Interventions to Improve Adherence to Oral Pre-exposure Prophylaxis: A Systematic Review and Network Meta-analysis.

For people at risk of HIV infection, pre-exposure prophylaxis (PrEP) can reduce the risk of infection in anticipation of exposure to HIV. The effectiveness of PrEP relies upon a user's adherence to their PrEP regimen. We sought to assess the effect of PrEP adherence interventions compared to usual care or another intervention for people at risk of HIV. We searched electronic databases from 2010 onwards for randomized controlled trials (RCTs) involving persons at risk of HIV randomized to an adherence promoting intervention vs usual care or another intervention. We used network meta-analyses to compare PrEP adherence for all participant populations. Certainty of evidence was assessed using Confidence in Network Meta-Analysis (CINeMA). 21 trials (N = 4917) were included in qualitative analysis (19 in network meta-analyses (N = 4101)). HIV self-testing interventions with adherence feedback elements improved adherence compared to usual care (risk ratio (RR): 1.83, 95%CI 1.19, 2.82). In contrast, HIV self-testing alone was inferior to HIV self-testing with adherence feedback (RR: 0.58, 95%CI 0.37-0.92). Reminders alone also were inferior to HIV self-testing with adherence feedback on adherence (RR: 0.53, 95%CI 0.34-0.84) and had similar effects on adherence as usual care (RR: 0.98, 95%CI: 0.86-1.11). Interventions with only one component were inferior for adherence than those with two components (RR: 0.74, 95%CI 0.62-0.88) and those with three components (RR: 0.78, 95%CI 0.65-0.93). The certainty of evidence was moderate for HIV self-testing plus adherence feedback and interventions with two or three components. When designing future PrEP adherence interventions, we recommend strategies with more than one but no more than three components.

Des-Arg(9) bradykinin as a causal metabolite for autism spectrum disorder.

BACKGROUND: Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder (ASD). However, the etiology of ASD is not completely understood. The presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for ASD. AIM: To estimate and interpret the causal relationship between ASD and metabolite profile, taking into consideration both genetic and environmental influences. METHODS: A two-sample Mendelian randomization (MR) analysis was conducted using summarized data from large-scale genome-wide association studies (GWAS) including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy controls. Metabolites in plasma were set as exposures with ASD as the main outcome. The causal relationships were estimated using the inverse variant weight (IVW) algorithm. We also performed leave-one-out sensitivity tests to validate the robustness of the results. Based on the drafted metabolites, enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome, SwissTargetPrediction, STRING, and Metascape. RESULTS: Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD (ß = 0.262, SE = 0.064, PIVW = 4.64 × 10-5). The association was robust, with no significant heterogeneity among instrument variables (PMR Egger = 0.663, PIVW = 0.906) and no evidence of pleiotropy (P = 0.949). Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9) bradykinin and ASD. CONCLUSION: Through the application of MR, this study provides practical insights into the potential causal association between plasma metabolites and ASD. These findings offer perspectives for the discovery of diagnostic or predictive biomarkers to support clinical practice in treating ASD.

Growing Like a Tree: Finding Trunks From Graph Skeleton Trees.

The message-passing paradigm has served as the foundation of graph neural networks (GNNs) for years, making them achieve great success in a wide range of applications. Despite its elegance, this paradigm presents several unexpected challenges for graph-level tasks, such as the long-range problem, information bottleneck, over-squashing phenomenon, and limited expressivity. In this study, we aim to overcome these major challenges and break the conventional "node- and edge-centric" mindset in graph-level tasks. To this end, we provide an in-depth theoretical analysis of the causes of the information bottleneck from the perspective of information influence. Building on the theoretical results, we offer unique insights to break this bottleneck and suggest extracting a skeleton tree from the original graph, followed by propagating information in a distinctive manner on this tree. Drawing inspiration from natural trees, we further propose to find trunks from graph skeleton trees to create powerful graph representations and develop the corresponding framework for graph-level tasks. Extensive experiments on multiple real-world datasets demonstrate the superiority of our model. Comprehensive experimental analyses further highlight its capability of capturing long-range dependencies and alleviating the over-squashing problem, thereby providing novel insights into graph-level tasks.

