Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

The Mechano-Ubiquitinome of Articular Cartilage: Differential Ubiquitination and Activation of a Group of ER-Associated DUBs and ER Stress Regulators.

Understanding how connective tissue cells respond to mechanical stimulation is important to human health and disease processes in musculoskeletal diseases. Injury to articular cartilage is a key risk factor in predisposition to tissue damage and degenerative osteoarthritis. Recently, we have discovered that mechanical injury to connective tissues including murine and porcine articular cartilage causes a significant increase in lysine-63 polyubiquitination. Here, we identified the ubiquitin signature that is unique to injured articular cartilage tissue upon mechanical injury (the "mechano-ubiquitinome"). A total of 463 ubiquitinated peptides were identified, with an enrichment of ubiquitinated peptides of proteins involved in protein processing in the endoplasmic reticulum (ER), also known as the ER-associated degradation response, including YOD1, BRCC3, ATXN3, and USP5 as well as the ER stress regulators, RAD23B, VCP/p97, and Ubiquilin 1. Enrichment of these proteins suggested an injury-induced ER stress response and, for instance, ER stress markers DDIT3/CHOP and BIP/GRP78 were upregulated following cartilage injury on the protein and gene expression levels. Similar ER stress induction was also observed in response to tail fin injury in zebrafish larvae, suggesting a generic response to tissue injury. Furthermore, a rapid increase in global DUB activity following injury and significant activity in human osteoarthritic cartilage was observed using DUB-specific activity probes. Combined, these results implicate the involvement of ubiquitination events and activation of a set of DUBs and ER stress regulators in cellular responses to cartilage tissue injury and in osteoarthritic cartilage tissues. This link through the ER-associated degradation pathway makes this protein set attractive for further investigation in in vivo models of tissue injury and for targeting in osteoarthritis and related musculoskeletal diseases.

Antiandrogens for the treatment of COVID-19 patients: A meta-analysis of randomized controlled trials.

Antiandrogens may carry a potential benefit as a therapeutic agent against COVID-19. However, studies have been yielding mixed results, thus hindering any objective recommendations. This necessitates a quantitative synthesis of data to quantify the benefits of antiandrogens. We systematically searched PubMed/MEDLINE, Cochrane Library, clinical trial registers, and reference lists of included studies to identify relevant randomized controlled trials (RCTs). Results from the trials were pooled using a random-effects model and outcomes were reported as risk ratios (RR) and mean differences (MDs) with 95% confidence intervals (CIs). Fourteen RCTs with a total sample size of 2593 patients were included. Antiandrogens yielded a significant mortality benefit (RR 0.37; 95% CI; 0.25-0.55). However, on subgroup analysis, only proxalutamide/enzalutamide and sabizabulin were found to significantly reduce mortality (RR 0.22, 95% CI: 0.16-0.30 and RR 0.42, 95% CI: 0.26-0.68, respectively), while aldosterone receptor antagonists and antigonadotropins did not show any benefit. No significant between-group difference was found in the early or late initiation of therapy. Antiandrogens also reduced hospitalizations and the duration of hospital stay, and improved recovery rates. Proxalutamide and sabizabulin may be effective against COVID-19, however, further large-scale trials are needed to confirm these findings.

Aspect-based classification of vaccine misinformation: a spatiotemporal analysis using Twitter chatter.

BACKGROUND: The spread of misinformation of all types threatens people's safety and interrupts resolutions. COVID-19 vaccination has been a widely discussed topic on social media platforms with numerous misleading and fallacious information. This false information has a critical impact on the safety of society as it prevents many people from taking the vaccine, decelerating the world's ability to go back to normal. Therefore, it is vital to analyze the content shared on social media platforms, detect misinformation, identify aspects of misinformation, and efficiently represent related statistics to combat the spread of misleading information about the vaccine. This paper aims to support stakeholders in decision-making by providing solid and current insights into the spatiotemporal progression of the common misinformation aspects of the various available vaccines. METHODS: Approximately 3800 tweets were annotated into four expert-verified aspects of vaccine misinformation obtained from reliable medical resources. Next, an Aspect-based Misinformation Analysis Framework was designed using the Light Gradient Boosting Machine (LightGBM) model, which is one of the most advanced, fast, and efficient machine learning models to date. Based on this dataset, spatiotemporal statistical analysis was performed to infer insights into the progression of aspects of vaccine misinformation among the public. Finally, the Pearson correlation coefficient and p-values are calculated for the global misinformation count against the vaccination counts of 43 countries from December 2020 until July 2021. RESULTS: The optimized classification per class (i.e., per an aspect of misinformation) accuracy was 87.4%, 92.7%, 80.1%, and 82.5% for the "Vaccine Constituent," "Adverse Effects," "Agenda," "Efficacy and Clinical Trials" aspects, respectively. The model achieved an Area Under the ROC Curve (AUC) of 90.3% and 89.6% for validation and testing, respectively, which indicates the reliability of the proposed framework in detecting aspects of vaccine misinformation on Twitter. The correlation analysis shows that 37% of the countries addressed in this study were negatively affected by the spread of misinformation on Twitter resulting in reduced number of administered vaccines during the same timeframe. CONCLUSIONS: Twitter is a rich source of insight on the progression of vaccine misinformation among the public. Machine Learning models, such as LightGBM, are efficient for multi-class classification and proved reliable in classifying vaccine misinformation aspects even with limited samples in social media datasets.

