Validation of the Sexual Discounting Task for Use in Adolescents.

The Sexual Discounting Task (SDT) was developed to evaluate the effects of delay on decision making as it relates to sexual risk-taking behaviors. Though previously validated with other populations, including urban emerging adults, the current study sought to validate the SDT with adolescents. A sample of adolescents (N = 155; 61% female) between ages 14 and 21 (Mage = 19.5 years) was recruited to complete the SDT (involving choices between immediate unprotected sex and delayed sex with a condom with hypothetical sexual partners) and the Delay Discounting Task (a delay discounting task for money outcomes). Additionally, they completed several self-report measures assessing demographics, sexual behavior, and sexual history. If the condom was readily available, respondents were more likely to use a condom for partners who were judged "most likely to have an STI" and for those that participants were "least likely to have sex with." Moreover, when a condom was not immediately available, greater self-reported sexual risk-taking was related to greater sexual discounting (i.e., greater effects of delay on decreasing condom use). Furthermore, sexual discounting was greater among partners deemed more desirable and those judged "least likely to have an STI." Differences in sexual discounting were significant after controlling for immediately available condom use. Findings from the current study suggest that the SDT is clinically meaningful for adolescents and is sensitive to factors that influence real-world decisions to use condoms. Future treatment and prevention should consider delay discounting as an important variable affecting sexual risk behavior.

Pulmonary Fibrosis Diagnosis and Disease Progression Detected Via Hair Metabolome Analysis.

BACKGROUND: Fibrotic interstitial lung disease is often identified late due to non-specific symptoms, inadequate access to specialist care, and clinical unawareness precluding proper and timely treatment. Biopsy histological analysis is definitive but rarely performed due to its invasiveness. Diagnosis typically relies on high-resolution computed tomography, while disease progression is evaluated via frequent pulmonary function testing. This study tested the hypothesis that pulmonary fibrosis diagnosis and progression could be non-invasively and accurately evaluated from the hair metabolome, with the longer-term goal to minimize patient discomfort. METHODS: Hair specimens collected from pulmonary fibrosis patients (n = 56) and healthy subjects (n = 14) were processed for metabolite extraction using 2DLC/MS-MS, and data were analyzed via machine learning. Metabolomic data were used to train machine learning classification models tuned via a rigorous combination of cross validation, feature selection, and testing with a hold-out dataset to evaluate classifications of diseased vs. healthy subjects and stable vs. progressed disease. RESULTS: Prediction of pulmonary fibrosis vs. healthy achieved AUROCTRAIN = 0.888 (0.794-0.982) and AUROCTEST = 0.908, while prediction of stable vs. progressed disease achieved AUROCTRAIN = 0.833 (0.784 - 0.882) and AUROCTEST = 0. 799. Top metabolites for diagnosis included ornithine, 4-(methylnitrosamino)-1-3-pyridyl-N-oxide-1-butanol, Thr-Phe, desthiobiotin, and proline. Top metabolites for progression included azelaic acid, Thr-Phe, Ala-Tyr, indoleacetyl glutamic acid, and cytidine. CONCLUSION: This study provides novel evidence that pulmonary fibrosis diagnosis and progression may in principle be evaluated from the hair metabolome. Longer term, this approach may facilitate non-invasive and accurate detection and monitoring of fibrotic lung diseases.

Identification of Idiopathic Pulmonary Fibrosis and Prediction of Disease Severity via Machine Learning Analysis of Comprehensive Metabolic Panel and Complete Blood Count Data.

