Detection and severity assessment of obstructive sleep apnea according to deep learning of single-lead electrocardiogram signals.

Developing a convenient detection method is important for diagnosing and treating obstructive sleep apnea. Considering availability and medical reliability, we established a deep-learning model that uses single-lead electrocardiogram signals for obstructive sleep apnea detection and severity assessment. The detection model consisted of signal preprocessing, feature extraction, time-frequency domain information fusion, and classification segments. A total of 375 patients who underwent polysomnography were included. The single-lead electrocardiogram signals obtained by polysomnography were used to train, validate and test the model. Moreover, the proposed model performance on a public dataset was compared with the findings of previous studies. In the test set, the accuracy of per-segment and per-recording detection were 82.55% and 85.33%, respectively. The accuracy values for mild, moderate and severe obstructive sleep apnea were 69.33%, 74.67% and 85.33%, respectively. In the public dataset, the accuracy of per-segment detection was 91.66%. A Bland-Altman plot revealed the consistency of true apnea-hypopnea index and predicted apnea-hypopnea index. We confirmed the feasibility of single-lead electrocardiogram signals and deep-learning model for obstructive sleep apnea detection and severity evaluation in both hospital and public datasets. The detection performance is high for patients with obstructive sleep apnea, especially those with severe obstructive sleep apnea.

Histone deacetylase 3-specific inhibitor RGFP966 attenuates oxidative stress and inflammation after traumatic brain injury by activating the Nrf2 pathway.

Background: Oxidative stress (OS) and inflammatory reactions play pivotal roles in secondary brain injury after traumatic brain injury (TBI). Histone deacetylase 3 (HDAC3) controls the acetylation of histones and non-histones, which has a significant impact on the central nervous system's reaction to damage. This research determined the implications of RGFP966, a new and specific inhibitor of HDAC3, for the antioxidant (AO) systems mediated by nuclear factor erythroid2-related factor 2 (Nrf2) and the Nod-like receptor protein 3 (NLRP3) inflammasome in TBI. The study also studied the underlying mechanisms of RGFP966's actions. Our objective was to examine the impacts and underlying RGFP966 mechanisms in TBI. Methods: In vitro, a rat cortical neuron OS model was induced by H2O2, followed by the addition of RGFP966 to the culture medium. Neurons were collected after 24 h for western blot (WB), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and 2'-7'-dichlorodihydrofluorescein diacetate staining. In vivo, RGFP966 (10 mg/kg) was administered post-TBI. Brain tissue water content and modified neurological severity scores were assessed 72 h post-injury. Cortical tissues surrounding the focal injury were subjected to western blot, TUNEL staining, Nissl staining and immunofluorescence/immunohistochemistry staining, and malondialdehyde level, hindered glutathione content and superoxide dismutase activity were measured. Serum was collected for the enzyme-linked immunosorbent assay. Nrf2-specific shRNA lentivirus was injected into the lateral ventricle of rats for 7 days, and cerebral cortex tissue was analyzed by WB and real-time polymerase chain reaction. Results: During in vitro and in vivo experiments, RGFP966 suppressed HDAC3 expression, promoted Nrf2 nuclear translocation, activated downstream AO enzymes, mitigated excessive reactive oxygen species production and alleviated nerve cell apoptosis. RGFP966 effectively reduced brain edema and histological damage and enhanced neurological and cognitive function in rats with TBI. RGFP966 markedly inhibited NLRP3 inflammasome activation mediated by high-mobility group box 1 (HMGB1)/toll-like receptor 4 (TLR4). Nrf2 knockdown in TBI rats attenuated the AO and anti-inflammatory, neuroprotective impacts of RGFP966. Conclusions: Overall, our findings demonstrate that RGFP966 can mitigate the first brain damage and neurological impairments in TBI. The underlying mechanism involves triggering the Nrf2-mediated AO system and negatively regulating the HMGB1/TLR4-mediated NLRP3 inflammasome pathway.

A validated LC-MS/MS method for determination of six Anti-SARS-CoV-2 drugs in plasma and its application for a pharmacokinetic study in rats.