Asymmetric Dimethylation of Ribosomal S6 Kinase 2 Regulates Its Cellular Localisation and Pro-Survival Function.

Ribosomal S6 kinases (S6Ks) are critical regulators of cell growth, homeostasis, and survival, with dysregulation of these kinases found to be associated with various malignancies. While S6K1 has been extensively studied, S6K2 has been neglected despite its clear involvement in cancer progression. Protein arginine methylation is a widespread post-translational modification regulating many biological processes in mammalian cells. Here, we report that p54-S6K2 is asymmetrically dimethylated at Arg-475 and Arg-477, two residues conserved amongst mammalian S6K2s and several AT-hook-containing proteins. We demonstrate that this methylation event results from the association of S6K2 with the methyltransferases PRMT1, PRMT3, and PRMT6 in vitro and in vivo and leads to nuclear the localisation of S6K2 that is essential to the pro-survival effects of this kinase to starvation-induced cell death. Taken together, our findings highlight a novel post-translational modification regulating the function of p54-S6K2 that may be particularly relevant to cancer progression where general Arg-methylation is often elevated.

Fasting C-peptide values among adolescents in the National Health and Nutrition Examination Surveys.

AIM: To report fasting C-peptide values and variations across demographics in healthy non-diabetic adolescents included in the National Health and Nutrition Examination Surveys (NHANES) dataset. RESEARCH DESIGN AND METHODS: In this analysis, we used fasting C-peptide data from the 1999 to 2004 NHANES dataset for participants aged 12 to <18 years (n = 2063). RESULTS: The mean ± SE age of the participants was 14.99 ± 0.06 years. The participants included 992 girls and 1071 boys, and more than 80% of participants had a body mass index (BMI) percentile of <85%. Among boys, the most notable finding was the increase in geometric mean C-peptide level from 0.51 nmol/L at age 12, to 0.65 nmol/L at age 15 years. Among girls, levels fluctuated around a geometric mean of 0.67 nmol/L. Girls had significantly higher mean log-transformed C-peptide concentrations than boys (P < 0.0001) after adjusting for age, race and BMI percentile category. After adjusting for age and BMI percentile category, non-Hispanic Black boys and girls had significantly lower C-peptide levels than non-Hispanic White (P = 0.0026 and P = 0.0093) and Mexican American boys and girls (P < 0.0001 and P < 0.0001), respectively. Despite these findings, both insulin and homeostatic model assessment of insulin resistance were greater in non-Hispanic Black compared to non-Hispanic White participants. CONCLUSIONS: Here we describe fasting C-peptide levels in a non-diabetic adolescent population. These data provide crucial insight into evaluating racial differences in endogenous insulin release and clearance and will provide novel information which can be used in assessing residual ß-cell function and response to intervention therapy.

COVID-19 Pandemic Effects on Caregivers of Youth With Type 1 Diabetes: Stress and Self-Efficacy.