BACKGROUND: Diagnosis of idiopathic pulmonary fibrosis (IPF) typically relies on high-resolution computed tomography imaging (HRCT) or histopathology, while monitoring disease severity is done via frequent pulmonary function testing (PFT). More reliable and convenient methods of diagnosing fibrotic interstitial lung disease (ILD) type and monitoring severity would allow for early identification and enhance current therapeutic interventions. This study tested the hypothesis that a machine learning (ML) ensemble analysis of comprehensive metabolic panel (CMP) and complete blood count (CBC) data can accurately distinguish IPF from connective tissue disease ILD (CTD-ILD) and predict disease severity as seen with PFT. METHODS: Outpatient data with diagnosis of IPF or CTD-ILD (n = 103 visits by 53 patients) were analyzed via ML methodology to evaluate (1) IPF vs CTD-ILD diagnosis; (2) %predicted Diffusing Capacity of Lung for Carbon Monoxide (DLCO) moderate or mild vs severe; (3) %predicted Forced Vital Capacity (FVC) moderate or mild vs severe; and (4) %predicted FVC mild vs moderate or severe. RESULTS: ML methodology identified IPF from CTD-ILD with AUCTEST = 0.893, while PFT was classified as DLCO moderate or mild vs severe with AUCTEST = 0.749, FVC moderate or mild vs severe with AUCTEST = 0.741, and FVC mild vs moderate or severe with AUCTEST = 0.739. Key features included albumin, alanine transaminase, %lymphocytes, hemoglobin, %eosinophils, white blood cell count, %monocytes, and %neutrophils. CONCLUSION: Analysis of CMP and CBC data via proposed ML methodology offers the potential to distinguish IPF from CTD-ILD and predict severity on associated PFT with accuracy that meets or exceeds current clinical practice.

Normoxic Management during Cardiopulmonary Bypass Does Not Reduce Cerebral Mitochondrial Dysfunction in Neonatal Swine.

Optimal oxygen management during pediatric cardiopulmonary bypass (CPB) is unknown. We previously demonstrated an increase in cortical mitochondrial reactive oxygen species and decreased mitochondrial function after CPB using hyperoxic oxygen management. This study investigates whether controlled oxygenation (normoxia) during CPB reduces cortical mitochondrial dysfunction and oxidative injury. Ten neonatal swine underwent three hours of continuous CPB at 34 °C (flow > 100 mL/kg/min) via cervical cannulation targeting a partial pressure of arterial oxygen (PaO2) goal < 150 mmHg (normoxia, n = 5) or >300 mmHg (hyperoxia, n = 5). The animals underwent continuous hemodynamic monitoring and serial arterial blood sampling. Cortical microdialysate was serially sampled to quantify the glycerol concentration (represents neuronal injury) and lactate-to-pyruvate ratio (represents bioenergetic dysfunction). The cortical tissue was analyzed via high-resolution respirometry to quantify mitochondrial oxygen consumption and reactive oxygen species generation, and cortical oxidized protein carbonyl concentrations were quantified to assess for oxidative damage. Serum PaO2 was higher in hyperoxia animals throughout CPB (p < 0.001). There were no differences in cortical glycerol concentration between groups (p > 0.2). The cortical lactate-to-pyruvate ratio was modestly elevated in hyperoxia animals (p < 0.03) but the values were not clinically significant (<30). There were no differences in cortical mitochondrial respiration (p = 0.48), protein carbonyls (p = 0.74), or reactive oxygen species generation (p = 0.93) between groups. Controlled oxygenation during CPB does not significantly affect cortical mitochondrial function or oxidative injury in the acute setting. Further evaluation of the short and long-term effects of oxygen level titration during pediatric CPB on cortical tissue and other at-risk brain regions are needed, especially in the presence of cyanosis.

Digital Glomus Tumor - A Commonly Undiagnosed Cause of Finger Pain: Case Report.

