A survey of circular RNAs in complex diseases: databases, tools and computational methods.

Circular RNAs (circRNAs) are a category of novelty discovered competing endogenous non-coding RNAs that have been proved to implicate many human complex diseases. A large number of circRNAs have been confirmed to be involved in cancer progression and are expected to become promising biomarkers for tumor diagnosis and targeted therapy. Deciphering the underlying relationships between circRNAs and diseases may provide new insights for us to understand the pathogenesis of complex diseases and further characterize the biological functions of circRNAs. As traditional experimental methods are usually time-consuming and laborious, computational models have made significant progress in systematically exploring potential circRNA-disease associations, which not only creates new opportunities for investigating pathogenic mechanisms at the level of circRNAs, but also helps to significantly improve the efficiency of clinical trials. In this review, we first summarize the functions and characteristics of circRNAs and introduce some representative circRNAs related to tumorigenesis. Then, we mainly investigate the available databases and tools dedicated to circRNA and disease studies. Next, we present a comprehensive review of computational methods for predicting circRNA-disease associations and classify them into five categories, including network propagating-based, path-based, matrix factorization-based, deep learning-based and other machine learning methods. Finally, we further discuss the challenges and future researches in this field.

Chinese medical dialogue information extraction via contrastive multi-utterance inference.

Medical Dialogue Information Extraction (MDIE) is a promising task for modern medical care systems, which greatly facilitates the development of many real-world applications such as electronic medical record generation, automatic disease diagnosis, etc. Recent methods have firstly achieved considerable performance in Chinese MDIE but still suffer from some inherent limitations, such as poor exploitation of the inter-dependencies in multiple utterances, weak discrimination of the hard samples. In this paper, we propose a contrastive multi-utterance inference (CMUI) method to address these issues. Specifically, we first use a type-aware encoder to provide an efficient encode mechanism toward different categories. Subsequently, we introduce a selective attention mechanism to explicitly capture the dependencies among utterances, which thus constructs a multi-utterance inference. Finally, a supervised contrastive learning approach is integrated into our framework to improve the recognition ability for the hard samples. Extensive experiments show that our model achieves state-of-the-art performance on a public benchmark Chinese-based dataset and delivers significant performance gain on MDIE as compared with baselines. Specifically, we outperform the state-of-the-art results in F1-score by 2.27%, 0.55% in Recall and 3.61% in Precision (The codes that support the findings of this study are openly available in CMUI at https://github.com/jc4357/CMUI.).

Adaptive multi-source multi-view latent feature learning for inferring potential disease-associated miRNAs.

Accumulating evidence has shown that microRNAs (miRNAs) play crucial roles in different biological processes, and their mutations and dysregulations have been proved to contribute to tumorigenesis. In silico identification of disease-associated miRNAs is a cost-effective strategy to discover those most promising biomarkers for disease diagnosis and treatment. The increasing available omics data sources provide unprecedented opportunities to decipher the underlying relationships between miRNAs and diseases by computational models. However, most existing methods are biased towards a single representation of miRNAs or diseases and are also not capable of discovering unobserved associations for new miRNAs or diseases without association information. In this study, we present a novel computational method with adaptive multi-source multi-view latent feature learning (M2LFL) to infer potential disease-associated miRNAs. First, we adopt multiple data sources to obtain similarity profiles and capture different latent features according to the geometric characteristic of miRNA and disease spaces. Then, the multi-modal latent features are projected to a common subspace to discover unobserved miRNA-disease associations in both miRNA and disease views, and an adaptive joint graph regularization term is developed to preserve the intrinsic manifold structures of multiple similarity profiles. Meanwhile, the Lp,q-norms are imposed into the projection matrices to ensure the sparsity and improve interpretability. The experimental results confirm the superior performance of our proposed method in screening reliable candidate disease miRNAs, which suggests that M2LFL could be an efficient tool to discover diagnostic biomarkers for guiding laborious clinical trials.

NSL2CD: identifying potential circRNA-disease associations based on network embedding and subspace learning.

