Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework.

OBJECTIVES: This study investigates the impact of participation in self-help groups on treatment completion among individuals undergoing medication for opioid use disorder (MOUD) treatment. Given the suboptimal adherence and retention rates for MOUD, this research seeks to examine the association between treatment completion and patient-level factors. Specifically, we evaluated the causal relationship between self-help group participation and treatment completion for patients undergoing MOUD. METHODS: We used the Substance Abuse and Mental Health Services Administration's (SAMHSA) Treatment Episode Data Set: Discharges (TEDS-D) from 2015 to 2019. The data are filtered by the patient's opioid use history, demographics, treatment modality, and other relevant information. In this observational study, machine learning models (Lasso Regression, Decision Trees, Random Forest, and XGBoost) were developed to predict treatment completion. Outcome Adaptive Elastic Net (OAENet) was used to select confounders and outcome predictors, and the robust McNemars test was used to evaluate the causal relationship between self-help group participation and MOUD treatment completion. RESULTS: The machine-learning models showed a strong association between participation in self-help groups and treatment completion. Our causal analysis demonstrated an average treatment effect on treated (ATT) of 0.260 and a p-value < 0.0001 for the robust McNemars test. CONCLUSIONS: Our study demonstrates the importance of participation in self-help groups for MOUD treatment recipients. We found that participation in MOUD along with self-help groups caused higher chances of treatment completion than MOUD alone. This suggests that policymakers should consider further integrating self-help groups into the treatment for OUD to improve the adherence and completion rate.

COVID-19 olfactory dysfunction: associations between coping, quality of life, and mental health.

BACKGROUND: Persistent olfactory dysfunction (OD) is a common symptom following SARS-CoV-2 infection that can greatly impact quality of life (QoL). Because coping strategies have been shown to moderate the effect of disease symptoms on functional and affective outcomes, this study aims to determine whether specific coping strategies are associated with and moderate QoL outcomes. METHODOLOGY: Participants with prior SARS-CoV-2 infection underwent psychophysical olfactory testing with Sniffin' Sticks and completed questionnaires to elicit subjective olfactory function, coping strategies, olfactory-specific QoL, general QoL, and mental health. RESULTS: There were 93 participants included in the study. Olfactory specific QoL scores were significantly worse among individuals with subjective and psychophysically measured OD compared to those with subjective and psychophysically confirmed normosmia. Olfactory-specific QoL, general QoL, and anxiety symptom scores were positively correlated with avoidant and disengagement coping among individuals with subjective and psychophysically measured OD. Depression symptom scores were positively correlated with avoidant and disengagement coping and negatively correlated with approach and engagement coping. There were no significant moderating effects on the association between olfactory performance and QoL or mental health screening assessment. CONCLUSIONS: Approach and engagement coping mechanisms are associated with improved depression, whereas avoidant and disengagement coping tracks with worse QoL and mental health screening assessment, offering an opportunity to counsel patients accordingly.

Predicting Collision Cross-Section Values for Small Molecules through Chemical Class-Based Multimodal Graph Attention Network.

Libraries of collision cross-section (CCS) values have the potential to facilitate compound identification in metabolomics. Although computational methods provide an opportunity to increase library size rapidly, accurate prediction of CCS values remains challenging due to the structural diversity of small molecules. Here, we developed a machine learning (ML) model that integrates graph attention networks and multimodal molecular representations to predict CCS values on the basis of chemical class. Our approach, referred to as MGAT-CCS, had superior performance in comparison to other ML models in CCS prediction. MGAT-CCS achieved a median relative error of 0.47%/1.14% (positive/negative mode) and 1.40%/1.63% (positive/negative mode) for lipids and metabolites, respectively. When MGAT-CCS was applied to real-world metabolomics data, it reduced the number of false metabolite candidates by roughly 25% across multiple sample types ranging from plasma and urine to cells. To facilitate its application, we developed a user-friendly stand-alone web server for MGAT-CCS that is freely available at https://mgat-ccs-web.onrender.com. This work represents a step forward in predicting CCS values and can potentially facilitate the identification of small molecules when using ion mobility spectrometry coupled with mass spectrometry.