Glomus tumors are rare vascular hamartomas most commonly found in the subungual region of the fingers. They present with a classic triad of paroxysmal pain, point tenderness, and cold sensitivity. The diagnosis is often missed for several years due to under recognition of this condition. A 42-year-old female presented with a several year history of pain in the middle finger when it was struck or exposed to cold. She had point tenderness on the fingernail, and increased curvature of the nail. Magnetic Resonance Imaging (MRI) revealed a 7mm subungual glomus tumor. The tumor was surgically excised via a transungual approach, resulting in complete relief of her pain. Glomus tumors are diagnosed clinically based on the presence of classic symptoms and positive provocative tests. These tests include point tenderness on palpation and pain when ice is placed on the digit. MRI imaging can be used when the diagnosis is unclear or to localize the tumor prior to surgery. Increased awareness of this condition among physicians could reduce the time to diagnosis and treatment.

Fate of Quasiparticles at High Temperature in the Correlated Metal Sr_{2}RuO_{4}.

We study the temperature evolution of quasiparticles in the correlated metal Sr_{2}RuO_{4}. Our angle resolved photoemission data show that quasiparticles persist up to temperatures above 200 K, far beyond the Fermi liquid regime. Extracting the quasiparticle self-energy, we demonstrate that the quasiparticle residue Z increases with increasing temperature. Quasiparticles eventually disappear on approaching the bad metal state of Sr_{2}RuO_{4} not by losing weight but via excessive broadening from super-Planckian scattering. We further show that the Fermi surface of Sr_{2}RuO_{4}-defined as the loci where the spectral function peaks-deflates with increasing temperature. These findings are in semiquantitative agreement with dynamical mean field theory calculations.

The development and acceptability of an educational and training intervention for recruiters to neonatal trials: the TRAIN project.

BACKGROUND: Suboptimal or slow recruitment affects 30-50% of trials. Education and training of trial recruiters has been identified as one strategy for potentially boosting recruitment to randomised controlled trials (hereafter referred to as trials). The Training tRial recruiters, An educational INtervention (TRAIN) project was established to develop and assess the acceptability of an education and training intervention for recruiters to neonatal trials. In this paper, we report the development and acceptability of TRAIN. METHODS: TRAIN involved three sequential phases, with each phase contributing information to the subsequent phase(s). These phases were 1) evidence synthesis (systematic review of the effectiveness of training interventions and a content analysis of the format, content, and delivery of identified interventions), 2) intervention development using a Partnership (co-design/co-creation) approach, and 3) intervention acceptability assessments with recruiters to neonatal trials. RESULTS: TRAIN, accompanied by a comprehensive intervention manual, has been designed for online or in-person delivery. TRAIN can be offered to recruiters before trial recruitment begins or as refresher sessions during a trial. The intervention consists of five core learning outcomes which are addressed across three core training units. These units are the trial protocol (Unit 1, 50 min, trial-specific), understanding randomisation (Unit 2, 5 min, trial-generic) and approaching and engaging with parents (Unit 3, 70 min, trial-generic). Eleven recruiters to neonatal trials registered to attend the acceptability assessment training workshops, although only four took part. All four positively valued the training Units and resources for increasing recruiter preparedness, knowledge, and confidence. More flexibility in how the training is facilitated, however, was noted (e.g., training divided across two workshops of shorter duration). Units 2 and 3 were considered beneficial to incorporate into Good Clinical Practice Training or as part of induction training for new staff joining neonatal units. CONCLUSION: TRAIN offers a comprehensive co-produced training and education intervention for recruiters to neonatal trials. TRAIN was deemed acceptable, with minor modification, to neonatal trial recruiters. The small number of recruiters taking part in the acceptability assessment is a limitation. Scale-up of TRAIN with formal piloting and testing for effectiveness in a large cluster randomised trial is required.

Nuclear receptor REVERBα is a state-dependent regulator of liver energy metabolism.

