Repression of PRMT activities sensitize homologous recombination-proficient ovarian and breast cancer cells to PARP inhibitor treatment.

An "induced PARP inhibitor (PARPi) sensitivity by epigenetic modulation" strategy is being evaluated in the clinic to sensitize homologous recombination (HR)-proficient tumors to PARPi treatments. To expand its clinical applications and identify more efficient combinations, we performed a drug screen by combining PARPi with 74 well-characterized epigenetic modulators that target five major classes of epigenetic enzymes. Both type I PRMT inhibitor and PRMT5 inhibitor exhibit high combination and clinical priority scores in our screen. PRMT inhibition significantly enhances PARPi treatment-induced DNA damage in HR-proficient ovarian and breast cancer cells. Mechanistically, PRMTs maintain the expression of genes associated with DNA damage repair and BRCAness and regulate intrinsic innate immune pathways in cancer cells. Analyzing large-scale genomic and functional profiles from TCGA and DepMap further confirms that PRMT1, PRMT4, and PRMT5 are potential therapeutic targets in oncology. Finally, PRMT1 and PRMT5 inhibition act synergistically to enhance PARPi sensitivity. Our studies provide a strong rationale for the clinical application of a combination of PRMT and PARP inhibitors in patients with HR-proficient ovarian or breast cancer.

Association of handgrip strength asymmetry and weakness with cognitive function: a nationally representative cohort study.

OBJECTIVE: To describe the association of handgrip strength asymmetry and weakness with cognitive function among Chinese middle-aged and older adults. STUDY DESIGN: We used data from four waves (2011, 2013, 2015, and 2018) of the China Health and Retirement Longitudinal Study. Handgrip strength was measured at baseline. Handgrip strength asymmetry was defined on the basis of the ratio of handgrip strength of the non-dominant hand to that of the dominant hand (i.e. non-dominant/dominant): a ratio of <0.9 defined as dominant handgrip strength asymmetry and >1.1 as non-dominant handgrip strength asymmetry. Weakness was defined as a handgrip strength of <28 kg for males or <18 kg for females. MAIN OUTCOME MEASURES: Cognitive function with its two core dimensions (episodic memory and mental status) at each wave was assessed and standardized. RESULTS: 9333 participants (48.3 % female, age 58.2 ± 9.0 years) were included. Non-dominant but not dominant handgrip strength asymmetry was significantly associated with poorer cognitive function at baseline (ß = -0.121, -0.092, and -0.132 for mental status, episodic memory, and global cognition, respectively). In longitudinal analyses over 2 years, dominant handgrip strength asymmetry significantly slowed cognitive decline (ß = -0.078 and -0.069 for mental status and global cognition, respectively), and non-dominant handgrip strength asymmetry accelerated cognitive decline (ß = 0.053 and 0.043 for episodic memory and global cognition, respectively). Weakness was associated with poorer cognitive function at baseline and cognitive decline over 2, 4, and 7 years (all P < 0.05). CONCLUSIONS: In middle-aged and older adults, non-dominant handgrip strength asymmetry and weakness were associated with poorer cognitive function and predicted accelerated cognitive decline. Dominant handgrip strength asymmetry may be beneficial for maintaining cognitive function.

Research on the dynamic tensile characteristics and surface crack evolution of coal under impact loading.

The tensile properties of coal under dynamic loading are important mechanical characteristics of coal and are highly important for controlling coal rock stability under impact loading conditions, selecting blasting engineering parameters, and studying the mechanism of rockburst disasters. To investigate the dynamic tensile failure process of coal subjected to impact loading, this study used high-speed photography and digital image correlation technology to capture the dynamic tensile failure of coal under impact loading. The dynamic tensile evolution was quantitatively analyzed from the beginning of coal sample being loaded to failure. The captured images of the coal were processed, and the fractal dimension was used to quantitatively describe the evolution of the coal surface cracks under impact loading. The following conclusions were drawn from the experimental results: (1) An empirical formula was established to describe the dynamic tensile strength characteristics of coal under different loading rates. (2) Under impact loading, the maximum strain of a Brazilian disc coal sample first appeared at the contact end between the sample and the incident rod. (3) Under impact loading, a Brazilian disc coal sample cracked from the center of the sample outward, and the crack subsequently extended toward both ends. The fractal dimension of the crack exhibited a power function relationship with time, and the variation range of the fractal dimension of the crack was 1.05-1.39.

