration and caused slight changes in subchondral bone in a DMM-induced OA model. WBV had no morphologic effect on normal joints.

Regulation of cholesterol homeostasis in osteoporosis mechanisms and therapeutics.

Osteoporosis is a metabolic bone disease that affects hundreds of millions of people worldwide and is characterized by excessive loss of bone protein and mineral content. The incidence and mortality of osteoporosis increase with age, creating a significant medical and economic burden globally. The importance of cholesterol levels has been reported in the development of diseases including osteoporosis. It is important to note that key enzymes and molecules involved in cholesterol homeostasis are closely related to bone formation. Excessive cholesterol may cause osteoporosis, cholesterol and its metabolites affect bone homeostasis by regulating the proliferation and stimulation of osteoblasts and osteoclasts. Therefore, antagonism of elevated cholesterol levels may be a potential strategy to prevent osteoporosis. There is sufficient evidence to support the use of bisphosphonates and statin drugs for osteoporosis in the clinic. Therefore, in view of the aggravation of the aging problem, we summarize the intracellular mechanism of cholesterol homeostasis and its relationship with osteoporosis (including cholesterol and cholesterol oxidation products (COPs) in osteoporosis). Furthermore, the current clinical cholesterol-lowering drugs for osteoporosis were also summarized, as are new and promising therapies (cell-based therapies (e.g., stem cells) and biomaterial-delivered target drug therapies for osteoporosis as well).

MiR-30 Family: A Novel Avenue for Treating Bone and Joint Diseases?

Bone and joint diseases are a group of clinically heterogeneous diseases characterized by various bone strength disorders, bone structural defects and bone mass abnormalities. Common bone diseases include osteoporosis, skeletal dysplasia, and osteosarcoma, and common joint diseases include osteoarthritis, rheumatoid arthritis, and degenerative disc disease. all of them lead to high medical costs. The miR-30 family consists of a total of 5 members: miR-30a, miR-30b, miR-30c, miR-30d and miR-30e. Accumulating evidence has indicated that the miR-30 family may be involved in the occurrence and development of bone and joint diseases. For example, miR-30a is highly expressed in blood samples of osteoporosis patients, miR-30a/b increases in cartilage tissue of osteoarthritis patients, and lower expression of miR-30c is associated with higher malignance and shorter survival time of osteosarcoma. Mechanistically, by targeting crucial transcription factors (RUNX2, SOX9, beclin-1, etc.), the miR-30 family regulates some critical pathways of bone homeostasis (Wnt/ß-Catenin, mTOR, PI3K/AKT, etc.). In view of the distinct actions of the miR-30 family on bone metabolism, we hypothesize that the miR-30 family may be a new remedy for the clinical treatment and prevention of some bone and joint diseases.

Correlation of DNA methylation and lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer with a primarily good prognosis, and its 10-year survival rate is over 90%. However, PTC is prone to early lymph node metastasis. METHODS: Thyroid cancer tissues from PTC patients with lymphatic metastasis and normal tissues were collected for DNA methylation analysis. Different methylation sites, different methylation regions, gene-enriched pathways, and protein-protein interactions (PPIs) were analyzed. RESULTS: There were 1004 differentially methylated sites in the PTC group versus the control group; these involved 479 hypermethylated sites in 415 related genes, 525 hypomethylated sites in 482 related genes, 64 differentially methylated regions located in the CpG island region, 34 differentially methylated genes closely related to thyroid cancer, and 17 genes with differentially methylated genes in the DNA promoter region. CONCLUSION: NDRG4 hypermethylation and FOXO3, ZEB2, and CDK6 hypomethylation were associated with PTC lymph node metastasis.

Adopting a metaverse-based workspace to support research team collaboration: a pilot study from an academic health informatics laboratory.

Objective: This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab. Materials and Methods: A survey of lab members (n = 14) was analyzed according to a concurrent triangulation mixed methods design. The qualitative survey data were organized according to the Capability, Opportunity, Motivation, Behavior (COM-B) model and combined to generate personas that represent the overall types of lab members. Additionally, scheduled work hours were analyzed quantitatively to complement the findings of the survey feedback. Results: Four personas, representative of different types of virtual workers, were developed using the survey responses. These personas reflected the wide variety of opinions about virtual work among the participants and helped to categorize the most common feedback. The Work Hours Schedule Sheet analysis showed the low number of possible collaboration opportunities that were utilized compared to the number available. Discussion: We found that informal communication and co-location were not supported by the virtual workplace as we had originally planned. To solve this issue, we offer 3 design recommendations for those looking to implement their own virtual informatics lab. First, labs should establish common goals and norms for virtual workplace interactions. Second, labs should carefully plan the virtual space layout to maximize communication opportunities. Finally, labs should work with their platform of choice to address technical limitations for their lab members to improve user experience. Future work includes a formal, theory-guided experiment with consideration on ethical and behavioral impact.