Background: Little is known about the coronavirus disease 2019 (COVID-19) pandemic's psychological effects on caregivers of children with type 1 diabetes. Objective: This study aimed to investigate the experience of caregivers of youth with type 1 diabetes during the COVID-19 pandemic. Methods: A 49-item questionnaire using a 5-point Likert scale and open-response questions was distributed via e-mail and type 1 diabetes-related social media platforms from 4 May to 22 June 2020. Quantitative data were analyzed using SPSS v.25 statistical software. Descriptive statistics were used. Relationships were compared using Pearson correlation. Qualitative data were coded and categorized. Results: A total of 272 caregivers participated (mean ± SD respondent age 42.1 ± 7.8 years; 94.5% females; 81.3% with college degree or higher; 52.6% with annual income >$99,000; 80.1% with private insurance). The mean ± SD age of caregivers' children with type 1 diabetes was 11.0 ± 4.1 years, and their mean ± SD diabetes duration was 4.2 ± 3.5 years. Participants reported being diagnosed with or knowing someone with COVID-19 (24.6%), increased stress (71.9%), job loss (10.3%), and financial difficulty (26.8%) as a result of the pandemic. General self-efficacy scores were high (mean ± SD 16.2 ± 2.6, range 8-20) and significantly correlated with COVID-19-related self-efficacy (mean ± SD 12.6 ± 2.1; R = 0.394, P <0.001) and type 1 diabetes self-efficacy during COVID-19 (mean ± SD 17.1 ± 2.5; R = 0.421, P <0.001). Conclusion: Despite reporting high overall self-efficacy, caregivers of children with type 1 diabetes reported greater overall stress and challenges during the pandemic. Health care providers should be prepared to provide families with specific social and mental health support.

Medical chart validation of inpatient diagnosis codes for transfusion-related acute lung injury 2013-2015.

INTRODUCTION: Transfusion-related acute lung injury (TRALI), an adverse event occurring during or within 6 hours of transfusion, is a leading cause of transfusion-associated fatalities reported to the US Food and Drug Administration. There is limited information on the validity of diagnosis codes for TRALI recorded in inpatient electronic medical records (EMRs). STUDY DESIGNS AND METHODS: We conducted a validation study to establish the positive predictive value (PPV) of TRALI International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes recorded within a large hospital system between 2013 and 2015. A physician with critical care expertise confirmed the TRALI diagnosis. As TRALI is likely underdiagnosed, we used the specific code (518.7), and codes for respiratory failure (518.82) in combination with transfusion reaction (999.80, 999.89, E934.7). RESULTS: Among almost four million inpatient stays, we identified 208 potential TRALI cases with ICD-9-CM codes and reviewed 195 medical records; 68 (35%) met clinical definitions for TRALI (26 [38%] definitive, 15 [22%] possible, 27 [40%] delayed). Overall, the PPV for all inpatient TRALI diagnoses was 35% (95% confidence interval (CI), 28-42). The PPV for the TRALI-specific code was 44% (95% CI, 35-54). CONCLUSION: We observed low PPVs (<50%) for TRALI ICD-9-CM diagnosis codes as validated by medical charts, which may relate to inconsistent code use, incomplete medical records, or other factors. Future studies using TRALI diagnosis codes in EMR databases may consider confirming diagnoses with medical records, assessing TRALI ICD, Tenth Revision, Clinical Modification codes, or exploring alternative ways for of accurately identifying TRALI in EMR databases. KEY POINTS: In 169 hospitals, we identified 208 potential TRALI cases, reviewed 195 charts, and confirmed 68 (35%) cases met TRALI clinical definitions. As many potential TRALI cases identified with diagnosis codes did not meet clinical definitions, medical record confirmation may be prudent.

Early and late C-peptide responses during oral glucose tolerance testing are oppositely predictive of type 1 diabetes in autoantibody-positive individuals.

We examined whether the timing of the C-peptide response during an oral glucose tolerance test (OGTT) in relatives of patients with type 1 diabetes (T1D) is predictive of disease onset. We examined baseline 2-h OGTTs from 670 relatives participating in the Diabetes Prevention Trial-Type 1 (age: 13.8 ± 9.6 years; body mass index z-score: 0.3 ± 1.1; 56% male) using univariate regression models. T1D risk increased with lower early C-peptide responses (30-0 min) (χ2 = 28.8, P < 0.001), and higher late C-peptide responses (120-60 min) (χ2 = 23.3, P < 0.001). When both responses were included in a proportional hazards model, they remained independently and oppositely associated with T1D, with a stronger overall association for the combined model than either response alone (χ2 = 41.1; P < 0.001). Using receiver operating characteristic curve analysis, the combined early and late C-peptide response was more accurately predictive of T1D than area under the curve C-peptide (P = 0.005). Our findings demonstrate that lower early and higher late C-peptide responses serve as indicators of increased T1D risk.

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges.