New approach for near-infrared wavelength selection using a combination of MIC and firefly evolution.

Full-length spectral data analysis has a big problem that the variables are highly in collinearity and correlation. Spectral wavelength selection is a continuing hot topic in quantitative or qualitative analysis. In this paper, we propose a new approach for near-infrared (NIR) wavelength selection. The novel strategy mainly refers to the modification of maximum information coefficient (MIC) method and an improvement of firefly evolutionary algorithm. We introduce the orthogonal decomposition to modify the MIC method, so as to search the informative signals conceived in projection vectors. We also raise the common firefly algorithm (FA) as in the discretized mode, and design a novel adaptive mapping function to improve its intelligent computing effect. In experiment, the modified MIC (MICm) method and the adaptive discrete FA algorithm (DFAadp) are joint together for combined optimization of the NIR calibration model. The proposed combined modeling strategy is applied for quantitative analysis of the fishmeal samples, in the concern to select their informative variables/wavelengths. Experimental results indicate that the combination of MICm and DFAadp perform better than traditional MIC method and common DFA. We conclude that the proposed combined optimization strategy is beneficial for wavelength selection in NIR spectral analysis. It is anticipated to be validated for further applications in a wide range.

Serum ferritin is associated with the presence of ischemic stroke among individuals with type 2 diabetes.

Background: Epidemiological evidence regarding the possible link between serum ferritin (SF) level and ischemic stroke risk among individuals with type 2 diabetes mellitus (T2DM) is sparse. Aim: To evaluate the association between SF level in plasma and ischemic stroke risk among individuals with T2DM. Methods: SF levels were measured in 210 T2DM patients with (n = 165) or without ischemic stroke (n = 45). Multivariate logistic regression analyses were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Results: The SF level of T2DM patients with ischemic stroke was significantly higher than that of patients without ischemic stroke (P = 0.003). The multivariate logistic regression analyses revealed that each 1-SD increase in SF (OR: 1.92; 95%CI: 1.22, 3.03) was significantly associated with increased ischemic stroke risk among T2DM patients. In addition, interaction effect of SF and BMI on ischemic stroke risk were also observed (Pfor interaction = 0.037). Conclusions: Higher levels of SF were independently associated with increased risk of ischemic stroke among individuals with T2DM.

Molecular biomarkers of diffuse axonal injury: recent advances and future perspectives.

INTRODUCTION: Diffuse axonal injury (DAI), with high mortality and morbidity both in children and adults, is one of the most severe pathological consequences of traumatic brain injury. Currently, clinical diagnosis, disease assessment, disability identification, and postmortem diagnosis of DAI is mainly limited by the absent of specific molecular biomarkers. AREAS COVERED: In this review, we first introduce the pathophysiology of DAI, summarized the reported biomarkers in previous animal and human studies, and then the molecular biomarkers such as ß-Amyloid precursor protein, neurofilaments, S-100ß, myelin basic protein, tau protein, neuron-specific enolase, Peripherin and Hemopexin for DAI diagnosis is summarized. Finally, we put forward valuable views on the future research direction of diagnostic biomarkers of DAI. EXPERT OPINION: In recent years, the advanced technology has ultimately changed the research of DAI, and the numbers of potential molecular biomarkers was introduced in related studies. We summarized the latest updated information in such studies to provide references for future research and explore the potential pathophysiological mechanism on diffuse axonal injury.

Xylazine Poisoning in Clinical and Forensic Practice: Analysis Method, Characteristics, Mechanism and Future Challenges.