Antiviral treatment for COVID-19 is considered an effective tool in reducing the rate of severe cases and deaths. As of June 2023, a total of six small molecule antiviral drugs have been conditionally approved for marketing by the National Medical Products Administration (NMPA) within China. In this study, a method of HPLC-MS/MS was established and validated for the determination of six small molecule antiviral drugs in plasma using Lamivudine as an internal standard. The chromatographic separation was performed using gradient elution with an ACE 3 C18-PFP column (3.0 mm × 150 mm, 3 µm), and the mobile phase consisted of deionized water and acetonitrile/water (90:10, v/v), both with 10 mmol/L of ammonium acetate and 0.1 % ammonium hydroxide added. Quantitative analysis of the six small molecule drugs was carried out through selective reaction monitoring based on the positive ion spray ionization mode. The method exhibited excellent precision, accuracy, recovery, and linearity, and it was used to determine the pharmacokinetic characteristics in rats. Our work not only established a bioanalytical method for six small molecule antiviral drugs but also provided scientific references for clinical pharmacokinetic studies.

In-situ generation of iron activated percarbonate for sustainable sludge dewatering.

Effective dewatering of sewage sludge could potentially address the issues of high energy consumption and large carbon footprint inherent in the sludge treatment process, advancing toward carbon neutrality in environmental remediation. Yet, the surface hydrophilic characteristics and water-holding interfacial affinity in sludge led to dwindled sludge-water separation performance. Here, the integration of in-situ generation of iron from zero-valent scrap iron (ZVSI) and sodium percarbonate (SPC) was attempted to attenuate the water-retaining interfacial affinity within sludge, thus achieving superior sludge dewatering performance. Results showed that under the optimal conditions, the ZVSI + SPC system led to a remarkable decline of 76.09 % in the specific resistance to filtration of the sludge, accompanied by a notable decline of 34.96 % in the water content. Moreover, the utilization of ZVSI + SPC system could be a viable alternative to the traditional strategies in terms of enhanced sludge dewaterability, offering application potential with stable operating performance, economic feasibility, and reduced carbon emissions. Investigation into dewatering mechanism revealed that ZVSI could maintain the Fe3+/Fe2+ in a stable dynamic cycle and continuously in-situ generate Fe2+, thereby efficaciously fostering the SPC activation for the ceaseless yield of reactive oxygen species. The predominant •OH and 1O2 efficiently decomposed the hydrophilic biopolymers, therefore minimizing the hydrophilic protein secondary structures, along with the hydrogen and disulfide bonds within proteins. Subsequently, the water-holding interfacial affinity was profoundly diminished, leading to intensified hydrophobicity, self-flocculation, and dewaterability. These findings have important implications for the advancement of efficacious ZVSI + SPC conditioning techniques toward sustainable energy and low-carbon prospects.

Triclocarban transformation and removal in sludge conditioning using chalcopyrite-triggered percarbonate treatment.

Herein, a facile combination approach of chalcopyrite and sodium percarbonate (CuFeS2+ SPC) was established to augment both TCC removal efficiency and sludge dewatering. Results showed that utilizing the CuFeS2 dosage of 600 mg/g total solids (TS) under the optimal condition, along with the SPC dosage of 12.5 mg/g TS, an initial pH of 4.0, and a reaction duration of 40 min, led to a substantial reduction of 53.9% in the TCC content within the sludge, accompanied by a notable decrease of 36.9% in the water content. Compared to well-studied iron-based advanced oxidation processes, CuFeS2 + SPC treatment proved to be more cost-effective and environmentally friendly. Mechanistic findings demonstrated that •OH oxidation played a significant role in TCC removal, with O2•- and 1O2 acting as secondary factors. During the CuFeS2 + SPC process, the received •OH, O2•-, and 1O2 destroyed the main binding sites of extracellular polymeric substances to TCC, including tryptophan-like protein, amide, CO stretch, and -COO- functional groups. As a result, approximately 50% of TCC was partially degraded within the solid sludge phase after the attack of radicals. Meanwhile, the decreased macromolecular organic compounds in solid sludge attenuated the binding efficacy of TCC, giving rise to the transfer of partial TCC to the liquid phase. Ultimately, the TCC in sludge was successfully removed, and five transformation products were identified. This study significantly contributes to our understanding regarding TCC transformation and removal in the sludge conditioning process.

Near-infrared Piezochromic Materials at High Pressure.