Many studies have evidenced that circular RNAs (circRNAs) are important regulators in various pathological processes and play vital roles in many human diseases, which could serve as promising biomarkers for disease diagnosis, treatment and prognosis. However, the functions of most of circRNAs remain to be unraveled, and it is time-consuming and costly to uncover those relationships between circRNAs and diseases by conventional experimental methods. Thus, identifying candidate circRNAs for human diseases offers new opportunities to understand the functional properties of circRNAs and the pathogenesis of diseases. In this study, we propose a novel network embedding-based adaptive subspace learning method (NSL2CD) for predicting potential circRNA-disease associations and discovering those disease-related circRNA candidates. The proposed method first calculates disease similarities and circRNA similarities by fully utilizing different data sources and learns low-dimensional node representations with network embedding methods. Then, we adopt an adaptive subspace learning model to discover potential associations between circRNAs and diseases. Meanwhile, an integrated weighted graph regularization term is imposed to preserve local geometric structures of data spaces, and L1,2-norm constraint is also incorporated into the model to realize the smoothness and sparsity of projection matrices. The experiment results show that NSL2CD achieves comparable performance under different evaluation metrics, and case studies further confirm its ability to discover potential candidate circRNAs for human diseases.

Integrated Transcriptomic and Metabolomic Analysis Reveal the Underlying Mechanism of Anthocyanin Biosynthesis in Toona sinensis Leaves.

Toona sinensis, commonly known as Chinese Toon, is a plant species that possesses noteworthy value as a tree and vegetable. Its tender young buds exhibit a diverse range of colors, primarily determined by the presence and composition of anthocyanins and flavonoids. However, the underlying mechanisms of anthocyanin biosynthesis in Toona sinensis have been rarely reported. To explore the related genes and metabolites associated with composition of leaf color, we conducted an analysis of the transcriptome and metabolome of five distinct Toona clones. The results showed that differentially expressed genes and metabolites involved in anthocyanin biosynthesis pathway were mainly enriched. A conjoint analysis of transcripts and metabolites was carried out in JFC (red) and LFC (green), resulting in the identification of 510 genes and 23 anthocyanin-related metabolites with a positive correlation coefficient greater than 0.8. Among these genes and metabolites, 23 transcription factors and phytohormone-related genes showed strong coefficients with 13 anthocyanin derivates, which mainly belonged to the stable types of delphinidin, cyanidin, peonidin. The core derivative was found to be Cyanidin-3-O-arabinoside, which was present in JFC at 520.93 times the abundance compared to LFC. Additionally, the regulatory network and relative expression levels of genes revealed that the structural genes DFR, ANS, and UFGT1 might be directly or indirectly regulated by the transcription factors SOC1 (MADS-box), CPC (MYB), and bHLH162 (bHLH) to control the accumulation of anthocyanin. The expression of these genes was significantly higher in red clones compared to green clones. Furthermore, RNA-seq results accurately reflected the true expression levels of genes. Overall, this study provides a foundation for future research aimed at manipulating anthocyanin biosynthesis to improve plant coloration or to derive human health benefits.

Identification of HMGB2 associated with proliferation, invasion and prognosis in lung adenocarcinoma via weighted gene co-expression network analysis.

BACKGROUND: High mobility group protein B2 (HMGB2) is a multifunctional protein that plays various roles in different cellular compartments. Moreover, HMGB2 serves as a potential prognostic biomarker and therapeutic target for lung adenocarcinoma (LUAD). METHODS: In this study, the expression pattern, prognostic implication, and potential role of HMGB2 in LUAD were evaluated using the integrated bioinformatics analyses based on public available mRNA expression profiles from The Cancer Genome Atlas and Gene Expression Omnibus databases, both at the single-cell level and the tissue level. Further study in the patient-derived samples was conducted to explore the correlation between HMGB2 protein expression levels with tissue specificity, (tumor size-lymph node-metastasis) TNM stage, pathological grade, Ki-67 status, and overall survival. In vitro experiments, such as CCK-8, colony-formation and Transwell assay, were performed with human LUAD cell line A549 to investigate the role of HMGB2 in LUAD progression. Furthermore, xenograft tumor model was generated with A549 in nude mice. RESULTS: The results showed that the HMGB2 expression was higher in the LUAD samples than in the adjacent normal tissues and was correlated with high degree of malignancy in different public data in this study. Besides, over-expression of HMGB2 promoted A549 cells proliferation and migration while knocking down of HMGB2 suppressed the tumor promoting effect. CONCLUSIONS: Our study indicated that HMGB2 was remarkably highly expressed in LUAD tissues, suggesting that it is a promising diagnostic and therapeutic marker for LUAD in the future.