Health monitoring and its related technologies is an attractive research area. The electrocardiogram (ECG) has always been a popular measurement scheme to assess and diagnose cardiovascular diseases (CVDs). The number of ECG monitoring systems in the literature is expanding exponentially. Hence, it is very hard for researchers and healthcare experts to choose, compare, and evaluate systems that serve their needs and fulfill the monitoring requirements. This accentuates the need for a verified reference guiding the design, classification, and analysis of ECG monitoring systems, serving both researchers and professionals in the field. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. This provides evidence-based support for critically understanding ECG monitoring systems' components, contexts, features, and challenges. Hence, a generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG monitoring systems' value chain is conducted, and a thorough review of the relevant literature, classified against the experts' taxonomy, is presented, highlighting challenges and current trends. Finally, we identify key challenges and emphasize the importance of smart monitoring systems that leverage new technologies, including deep learning, artificial intelligence (AI), Big Data and Internet of Things (IoT), to provide efficient, cost-aware, and fully connected monitoring systems.

Associations of HbA1c with the timing of C-peptide responses during the oral glucose tolerance test at the diagnosis of type 1 diabetes.

BACKGROUND: In new onset type 1 diabetes (T1D), overall C-peptide measures such as area under the curve (AUC) C-peptide and peak C-peptide are useful for estimating the extent of ß-cell dysfunction, and for assessing responses to intervention therapy. However, measures of the timing of C-peptide responsiveness could have additional value. OBJECTIVES: We assessed the contribution of the timing of C-peptide responsiveness during oral glucose tolerance tests (OGTTs) to hemoglobin A1c (HbA1c) variation at T1D diagnosis. METHODS: We analyzed data from 85 individuals <18 years with OGTTs and HbA1c measurements at diagnosis. Overall [AUC and peak C-peptide] and timing measures [30-0 minute C-peptide (early); 60 to 120 minute C-peptide sum-30 minutes (late); 120/30 C-peptide; time to peak C-peptide] were utilized. RESULTS: At diagnosis, the mean (±SD) age was 11.2 ± 3.3 years, body mass index (BMI)-z was 0.4 ± 1.1, 51.0% were male. The average HbA1c was 43.54 ± 8.46 mmol/mol (6.1 ± 0.8%). HbA1c correlated inversely with the AUC C-peptide (P < 0.001), peak C-peptide (P < 0.001), early and late C-peptide responses (P < 0.001 each), and 120/30 C-peptide (P < 0.001). Those with a peak C-peptide occurring at ≤60 minutes had higher HbA1c values than those with peaks later (P = 0.003). HbA1c variance was better explained with timing measures added to regression models (R2 = 11.6% with AUC C-peptide alone; R2 = 20.0% with 120/30 C-peptide added; R2 = 13.7% with peak C-peptide alone, R2 = 20.4% with timing of the peak added). Similar associations were seen between the 2-hour glucose and the C-peptide measures. CONCLUSIONS: These findings show that the addition of timing measures of C-peptide responsiveness better explains HbA1c variation at diagnosis than standard measures alone.

The shape of the glucose concentration curve during an oral glucose tolerance test predicts risk for type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to examine: (1) whether specific glucose-response curve shapes during OGTTs are predictive of type 1 diabetes development; and (2) the extent to which the glucose-response curve is influenced by insulin secretion. METHODS: Autoantibody-positive relatives of people with type 1 diabetes whose baseline OGTT met the definition of a monophasic or biphasic glucose-response curve were followed for the development of type 1 diabetes (n = 2627). A monophasic curve was defined as an increase in OGTT glucose between 30 and 90 min followed by a decline of ≥ 0.25 mmol/l between 90 and 120 min. A biphasic response curve was defined as a decrease in glucose after an initial increase, followed by a second increase of ≥ 0.25 mmol/l. Associations of type 1 diabetes risk with glucose curve shapes were examined using cumulative incidence curve comparisons and proportional hazards regression. C-peptide responses were compared with and without adjustments for potential confounders. RESULTS: The majority of participants had a monophasic curve at baseline (n = 1732 [66%] vs n = 895 [34%]). The biphasic group had a lower cumulative incidence of type 1 diabetes (p < 0.001), which persisted after adjustments for age, sex, BMI z score and number of autoantibodies (p < 0.001). Among the monophasic group, the risk of type 1 diabetes was greater for those with a glucose peak at 90 min than for those with a peak at 30 min; the difference persisted after adjustments (p < 0.001). Compared with the biphasic group, the monophasic group had a lower early C-peptide (30-0 min) response, a lower C-peptide index (30-0 min C-peptide/30-0 min glucose), as well as a greater 2 h C-peptide level (p < 0.001 for all). CONCLUSIONS/INTERPRETATION: Those with biphasic glucose curves have a lower risk of progression to type 1 diabetes than those with monophasic curves, and the risk among the monophasic group is increased when the glucose peak occurs at 90 min than at 30 min. Differences in glucose curve shapes between the monophasic and biphasic groups appear to be related to C-peptide responses.