From Llama to Nanobody: A Streamlined Workflow for the Generation of Functionalised VHHs.

Nanobodies are recombinant antigen-specific single domain antibodies (VHHs) derived from the heavy chain-only subset of camelid immunoglobulins. Their small molecular size, facile expression, high affinity, and stability have combined to make them unique targeting reagents with numerous applications in the biomedical sciences. From our work in producing nanobodies to over sixty different proteins, we present a standardised workflow for nanobody discovery from llama immunisation, library building, panning, and small-scale expression for prioritisation of binding clones. In addition, we introduce our suites of mammalian and bacterial vectors, which can be used to functionalise selected nanobodies for various applications such as in imaging and purification. Key features • Standardise the process of building nanobody libraries and finding nanobody binders so that it can be repeated in any lab with reasonable equipment. • Introduce two suites of vectors to functionalise nanobodies for production in either bacterial or mammalian cells.

SMIM1 absence is associated with reduced energy expenditure and excess weight.

BACKGROUND: Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments. METHODS: We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan. FINDINGS: We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure. CONCLUSION: This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them. FUNDING: This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant.

Development of novel tools for dissection of central versus peripheral dopamine D2-like receptor signaling in dysglycemia.

Dopamine (DA) D2-like receptors in both the central nervous system (CNS) and the periphery are key modulators of metabolism. Moreover, disruption of D2-like receptor signaling is implicated in dysglycemia. Yet, the respective metabolic contributions of CNS versus peripheral D2-like receptors including D2 (D2R) and D3 (D3R) receptors remain poorly understood. To address this, we developed new pharmacological tools, D2-like receptor agonists with diminished and delayed blood-brain barrier capability, to selectively manipulate D2R/D3R signaling in the periphery. We designated bromocriptine methiodide (BrMeI), a quaternary methiodide analogue of D2R/D3R agonist and diabetes drug bromocriptine, as our lead compound based on preservation of D2R/D3R binding and functional efficacy. We then used BrMeI and unmodified bromocriptine to dissect relative contributions of CNS versus peripheral D2R/D3R signaling in treating dysglycemia. Systemic administration of bromocriptine, with unrestricted access to CNS and peripheral targets, significantly improved both insulin sensitivity and glucose tolerance in obese, dysglycemic mice in vivo. In contrast, metabolic improvements were attenuated when access to bromocriptine was restricted either to the CNS through intracerebroventricular administration or delayed access to the CNS via BrMeI. Our findings demonstrate that the coordinated actions of both CNS and peripheral D2-like receptors are required for correcting dysglycemia. Ultimately, the development of a first-generation of drugs designed to selectively target the periphery provides a blueprint for dissecting mechanisms of central versus peripheral DA signaling and paves the way for novel strategies to treat dysglycemia.

Loss of mitochondrial pyruvate transport initiates cardiac glycogen accumulation and heart failure.