Gold-Nanorod-Assisted Live Cell Nuclear Imaging Based on Near-Infrared II Dark-Field Microscopy.

Dark-field microscopy offers several advantages, including high image contrast, minimal cell damage, and the absence of photobleaching of nanoprobes, which make it highly advantageous for cell imaging. The NIR-II window has emerged as a prominent research focus in optical imaging in recent years, with its low autofluorescence background in biological samples and high imaging SBR. In this study, we initially compared dark-field imaging results of colorectal cancer cells in both visible and NIR-II wavelengths, confirming the superior performance of NIR-II imaging. Subsequently, we synthesized gold nanorods with localized surface plasmon resonance (LSPR) absorption peaks in the NIR-II window. After bio-compatible modification, we non-specifically labeled colorectal cancer cells for NIR-II dark-field scattering imaging. The imaging results revealed a sixfold increase in SBR, especially in the 1425-1475 nm wavelength range. Finally, we applied this imaging system to perform dark-field imaging of cell nuclei in the NIR-II region and used GNRs for specific nuclear labeling in colorectal cancer cells. The resulting images exhibited higher SBR than non-specifically-labeled cell imaging, and the probe's labeling was precise, confirming the potential application of this system in photothermal therapy and drug delivery for cancer cells.

A New Imidazole Derivative for Corrosion Inhibition of Q235 Carbon Steel in an Acid Environment.

Q235 carbon steel is a commonly used engineering material, but its application in marine environments is limited by its susceptibility to corrosion, especially localized corrosion that can lead to material perforation. Effective inhibitors are crucial to addressing this issue, particularly in acidic environments where localized areas become increasingly acidic. This study reports the synthesis of a new imidazole derivative corrosion inhibitor and evaluates its effectiveness in corrosion inhibition performance using potentiodynamic polarization curve and electrochemical impedance spectroscopy techniques. High-resolution optical microscopy and scanning electron microscopy were employed for surface morphology analysis. Fourier-transform infrared spectroscopy was used to explore the protection mechanisms. The results demonstrate that the self-synthesized imidazole derivative corrosion inhibitor offers an excellent corrosion protection performance for Q235 carbon steel in a 3.5 wt. % NaCl acidic solution. This inhibitor can provide a new strategy for carbon steel corrosion protection.

Graph-Enhanced Emotion Neural Decoding.

Brain signal-based emotion recognition has recently attracted considerable attention since it has powerful potential to be applied in human-computer interaction. To realize the emotional interaction of intelligent systems with humans, researchers have made efforts to decode human emotions from brain imaging data. The majority of current efforts use emotion similarities (e.g., emotion graphs) or brain region similarities (e.g., brain networks) to learn emotion and brain representations. However, the relationships between emotions and brain regions are not explicitly incorporated into the representation learning process. As a result, the learned representations may not be informative enough to benefit specific tasks, e.g., emotion decoding. In this work, we propose a novel idea of graph-enhanced emotion neural decoding, which takes advantage of a bipartite graph structure to integrate the relationships between emotions and brain regions into the neural decoding process, thus helping learn better representations. Theoretical analyses conclude that the suggested emotion-brain bipartite graph inherits and generalizes the conventional emotion graphs and brain networks. Comprehensive experiments on visually evoked emotion datasets demonstrate the effectiveness and superiority of our approach.

What Factors Dominate the Change of PM2.5 in the World from 2000 to 2019? A Study from Multi-Source Data.