The nuclear receptor REVERBα is a core component of the circadian clock and proposed to be a dominant regulator of hepatic lipid metabolism. Using antibody-independent ChIP-sequencing of REVERBα in mouse liver, we reveal a high-confidence cistrome and define direct target genes. REVERBα-binding sites are highly enriched for consensus RORE or RevDR2 motifs and overlap with corepressor complex binding. We find no evidence for transcription factor tethering and DNA-binding domain-independent action. Moreover, hepatocyte-specific deletion of Reverbα drives only modest physiological and transcriptional dysregulation, with derepressed target gene enrichment limited to circadian processes. Thus, contrary to previous reports, hepatic REVERBα does not repress lipogenesis under basal conditions. REVERBα control of a more extensive transcriptional program is only revealed under conditions of metabolic perturbation (including mistimed feeding, which is a feature of the global Reverbα-/- mouse). Repressive action of REVERBα in the liver therefore serves to buffer against metabolic challenge, rather than drive basal rhythmicity in metabolic activity.

Metabolomic differentiation of tumor core versus edge in glioma.

OBJECTIVE: Gliomas exhibit high intratumor and interpatient heterogeneity. Recently, it has been shown that the microenvironment and phenotype differ significantly between the glioma core (inner) and edge (infiltrating) regions. This proof-of-concept study differentiates metabolic signatures associated with these regions, with the potential for prognosis and targeted therapy that could improve surgical outcomes. METHODS: Paired glioma core and infiltrating edge samples were obtained from 27 patients after craniotomy. Liquid-liquid metabolite extraction was performed on the samples and metabolomic data were obtained via 2D liquid chromatography-mass spectrometry/mass spectrometry. To gauge the potential of metabolomics to identify clinically relevant predictors of survival from tumor core versus edge tissues, a boosted generalized linear machine learning model was used to predict metabolomic profiles associated with O6-methylguanine DNA methyltransferase (MGMT) promoter methylation. RESULTS: A panel of 66 (of 168) metabolites was found to significantly differ between glioma core and edge regions (p ≤ 0.05). Top metabolites with significantly different relative abundances included DL-alanine, creatine, cystathionine, nicotinamide, and D-pantothenic acid. Significant metabolic pathways identified by quantitative enrichment analysis included glycerophospholipid metabolism; butanoate metabolism; cysteine and methionine metabolism; glycine, serine, alanine, and threonine metabolism; purine metabolism; nicotinate and nicotinamide metabolism; and pantothenate and coenzyme A biosynthesis. The machine learning model using 4 key metabolites each within core and edge tissue specimens predicted MGMT promoter methylation status, with AUROCEdge = 0.960 and AUROCCore = 0.941. Top metabolites associated with MGMT status in the core samples included hydroxyhexanoycarnitine, spermine, succinic anhydride, and pantothenic acid, and in the edge samples metabolites included 5-cytidine monophosphate, pantothenic acid, itaconic acid, and uridine. CONCLUSIONS: Key metabolic differences are identified between core and edge tissue in glioma and, furthermore, demonstrate the potential for machine learning to provide insight into potential prognostic and therapeutic targets.

Clinical Practice Update: Achilles Tendon Rupture.

Achilles tendon rupture is a common injury. It most often occurs in middle aged men who participate in recreational sports. The injury classically presents with a loud popping noise and immediate pain and weakness of the lower extremity during actions such as jumping or running. The diagnosis is made clinically, but an MRI is often obtained for confirmation of rupture and to aid in surgical planning. Treatment is either operative, with open or minimally invasive approaches, or non-operative, with functional bracing or plaster casting. Surgical treatment was preferred for much of the 20th century, but non-operative treatment has gained significant favor in the past 15 years as new evidence has demonstrated similar long-term outcomes to surgery. Neither treatment option is currently considered superior to the other in all cases. Surgery is associated with a risk for surgical complications and is, therefore, often a poor option for the elderly and those with significant comorbidities. Non-operative management is associated with an increased risk for re-injury which is often undesirable for young and highly active patients. Ultimately, the goals and priorities of each individual patient should guide the decision of which treatment option to pursue.

Lung cancer survival prediction and biomarker identification with an ensemble machine learning analysis of tumor core biopsy metabolomic data.