Pharmacokinetics and safety of pegylated recombinant human granulocyte colony-stimulating factor in children with acute leukaemia.

AIMS: This open-label, phase I study evaluated the pharmacokinetics and safety of pegylated recombinant human granulocyte colony-stimulating factor (PEG-rhG-CSF) for the treatment of chemotherapy-induced neutropenia in children with acute leukaemia. METHODS: PEG-rhG-CSF was administered as a single 100 mcg/kg (3 mg maximum dose) subcutaneous injection at the end of each chemotherapy period when neutropenia occurred. Blood samples were obtained from patients treated with PEG-rhG-CSF. PEG-rhG-CSF serum concentrations were determined by an enzyme-linked immunosorbent assay. Population pharmacokinetic (PPK) analysis was implemented using the nonlinear mixed-effects model. Short-term safety was evaluated through adverse events collection (registered at clinicaltrials.gov identifier: 03844360). RESULTS: A total of 16 acute leukaemia patients (1.8-13.6 years) were included, of whom two (12.5%) had grade 3 neutropenia, six (37.5%) had grade 4 neutropenia, and eight (50.0%) had severe neutropenia. For PPK modelling, 64 PEG-rhG-CSF serum concentrations were obtainable. A one-compartment model with first-order elimination was used for pharmacokinetic data modelling. The current weight was a significant covariate. The median (range) of clearance (CL) and area under the serum concentration-time curve (AUC) were 5.65 (1.49-14.45) mL/h/kg and 16514.75 (6632.45-54423.30) ng·h/mL, respectively. Bone pain, pyrexia, anaphylaxis and nephrotoxicity were not observed. One patient died 13 days after administration, and the objective assessment of causality was that an association with PEG-rhG-CSF was "possible". CONCLUSIONS: The AUC of PEG-rhG-CSF (100 mcg/kg, 3 mg maximum dose) in paediatric patients with acute leukaemia were similar to those of PEG-rhG-CSF (100 mcg/kg) in children with sarcoma. PEG-rhG-CSF is safe, representing an important therapeutic option for chemotherapy-induced neutropenia in paediatric patients with acute leukaemia.

Effect of Ag-1031 on apoptosis in gastric cancer AGS cells and its effects on the PI3K/AKT/mTOR signaling pathway.

PURPOSE: To investigate the effect of Ag-1031 on apoptosis of gastric cancer AGS cells and the PI3K/AKT/mTOR signaling pathway. METHODS: Gastric cancer cells were treated with different doses of Ag-1031. Cell viability was determined with MTT assay. Apoptosis was analyzed with Hoechst 33342 staining and Annexin V-FITC/PI double staining. The protein expression levels of p-PI3K, p-AKT, p-mTOR, PI3K, AKT and mTOR were assayed with western blotting method. RESULTS: Different doses of Ag-1031 significantly inhibited the proliferation of AGS cells. Moreover, Ag-1031 induced apoptosis,in gastric cancer cells. In addition, Ag-1031 significantly and dose-dependently inhibited the protein expressions of p-PI3K, p-AKT and p-mTOR. However, it had no effect on the protein expressions of PI3K, AKT and mTOR. CONCLUSION: In this study, it was found for the first time that Ag-1031 exerts an anti-tumor effect by induction apoptosis in gastric cancer AGS cells, through a mechanism related to inhibition of the activation of the PI3K/AKT/mTOR signaling pathway.

Application of Glutamine-enriched nutrition therapy in childhood acute lymphoblastic leukemia.