Xylazine abuse is emerging globally, while the identification of xylazine lethal cases poses a great challenge in clinical and forensic practice. The non-specific symptoms delay the diagnosis and treatment of xylazine poisoning, the pathological changes and lethal concentration of xylazine in body fluid and organs of fatal xylazine poisoning cases are seldom reported and the other toxins detected in such cases complicate the role of xylazine in the cause of death. Therefore, we carefully reviewed related updated information on xylazine, summarized the knowledge from clinical and forensic perspectives and can thus provide a reference in such cases and throw light on further study in the field of xylazine poisoning.

Association of blood trihalomethane concentrations with hypertension in US adults: A nationwide cross-sectional study.

Trihalomethanes (THMs), as the most common species of disinfection byproducts in chlorinated water, have been associated with hypertensive disorders in pregnancy. However, there is sparse epidemiological evidence regarding the possible link between THMs exposure and hypertension in general adults. In the present study, we aimed to characterize the associations between THMs exposure and hypertension in general adults. We performed cross-sectional analyses of 15,135 adults from the 1999-2018 National Health and Nutrition Examination Survey. In the general US adults, the median blood concentrations of the chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM) and bromoform (TBM) were: 4.80 pg/mL, 0.71 pg/mL, 0.44 pg/mL and 0.71 pg/mL, respectively. And adults in the highest tertile of blood TBM and DBCM had odds ratios of 1.20 (95 % confidence intervals: 1.02, 1.42) and 1.15 (1.01, 1.30), respectively, for hypertension, compared with adults in the lowest tertile. Also, significant positive associations between blood brominated THM concentrations (sum of TBM, BDCM and DBCM) and prevalent hypertension were observed. In addition, significant interactions with BMI were demonstrated for Br-THMs (P for interaction = 0.017). Our study provides epidemiological evidence supporting a positive association between blood THMs and hypertension by using the nationally representative data, highlighting the need for further investigations to deepen our findings and elucidate the underlying mechanisms.

Association of knee and hip osteoarthritis with the risk of falls and fractures: a systematic review and meta-analysis.

OBJECTIVE: Studies evaluating the association of knee and hip osteoarthritis (OA) with falls and fractures have inconsistent findings. We aimed to investigate associations of symptomatic and radiographic knee and hip OA with risk of falls, recurrent falls, and fractures. METHODS: We conducted an electronic search of databases from inception to February 2023. Two authors independently screened studies, extracted data, and assessed the risk of bias using the Newcastle-Ottawa Scale tool in eligible studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models. RESULTS: Of 17 studies included (n = 862849), 2 had a high risk of bias. Among studies that evaluated falls or fractures as outcomes, 7/8 (87.5%) and 5/11 (45.5%) were self-reported, respectively. Both symptomatic knee and hip OA were associated with increased risk of recurrent falls (knee: OR = 1.55, 95% CI 1.10 to 2.18; hip: OR = 1.50, 95% CI 1.28 to 1.75) but not falls or fractures. Radiographic knee OA increased risk of falls (OR = 1.28, 95% CI 1.03 to 1.59) and did not significantly increase risk of recurrent falls (OR = 1.39, 95% CI 0.97 to 1.97) or fractures (OR = 1.22, 95% CI 0.99 to 1.52). Radiographic hip OA decreased the risk of recurrent falls (OR = 0.70, 95% CI 0.51 to 0.96) but had no statistically significant association with fractures (OR = 1.16, 95% CI 0.79 to 1.71). CONCLUSION: Symptomatic knee and hip OA were both associated with an increased risk of recurrent falls, and radiographic knee OA was associated with an increased risk of falls. No statistically significant associations of radiographic and symptomatic knee or hip OA with fractures were found.

Frailty predicts knee pain trajectory over 9 years: results from the Osteoarthritis Initiative.