INTRODUCTION: While prediction of short versus long term survival from lung cancer is clinically relevant in the context of patient management and therapy selection, it has proven difficult to identify reliable biomarkers of survival. Metabolomic markers from tumor core biopsies have been shown to reflect cancer metabolic dysregulation and hold prognostic value. OBJECTIVES: Implement and validate a novel ensemble machine learning approach to evaluate survival based on metabolomic biomarkers from tumor core biopsies. METHODS: Data were obtained from tumor core biopsies evaluated with high-resolution 2DLC-MS/MS. Unlike biofluid samples, analysis of tumor tissue is expected to accurately reflect the cancer metabolism and its impact on patient survival. A comprehensive suite of machine learning algorithms were trained as base learners and then combined into a stacked-ensemble meta-learner for predicting "short" versus "long" survival on an external validation cohort. An ensemble method of feature selection was employed to find a reliable set of biomarkers with potential clinical utility. RESULTS: Overall survival (OS) is predicted in external validation cohort with AUROCTEST of 0.881 with support vector machine meta learner model, while progression-free survival (PFS) is predicted with AUROCTEST of 0.833 with boosted logistic regression meta learner model, outperforming a nomogram using covariate data (staging, age, sex, treatment vs. non-treatment) as predictors. Increased relative abundance of guanine, choline, and creatine corresponded with shorter OS, while increased leucine and tryptophan corresponded with shorter PFS. In patients that expired, N6,N6,N6-Trimethyl-L-lysine, L-pyrogluatmic acid, and benzoic acid were increased while cystine, methionine sulfoxide and histamine were decreased. In patients with progression, itaconic acid, pyruvate, and malonic acid were increased. CONCLUSION: This study demonstrates the feasibility of an ensemble machine learning approach to accurately predict patient survival from tumor core biopsy metabolomic data.

Lung cancer metabolomic data from tumor core biopsies enables risk-score calculation for progression-free and overall survival.

INTRODUCTION: Metabolomics has emerged as a powerful method to provide insight into cancer progression, including separating patients into low- and high-risk groups for overall (OS) and progression-free survival (PFS). However, survival prediction based mainly on metabolites obtained from biofluids remains elusive. OBJECTIVES: This proof-of-concept study evaluates metabolites as biomarkers obtained directly from tumor core biopsies along with covariates age, sex, pathological stage at diagnosis (I/II vs. III/VI), histological subtype, and treatment vs. no treatment to risk stratify lung cancer patients in terms of OS and PFS. METHODS: Tumor core biopsy samples obtained during routine lung cancer patient care at the University of Louisville Hospital and Norton Hospital were evaluated with high-resolution 2DLC-MS/MS, and the data were analyzed by Kaplan-Meier survival analysis and Cox proportional hazards regression. A linear equation was developed to stratify patients into low and high risk groups based on log-transformed intensities of key metabolites. Sparse partial least squares discriminant analysis (SPLS-DA) was performed to predict OS and PFS events. RESULTS: Univariable Cox proportional hazards regression model coefficients divided by the standard errors were used as weight coefficients multiplied by log-transformed metabolite intensity, then summed to generate a risk score for each patient. Risk scores based on 10 metabolites for OS and 5 metabolites for PFS were significant predictors of survival. Risk scores were validated with SPLS-DA classification model (AUROC 0.868 for OS and AUROC 0.755 for PFS, when combined with covariates). CONCLUSION: Metabolomic analysis of lung tumor core biopsies has the potential to differentiate patients into low- and high-risk groups based on OS and PFS events and probability.

Theranostic Copolymers Neutralize Reactive Oxygen Species and Lipid Peroxidation Products for the Combined Treatment of Traumatic Brain Injury.