BACKGROUND: We investigated the effects of glutamine (Gln)-enriched nutritional therapy during chemotherapy on the nutritional status and immune function of children with acute lymphoblastic leukemia (ALL). METHODS: We enrolled 48 children who were newly diagnosed with ALL in our department during the period of 2013.1-2014.12. The patients (follow random number table) were randomly divided into the control group (peptamen) and the treatment group (peptamen + glutamine), 24 cases in each group. The remission induction regimens were all based on VDLP (D) chemotherapy (VCR (Vincrisstine), DNR (Daunomycin), L-ASP (L-Asparagiase), Prednisolone and Dexamethasone). The treatment group received Gln-enriched nutritional therapy every day during the full course of chemotherapy,and the control group is as same as the treatment group except without glutamine. The indicators of general nutritional status, such as weight, height, and triceps skinfold thickness, and the indicators of biochemical tests, such as serum albumin, prealbumin, creatinine-height index, retinol binding protein, and urinary hydroxyproline index, were compared between the two groups at the end of the first, second, third and the fourth week when the chemotherapy was completed. And in the fourth week, flow cytometry was applied to detect the levels of T cell subsets and the activities of natural killer (NK) cells in peripheral blood of the two groups. RESULTS: 1. after 4 weeks nutritional therapy, there is no significant difference (p > 0.05) between the two groups of children in weight, height and other indicators. 2. At the end of 2 weeks treatment, the level of prealbumin (PA) and retinol-binding protein (RBP) is higher in treatment group than that in the control group (P <0.05), at the end of 3 weeks treatment, the thickness of triceps skinfold is higher (P <0.05) than that in the control group; 3. At the end of 3 and 4 weeks, the concentrations serum ALB, PA, RBP and UHI were higher than in the control group (P <0.05); 4. There is statistically significant (p < 0.05) between the two groups in edema incidence; 5. At the end of treatment (4 weeks), the percentages of CD3 +, CD4 +, CD4 +/CD8 +, NK cell are significantly decreased in the two groups (P <0.05). CONCLUSION: Gln-enriched nutritional therapy can effectively improve the systemic nutritional status of children with leukemia, improve immune function.

Endoscopic classification can predict the infiltrative growth patterns of early-stage esophageal cancer: a retrospective study of 133 patients at a single academic tertiary care center.

The relationships between two endoscopic classification systems (type I and II) and the infiltrative growth patterns (INF) of early esophageal cancers were evaluated. Among type I carcinomas, the INFs were mainly INFb in the polypoid and mixed types, INFa in the superficial type, and INFc in the excavated type. Among type II carcinomas, INFa was the main pattern in the surface-propagating type, whereas INFb was observed in the intraluminal, bilateral, and mixed types. INFb and INFc were observed in the intramural type. Our results indicate that the superficial and surface-propagating types had the weakest infiltrative potential, whereas the excavated and intramural types had the highest infiltrative potential.

Integrating GC-MS and comparative transcriptome analysis reveals that TsERF66 promotes the biosynthesis of caryophyllene in Toona sinensis tender leaves.

Introduction: The strong aromatic characteristics of the tender leaves of Toona sinensis determine their quality and economic value. Methods and results: Here, GC-MS analysis revealed that caryophyllene is a key volatile compound in the tender leaves of two different T. sinensis varieties, however, the transcriptional mechanisms controlling its gene expression are unknown. Comparative transcriptome analysis revealed significant enrichment of terpenoid synthesis pathway genes, suggesting that the regulation of terpenoid synthesis-related gene expression is an important factor leading to differences in aroma between the two varieties. Further analysis of expression levels and genetic evolution revealed that TsTPS18 is a caryophyllene synthase, which was confirmed by transient overexpression in T. sinensis and Nicotiana benthamiana leaves. Furthermore, we screened an AP2/ERF transcriptional factor ERF-IX member, TsERF66, for the potential regulation of caryophyllene synthesis. The TsERF66 had a similar expression trend to that of TsTPS18 and was highly expressed in high-aroma varieties and tender leaves. Exogenous spraying of MeJA also induced the expression of TsERF66 and TsTPS18 and promoted the biosynthesis of caryophyllene. Transient overexpression of TsERF66 in T. sinensis significantly promoted TsTPS18 expression and caryophyllene biosynthesis. Discussion: Our results showed that TsERF66 promoted the expression of TsTPS18 and the biosynthesis of caryophyllene in T. sinensis leaves, providing a strategy for improving the aroma of tender leaves.

Enhanced anaerobic digestion performance and sludge filterability by membrane microaeration for anaerobic membrane bioreactor application.