OBJECTIVE: Frailty is a multisystem syndrome and its relationship with symptomatic osteoarthritis has been reported. We aimed to identify trajectories of knee pain in a large prospective cohort and to describe the effect of frailty status at baseline on the pain trajectories over 9 years. METHODS: We included 4419 participants (mean age 61.3 years, 58% female) from the Osteoarthritis Initiative cohort. Participants were classified as "no frailty," "pre-frailty," or "frailty" at baseline, based on 5 characteristics (ie, unintentional weight loss, exhaustion, weak energy, slow gait speed, and low physical activity). Knee pain was evaluated annually using the Western Ontario and McMaster Universities Osteoarthritis Index pain subscale (0-20) from baseline to 9 years. RESULTS: Of the participants included, 38.4%, 55.4%, and 6.3% were classified as "no frailty," "pre-frailty," and "frailty," respectively. Five pain trajectories were identified: "No pain" (n = 1010, 22.8%), "Mild pain" (n = 1656, 37.3%), "Moderate pain" (n = 1149, 26.0%), "Severe pain" (n = 477, 10.9%), and "Very Severe pain" (n = 127, 3.0%). Compared to participants with no frailty, those with pre-frailty and frailty were more likely to have more severe pain trajectories (pre-frailty: odds ratios [ORs] 1.5 to 2.1; frailty: ORs 1.5 to 5.0), after adjusting for potential confounders. Further analyses indicated that the associations between frailty and pain were mainly driven by exhaustion, slow gait speed, and weak energy. CONCLUSIONS: Approximately two-thirds of middle-aged and older adults were frail or pre-frail. The role of frailty in predicting pain trajectories suggests that frailty may be an important treatment target for knee pain.

Longitudinal associations of body mass index and abdominal circumference with back pain among community-dwelling adults: data from the Osteoarthritis Initiative.

BACKGROUND CONTEXT: Back pain is the most common musculoskeletal problem in both developed and developing countries. The prevalence and burden of back pain increases with age, and the management of back pain becomes increasingly important in the context of global aging. There is increasing evidence that obesity is a modifiable risk factor for musculoskeletal pain in different locations. Understanding the role of obesity in back pain holds great potential for improving understanding of the mechanisms of back pain and for developing new preventive and therapeutic approaches. PURPOSE: To evaluate the role of weight, body mass index (BMI) and abdominal circumference (AC) in risk of back pain over 96 months. DESIGN: Prospective cohort study. PATIENT SAMPLE: The sample was from 4,793 adults in the Osteoarthritis Initiative (OAI) database who had or were at increased risk for knee Osteoarthritis. OUTCOME MEASURES: Outcome variables included the presence, severity, and frequency of back pain, using the past 30 days as the time frame. METHODS: Longitudinal analysis of data from 4,793 participants enrolled in the Osteoarthritis Initiative, assessed every 12 or 24 months for weight, BMI (kg/m2), AC (cm), and presence, severity (none, mild, moderate, severe), and frequency (none, rarely, sometimes, often, always) of back pain. BMI and AC were decomposed into between-person and with-person components. Data analyses were performed using mixed-effects logistic (for presence of back pain) or ordered logistic regression (for severity and frequency of back pain) models. RESULTS: Back pain was reported in 58% of participants at baseline; 70% of those without back pain had incident back pain over 96 months. Both between-person (average value across a participant's all measurements) and within-person (deviations from the participant's average) effects of weight and BMI increased risk of presence, severity, and frequency of back pain (Odds radios (OR) per kg/m2: 1.010-1.046, p<.05) in females but not males, with statistically significant weight*sex and BMI*sex interactions. Similar findings were observed for between-person effects of AC on back pain, and the within-person effect of AC was only associated with back pain severity (OR per cm: 1.009, 95% confidence interval 1.002-1.017, p=.019) in females. CONCLUSIONS: Greater average weight and BMI and increases in them increased odds of presence, severity, and frequency of back pain over 96 months in middle aged and older women but not men. Only average AC increased odds of back pain over time, in women. These findings suggest that preventing obesity and slowing weight gain is important for the management of back pain.

