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This study investigates the relationship between geomagnetic activities and ionospheric scintillations, focusing on how solar and geomagnetic parameters influence ionospheric disturbances across varying time frames and latitudes. Utilizing indices such as Kp, Dst, sunspot numbers, and the F10.7 solar flux, we elucidate the dynamics influencing ionospheric conditions, which are vital for the reliability of satellite communications, particularly in low-latitude regions. Our analysis demonstrates a clear correlation between periods of high solar activity and increased geomagnetic disturbances, leading to heightened ionospheric scintillations, such as occurred during the solar maximum of 2015. In contrast, 2020—a solar minimum period—exhibited fewer disturbances, highlighting the impact of solar activity levels on ionospheric conditions. Innovatively employing ConvGRU networks, this research advances the modeling and prediction of ionospheric scintillations by integrating deep learning techniques suited to the spatiotemporal complexities of ionospheric data. The ConvGRU model effectively captures both temporal sequences and spatial distributions, offering enhanced accuracy in depicting ionospheric scintillation patterns crucial for satellite-based navigation and communication systems. Ground-based GNSS data from 121 stations across South America, collected during 2015 and 2020, provide a robust dataset for our analysis. The study highlights the influence of the solar cycle on ionospheric scintillations, with the years of maximum and minimum solar activity showing significant differences in scintillation intensity and frequency. Our evaluation of the ConvGRU models using statistical parameters demonstrated their potential for reliable ionospheric scintillation prediction. The research underscores the necessity of integrating adaptive mechanisms within models to effectively handle the dynamic nature of ionospheric disturbances influenced by external geomagnetic and solar factors. This study enhances the understanding of ionospheric scintillations and significantly advances predictive modeling capabilities using advanced machine learning techniques. The potential establishment of real-time alert systems for ionospheric disturbances could significantly benefit civilian applications, enhancing the operational efficiency of technologies reliant on accurate ionospheric information.

Human papillomavirus (HPV)-positive Head and Neck Squamous Cell Carcinomas (HNSCC) comprise a particular cancer entity traditionally associated with better clinical outcomes. Around 25% of HNSCC are HPV positive, HPV16 being the most prevalent type. Nevertheless, close to 30% of the HPV-positive patients have an unfavorable prognosis, revealing that this type of tumor exhibits great heterogeneity leading to different clinical behaviors. Efforts have been made to identify RNA molecules with prognostic value associated with the clinical outcome of patients with HPV-positive HNSCC, with the aim of identifying patients at high risk of metastasis, disease recurrence, and poor survival, who would require closer clinical follow-up and timely intervention. Moreover, the molecular identification of those HPV-positive HNSCC patients with good prognosis will allow the implementation of de-escalating therapeutic strategies, aiming to reduce side effects, resulting in a better quality of life. This review compiles a series of recent studies addressing different methodological and conceptual approaches aimed at searching for potential gene expression-based biomarkers associated with the prognosis of patients with HPV-positive HNSCC.

Individual grip strength provides a functional window into somatosensory processes and their effects on motor behaviour in healthy, impaired, and ageing individuals. Variations in grip strength during hand–tool interaction are therefore exploited in a variety of experimental tasks to study the effects of pathology or ageing-related changes on sensory, motor, and cognitive ability. However, many different factors may influence individual grip strength systematically in a given task context without being explicitly identified and controlled for. Grip strength may vary as a function of the location of the measurement device (sensor) on the fingers/hand, the shape, weight and size of object(s) being gripped, the type of grip investigated (static versus dynamic grip), and the hand (dominant versus non-dominant) used for gripping. This study tests for additional factors such as sight, sound, and interactions with/between any of the other factors in a complex task context. A wearable biosensor system, designed for measuring grip strength variations in operators gripping cylindrical objects bi-manually, was used. Grip force signals were recorded from all sensors of the wearable (glove) system, including three directly task-relevant sensors for bi-manually gripping cylindrical objects with the dominant and non-dominant hands. Five young male participants were tested for the effects of sound, movement, and sight on grip strength. The participants had to pick up two cylindrical objects of identical size and weight, then hold them still (static grip) or move them upwards and downwards (dynamic grip) for ten seconds while listening to soft or hard music, with their eyes open or blindfolded. Significant effects of sensor location, hand, movement, sight, and sound on bi-manual grip strength were found. Stronger grip force signals were produced by task-relevant sensors in the dominant hand when moving the cylindrical handles (dynamic grip) in comparison with the static grip condition, depending, as expected, on whether grip signals were measured from the dominant or the non-dominant hand. Significantly weaker grip strength was produced blindfolded (sight condition), and grips were significantly stronger with exposure to harder music (sound factor). It is concluded that grip strength is significantly influenced by sensory factors and interactions between the other factors tested for, pointing towards the need for identifying and systematically controlling such potential sources of variation in complex study task contexts.

This review investigates the multifaceted role of the p66Shc adaptor protein and the gut microbiota in regulating mitochondrial function and oxidative stress, and their collective impact on the pathogenesis of chronic diseases. The study delves into the molecular mechanisms by which p66Shc influences cellular stress responses through Rac1 activation, Forkhead-type transcription factors inactivation, and mitochondria-mediated apoptosis, alongside modulatory effects of gut microbiota-derived metabolites and endotoxins. Employing an integrative approach, the review synthesizes findings from a broad array of studies, including molecular biology techniques and analyses of microbial metabolites’ impacts on host cellular pathways. The results underscore a complex interplay between microbial metabolites, p66Shc activation, and mitochondrial dysfunction, highlighting the significance of the gut microbiome in influencing disease outcomes through oxidative stress pathways. Conclusively, the review posits that targeting the gut microbiota-p66Shc–mitochondrial axis could offer novel therapeutic strategies for mitigating the development and progression of metabolic diseases. This underscores the potential of dietary interventions and microbiota modulation in managing oxidative stress and inflammation, pivotal factors in chronic disease etiology.