Background: Heart failure involves metabolic alterations including increased glycolysis despite unchanged or decreased glucose oxidation. The mitochondrial pyruvate carrier (MPC) regulates pyruvate entry into the mitochondrial matrix, and cardiac deletion of the MPC in mice causes heart failure. How MPC deletion results in heart failure is unknown. Methods: We performed targeted metabolomics and isotope tracing in wildtype (fl/fl) and cardiac-specific Mpc2-/- (CS-Mpc2-/-) hearts after in vivo injection of U-13C-glucose. Cardiac glycogen was assessed biochemically and by transmission electron microscopy. Cardiac uptake of 2-deoxyglucose was measured and western blotting performed to analyze insulin signaling and enzymatic regulators of glycogen synthesis and degradation. Isotope tracing and glycogen analysis was also performed in hearts from mice fed either low-fat diet or a ketogenic diet previously shown to reverse the CS-Mpc2-/- heart failure. Cardiac glycogen was also assessed in mice infused with angiotensin-II that were fed low-fat or ketogenic diet. Results: Failing CS-Mpc2-/- hearts contained normal levels of ATP and phosphocreatine, yet these hearts displayed increased enrichment from U-13C-glucose and increased glycolytic metabolite pool sizes. 13C enrichment and pool size was also increased for the glycogen intermediate UDP-glucose, as well as increased enrichment of the glycogen pool. Glycogen levels were increased ~6-fold in the failing CS-Mpc2-/- hearts, and glycogen granules were easily detected by electron microscopy. This increased glycogen synthesis occurred despite enhanced inhibitory phosphorylation of glycogen synthase and reduced expression of glycogenin-1. In young, non-failing CS-Mpc2-/- hearts, increased glycolytic 13C enrichment occurred, but glycogen levels remained low and unchanged compared to fl/fl hearts. Feeding a ketogenic diet to CS-Mpc2-/- mice reversed the heart failure and normalized the cardiac glycogen and glycolytic metabolite accumulation. Cardiac glycogen levels were also elevated in mice infused with angiotensin-II, and both the cardiac hypertrophy and glycogen levels were improved by ketogenic diet. Conclusions: Our results indicate that loss of MPC in the heart causes glycogen accumulation and heart failure, while a ketogenic diet can reverse both the glycogen accumulation and heart failure. We conclude that maintaining mitochondrial pyruvate import and metabolism is critical for the heart, unless cardiac pyruvate metabolism is reduced by consumption of a ketogenic diet.

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment effectiveness, increasing the risk of mortality and overdose. We developed and evaluated a machine learning (ML) framework for predicting buprenorphine care discontinuity within 12 months following treatment initiation. METHODS: This retrospective study used United States (US) 2018-2021 MarketScan commercial claims data of insured individuals aged 18-64 who initiated buprenorphine between July 2018 and December 2020 with no buprenorphine prescriptions in the previous six months. We measured buprenorphine prescription discontinuation gaps of ≥30 days within 12 months of initiating treatment. We developed predictive models employing logistic regression, decision tree classifier, random forest, extreme gradient boosting, Adaboost, and random forest-extreme gradient boosting ensemble. We applied recursive feature elimination with cross-validation to reduce dimensionality and identify the most predictive features while maintaining model robustness. For model validation, we used several statistics to evaluate performance, such as C-statistics and precision-recall curves. We focused on two distinct treatment stages: at the time of treatment initiation and one and three months after treatment initiation. We employed SHapley Additive exPlanations (SHAP) analysis that helped us explain the contributions of different features in predicting buprenorphine discontinuation. We stratified patients into risk subgroups based on their predicted likelihood of treatment discontinuation, dividing them into decile subgroups. Additionally, we used a calibration plot to analyze the reliability of the models. RESULTS: A total of 30,373 patients initiated buprenorphine and 14.98% (4551) discontinued treatment. C-statistic varied between 0.56 and 0.76 for the first-stage models including patient-level demographic and clinical variables. Inclusion of proportion of days covered (PDC) measured after one month and three months following treatment initiation significantly increased the models' discriminative power (C-statistics: 0.60 to 0.82). Random forest (C-statistics: 0.76, 0.79 and 0.82 with baseline predictors, one-month PDC and three-months PDC, respectively) outperformed other ML models in discriminative performance in all stages (C-statistics: 0.56 to 0.77). Most influential risk factors of discontinuation included early stage medication adherence, age, and initial days of supply. CONCLUSION: ML algorithms demonstrated a good discriminative power in identifying patients at higher risk of buprenorphine care discontinuity. The proposed framework may help healthcare providers optimize treatment strategies and deliver targeted interventions to improve buprenorphine care continuity.

Development and external validation of a head and neck cancer risk prediction model.