Slow dissolution/hydrolysis of insoluble/macromolecular organics and poor sludge filterability restrict the application potential of anaerobic membrane bioreactor (AnMBR). Bubble-free membrane microaeration was firstly proposed to overcome these obstacles in this study. The batch anaerobic digestion tests feeding insoluble starch and soluble peptone with and without microaeration showed that microaeration led to a 65.7-144.8% increase in methane production and increased critical flux of microfiltration membrane via driving the formation of large sludge flocs and the resultant improvement of sludge settleability. The metagenomic and bioinformatic analyses showed that microaeration significantly enriched the functional genes and bacteria for polysaccharide and protein hydrolysis, microaeration showed little negative effects on the functional genes involved in anaerobic metabolisms, and substrate transfer from starch to peptone significantly affected the functional genes and microbial community. This study demonstrates the dual synergism of microaeration to enhance the dissolution/hydrolysis/acidification of insoluble/macromolecular organics and sludge filterability for AnMBR application.

Willingness intensity and co-evolution of decision rationality depending on aspiration enhance cooperation in the spatial public goods game.

The Fermi rule states that rational or irrational sentiment affects individual decision-making. Existing studies have assumed that individuals' irrational sentiments and behavior willingness have fixed values and do not change with time. In reality, people's rationality sentiment and behavior willingness may be influenced by some factors. Therefore, we propose a spatial public goods game mechanism, in which individuals' rational sentiment is co-evolution synchronously depending on the difference between aspiration and payoff. Moreover, the intensity of their subjective willingness to change the status quo depends on the gap between aspiration and payoff. We likewise compare the combined promotion effect of the stochastic "Win-Stay-Lose-Shift" (WSLS) and random imitation (IM) rules. Simulation experiments indicate that high enhancement factors are not conducive to cooperation under the IM rules. When aspiration is small, WSLS is more conducive to promoting cooperation than IM, while increasing aspiration, and the opposite phenomenon will appear. The heterogeneous strategic update rule is beneficial to the evolution of cooperation. Lastly, we find that this mechanism performs better than the traditional case in enhancing cooperation.

Design and Analysis of a Self-Adaptive Zeroing Neural Network for Solving Time-Varying Quadratic Programming.

In order to solve the time-varying quadratic programming (TVQP) problem more effectively, a new self-adaptive zeroing neural network (ZNN) is designed and analyzed in this article by using the Takagi-Sugeno fuzzy logic system (TSFLS) and thus called the Takagi-Sugeno (T-S) fuzzy ZNN (TSFZNN). Specifically, a multiple-input-single-output TSFLS is designed to generate a self-adaptive convergence factor to construct the TSFZNN model. In order to obtain finite- or predefined-time convergence, four novel activation functions (AFs) [namely, power-bi-sign AF (PBSAF), tanh-bi-sign AF (TBSAF), exp-bi-sign AF (EBSAF), and sinh-bi-sign AF (SBSAF)] are developed and applied in the TSFZNN model for solving the TVQP problem. Both theoretical proofs and experimental simulations show that the TSFZNN model using PBSAF or TBSAF has the property of converging in a finite time, and the TSFZNN model using EBSAF or SBSAF has the property of converging in a predefined time, which have superior convergence performance compared to the traditional ZNN model.

A Segmented Variable-Parameter ZNN for Dynamic Quadratic Minimization With Improved Convergence and Robustness.

As a category of the recurrent neural network (RNN), zeroing neural network (ZNN) can effectively handle time-variant optimization issues. Compared with the fixed-parameter ZNN that needs to be adjusted frequently to achieve good performance, the conventional variable-parameter ZNN (VPZNN) does not require frequent adjustment, but its variable parameter will tend to infinity as time grows. Besides, the existing noise-tolerant ZNN model is not good enough to deal with time-varying noise. Therefore, a new-type segmented VPZNN (SVPZNN) for handling the dynamic quadratic minimization issue (DQMI) is presented in this work. Unlike the previous ZNNs, the SVPZNN includes an integral term and a nonlinear activation function, in addition to two specially constructed time-varying piecewise parameters. This structure keeps the time-varying parameters stable and makes the model have strong noise tolerance capability. Besides, theoretical analysis on SVPZNN is proposed to determine the upper bound of convergence time in the absence or presence of noise interference. Numerical simulations verify that SVPZNN has shorter convergence time and better robustness than existing ZNN models when handling DQMI.

Role of endoscopic ultrasound in the evaluation of unexplained extrahepatic bile duct dilatation.