The influence of body mass index and age on C-peptide at the diagnosis of type 1 diabetes in children who participated in the diabetes prevention trial-type 1.

BACKGROUND/OBJECTIVE: The extent of influence of BMI and age on C-peptide at the diagnosis of type 1 diabetes (T1D) is unknown. We thus studied the impact of body mass index Z-scores (BMIZ) and age on C-peptide measures at and soon after the diagnosis of T1D. METHODS: Data from Diabetes Prevention Trial-Type 1 (DPT-1) participants <18.0 years at diagnosis was analyzed. Analyses examined associations of C-peptide measures with BMIZ and age in 2 cohorts: oral glucose tolerance tests (OGTTs) at diagnosis (n = 99) and mixed meal tolerance tests (MMTTs) <6 months after diagnosis (n = 80). Multivariable linear regression was utilized. RESULTS: Fasting and area under the curve (AUC) C-peptide from OGTTs (n = 99) at diagnosis and MMTTs (n = 80) after diagnosis were positively associated with BMIZ and age (P < .001 for all). Associations persisted when BMIZ and age were included as independent variables in regression models (P < .001 for all). BMIZ and age explained 31%-47% of the variance of C-peptide measures. In an example, 2 individuals with identical AUC C-peptide values had an approximate 5-fold difference in values after adjustments for BMIZ and age. The association between fasting glucose and C-peptide decreased markedly when fasting C-peptide values were adjusted (r = 0.30, P < .01 to r = 0.07, n.s.). CONCLUSIONS: C-peptide measures are strongly and independently related to BMIZ and age at and soon after the diagnosis of T1D. Adjustments for BMIZ and age cause substantial changes in C-peptide values, and impact the association between glycemia and C-peptide. Such adjustments can improve assessments of ß-cell impairment at diagnosis.

Presenting predictors and temporal trends of treatment-related outcomes in diabetic ketoacidosis.

OBJECTIVE: This study examines temporal trends in treatment-related outcomes surrounding a diabetic ketoacidosis (DKA) performance improvement intervention consisting of mandated intensive care unit admission and implementation of a standardized management pathway, and identifies physical and biochemical characteristics associated with outcomes in this population. METHODS: A retrospective cohort of 1225 children with DKA were identified in the electronic health record by international classification of diseases codes and a minimum pH less than 7.3 during hospitalization at a quaternary children's hospital between April, 2009 and May, 2016. Multivariable regression examined predictors and trends of hypoglycemia, central venous line placement, severe hyperchloremia, head computed tomography (CT) utilization, treated cerebral edema and hospital length of stay (LOS). RESULTS: The incidence of severe hyperchloremia and head CT utilization decreased during the study period. Among patients with severe DKA (presenting pH < 7.1), the intervention was associated with decreasing LOS and less variability in LOS. Lower pH at presentation was independently associated with increased risk for all outcomes except hypoglycemia, which was associated with higher pH. Patients treated for cerebral edema had a lower presenting mean systolic blood pressure z score (0.58 [95% confidence interval (CI) -0.02-1.17] vs 1.23 [1.13-1.33]) and a higher maximum mean systolic blood pressure (SBP) z score during hospitalization (3.75 [3.19-4.31] vs 2.48 [2.38-2.58]) compared to patients not receiving cerebral edema treatment. Blood pressure and cerebral edema remained significantly associated after covariate adjustment. CONCLUSION: Treatment-related outcomes improved over the entire study period and following a performance improvement intervention. The association of SBP with cerebral edema warrants further study.

First test effect in intravenous glucose tolerance testing.