Association of Sleep Disturbance With Catastrophizing and Knee Pain: Data From the Osteoarthritis Initiative.

OBJECTIVE: To investigate the relationship between sleep disturbance, catastrophizing, and knee pain in middle-aged and older individuals. METHODS: Data from the Osteoarthritis Initiative cohort from months 48 to 96 were used, where month 48 was treated as baseline. Knee pain (Western Ontario and McMaster Universities Osteoarthritis Index pain scale score ≥5 [range 0-20]), catastrophizing (extracted from Coping Strategies Questionnaire score ≥3 [range 0-6]), and sleep quality (extracted from Center for Epidemiologic Studies Depression Scale [range 1-4]) were assessed annually. We described the association of sleep disturbance with the presence and risk of knee pain and catastrophizing. The mediation effect of knee pain and catastrophizing on the sleep-catastrophizing and sleep-pain association was evaluated, respectively. RESULTS: Catastrophizing and knee pain were reported in 346 (10%) and 917 (24%) of the 3,813 participants (mean 64.9 years, 58% female) at baseline. Participants with worse sleep disturbance were more likely to have knee pain (prevalence ratio [PR] 1.4-2.0, P for trend <0.001) and catastrophizing (PR 1.4-3.1, P for trend <0.001). Sleep disturbance at baseline predicted the risk of knee pain (risk ratio [RR] 1.1, P for trend <0.001) and catastrophizing (RR 1.2-1.7, P for trend <0.001) during follow-up. No statistically significant interactions between sleep disturbance and knee pain or catastrophizing were observed. Knee pain and catastrophizing mediated the sleep-catastrophizing and sleep-pain association, respectively, at baseline, and knee pain negatively mediated the sleep-catastrophizing association longitudinally. CONCLUSION: Sleep disturbance was associated with the presence and risk of catastrophizing and knee pain. Sleep interventions may have a universal and independent effect in preventing incident knee pain.

Risk Factors of Ischemia Reperfusion Injury After PCI in Patients with Acute ST-Segment Elevation Myocardial Infarction and its Influence on Prognosis.

Purpose: To explore the risk factors of ischemia reperfusion injury (IRI) after percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) and its influence on prognosis. Methods: The clinical data of 80 patients with STMEI undergoing PCI in our hospital from June 2020 to June 2021 were collected. According to whether IRI occurred after PCI, STMEI patients were divided into IRI group and non-IRI group. The basic information, clinical characteristics, examination parameters and other data of all patients were collected, and the prognosis of the two groups was observed. Risk factors were analyzed by fitting binary Logistic regression model. The survival prognosis was analyzed by Kaplan-Meier survival curve. Results: Logistic regression analysis showed that type 2 diabetes mellitus (T2DM), pre-hospital delay time (PHD) and door-to-balloon expansion time (DTB) were the influencing factors of IRI in patients with STMEI (p < 0.05). MACE occurred in 11 cases (32.35%) in the IRI group and 13 cases (28.26%) in the non-IRI group. Log-rank test showed p = 0.503, indicating no statistically significant difference. Conclusion: T2DM, PHD and DTB were the influencing factors of IRI in patients with STMEI, and IRI will not reduce the prognosis of patients.

Improvement of NIR prediction ability by dual model optimization in fusion of NSIA and SA methods.