The study of piezochromic materials (PCMs) has become an attractive field and numerous scholars have reported various material structures and phenomena. PCMs incorporating near-infrared (NIR) emission have led to a broader range of applications due to the strong penetration and interference resistance of longer wavelength light sources. However, NIR PCMs are still rare due to difficulties in tuning molecular configuration, conformation and stacking structure. In this review, organic compounds are classified according to their types and structures, and recent advances in NIR PCMs are comprehensively summarized and described. The various factors affecting the piezochromic properties from the perspective of the compound structure are shown. The effects of pressure on the photophysical changes of different compounds are discussed. It is expected to provide ideas for subsequent NIR PCMs, from structural design to predicting their photophysical properties under pressure.

Pharmacokinetic study on the effect of ligustrazine-tangeretin co-administration on the pharmacokinetics of ligustrazine and its potential mechanism in rats.

Both ligustrazine and tangeretin are usually prescribed in the treatment of cardiovascular diseases, which makes their co-administration possible. The investigation of the interaction between ligustrazine and tangeretin is necessary for the clinical compatibility of their source herbs. This study aimed to investigate the interaction of ligustrazine and tangeretin during their co-administration. The pharmacokinetics of ligustrazine (15 mg/kg) was investigated in the presence of 50, 100, and 150 mg/kg tangeretin in rats with six of each. A single dose of ligustrazine was set as the control. The effect of tangeretin on the in vitro metabolic stability of ligustrazine was also investigated in rat liver microsomes. Tangeretin significantly reduced the system exposure of ligustrazine under all experimental concentrations. Specifically, tangeretin reduced the AUC (from 48.86 ± 12.57 to 41.02 ± 4.85 (50 mg/kg tangeretin), 31.47 ± 5.26 (100 mg/kg tangeretin), and 27.55 ± 9.60 (150 mg/kg) µg/mL × h), MRT (from 7.05 ± 0.26 to 6.33 ± 0.48, 5.53 ± 0.68, and 5.21 ± 1.31 h), Cmax (from 7.45 ± 0.44 to 6.03 ± 0.44, 5.24 ± 0.47, and 5.02 ± 0.56 µg/mL), and t1/2 (from 5.90 ± 1.27 to 4.84 ± 1.19, 3.48 ± 1.33, 3.09 ± 0.62 h) in rats. In vitro, tangeretin also reduced the metabolic stability of ligustrazine behaved as the decreased half-life and increased intrinsic clearance rate. Co-consumption of ligustrazine with tangeretin induced interactions, which shortens the system exposure of ligustrazine. This study provides theoretical guidance for the clinical prescription of ligustrazine- and tangeretin-containing herbs.

Characteristics and risk factors for renal recovery after acute kidney injury in critically ill patients in cohorts of elderly and non-elderly: a multicenter retrospective cohort study.

BACKGROUND: The purpose of this study was to explore the risk factors for renal nonrecovery among elderly and nonelderly patients with acute kidney injury (AKI) in critically ill patients. METHODS: A multicenter retrospective cohort of 583 critically ill patients with AKI was examined. We found the best cutoff value for predicting renal recovery by age was 63 years old through logistic regression. All patients were divided into two cohorts, age <63 and age ≥63-years old; on the basis of renal recovery at 30 days after AKI, the two patient cohorts were further divided into a renal recovery group and a renal nonrecovery group. Multivariate logistic regression was used to analyze the risk factors affecting renal recovery in the two cohorts. RESULTS: The 30-day renal recovery rate of patients aged <63 years was 70.0% (198/283), multivariate analysis showed that the independent risk factors affecting renal nonrecovery in age <63 years old included AKI stage, blood lactate level and hemoglobin level. The 30-day renal recovery rate of patients aged ≥63 years was 28.7% (86/300), multivariate analysis showed that the independent risk factors for renal nonrecovery in age ≥63-years old included diabetes mellitus, surgery with general anesthesia, AKI stage, APACHE II score, eGFR, and hemoglobin level. CONCLUSIONS: The renal nonrecovery after AKI in critically ill patients in patients aged ≥63 years was more strongly affected by multiple risk factors, such as diabetes mellitus, surgery with general anesthesia, eGFR, and APACHE II score, in addition to hemoglobin and AKI stage.

Ebracteolatain A exerts anti-proliferation of breast cancer by inhibiting Protein kinase D 1 in MEK/ERK and PI3K/AKT signaling pathways.