OBJECTIVE: This study was performed to assess the diagnostic performance of endoscopic ultrasonography (EUS) in patients with extrahepatic bile duct (EBD) dilatation and develop a novel model incorporating EUS-based signature with clinical parameters for distinguishing the malignant dilation of EBD. METHODS: The EUS data and clinical parameters of the patients were collected and analyzed retrospectively. First, we evaluated the diagnostic performance of EUS in detecting the cause of EBD dilatation. Then, we performed univariate and multivariate binary logistic regression analyses based on clinical and EUS features. Finally, a nomogram was established to aid in distinguishing between malignant dilation and noncalculous benign dilatation of EBD in patients. RESULTS: A total of 184 patients were enrolled. For the diagnosis of malignant dilation, EUS achieved an accuracy of 90.76%, sensitivity of 85.96%, and specificity of 92.91%. For the diagnosis of calculous dilation, EUS achieved an accuracy of 100%, sensitivity of 100%, and specificity of 100%. For the diagnosis of noncalculous benign dilatation, EUS achieved an accuracy of 90.76%, sensitivity of 90.90%, and specificity of 90.58%. Multivariable logistic regression analyses indicated that abnormal liver function test, elevated tumor markers, and EUS findings were the well-diagnostic factors of malignant EBD dilation. The nomogram established by these factors showed good calibration and discrimination. CONCLUSION: EUS is a useful examinational modality in the work-up of EBD dilatation. In combination with abnormal liver function test and elevated tumor markers, EUS may provide additional information for the detection of malignant dilation of EBD and should be further investigated.

Regional variation of polybrominated diphenyl ethers in East Asian finless porpoises in the East China Sea.

Certain polybrominated diphenyl ethers (PBDEs) have been banned for years, however, they still possess the potential to harm marine cetaceans. In this study, 56 East Asian finless porpoises (EAFPs) collected from three locations of the East China Sea between 2009 and 2011, were analyzed to determine the presence of typical PBDE congeners. Among all the samples, BDE47 was the main congener, constituting ∼48.3 % of the ΣPBDEs. Significant variations (p < 0.01) in PBDE abundance were observed among different regions (Pingtan: 172.8 ng/g, Lvsi: 61.2 ng/g and Ningbo: 32.9 ng/g). In addition, there was a significant positive correlation between PBDE abundance and male body length. The general ΣPBDEs concentration of this population was lower compared to other populations and cetaceans. Although combined risk assessments indicated a low risk to porpoise health, long-term surveillance is essential as PBDEs are not completely banned.

Modified Noise-Immune Fuzzy Neural Network for Solving the Quadratic Programming With Equality Constraint Problem.

Quadratic programming with equality constraint (QPEC) problems have extensive applicability in many industries as a versatile nonlinear programming modeling tool. However, noise interference is inevitable when solving QPEC problems in complex environments, so research on noise interference suppression or elimination methods is of great interest. This article proposes a modified noise-immune fuzzy neural network (MNIFNN) model and use it to solve QPEC problems. Compared with the traditional gradient recurrent neural network (TGRNN) and traditional zeroing recurrent neural network (TZRNN) models, the MNIFNN model has the advantage of inherent noise tolerance ability and stronger robustness, which is achieved by combining proportional, integral, and differential elements. Furthermore, the design parameters of the MNIFNN model adopt two disparate fuzzy parameters generated by two fuzzy logic systems (FLSs) related to the residual and residual integral term, which can improve the adaptability of the MNIFNN model. Numerical simulations demonstrate the effectiveness of the MNIFNN model in noise tolerance.

Novel combined endoscopic and laparoscopic surgery for advanced T2 gastric cancer: Two case reports.

BACKGROUND: The standard treatment for advanced T2 gastric cancer (GC) is laparoscopic or surgical gastrectomy (either partial or total) and D2 lymphadenectomy. A novel combined endoscopic and laparoscopic surgery (NCELS) has recently been proposed as a better option for T2 GC. Here we describe two case studies demonstrating the efficacy and safety of NCELS. CASE SUMMARY: Two T2 GC cases were both resected by endoscopic submucosal dissection and full-thickness resection and laparoscopic lymph nodes dissection. This method has the advantage of being more precise and minimally invasive compared to current methods. The treatment of these 2 patients was safe and effective with no complications. These cases were followed up for nearly 4 years without recurrence or metastasis. CONCLUSION: This novel method provides a minimally invasive treatment option for T2 GC, and its potential indications, effectiveness and safety needs to be further evaluated in controlled studies.