As the threat to human life and health from fine particulate matter (PM2.5) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM2.5 and exploring the drivers of PM2.5 are important tools for addressing the life-threatening health problems caused by PM2.5. In this study, we calculated the change in annual average global PM2.5 concentrations from 2000 to 2020 using the Theil-Sen median trend analysis method and reveal spatial and temporal trends in PM2.5 concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM2.5 concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM2.5 concentration, with significant decreases in PM2.5 concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM2.5 in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM2.5 concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM2.5 concentration, while an increase in NDVI can play an important role in the reduction in PM2.5 concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.

FgMet3 and FgMet14 related to cysteine and methionine biosynthesis regulate vegetative growth, sexual reproduction, pathogenicity, and sensitivity to fungicides in Fusarium graminearum.

Fusarium graminearum is a destructive filamentous fungus, which widely exists in wheat and other cereal crops. Cysteine and Methionine are unique sulfur-containing amino acids that play an essential role in protein synthesis and cell life, but their functions and regulation in F. graminearum remain largely unknown. Here we identified two proteins, FgMet3 and FgMet14 in F. graminearum, which are related to the synthesis of cysteine and methionine. We found FgMet3 and FgMet14 were localized to the cytoplasm and there was an interaction between them. FgMet3 or FgMet14 deletion mutants (ΔFgMet3 and ΔFgMet14) were deficient in vegetative growth, pigment formation, sexual development, penetrability and pathogenicity. With exogenous addition of cysteine and methionine, the vegetative growth and penetrability could be completely restored in ΔFgMet3 and ΔFgMet14, while sexual reproduction could be fully restored in ΔFgMet3 and partially restored in ΔFgMet14. ΔFgMet3 and ΔFgMet14 exhibited decreased sensitivity to Congo red stress and increased sensitivity to SDS, NaCl, KCl, Sorbitol, Menadione, and Zn ion stresses. Moreover, FgMet3 and FgMet14 nonspecifically regulate the sensitivity of F. graminearum to fungicides. In conclusion, FgMet3 and FgMet14 interacted to jointly regulate the development, pathogenicity, pigment formation, sensitivity to fungicides and stress factors in F. graminearum.

Comprehensive analysis of somatic mutator-derived and immune infiltrates related lncRNA signatures of genome instability reveals potential prognostic biomarkers involved in non-small cell lung cancer.

Background: The function and features of long non-coding RNAs (lncRNAs) are already attracting attention and extensive research on their role as biomarkers of prediction in lung cancer. However, the signatures that are both related to genomic instability (GI) and tumor immune microenvironment (TIME) have not yet been fully explored in previous studies of non-small cell lung cancer (NSCLC). Method: The clinical characteristics, RNA expression profiles, and somatic mutation information of patients in this study came from The Cancer Genome Atlas (TCGA) database. Cox proportional hazards regression analysis was performed to construct genomic instability-related lncRNA signature (GIrLncSig). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the potential functions of lncRNAs. CIBERSORT was used to calculate the proportion of immune cells in NSCLC. Result: Eleven genomic instability-related lncRNAs in NSCLC were identified, then we established a prognostic model with the GIrLncSig ground on the 11 lncRNAs. Through the computed GIrLncSig risk score, patients were divided into high-risk and low-risk groups. By plotting ROC curves, we found that patients in the low-risk group in the test set and TCGA set had longer overall survival than those in the high-risk group, thus validating the survival predictive power of GIrLncSig. By stratified analysis, there was still a significant difference in overall survival between high and low risk groups of patients after adjusting for other clinical characteristics, suggesting the prognostic significance of GIrLncSig is independent. In addition, combining GIrLncSig with TP53 could better predict clinical outcomes. Besides, the immune microenvironment differed significantly between the high-risk and the low-risk groups, patients with low risk scores tend to have upregulation of immune checkpoints and chemokines. Finally, we found that high-risk scores were associated with increased sensitivity to chemotherapy. Conclusion: we provided a new perspective on lncRNAs related to GI and TIME and revealed the worth of them in immune infiltration and immunotherapeutic response. Besides, we found that the expression of AC027288.1 is associated with PD-1 expression, which may be a potential prognostic marker in immune checkpoint inhibitor response to improve the prediction of clinical survival in NSCLC patients.

Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing.

Objectives: The aim of this study is to interpret a quantitative diagnosis model of traditional Chinese medicine (TCM) syndromes based on computer adaptive testing (CAT), from the perspective of both patients and clinicians. Methods: In this cross-sectional study, patients with postprandial distress syndrome completed the CAT model of TCM syndromes and the Chinese version of the Quality of Life Questionnaire for Functional Digestive Disorders (Chin-FDDQL); the clinicians' diagnosis was concurrently recorded. The patients completed this questionnaire again after 14 ± 2 days. The kappa test and paired chi-square test were used to evaluate the consistency between the CAT model and clinical diagnosis. Minimal clinically important differences (MCID) of the Chin-FDDQL scores were used to assess clinical efficacy from the patients' perspective. Logistic regression was used to examine the association between changes in the CAT model syndrome domain scores and changes in clinical outcomes. Results: Changes in the CAT model syndrome domain scores may affect the clinical outcomes of patients with the total scores of Chin-FDDQL (all P < 0.05). There was a correlation between changes in the CAT model syndrome domain scores and the patients' clinical outcomes. Different syndrome elements had different effects on various Chin-FDDQL domains, which was consistent with the theory of TCM. Conclusions: This study proposes a method for the clinical interpretation of the CAT model of TCM syndromes, including evidence derived from the application. It may provide a reference for future interpretation of other CAT models.

Assessment of NO2 population exposure from 2005 to 2020 in China.

Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions.

Comprehensive analysis of an immune infiltrate-related competitive endogenous RNA network reveals potential prognostic biomarkers for non-small cell lung cancer.

Globally, non-small cell lung cancer (NSCLC) is the most common malignancy and its prognosis remains poor because of the lack of reliable early diagnostic biomarkers. The competitive endogenous RNA (ceRNA) network plays an important role in the tumorigenesis and prognosis of NSCLC. Tumor immune microenvironment (TIME) is valuable for predicting the response to immunotherapy and determining the prognosis of NSCLC patients. To understand the TIME-related ceRNA network, the RNA profiling datasets from the Genotype-Tissue Expression and The Cancer Genome Atlas databases were analyzed to identify the mRNAs, microRNAs, and lncRNAs associated with the differentially expressed genes. Weighted gene co-expression network analysis revealed that the brown module of mRNAs and the turquoise module of lncRNAs were the most important. Interactions among microRNAs, lncRNAs, and mRNAs were prognosticated using miRcode, miRDB, TargetScan, miRTarBase, and starBase databases. A prognostic model consisting of 13 mRNAs was established using univariate and multivariate Cox regression analyses and validated by the receiver operating characteristic (ROC) curve. The 22 immune infiltrating cell types were analyzed using the CIBERSORT algorithm, and results showed that the high-risk score of this model was related to poor prognosis and an immunosuppressive TIME. A lncRNA-miRNA-mRNA ceRNA network that included 69 differentially expressed lncRNAs (DElncRNAs) was constructed based on the five mRNAs obtained from the prognostic model. ROC survival analysis further showed that the seven DElncRNAs had a substantial prognostic value for the overall survival (OS) in NSCLC patients; the area under the curve was 0.65. In addition, the high-risk group showed drug resistance to several chemotherapeutic and targeted drugs including cisplatin, paclitaxel, docetaxel, gemcitabine, and gefitinib. The differential expression of five mRNAs and seven lncRNAs in the ceRNA network was supported by the results of the HPA database and RT-qPCR analyses. This comprehensive analysis of a ceRNA network identified a set of biomarkers for prognosis and TIME prediction in NSCLC.

Development of a Computerized Adaptive Test for Quantifying Chinese Medicine Syndrome of Myasthenia Gravis on Basis of Multidimensional Item Response Theory.