BACKGROUND: Ebracteolatain A (EA) is an acetyl-phloroglucinol compound extracted from Euphorbiae Ebracteolatae Radix, which has been shown to have antitumor activity. PURPOSE: Current research addressed the antitumor activity of EA in breast cancer and further clarified its mechanism. STUDY DESIGN: Based on the pharmacodynamic evaluation in breast cancer cells and animal models, the antitumor effects of EA will be validated in vitro and in vivo. METHODS: Breast cancer cells were processed with increasing concentrations of EA. CCK-8 and colony formation assays were employed to examine the effects of EA on proliferation and survival. Flow cytometry detected the blocking function of EA on the cell cycle. The specific mechanism of EA in breast cancer was studied by transfection experiments and Western Blot analysis. Finally, a nude mice xenograft tumor model was constructed to assess the therapeutic and potential mechanism of EA. RESULTS: We proved that EA caused a dose-dependent inhibition on MCF-7 and MDA-MB-415 cells with IC50 of 6.164 and 6.623 µmol/l, respectively. While EA reduced cell proliferation and clone formation, and markedly arrested cells in the G0/G1 phase. In vivo, EA remarkably suppressed the tumor weight and volume in xenograft nude mice. Besides, PKD1 reversed the inhibition of EA on breast cancer cell proliferation, clone formation, and cycle arrest, and restored tumor growth in xenograft nude mice. Western Blot confirmed that EA regulates breast cancer by suppressing PKD1 in MEK/ERK and PI3K/AKT signaling pathways. CONCLUSION: Herein, we first confirmed EA exerts anti-proliferation by inhibiting PKD1 in MEK/ERK and PI3K/AKT signaling pathways, indicating that EA is a prodigious breast cancer drug candidate.

Iron-rich digestate biochar toward sustainable peroxymonosulfate activation for efficient anaerobic digestate dewaterability.

In this study, a suite of Fe-rich biochars derived from Fenton-like treated digestate (Fe-BC) were fabricated under different pyrolysis temperatures (300, 500, and 800 °C), which were firstly utilized as peroxymonosulfate (PMS) activators for promoting digestate dewaterability with wide applicability. Results showed that compared to the Fe-BC300/Fe-BC500 + PMS treatments, Fe-BC800 + PMS process performed superior digestate dewaterability in which specific resistance to filtration reduction and water content reduction improved by > 12.5% and > 130%, respectively, under the optimal conditions. Mechanistic results demonstrated that in Fe-BC800 + PMS system, HO• and SO4•- oxidation played a pivotal role on promoted digestate dewaterability, while HO• and 1O2 oxidation was dominated in Fe-BC300/Fe-BC500 + PMS treatments. Fe-BC800 containing higher Fe and CO contents could efficiently interact with PMS to generate numerous HO• and SO4•- via iron cycle. These highly reactive oxygen species proficiently reduced the hydrophilic biopolymers, protein molecules, and amino acids in extracellular polymeric substances, leading to remarkable decrease in particle size, hydrophilicity, adhesion, network strength, and bound water of digestate. Consequently, the flowability and dewaterability of digestate could be significantly enhanced. The cost-benefit result indicated the Fe-BC + PMS treatment possessed desirable reusability, applicability, and economic viability. Collectively, the Fe-BC + PMS is a high-performance and eco-friendly technique for digestate dewatering, which opens a new horizon towards a closed-loop of digestate reutilization.

Multitarget and Multipathway Regulation of Zhenqi Fuzheng Granule against Non-Small Cell Lung Cancer Based On Network Pharmacology and Molecular Docking.