Traumatic brain injury (TBI) results in the generation of reactive oxygen species (ROS) and lipid peroxidation product (LPOx), including acrolein and 4-hydroxynonenal (4HNE). The presence of these biochemical derangements results in neurodegeneration during the secondary phase of the injury. The ability to rapidly neutralize multiple species could significantly improve outcomes for TBI patients. However, the difficulty in creating therapies that target multiple biochemical derangements simultaneously has greatly limited therapeutic efficacy. Therefore, our goal was to design a material that could rapidly bind and neutralize both ROS and LPOx following TBI. To do this, a series of thiol-functionalized biocompatible copolymers based on lipoic acid methacrylate and polyethylene glycol monomethyl ether methacrylate (FW ∼ 950 Da) (O950) were prepared. A polymerizable gadolinium-DOTA methacrylate monomer (Gd-MA) was also synthesized starting from cyclen to facilitate direct magnetic resonance imaging and in vivo tracking of accumulation. These neuroprotective copolymers (NPCs) were shown to rapidly and effectively neutralize both ROS and LPOx. Horseradish peroxidase absorbance assays showed that the NPCs efficiently neutralized H2O2, while R-phycoerythrin protection assays demonstrated their ability to protect the fluorescent protein from oxidative damage. 1H NMR studies indicated that the thiol-functional NPCs rapidly form covalent bonds with acrolein, efficiently removing it from solution. In vitro cell studies with SH-SY5Y-differentiated neurons showed that NPCs provide unique protection against toxic concentrations of both H2O2 and acrolein. NPCs rapidly accumulate and are retained in the injured brain in controlled cortical impact mice and reduce post-traumatic oxidative stress. Therefore, these materials show promise for improved target engagement of multiple biochemical derangements in hopes of improving TBI therapeutic outcomes.

Discrepancies in metabolomic biomarker identification from patient-derived lung cancer revealed by combined variation in data pre-treatment and imputation methods.

INTRODUCTION: The identification of metabolomic biomarkers predictive of cancer patient response to therapy and of disease stage has been pursued as a "holy grail" of modern oncology, relying on the metabolic dysfunction that characterizes cancer progression. In spite of the evaluation of many candidate biomarkers, however, determination of a consistent set with practical clinical utility has proven elusive. OBJECTIVE: In this study, we systematically examine the combined role of data pre-treatment and imputation methods on the performance of multivariate data analysis methods and their identification of potential biomarkers. METHODS: Uniquely, we are able to systematically evaluate both unsupervised and supervised methods with a metabolomic data set obtained from patient-derived lung cancer core biopsies with true missing values. Eight pre-treatment methods, ten imputation methods, and two data analysis methods were applied in combination. RESULTS: The combined choice of pre-treatment and imputation methods is critical in the definition of candidate biomarkers, with deficient or inappropriate selection of these methods leading to inconsistent results, and with important biomarkers either being overlooked or reported as a false positive. The log transformation appeared to normalize the original tumor data most effectively, but the performance of the imputation applied after the transformation was highly dependent on the characteristics of the data set. CONCLUSION: The combined choice of pre-treatment and imputation methods may need careful evaluation prior to metabolomic data analysis of human tumors, in order to enable consistent identification of potential biomarkers predictive of response to therapy and of disease stage.

Recurrent Sinopulmonary Infections in a Patient Whose HIV Masked Common Variable Immunodeficiency.

It is generally accepted that persons infected with human immunodeficiency virus (HIV) are at an increased risk of infection due to direct destruction of CD4+ lymphocytes and subsequently impaired cell-mediated immunity. Typically, HIV infection is associated with immunoglobulin elevations, but quantitative deficiencies in immunoglobulins have also been rarely described. We present an unusual case of common variable immunodeficiency (CVID) in a HIV-positive patient with recurrent severe respiratory infections. We review epidemiology, clinical presentation, and treatment of primary immunoglobulin deficiency. We also review the relationship between immunoglobulin deficiency and HIV and highlight the importance of recognizing the coexistence of two distinct immunodeficiency syndromes.

Variation in outer blubber lipid concentration does not reflect morphological body condition in humpback whales.