BACKGROUND: Making comprehensive management of myasthenia gravis (MG) is a challenge in clinical practice due to heterogeneity and multiple comorbidities among patients. AIM: To develop an end-to-end instrument for individualized assessment of MG in the perspective of Chinese medicine (TCM) with the application of multidisciplinary quantification approaches. METHODS: A self-administrated questionnaire was developed integrating typical symptoms of MG and spleen-kidney deficiency syndrome on basis of the conceptual framework of TCM. With data collected in a multicenter cross-sectional study, confirmatory factor analysis together with multidimensional item response theory (MIRT) was used for evaluating the psychometric property of the questionnaire. A computerized adaptive test was developed based on the MIRT model, and scores of syndrome factors were calculated in simulation. A logistics regression model was also estimated for evaluating the consistency between the quantitative result and the clinical diagnosis of syndrome from clinical practitioners. RESULT: With 337 patients enrolled and assessed, the 14-item questionnaire was evaluated to be with adequate validity and reliability (Cronbach's alpha indices = 0.87, AIC = 195.827, BIC = 348.631, CFI = 0.921, RMR = 0.006, GFI = 0.954, RMSEA = 0.048, and χ2/df = 1.782). With adequate factor loadings of symptoms on related syndrome factor, the instrument was evaluated with preliminary interpretation and was suitable for evaluating patients with moderate severity of the spleen and kidney deficiency syndrome. CONCLUSION: Setting typical symptoms of MG together with systemic discomforts in a computerized adaptive test on the basis of MIRT, this study proposed an innovative research paradigm for quantifying individual condition in the perspective of TCM with application of interdisciplinary approaches.

Current Prevention of COVID-19: Natural Products and Herbal Medicine.

Starting from December 2019, novel coronavirus disease 2019 (COVID-19) pandemic has caused tremendous economic loss and unprecedented health crisis across the globe. While the development of cure is at full speed, less attention and fewer effort have been spent on the prevention of this rapidly spreading respiratory infectious disease. Although so far, several vaccine candidates have advanced into clinical trials, limited data have been released regarding the vaccine efficacy and safety in human, not mention the long-term effectiveness of those vaccines remain as open question yet. Natural products and herbal medicines have been historically used for acute respiratory infection and generally show acceptable toxicity. The favorable stability for oral formulation and ease of scaling up manufacture make it ideal candidate for prophylactic. Hereby, we summarized the most recent advance in SARS-CoV-2 prevention including vaccine development as well as experimental prophylactics. Mainly, we reviewed the natural products showing inhibitory effect on human coronavirus, and discussed the herbal medicines lately used for COVID-19, especially focused on the herbal products already approved by regulatory agency with identifiable patent number. We demonstrated that to fill in the response gap between appropriate treatment and commercially available vaccine, repurposing natural products and herbal medicines as prophylactic will be a vigorous approach to stop or at least slow down SARS-CoV-2 transmission. In the interest of public health, this will lend health officials better control on the current pandemic.

A Methodological and Reporting Quality Assessment of Systematic Reviews/Meta-Analyses about Chinese Medical Treatment for Gastroesophageal Reflux Disease.