Background and Objective. The morbidity and mortality rates of non-small cell lung cancer (NSCLC) remain high. Zhenqi Fuzheng (ZQFZ) granule, which consists of Astragali Radix and Ligustri Lucidi Fructus, is commonly used to improve the immunity of cancer patients. However, the mechanism of ZQFZ granule against NSCLC is still unclear. In this study, the network pharmacology and molecular docking approaches were used to investigate the potential mechanism of ZQFZ granule on NSCLC. Methods. The ingredients in the ZQFZ granule were considered in one study based on UPLC, and the potential targets were predicted in the SwissTargetPrediction database. NSCLC targets were gathered from GeneCards, OMIM, and TTD databases. The ingredient-target-NSCLC network was drawn by Cytoscape. The protein-protein interaction was obtained from the STRING database, and the gene function and biological pathways were analyzed by Metascape. AutoDock Vina was used to verify the molecular docking between the key compounds and core targets, and PyMol visualized the results. Results. 244 targets were related to 13 candidate compounds and 1904 targets were related to NSCLC, of which a total of 106 anti-NSCLC targets were predicted. The compound-target-NSCLC network indicated that sinapinic acid, ferulic acid, asiatic acid, pratensein, and glycitein might be the key components for treating NSCLC. The 41 vital targets (out of 106 targets) above the median calculated by PPI degree were selected for bioinformatics analysis. The top 10 targets out of 41 ranked by MCC were IL-6, SRC, CTNNB1, STAT3, CASP3, TNF, EGFR, MAPK8, HSP90AA1, and PTGS2. ZQFZ granule treatment for NSCLC involved many pathways through KEGG analyses, which included pathways in cancer (hsa05200), proteoglycans in cancer (hsa05205), endocrine resistance (hsa01522), microRNAs in cancer (hsa05206), PI3K-Akt signaling pathway (hsa04151), and IL-17 signaling pathway (hsa04657). Molecular docking studies revealed that sinapinic acid, ferulic acid, asiatic acid, pratensein, and glycitein had good infinity with most core targets. Conclusions. This study indicated that ZQFZ granule with multicompounds could treat NSCLC through multitargets and multipathways.

Development and Verification of Prognostic Prediction Models for Patients with Brain Trauma Based on Coagulation Function Indexes.

Objective: To assess the effect of adding coagulation indices to the currently existing prognostic prediction models of traumatic brain injury (TBI) in the prediction of outcome. Methods: A total of 210 TBI patients from 2017 to 2019 and 131 TBI patients in 2020 were selected for development and internal verification of the new model. The primary outcomes include death at 14 days and Glasgow Outcome Score (GOS) at 6 months. The performance of each model is evaluated by means of discrimination (area under the curve (AUC)), calibration (Hosmer-Lemeshow (H-L) goodness-of-fit test), and precision (Brier score). Results: The IMPACT Core model showed better prediction ability than the CRASH Basic model. Adding one coagulation index at a time to the IMPACT Core model, the new combined models IMPACT Core+FIB and IMPACT Core+APTT are optimal for the 6-month unfavorable outcome and 6-month mortality, respectively (AUC, 0.830 and 0.878). The new models were built based on the regression coefficients of the models. Internal verification indicated that for the prediction of 6-month unfavorable outcome and 6-month mortality, both the IMPACT Core+FIB model and the IMPACT Core+APTT model show better discrimination (AUC, 0.823 vs. 0.818 and 0.853 vs. 0.837), better calibration (HL, p = 0.114 and p = 0.317) and higher precision (Brier score, 0.148 vs. 0.141 and 0.147 vs. 0.164), respectively, than the original models. Conclusion: Our research shows that the combination of the traumatic brain injury prognostic models and coagulation indices can improve the 6-month outcome prediction of patients with TBI.

Raman spectroscopy and machine learning for the classification of breast cancers.

Breast cancer is a major health threat for women. The drug responses associated with different breast cancer subtypes have obvious effects on therapeutic outcomes; therefore, the accurate classification of breast cancer subtypes is critical. Breast cancer subtype classification has recently been examined using various methods, and Raman spectroscopy has emerged as an effective technique that can be used for noninvasive breast cancer analysis. However, the accurate and rapid classification of breast cancer subtypes currently requires a great deal of effort and experience with the processing and analysis of Raman spectra data. Here, we adopted Raman spectroscopy and machine learning techniques to simplify and accelerate the process used to distinguish normal from breast cancer cells and classify breast cancer subtypes. Raman spectra were obtained from cultured breast cancer cell lines, and the data were analyzed by two machine learning algorithms: principal component analysis (PCA)-discriminant function analysis (DFA) and PCA-support vector machine (SVM). The accuracies with which these two algorithms were able to distinguish normal breast cells from breast cancer cells were both greater than 97%, and the accuracies of breast cancer subtype classification for both algorithms were both greater than 92%. Moreover, our results showed evidence to support the use of characteristic Raman spectral features as cancer cell biomarkers, such as the intensity of intrinsic Raman bands, which increased in cancer cells. Raman spectroscopy combined with machine learning techniques provides a rapid method for breast cancer analysis able to reveal differences in intracellular compositions and molecular structures among subtypes.