BACKGROUND: Head and neck cancer (HNC) incidence is on the rise, often diagnosed at late stage and associated with poor prognoses. Risk prediction tools have a potential role in prevention and early detection. METHODS: The IARC-ARCAGE European case-control study was used as the model development dataset. A clinical HNC risk prediction model using behavioral and demographic predictors was developed via multivariable logistic regression analyses. The model was then externally validated in the UK Biobank cohort. Model performance was tested using discrimination and calibration metrics. RESULTS: 1926 HNC cases and 2043 controls were used for the development of the model. The development dataset model including sociodemographic, smoking, and alcohol variables had moderate discrimination, with an area under curve (AUC) value of 0.75 (95% CI, 0.74-0.77); the calibration slope (0.75) and tests were suggestive of good calibration. 384 616 UK Biobank participants (with 1177 HNC cases) were available for external validation of the model. Upon external validation, the model had an AUC of 0.62 (95% CI, 0.61-0.64). CONCLUSION: We developed and externally validated a HNC risk prediction model using the ARCAGE and UK Biobank studies, respectively. This model had moderate performance in the development population and acceptable performance in the validation dataset. Demographics and risk behaviors are strong predictors of HNC, and this model may be a helpful tool in primary dental care settings to promote prevention and determine recall intervals for dental examination. Future addition of HPV serology or genetic factors could further enhance individual risk prediction.

Receptor-Targeted Peptide Conjugates Based on Diphosphines Enable Preparation of 99mTc and 188Re Theranostic Agents for Prostate Cancer.

Benchtop 99Mo/99mTc and 188W/188Re generators enable economical production of molecular theranostic 99mTc and 188Re radiopharmaceuticals, provided that simple, kit-based chemistry exists to radiolabel targeting vectors with these radionuclides. We have previously described a diphosphine platform that efficiently incorporates 99mTc into receptor-targeted peptides. Here, we report its application to label a prostate-specific membrane antigen (PSMA)-targeted peptide with 99mTc and 188Re for diagnostic imaging and systemic radiotherapy of prostate cancer. Methods: Two diphosphine-dipeptide bioconjugates, DP1-PSMAt and DP2-PSMAt, were formulated into kits for radiolabeling with 99mTc and 188Re. The resulting radiotracers were studied in vitro, in prostate cancer cells, and in vivo in mouse xenograft models, to assess similarity of uptake and biodistribution for each 99mTc/188Re pair of agents. Results: Both DP1-PSMAt and DP2-PSMAt could be efficiently radiolabeled with 99mTc and 188Re using kit-based methods to furnish the isostructural compounds M-DP1-PSMAt and M-DP2-PSMAt (M = [99mTc]Tc, [188Re]Re). All 99mTc/188Re radiotracers demonstrated specific uptake in PSMA-expressing prostate cancer cells, with negligible uptake in prostate cancer cells that did not express PSMA or in which PSMA uptake was blocked. M-DP1-PSMAt and M-DP2-PSMAt also exhibited high tumor uptake (18-30 percentage injected dose per gram at 2 h after injection), low retention in nontarget organs, fast blood clearance, and excretion predominantly via a renal pathway. Importantly, each pair of 99mTc/188Re radiotracers showed near-identical biologic behavior in these experiments. Conclusion: We have prepared and developed novel pairs of isostructural PSMA-targeting 99mTc/188Re theranostic agents. These generator-based theranostic agents have potential to provide access to the benefits of PSMA-targeted diagnostic imaging and systemic radiotherapy in health care settings that do not routinely have access to either reactor-produced 177Lu radiopharmaceuticals or PET/CT infrastructure.

Implementing circulating tumor DNA as a prognostic biomarker in resectable non-small cell lung cancer.

Systemic treatment of resectable non-small cell lung cancer (NSCLC) is evolving with emerging neoadjuvant, perioperative, and adjuvant immunotherapy approaches. Circulating tumor DNA (ctDNA) detection at clinical diagnosis, during neoadjuvant therapy, or after resection may discern high-risk patients who might benefit from therapy escalation or switch. This Review summarizes translational implications of data supporting ctDNA-based risk determination in NSCLC and outstanding questions regarding ctDNA validity/utility as a prognostic biomarker. We discuss emerging ctDNA capabilities to refine clinical tumor-node-metastasis (TNM) staging in lung adenocarcinoma, ctDNA dynamics during neoadjuvant therapy for identifying patients deriving suboptimal benefit, and postoperative molecular residual disease (MRD) detection to escalate systemic therapy. Considering differential relapse characteristics in landmark MRD-negative/MRD-positive patients, we propose how ctDNA might integrate with pathological response data for optimal postoperative risk stratification.