OBJECTIVE: To access the methodological and reporting quality of systematic reviews (SRs)/meta-analyses (MAs) about Chinese medical treatment for gastroesophageal reflux disease (GERD). METHODS: The PubMed, Wanfang Data, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), Chinese Biomedical (CBM), Web of Science, and Cochrane Library databases were searched from inception to June 2020. Two researchers independently screened the literature considering the eligibility criteria. Overview Quality Assessment Questionnaire (OQAQ), Assessment of Multiple Systematic Reviews 2 (AMSTAR 2), and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to assess the methodological and reporting quality of the included reports. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to evaluate the level of evidence in each report. RESULTS: Thirty-three SRs/MAs met the inclusion criteria. The OQAQ results showed that defects in the methodological quality of 17/32 reports were major, with scores of 3 points. Analyzing a single item as the object, search strategies (item 2), and risk of bias in individual studies (item 4) was considered poor. The AMSTAR 2 results showed that 25.4% of the items were not reported, and 7.8% of the items were only partially reported. The overall assessment of AMSTAR 2 showed the majority of systematic reviews and meta-analyses were of low/very low (31/33, 93.9%) methodological quality, with a lack of protocol registration and excluded study list. The PRISMA results showed that 19.9% of items were not reported, and 15.2% of items were only partially reported, due to a lack of protocol registration and study selection methods. The methodological and reporting quality of the included studies was generally poor. Evidence evaluation with GRADE showed that most (31/33) of the included studies had low or very low levels of evidence. CONCLUSION: The methodological and reporting quality of SRs/MAs about Chinese medical treatment for GERD is generally poor. The main problems included incomplete search strategies, risk of bias in individual studies, the lack of protocol registration and excluded study list, and incorrect study selection methods.

Quantifying Liver-Stomach Disharmony Pattern of Functional Dyspepsia Using Multidimensional Analysis Methods.

PURPOSE: This study aims to develop and validate a quantitative model for measuring severity of a typical traditional Chinese medicine (TCM) pattern for functional dyspepsia (FD) using multidimensional analysis methods including confirmatory factor analysis (CFA) and multidimensional item response theory (MIRT). METHODS: A scale and theoretical models were constructed according to the definition of pathogenesis about "liver-stomach disharmony" patterns of FD. With data collected from 502 patients in a cross-section study, the theoretical model was validated with CFA, and the related validity and reliability were evaluated in Amos 21.0. By the use of the MIRT paradigm, psychometric properties of the scale were estimated and evaluated for pattern quantification. RESULTS: A scale consisting of 12 items was constructed detecting three latent traits of the pattern. The theoretical model was evaluated to be with adequate consistency with clinical data as RMSEA < 0.05, CFI = 0.94, and χ 2/Df = 2.29. As the correlation between symptoms and related pattern factors evaluated to be with adequate factor loading, the instrument is of preliminary interpretation. Most precision of assessment could be achieved for patients with moderate severity of the pattern as shown in test information and standard error functions. CONCLUSIONS: An instrument with an interpretable conceptual framework was developed for pattern quantification in TCM clinical practice. By constructing and evaluating both psychological and physical effects in a multidimensional model of the TCM pattern of FD, the paradigm raised in this article provided a valuable reference for interpreting complex diseases and theories such as FD and TCM patterns.

Reviews and Thoughts on the Relevance between Qualitative Chinese Medicinal Properties and Quantitative Material Components.

OBJECTIVE: Chinese Medicinal Properties (CMP) play a vital role in theoretical research and clinical practice. However, the traditional CMP system is subjective, qualitative, fixed, inconsistent, and obscured. Nowadays, quantifying CMP research achieved a notable progress. This study aims to review and reflect the relevance between qualitative CMP and quantitative material components. METHODS: A raw literature search was performed firstly in CNKI and Pubmed database to get a rough idea on the general advances in measuring CMP. Then, a strict literature search and data extraction from two dependent research studies were performed to analyze the relevance and discrimination between CMP and material components. RESULTS: The quantitative CMP research mainly focused on the microelements and chemical compositions. The largest microelements research listed 747 Chinese Materia Medica (CMM) (6780 flavors) and 120,000 element data. The measurement of chemical composition of CMM has risen rapidly in the 1990s and continues till the present. Thirty-seven articles were finally identified for the relevance analysis of CMP and material components. Of these, 18 and 19 articles correspondingly focused on the chemical compositions and microelements, and 26 and 11 articles correspondingly focused on their correlation and discrimination relationship. The most commonly used method for correlation analysis is intuitive analysis. The support vector machine maybe highly efficient and would act as the preferred method in discriminant analysis. Twelve (67%) and 5 (26%) articles' data came from the literature search in chemical compositions and microelement research studies. Four studies indicated that the research objects are the basic substances and material basis of CMP, 15 articles claimed that the chemical compositions were significantly related to CMP, 12 research studies concluded that the regularity and causality were identified between the research objects and CMP, and 9 research studies successfully established discriminant models for CMP basing on the detected substances. CONCLUSIONS: The relevance research between qualitative CMP and quantitative material components achieved a positive progress, though it is weak and defective. Standardizing the qualitative CMP system, establishing series comprehensive databases for the material components, innovating statistical and data mining methods, and integrating doctors' experiences are important and feasible for future research.