Feature selection and sample partitioning are both important to establish a quantitative analytical model for near-infrared (NIR) spectroscopy. The classical interval partial least squares (iPLS) model for waveband selection can be improved in combination of the simulated annealing (SA) algorithm. The sample set partitioning based on a joint x-y distance (SPXY) method for sample partitioning is based on the distances of both the x- and y- dimensions; it is expected to be optimized using the non-dominant sorting strategies (NS) combined with the immune algorithm (IA). In this study, we investigated the dual model optimization mode for simultaneous selection of feature waveband and sample partitioning, and proposed a novel method defined as SA-iPLS & SPXY-NSIA. The method explores a population evolution process, and takes the candidate individual as the link for the fusion optimization of SA-iPLS and SPXY-NSIA. The method screens feature wavebands and observes a good partition of the modeling samples, to construct a combined optimization strategy for fusion optimization of the target waveband and suitable sets of sample partitioning. The performance of the SA-iPLS & SPXY-NSIA method was tested using a soil sample dataset. To prove model enhancement, the proposed method was compared to the two traditional methods of Kennard-Stone (KS) and SPXY in combination with SA-iPLS. Experimental results show that the fusion model established by SA-iPLS & SPXY-NSIA performed better than the KS-SA-iPLS and SPXY-SA-iPLS models. The best testing results of the fusion model is with RMSET, RPDT and RT observed as 0.0107, 1.7233 and 0.9097, respectively. The proposed method is prospectively able to effectively improve the predictive ability of the NIR analytical model.

Systematic illumination of druggable genes in cancer genomes.

By combining 6 druggable genome resources, we identify 6,083 genes as potential druggable genes (PDGs). We characterize their expression, recurrent genomic alterations, cancer dependencies, and therapeutic potentials by integrating genome, functionome, and druggome profiles across cancers. 81.5% of PDGs are reliably expressed in major adult cancers, 46.9% show selective expression patterns, and 39.1% exhibit at least one recurrent genomic alteration. We annotate a total of 784 PDGs as dependent genes for cancer cell growth. We further quantify 16 cancer-related features and estimate a PDG cancer drug target score (PCDT score). PDGs with higher PCDT scores are significantly enriched for genes encoding kinases and histone modification enzymes. Importantly, we find that a considerable portion of high PCDT score PDGs are understudied genes, providing unexplored opportunities for drug development in oncology. By integrating the druggable genome and the cancer genome, our study thus generates a comprehensive blueprint of potential druggable genes across cancers.

Systematic Pan-Cancer Characterization of Nuclear Receptors Identifies Potential Cancer Biomarkers and Therapeutic Targets.

The nuclear receptor (NR) superfamily is one of the major druggable gene families, representing targets of approximately 13.5% of approved drugs. Certain NRs, such as estrogen receptor and androgen receptor, have been well demonstrated to be functionally involved in cancer and serve as informative biomarkers and therapeutic targets in oncology. However, the spectrum of NR dysregulation across cancers remains to be comprehensively characterized. Through computational integration of genetic, genomic, and pharmacologic profiles, we characterized the expression, recurrent genomic alterations, and cancer dependency of NRs at a large scale across primary tumor specimens and cancer cell lines. Expression levels of NRs were highly cancer-type specific and globally downregulated in tumors compared with corresponding normal tissue. Although the majority of NRs showed copy-number losses in cancer, both recurrent focal gains and losses were identified in select NRs. Recurrent mutations and transcript fusions of NRs were observed in a small portion of cancers, serving as actionable genomic alterations. Analysis of large-scale CRISPR and RNAi screening datasets identified 10 NRs as strongly selective essential genes for cancer cell growth. In a subpopulation of tumor cells, growth dependencies correlated significantly with expression or genomic alterations. Overall, our comprehensive characterization of NRs across cancers may facilitate the identification and prioritization of potential biomarkers and therapeutic targets, as well as the selection of patients for precision cancer treatment. SIGNIFICANCE: Computational analysis of nuclear receptors across multiple cancer types provides a series of biomarkers and therapeutic targets within this protein family.

NRXN2 Possesses a Tumor Suppressor Potential via Inhibiting the Growth of Thyroid Cancer Cells.