Efficacy and safety of once weekly selinexor 40 mg versus 60 mg with pomalidomide and dexamethasone in relapsed and/or refractory multiple myeloma.

Objective: To identify the optimal dose of selinexor in combination with pomalidomide and dexamethasone (SPd). Methods: An analysis of efficacy and safety of 2 once-weekly selinexor regimens (60 mg and 40 mg) with pomalidomide and dexamethasone (SPd-60 and SPd-40, respectively) given to patients with relapsed/refractory multiple myeloma (RRMM) in the STOMP (NCT02343042) and XPORT-MM-028 (NCT04414475) trials. Results: Twenty-eight patients (60.7% males, median age 67.5 years) and 20 patients (35.0% males, median age 65.5 years) were analyzed in the SPd-40 and SPd-60 cohorts, respectively. Overall response rate was 50% (95% confidence interval [CI] 30.6-69.4%) and 65% (95% CI 40.8-84.6%), respectively. Very good partial response or better was reported in 28.6% (95% CI 13.2-48.7%) and 30.0% (95% CI 11.9-54.3%) of patients, respectively. Among 27 responders in both cohorts, the 12-month sustained response rate was 83.3% (95% CI 64.7-100.0%) for SPd-40 and 28.1% (95% CI 8.9-88.8%) for SPd-60. Median progression-free survival was 18.4 months (95% CI 6.5 months, not evaluable [NE]) and 9.5 months (95% CI 7.6 months-NE) for SPd-40 and SPd-60, respectively. Twenty-four-month survival rates were 64.2% (95% CI 47.7-86.3%) for SPd-40 and 51.1% (95% CI 29.9-87.5%) for SPd-60. Treatment-emergent adverse events (TEAEs) included neutropenia (all grades: SPd-40 64.3% versus SPd-60 75.0%), anemia (46.4% versus 65.0%), thrombocytopenia (42.9% versus 45.0%), fatigue (46.4% versus 75.0%), nausea (32.1% versus 70.0%) and diarrhea (28.6% versus 35.0%). Conclusion: The all-oral combination of SPd exhibited preliminary signs of efficacy and was generally tolerable in patients with RRMM. The overall risk-benefit profile favored the SPd-40 regimen.

Prepregnancy physiology and subsequent preterm preeclampsia.

BACKGROUND: Preeclampsia is a common pregnancy complication with debated etiology. OBJECTIVE: To evaluate the contribution of prepregnancy physiology, biochemistry, and anthropometrics to the subsequent development of preterm preeclampsia. STUDY DESIGN: One hundred twenty-four participants were recruited through open recruitment and targeted mailings. Participants included 81 nulliparous women and 43 with a history of preterm preeclampsia. We characterized cardiovascular function, metabolic profile, and body composition in 100 nonpregnant women who went on to subsequent pregnancy. Measures included plasma volume, baseline cardiovascular function and cardiovascular response to volume challenge, body composition, and circulating biochemical measures. Pregnancy outcome was obtained through chart review. Prepregnancy metrics for women who developed preterm preeclampsia were compared with measurements for those who did not, with adjustment for a history of prior preterm preeclampsia. Logistic regression modeling was used to identify the strongest prepregnancy factors associated with preterm preeclampsia. RESULTS: Pregnancy outcomes included 11 women with preterm preeclampsia, 7 women with term preeclampsia, 20 women with other hypertension affecting their pregnancy, and 62 with uncomplicated pregnancies. We observed no difference in maternal age, study cycle day, lean body mass, uterine hemodynamics, or flow-mediated dilation across groups. Women with preterm preeclampsia had greater android fat content 3215±1143 vs 1918±1510 g (P=.002), faster supine pulse, 77±7 vs 67±10 beats per minute (P=.001), higher supine diastolic blood pressure 82±6 vs 68±6 mmHg (P<.001), increased cardiac output 5.6±1.1 vs 4.6±1 L/min (P=.002), faster aortic-popliteal pulse wave velocity 4.5±0.7 vs 3.8±0.5 m/sec (P<.001), and exaggerated cardiac output response to volume challenge 20±9 vs 9±12 L/min (P=.002) compared to those with other pregnancy outcomes. Women who developed preterm preeclampsia also had reduced renal vascular resistance index 0.86±0.08 vs 0.97±0.12 (P=.005) compared with other pregnancy outcomes when assessed prior to pregnancy. Women with subsequent preterm preeclampsia had higher serum c-reactive protein 10.7±12.5 vs 4.1±5.8 mg/mL (P=.003) and greater insulin resistance, as assessed by Homeostatic Model Assessment for Insulin Resistance calculation 2.2±1.1 vs 1.2±0.9 (P<.001). CONCLUSION: Prepregnancy physiology is linked to subsequent preterm preeclampsia. The same factors associated with metabolic syndrome are more prominent in patients who develop preterm preeclampsia than those who do not, including increased vessel stiffness, low vascular compliance, high cardiac output, reduced renal vascular resistance index, insulin resistance, and increased android fat, all consistent with subclinical features of the metabolic syndrome.