AIMS: Intravenous glucose tolerance testing (IVGTT) is a common test of ß-cell function in which a glucose load is administered and insulin and/or C-peptide responses are monitored. Since the first IVGTT may be more stressful and stress may alter ß-cell secretion or hepatic insulin extraction, we asked whether there was a first test effect. METHODS: Insulin and C-peptide responses were compared from two sequential IVGTTs performed within 6 months during staging for the Diabetes Prevention Trial-Type 1 (DPT-1) in 368 people at high risk for type 1 diabetes. Insulin data (1+3 min) were used because the first phase insulin response (and peak insulin concentration) occurs within this time frame. Areas under the curve (AUC) calculations represent early insulin or C-peptide responses from 0 through 10 min post-glucose challenge. RESULTS: More than half of all subjects were found to have first test values lower than the second. This was true for all measures of both insulin and C-peptide but the frequency was significantly different only for insulin measures corrected for basal and for insulin AUC (p < 0.05). However, for subjects (n = 99) whose 1+3 min insulin response was <10th percentile on the first test, there was a significant increase on the second test (p < 0.05). The C-peptide: insulin ratio did not change significantly between tests, indicating that differences are due to changes in ß-cell secretion rather than hepatic insulin uptake. CONCLUSIONS: A statistically significant first test effect occurs during the IVGTT attributable to variations in insulin secretion rather than hepatic uptake.

S6 kinase 2 is bound to chromatin-nuclear matrix cellular fractions and is able to phosphorylate histone H3 at threonine 45 in vitro and in vivo.

The activity of S6 kinases (S6K) is highly induced in cancer cells highlighting an essential role in carcinogenesis. The S6K family has two members: S6K1 and S6K2 which bear common as well as distinct features. In an attempt to identify S6K2 unique sequence features compared to S6K1, we applied extensive bioinformatic analysis and motif search approaches. Interestingly, we identified 14 unique protein signatures which are present in proteins directly connected to chromatin and/or involved in transcription regulation. Using chromatin binding assay, we biochemically showed that S6K2 is bound to chromatin as well as nuclear matrix cellular fractions in HEK293 cells. The presence of S6K2 in chromatin fractions raised the possibility that it may be in close proximity to a number of chromatin substrates. For that, we then searched for S6K phosphorylation consensus sites RXRXXT/S in mammalian proteins using the SWISS-PROT database. Interestingly, we identified some potential phosphorylation sites in histone H3 (Thr45). Using in vitro kinase assays and siRNA-based knockdown strategy; we confirmed that S6K2 but not S6K1 or AKT is essential for histone H3-Thr45 phosphorylation in HEK293 cells. Furthermore, we show that the nuclear localisation sequence in the S6K2 C-terminus is essential for this modification. We have found that, H3-Thr45 phosphorylation correlates to S6K activation in response to mitogens and TPA-induced cell differentiation of leukaemic cell lines U937, HL60 and THP1. Overall, we demonstrate that S6K2 is a novel kinase that can phosphorylate histone H3 at position Thr45, which may play a role during cell proliferation and/or differentiation.

Src and fibroblast growth factor 2 independently regulate signaling and gene expression induced by experimental injury to intact articular cartilage.

OBJECTIVE: To investigate whether cartilage injury activates protein tyrosine kinases distinct from fibroblast growth factor (FGF)-related signaling, and whether they contribute to injury-induced gene responses. METHODS: Phosphokinases and protein tyrosine phosphorylation were assayed by Western blotting of cartilage lysates. Immunoprecipitation and Western blotting with 4G10 antibody and immunoprecipitation kinase assay were carried out. Tyrosine-phosphorylated proteins on silver-stained gels of injured cartilage lysates were identified by mass spectrometry. Messenger RNA induction in cartilage explants was assessed by quantitative reverse transcriptase-polymerase chain reaction. RESULTS: Protein tyrosine phosphorylation occurred within seconds of injury to the surface of intact articular cartilage, as did activation of MAPKs and IKK. Activation did not reoccur upon reinjury of cultured explants. The prominent tyrosine-phosphorylated proteins focal adhesion kinase, paxillin, and cortactin were identified as substrates of Src family kinases. The Src family kinase inhibitor PP2 blocked injury-induced tyrosine phosphorylation. It did not prevent activation of the MAPKs and IKK but differentially inhibited 8 of 10 inflammatory response genes that were induced by injury. In contrast, FGF signaling blockade with PD173074 reduced all MAPK and IKK activation by ∼50% and inhibited a different subset of genes but had no effect on Src-like signaling. CONCLUSION: Injury to the surface of intact articular cartilage activates Src-like kinases as well as MAPKs and IKK (implying NF-κB activation). FGF-2 contributes to MAPK/IKK activation but not to Src-like signaling, suggesting that the latter is a parallel pathway that also regulates the injury-induced inflammatory gene response.