Thyroid cancer (THCA) is a common endocrine malignant tumor, and its global incidence of THCA has increased significantly. Neurexin 2 (NRXN2) is involved in the progression of some diseases. Nevertheless, it is still elusive towards the clinical implication and function of NRXN2 in THCA. As The Cancer Genome Atlas (TCGA) data demonstrated, we conducted a study to explore the links between NRXN2 expression and clinical features. Additionally, our data exhibited that, compared to normal thyroid tissues, NRXN2 showed low expression in THCA tissues. 20 important genes associated with NRXN2 were screened and identified. KEGG analysis data displayed that NRXN2 exhibited a link to the neuronal system, insulin secretion modulation, energy metabolism integration, muscle contraction, cardiac conduction, and neural adhesion molecule 1 (NCAM1) interactions. Our results in depth affirmed that NRXN2 was decreased in the tissues and cell lines of THCA patients. Functionally, we proved that overexpressing NRXN2 resulted in an inhibition of THCA cell proliferation, migration, and invasion in vitro. Collectively, our study demonstrated that, for the first time, NRXN2 behaved as an inhibitor of neoplasm and a promising biomarker in THCA.

PIAS3 suppresses damage in an Alzheimer's disease cell model by inducing the STAT3-associated STAT3/Nestin/Nrf2/HO-1 pathway.

BACKGROUND: Alzheimer's disease (AD), the most common form of dementia, is caused by the degeneration of the central nervous system (CNS). A previous study reported that signal transducer and activator of transcription 3 (STAT3) is activated during AD development; nonetheless, the related mechanism remains unknown. Thus, this study used a cell model to explore whether and how the protein inhibitor of activated STAT3 (PIAS3) is involved in AD development. METHODS: Cerebrospinal fluid (CSF) specimens of 30 patients with AD and 10 normal participants were included in this study. SH-SY5Y cells were used to constructed AD model. Relevant indices were then detected and analyzed. RESULTS: The results showed that compared with the control group, PIAS3 expression was substantially decreased in patients with AD and amyloid beta (Aß)-treated SH-SY5Y cells. PIAS3 overexpression was able to reverse the detrimental effects of Aß treatment on cell survival and growth. Further, it could also ameliorate apoptosis and oxidative stress in Aß-treated SH-SY5Y cells. Additionally, PIAS3 was shown to reduce the activated form of STAT3 and increase the activity of the downstream Nestin/nuclear factor erythroid 2-related factor/heme oxygenase-1 pathway. CONCLUSIONS: STAT3 reactivation by colivelin treatment negated the influence of PIAS3 on the survival, growth, apoptosis, and oxidative stress of Aß-treated SH-SY5Y cells.

Characterization of Long Non-coding RNA Associated Proteins by RNA-Immunoprecipitation.

With the advances in sequencing technology and transcriptome analysis, it is estimated that up to 75% of the human genome is transcribed into RNAs. This finding prompted intensive investigations on the biological functions of non-coding RNAs and led to very exciting discoveries of microRNAs as important players in disease pathogenesis and therapeutic applications. Research on long non-coding RNAs (lncRNAs) is in its infancy, yet a broad spectrum of biological regulations has been attributed to lncRNAs. RNA-immunoprecipitation (RNA-IP) is a technique of detecting the association of individual proteins with specific RNA molecules in vivo. It can be used to investigate lncRNA-protein interaction and identify lncRNAs that bind to a protein of interest. Here we describe the protocol of this assay with detailed materials and methods.

Detection of Long Non-coding RNA Expression by Non-radioactive Northern Blots.

With the advances in sequencing technology and transcriptome analysis, it is estimated that up to 75% of the human genome is transcribed into RNAs. This finding prompted intensive investigations on the biological functions of non-coding RNAs and led to very exciting discoveries of microRNAs as important players in disease pathogenesis and therapeutic applications. Research on long non-coding RNAs (lncRNAs) is in its infancy, yet a broad spectrum of biological regulations has been attributed to lncRNAs. As a novel class of RNA transcripts, the expression level and splicing variants of lncRNAs are various. Northern blot analysis can help us learn about the identity, size, and abundance of lncRNAs. Here we describe how to use northern blot to determine lncRNA abundance and identify different splicing variants of a given lncRNA.