Recent advances in paclitaxel biosynthesis and regulation.

Paclitaxel (PTX) is a high value plant natural product (PNP) derived from Taxus (yew) species. This plant secondary metabolite (PSM) and its derivatives constitute a cornerstone for the treatment of an increasing variety of cancers. New applications for PTX also continue to emerge, further promoting demand for this WHO designated essential medicine. Here we review recent advances in our understanding of PTX biosynthesis and its cognate regulation, which have been enabled by the development of transcriptomic approaches and the recent sequencing and annotation of three Taxus genomes. Collectively, this has resulted in the elucidation of two functional gene sets for PTX biosynthesis, unlocking new potential for the use of heterologous hosts to produce PTX. Knowledge of the PTX pathway also provides a valuable resource for understanding the regulation of this key PSM. Epigenetic regulation of PSM in plant cell culture (PCC) is a major concern for PTX production, given the loss of PSM production in long-term cell cultures. Recent developments aim to design tools for manipulating epigenetic regulation, potentially providing a means to reverse the silencing of PSM caused by DNA methylation. Exciting times clearly lie ahead for our understanding of this key PSM and improving its production potential.

The role of exercise in aromatase inhibitor-induced arthralgia.

Aromatase inhibitors are prescribed in breast cancer due to their associated lower rate of cancer recurrence compared to tamoxifen. However, aromatase inhibitor-induced arthralgia (AIIA) is one of the leading causes of treatment nonadherence, increasing the risk of cancer recurrence. The pathophysiology of AIIA is poorly understood, and although current recommendations for AIIA include lifestyle changes and analgesics depending on the severity of symptoms, there is no established effective treatment. The aim of this study is to explore the presentation and mechanism of AIIA and investigate the feasibility and efficacy of different exercise interventions (aerobic, resistance, aerobic and resistance combined, and yoga or tai chi) in patients with AIIA to guide the development of formal exercise prescription guidelines. Findings indicate that a mixed-modality regimen of aerobic and resistance exercises is feasible and safe and may serve the most benefit in improving joint pain, functionality, and quality of life. More specifically, the weekly regimen should consist of 150 min of aerobic exercise with two sessions of at least six resistance exercises, 8 to 12 repetitions, three sets each. Supplementary yoga and tai chi may be recommended twice a week depending on a patient's target symptoms. Yoga was associated with improved physical functionality, whereas tai chi was related to improvements in mental health. However, the feasibility and impact of combined aerobic and resistance exercise protocols with yoga or tai chi in our target population were not investigated in this review. The use of large, randomized controlled trials is recommended for future studies.

The histone methyltransferase SUV420H2 regulates brown and beige adipocyte thermogenesis.