An animal's body condition provides valuable information for ecophysiological studies, and is an important measure of fitness in population monitoring and conservation. While both the external body shape of an animal and its internal tissues (i.e. fat content) can be used as a measure of body condition, the relationship between the two is not always linear. We compared the morphological body condition (external metric obtained through aerial photogrammetry) of migrating humpback whales (Megaptera novaeangliae) with their outer blubber lipid concentration (internal metric obtained through blubber biopsy sampling) off the coast of south-west Australia early and late in the breeding season (spanning ∼4.5 months). The external body condition index of juvenile and adult humpback whales decreased by 26.9 (from 18.8% to -8.1%) and 12.0 percentage points (from 8.6% to -3.4%), respectively, between the early and late phase. In contrast, we found no intra-seasonal change in blubber lipid concentration, and no difference between reproductive classes (juveniles, adults and lactating females); however, the small sample size prevented us from effectively testing these effects. Importantly, however, in the 33 animals for which paired metrics were obtained, we found no correlation between the morphometric body condition index and the blubber lipid concentration of individual whales. The lack of a linear relationship suggests that changes in outer blubber lipid concentration do not reflect external changes in body shape, thus limiting the utility of outer blubber lipid reserves for individual body condition evaluation. The wider spectrum of change in body morphometry captured with aerial photogrammetry supports the use of body morphometry as a reliable and well-tested method.

Development and Characterization of Calmodulin-Based Copolymeric Hydrogels.

Recently, there has been growing interest in harnessing genetically engineered polymers to develop responsive biomaterials, such as hydrogels. Unlike their synthetic counterparts, genetically engineered polymers are produced without the use of toxic reagents and can easily be programmed to incorporate desirable hydrogel properties, including bioactivity, biodegradability, and monodispersity. Herein, we report the development of a copolymeric hydrogel that is based on the calcium-dependent protein, calmodulin (CaM). For our system, CaM and M13, a CaM-binding peptide, were incorporated into genetically engineered polymers with intervening linkers containing cleavable sequences. Spectroscopic and multiple-particle tracking (MPT) studies demonstrate that these polymers self-assemble through calcium-stabilized, noncovalent crosslinking to form a soft viscoelastic material. MPT further revealed that gelation is concentration-dependent. Collagenase digests show that the protein polymers are selectively degraded through specific cleavage. The modularity and stimuli-responsiveness of this system suggest its potential as a flexible scaffold for biomedical applications.

Quantum droplets of electrons and holes.

Interacting many-body systems are characterized by stable configurations of objects--ranging from elementary particles to cosmological formations--that also act as building blocks for more complicated structures. It is often possible to incorporate interactions in theoretical treatments of crystalline solids by introducing suitable quasiparticles that have an effective mass, spin or charge which in turn affects the material's conductivity, optical response or phase transitions. Additional quasiparticle interactions may also create strongly correlated configurations yielding new macroscopic phenomena, such as the emergence of a Mott insulator, superconductivity or the pseudogap phase of high-temperature superconductors. In semiconductors, a conduction-band electron attracts a valence-band hole (electronic vacancy) to create a bound pair, known as an exciton, which is yet another quasiparticle. Two excitons may also bind together to give molecules, often referred to as biexcitons, and even polyexcitons may exist. In indirect-gap semiconductors such as germanium or silicon, a thermodynamic phase transition may produce electron-hole droplets whose diameter can approach the micrometre range. In direct-gap semiconductors such as gallium arsenide, the exciton lifetime is too short for such a thermodynamic process. Instead, different quasiparticle configurations are stabilized dominantly by many-body interactions, not by thermalization. The resulting non-equilibrium quantum kinetics is so complicated that stable aggregates containing three or more Coulomb-correlated electron-hole pairs remain mostly unexplored. Here we study such complex aggregates and identify a new stable configuration of charged particles that we call a quantum droplet. This configuration exists in a plasma and exhibits quantization owing to its small size. It is charge neutral and contains a small number of particles with a pair-correlation function that is characteristic of a liquid. We present experimental and theoretical evidence for the existence of quantum droplets in an electron-hole plasma created in a gallium arsenide quantum well by ultrashort optical pulses.