Systematical construction of rice flavor types based on HS-SPME-GC-MS and sensory evaluation.

Rice is one of the main staple foods of Chinese people and its quality requirements are also improving. Aroma is one of the evaluation factors of rice quality, rice with better aroma quality is often more accepted by consumers. A universal aroma descriptive lexicon was established and four flavor types were formed based on samples from 9 representative rice cultivation regions. The key variables affecting the sensory quality of Chinese rice flavor were screened. It was found that the hexanal and nonanal with the highest content had no effect on the flavor properties, which suggests that volatile organic compounds (VOCs) content is not necessarily related to the influence of flavor properties. According to the aroma analysis of different rice flavor types, it can provide guidance for other flavor research.

[Distribution and Drug Resistance of Pathogens in Oral Mucositis Associated with Chemotherapy in Patients with Malignant Hematopathy].

OBJECTIVE: To analyze the distribution and drug resistance of pathogens in oral mucositis associated with chemotherapy in hospitalized patients with malignant hematopathy, so as to provide scientific evidences for rational selection of antibiotics and infection prevention and control. METHODS: From July 2020 to June 2022, 167 patients with malignant hematopathy were treated with chemical drugs in the Department of Hematology, Hainan Hospital, and secretions from oral mucosal infected wounds were collected. VITEK2 COMPECT automatic microbial identification system (BioMerieux, France) and bacterial susceptibility card (BioMerieux) were used for bacterial identification and drug susceptibility tests. RESULTS: A total of 352 strains of pathogens were isolated from 167 patients, among which 220 strains of Gram-positive bacteria, 118 strains of Gram-negative bacteria and 14 strains of fungi, accounted for 62.50%, 33.52% and 3.98%, respectively. The Gram-positive bacteria was mainly Staphylococcus and Streptococcus, while Gram-negative bacteria was mainly Klebsiella and Proteus. The resistance of main Gram-positive bacteria to vancomycin, ciprofloxacin and gentamicin was low, and the resistance to penicillin, cefuroxime, ampicillin, cefotaxime, erythromycin and levofloxacin was high. The main Gram-negative bacteria had low resistance to gentamicin, imipenem and penicillin, but high resistance to levofloxacin, cefotaxime, cefuroxime, ampicillin and vancomycin. The clinical data of oral mucositis patients with oral ulcer (severe) and without oral ulcer (mild) were compared, and it was found that there were statistically significant differences in poor oral hygiene, diabetes, sleep duration less than 8 hours per night between two groups (P<0.05). CONCLUSION: Gram-positive bacteria is the main pathogen of oral mucositis in patients with malignant hematopathy after chemotherapy. It is sensitive to glycopeptide antibiotics and aminoglycosides antibiotics. Poor oral hygiene, diabetes and sleep duration less than 8 hours per night are risk factors for oral mucositis with oral ulcer (severe).

Volatile metabolomics and chemometric study provide insight into the formation of the characteristic cultivar aroma of Hemerocallis.

Due to its ornamental, edible, and medicinal value, Hemerocallis has been historically loved and used in China. However, the current understanding of the aromatic profiles of this flower is rather limited. This work aimed to evaluate and classify the aromatic profiles of Hemerocallis flowers from 10 cultivars, the volatiles of which were analyzed using solid-phase microextraction-gas chromatography-mass spectrometry. Sensory evaluation, odor activity value and relative odor activity value calculations, and chemometric analysis were also performed, the result showed that a total of 81 volatile components were identified. Linalool, 3-furanmethanol, indole, phenylacetonitrile, nerolidol, benzaldehyde, nonanal, geranial, (E)-ß-ocimene, and volatile components specific to the different types were found to have an essential role in identifying these 10 varieties. The findings presented in this thesis add to our understanding of Hemerocallis.