Activation of brown adipose tissue (BAT) thermogenesis increases energy expenditure and alleviates obesity. Here we discover that histone methyltransferase suppressor of variegation 4-20 homolog 2 (Suv420h2) expression parallels that of Ucp1 in brown and beige adipocytes and that Suv420h2 knockdown significantly reduces - whereas Suv420h2 overexpression significantly increases - Ucp1 levels in brown adipocytes. Suv420h2 knockout (H2KO) mice exhibit impaired cold-induced thermogenesis and are prone to diet-induced obesity. In contrast, mice with specific overexpression of Suv420h2 in adipocytes display enhanced cold-induced thermogenesis and are resistant to diet-induced obesity. Further study shows that Suv420h2 catalyzes H4K20 trimethylation at eukaryotic translation initiation factor 4E-binding protein 1 (4e-bp1) promoter, leading to downregulated expression of 4e-bp1, a negative regulator of the translation initiation complex. This in turn upregulates PGC1α protein levels, and this upregulation is associated with increased expression of thermogenic program. We conclude that Suv420h2 is a key regulator of brown/beige adipocyte development and thermogenesis.

Factors influencing the outcomes of non-pharmacological interventions for managing fatigue across the lifespan of people living with musculoskeletal (MSK) conditions: a scoping review protocol.

INTRODUCTION: Fatigue is an important and distressing symptom for many people living with chronic musculoskeletal (MSK) conditions. Many non-pharmacological interventions have been investigated in recent years and some have been demonstrated to be effective in reducing fatigue and fatigue impact, however, there is limited guidance for clinicians to follow regarding the most appropriate management options. The objective of this scoping review is to understand and map the extent of evidence in relation to the factors that relate to the outcome of non-pharmacological interventions on MSK condition-related fatigue across the lifespan. METHODS AND ANALYSIS: This scoping review will include evidence relating to people of all ages living with chronic MSK conditions who have been offered a non-pharmacological intervention with either the intention or effect of reducing fatigue and its impact. Databases including AMED, PsycINFO, CINAHLPlus, MEDLINE, EMBASE and Scopus will be searched for peer-reviewed primary research studies published after 1 January 2007 in English language. These findings will be used to identify factors associated with successful interventions and to map gaps in knowledge. ETHICS AND DISSEMINATION: Ethical approval was not required for this review. Findings will be disseminated by journal publications, conference presentations and by communicating with relevant healthcare and charity organisations.

Young children's choices and thoughts about pro-social behaviour towards others with overweight.

OBJECTIVES: This study aimed to investigate weight bias within young children's pro-social choices between characters who differed in body size. METHODS: Seventy-six children aged 4-6 years read stories asking them to choose who they would first help, share with, comfort, and steal from, between a healthy weight and child with overweight. They also selected the one character they would most like to play with. Children's reasoning for these choices was recorded and analysed. RESULTS: The character with overweight was helped first in only a third of the choices made. Children chose the characters with overweight more often as the target for anti-social action. In friendship selections, children overwhelmingly rejected the characters with overweight. However, weight bias was not prominent in the reasons children gave for the choices. Most children were not negative about body shape, weight or appearance. Similarly, in friendship choices, these were mostly expressed positively to the character chosen. Only a small minority of children were explicitly negative about the character with overweight. CONCLUSIONS: A better understanding of weight bias acquisition and variation between children will benefit those working in health care and educational settings. Future research should link with developmental theory, such as on social categorization and theory of mind.

Estimating the Ca2+ Block of NMDA Receptors with Single-Channel Electrophysiology.

In vertebrate central neurons, NMDA receptors are glutamate- and glycine-gated ion channels that allow the passage of Na+ and Ca2+ ions into the cell when these neurotransmitters are simultaneously present. The passage of Ca2+ is critical for initiating the cellular processes underlying various forms of synaptic plasticity. These Ca2+ ions can autoregulate the NMDA receptor signal through multiple distinct mechanisms to reduce the total flux of cations. One such mechanism is the ability of Ca2+ ions to exclude the passage of Na+ ions resulting in a reduced unitary current conductance. In contrast to the well-characterized Mg2+ block, this "channel block" mechanism is voltage-independent. In this chapter, we discuss theoretical and experimental considerations for the study of channel block by Ca2+ using single-channel patch-clamp electrophysiology. We focus on two classic methodologies to quantify the dependence of unitary channel conductance on external concentrations of Ca2+ as the basis for quantifying Ca2+ block.