Hyperalgesia after a Drinking Episode in Young Adult Binge Drinkers: A Cross-Sectional Study.

AIMS: Rodent studies propose potential mechanisms linking excessive drinking and pain hypersensitivity (hyperalgesia), such that stress hormones (i.e. epinephrine and cortisol) mediate induction and maintenance of alcohol withdrawal-induced hyperalgesia. The first aim of this study was to examine whether hyperalgesia would occur within 48 h after a drinking episode in healthy young adult binge drinkers. The second was to examine whether stress hormones and negative effect would be associated with binge drinking or alcohol withdrawal-associated hyperalgesia. METHODS: A cross-sectional experiment was conducted in five groups with naturally occurring drinking (mean age = 19.6, range 18-29 years): abstainers (n = 43, 54% female), moderate drinkers with (n = 50, 50% female) or without recent drinking (i.e. within 48 h, n = 23, 26% female) and binge drinkers with (n = 36, 58% female) or without recent drinking (n = 25, 44% female). All types of drinkers endorsed drinking about 2-3 times a month and 2-3 years of drinking history. RESULTS: Muscle pressure pain thresholds were significantly lower in the binge group with recent drinking compared to other groups, but cutaneous mechanical and heat pain thresholds were not significantly different across the five groups. Basal epinephrine levels were significantly higher in binge groups regardless of recent drinking, but cortisol and negative effect were not significantly different across the five groups. CONCLUSIONS: This is the first study to show that alcohol withdrawal-associated muscle hyperalgesia may occur in healthy episodic binge drinkers with only 2-3 years of drinking history, and epinephrine may play a role in binge drinking-associated hyperalgesia.

Weighing as part of your care: a feasibility study exploring the re-introduction of weight measurements during pregnancy as part of routine antenatal care.

BACKGROUND: The UK does not currently have guidelines on gestational weight gain owing to gaps in the evidence base. Reintroducing routine weighing of women throughout pregnancy would begin to provide the evidence needed to fill this gap. The aim of this research was to re-introduce measurement of weight at each routine antenatal appointment in a small scale study, in order to determine the feasibility and acceptability of implementing the practice on a larger scale. METHODS: A feasibility study, incorporating quantitative and qualitative components, was conducted in one antenatal hospital clinic and with one community midwifery team. Thirty-eight pregnant women were recruited at their 20 week anomaly scan appointment and weighed at their appointments throughout the rest of their pregnancy; five participated in a telephone interview at approximately 37 weeks gestation. Data were collected on: numbers consenting to be weighed, reasons for declining to be weighed and number of weight measurements recorded. Qualitative interviews were used to explore acceptability of the practice to pregnant women. RESULTS: Overall, 79.2% (38 out of 48) of those approached consented to being weighed throughout pregnancy; of the 10 who declined, three cited not wanting to be weighed. In the interviews, women discussed routine weighing as a positive experience, described several benefits of weighing and indicated they would like more information about weight during pregnancy. No major barriers to the integration of a weight measurement into routine antenatal appointments were encountered. Completion of the weight record sheets that were inserted into women's handheld notes varied between staff: of the 26 sheets recovered from handheld notes, only 3 (11.5%) had no weights recorded, 17 (65.4%) had between one and three weights recorded and six (23.1%) had more than 4 weights recorded. CONCLUSIONS: In this feasibility study, routine weighing was acceptable to pregnant women. No barriers that would inhibit re-introduction of weighing women throughout pregnancy into standard antenatal care were encountered. Implementation of routine weighing during pregnancy on a larger scale should be considered as it may have benefits for women in the short and long-term, particularly with regard to informing appropriate gestational weight gain guidelines in the UK.