Large-scale molecular epidemiological analysis of AAV in a cancer patient population.

Recombinant adeno-associated viruses (rAAVs) are well-established vectors for delivering therapeutic genes. However, previous reports have suggested that wild-type AAV is linked to hepatocellular carcinoma, raising concern with the safety of rAAVs. In addition, a recent long-term follow-up study in canines, which received rAAVs for factor VIII gene therapy, demonstrated vector integration into the genome of liver cells, reviving the uncertainty between AAV and cancer. To further explore this relationship, we performed large-scale molecular epidemiology of AAV in resected tumor samples and non-lesion tissues collected from 413 patients, reflecting nine carcinoma types: breast carcinoma, rectal cancer, pancreas carcinoma, brain tumor, hepatoid adenocarcinoma, hepatocellular carcinoma, gastric carcinoma, lung squamous, and adenocarcinoma. We found that over 80% of patients were AAV-positive among all nine types of carcinoma examined. Importantly, the AAV sequences detected in patient-matched tumor and adjacent non-lesion tissues showed no significant difference in incidence, abundance, and variation. In addition, no specific AAV sequences predominated in tumor samples. Our data shows that AAV genomes are equally abundant in tumors and adjacent normal tissues, but lack clonality. The finding critically adds to the epidemiological profile of AAV in humans, and provides insights that may assist rAAV-based clinical studies and gene therapy strategies.

Nicotine withdrawal induces hyperalgesia via downregulation of descending serotonergic pathway in the nucleus raphe magnus.

Patients deprived of cigarettes exhibit increased pain sensitivity during perioperative periods, yet the underlying neuroanatomical and molecular bases of this hypersensitivity are unclear. The present study showed that both the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) were significantly decreased in a rat model of nicotine withdrawal. These rats showed less tryptophan hydroxylase 2 (TPH2) positive neurons and reduced TPH2 expression in the nucleus raphe magnus (NRM), and thus resulted in decreased 5-hydroxytryptamine (5-HT) levels in cerebrospinal fluid. Intrathecal injection of 5-HT or NRM microinjection of TPH-overexpression adeno-associated virus alleviated nicotine withdrawal-induced hyperalgesia, whereas 5-HT receptor pharmacological blockade by methysergide (a 5-HT receptor antagonist) exacerbated hypersensitivity and diminished the difference between the two groups. Together, these data indicate that hyperalgesia after nicotine withdrawal is mediated by declined descending serotonergic pathways in the NRM. This provides a new perspective to improve the postoperative pain management of patients, especially the smokers.

Effective and Accurate Gene Silencing by a Recombinant AAV-Compatible MicroRNA Scaffold.

Short hairpin RNAs that are delivered by recombinant adeno-associated virus (rAAV) have the potential to elicit long-term RNAi therapy for human disease. However, the discovery that short hairpin sequences can cause truncation of the rAAV genome calls into question the efficiency and gene-silencing specificity of this strategy in humans. Here, we report that embedding the guide strand of a small silencing RNA into an artificial microRNA (miRNA) scaffold derived from mouse miRNA-33 ensures rAAV genomic integrity and reduces off-targeting by 10-fold, while maintaining effective in vivo target gene repression in mice.

Preparation of siRNA Duplexes.

This protocol describes how to anneal synthetic sense and antisense siRNAs to form siRNA duplexes, as well as the analysis of siRNA duplexes using nondenaturing polyacrylamide gel electrophoresis.

RNAi in Drosophila S2 Cells by siRNA Duplex or dsRNA Transfection.

This protocol describes an efficient method to trigger RNAi in Drosophila S2 cells by using transfection reagents to deliver siRNAs or dsRNAs.

RNAi in Mammalian Cells by siRNA Duplex Transfection.

Long dsRNA cannot be used in most cultured mammalian cells because it triggers the interferon response, causing widespread changes in gene expression and apoptosis. This protocol describes a method for delivering into mammalian cells siRNA duplexes that are too short to elicit the sequence-nonspecific responses associated with long dsRNA.

RNA Interference and Small RNA Analysis.

Small silencing RNAs have provided powerful reverse genetics tools and have opened new areas of research. This introduction describes the use of RNAi to suppress expression of individual genes for loss-of-function analysis. It also summarizes methods for measuring specific and global changes in small RNA expression, as well as methods to inhibit the function of individual endogenous small RNA species such as miRNAs.