Quantifying Liver Stagnation Spleen Deficiency Pattern for Diarrhea Predominate Irritable Bowel Syndromes Using Multidimensional Analysis Methods.

OBJECTIVE: This study aims to offer a new approach for quantifying severity of traditional Chinese medicine pattern with multidimensional analysis methods. METHODS: A scale and theoretical models were constructed based on the definition of liver stagnation spleen deficiency pattern. Clinical data of 344 IBS-D patients from a cross-sectional study was used for feature validation of the model. Confirmatory factor analysis was used for evaluating the models. Also, multidimensional item response model was used for assessing multidimensional psychometric properties of the scale. RESULTS: Detecting two latent traits, the Cronbach's alpha of the 9-item scale was 0.745. Multidimensional model was evaluated with significant goodness of fit indices while the unidimensional model was rejected. The multidimensional item response model showed all the items had adequate discrimination. Parameters presented adequate explanation regarding mental syndromes having high factor loading on the liver stagnation factor and abdominal discomfort syndromes highly related to the spleen deficiency factor. Test information function showed that scale demonstrated the highest discrimination power among patients with moderate to high level of severity. CONCLUSIONS: The application of the multidimensional analysis methods on the basis of theoretical model construction provides a useful and rational approach for quantifying the severity of traditional Chinese medicine patterns.

Laparoscopic Partial Nephrectomy for T1 Renal Cell Carcinoma: Comparison of Two Resection Techniques in a Multi-institutional Propensity Score-Matching Analysis.

BACKGROUND: Enucleoresection is defined as presence of a minimal paratumor parenchyma that allows for clear visualization of the tumor's contours during partial nephrectomy (PN). Because there is variability in published reports regarding resection techniques during PN before the surface-intermediate-base (SIB) margin score reporting system, the association between postoperative outcomes and resection techniques are rarely reported. This study was designed to compare the perioperative, oncologic, and functional outcomes between laparoscopic enucleoresection (LER) (SIB score 1 + 1 + 1 = 3) and traditional laparoscopic partial nephrectomy (TLPN) (SIB score 1 + 2 + 2 = 5). METHODS: Data from 270 consecutive patients who underwent laparoscopic partial nephrectomy for single T1 RCC at 3 medical centers were prospectively collected. Propensity score matching was performed on age, gender, body mass index, American Society of Anesthesiologists score, preoperative estimated glomerular filtration rate (eGFR), tumor size, RENAL nephrometry score, Charlson score, and solitary kidney status. Normal parenchyma width of each patient was evaluated right after the surgery, and SIB score was assigned retrospectively. Ninety-eight matched patients undergoing LER or TLPN were compared for perioperative, oncologic, and functional outcomes. RESULTS: After matching, warm ischemia time (WIT) and operative time were significantly shorter in LER than TLPN group (20.8 vs. 23.8 min, P = 0.003 and 130.8 vs. 152.1 min, P = 0.005, respectively). Estimated blood loss (EBL) also was lower in LER than TLPN group (50 vs. 90 mL, P = 0.045). Complication rates, positive surgical margin rates, and local recurrence rates were comparable between groups (P = 0.3, P = 0.62, and P = 1.0, respectively). At last follow-up, the eGFRs also were comparable in both groups (P = 0.6). CONCLUSIONS: LER has similar oncologic, functional outcomes and complication rates with the advantage of a shorter WIT, operative time, and lower EBL compared with TLPN.