Childhood and adolescent cancer survivors are disproportionately more likely to develop cardiovascular diseases from the late effects of cardiotoxic therapies (e.g., anthracycline-based chemotherapy and chest-directed radiotherapy). Currently, dexrazoxane is the only approved drug for preventing cancer treatment-related cardiac damage. While animal models highlight the beneficial effects of exercise cancer treatment-related cardiac dysfunction, few clinical studies have been conducted. Thus, the objective of this scoping review was to explore the designs and impact of exercise-based interventions for managing cancer treatment-related cardiac dysfunction in childhood and adolescent cancer survivors. Reviewers used Joanna Briggs Institute’s methodology to identify relevant literature. Then, 4616 studies were screened, and three reviewers extracted relevant data from six reports. Reviewers found that exercise interventions to prevent cancer treatment-related cardiac dysfunction in childhood and adolescent cancer survivors vary regarding frequency, intensity, time, and type of exercise intervention. Further, the review suggests that exercise promotes positive effects on managing cancer treatment-related cardiac dysfunction across numerous indices of heart health. However, the few clinical studies employing exercise interventions for childhood and adolescent cancer survivors highlight the necessity for more research in this area.

Background: Persistent symptoms after SARS CoV-2 infection such as fatigue, shortness of breath, and cognitive dysfunction that cannot be explained by an alternative diagnosis have been termed long COVID and present a significant emerging public health problem. Current approaches include rehabilitation and symptom management involving multiple health disciplines and as yet there are no pharmaceutical approaches other than routine symptom management. Manual lymph drainage (MLD) has been used to support recovery during pulmonary rehabilitation and reduce chronic inflammation including symptoms associated with long COVID. Case description and outcomes: Two adult females who had reported long-COVID symptoms more than 10 weeks after the resolution of the acute infection were treated with MLD by Remedial Therapists trained in the Dr Vodder method of MLD. Respiratory function (Peak Flow Meter) and blood oxygen levels (Oximeter) were recorded before and after a one-minute sit-to-stand test prior to the treatment. The Dyspnea-12 Questionnaire, the Revised Piper Fatigue Scale, and Likert scales were used to collect client-reported outcomes. Six 45-min treatments were applied weekly, with a follow-up review and treatment at three months. In both cases, all outcomes improved after the third treatment with further improvement noted at three months. Conclusions: MLD may offer a non-invasive, non-pharmaceutical approach to the resolution of long-COVID symptoms such as cough, breathlessness, and fatigue.

When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in the dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain correlate of mental health, dopamine has a central functional role in behavioral regulation from healthy reward-seeking to pathological adaptation to stress in response to adversity. This narrative review offers a spotlight view of the transition from healthy reward function, under the control of dopamine, to the progressive deregulation of this function in interactions with other brain centers and circuits, producing what may be called an anti-reward brain state. How such deregulation is linked to specific health-relevant behaviors is then explained and linked to pandemic-related adversities and the stresses they engendered. The long lockdown periods where people in social isolation had to rely on drink, food, and digital rewards via the internet may be seen as the major triggers of changes in motivation and reward-seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain is discussed. It is argued that, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior changes and mental health is affected, depending on individual vulnerabilities. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.

Snow sampling, either by inserting a tube through the entire snowpack or by taking samples from the vertical profile, is widely applied to measure the snow depth, density, and snow water equivalent (SWE). A comparative study of snow-sampling methods was carried out on 24 March 2022 in Sodankylä, Finland. Six groups from five countries (Estonia, Finland, Greenland, Iceland, and Sweden) participated, using 12 different snow samplers, including 9 bulk tube samplers and 3 density cutters. The cross-sectional area of the SWE samplers varied from 11 to 100 cm2, while tube length varied from 30 cm to 100 cm. The cross-sectional area of the density profile cutters varied from 100 cm2 to 200 cm2 and the vertical sampling step varied from 5 cm to 10 cm. The samples were taken from snow pits in 55–65-centimeter-deep snow cover in a flat area with sparse pine trees, with the pits at a maximum distance of 10 m from each other. Each tube sampling series consisted of 3–10 vertical columns to ensure statistical validation. The snowpack was relatively soft, with two moderately hard crust layers. The density recorded in the tube sample measurements varied from 218 to 265 kgm−3. The measurement results of SWE, however, varied depending on the sampling equipment used, ranging from 148 to 180 kgm−2, with two outliers of 77 and 106 kgm−2, both with 11 cm2 samplers.

Peanut skin is a rich source of bioactive compounds which may be able to reduce the risk factors associated with metabolic syndromes. This study aimed to characterize bio-compounds from peanut skin (Arachis hypogaea) and their bioactivity (antioxidant activity, inhibition of lipase, and carbohydrase enzymes) and to evaluate their anti-proliferative properties in colorectal cancer cells (HCT116) upon in vitro digestion. Peanut skin was digested in two sequential phases, and the final content, named phase-1 (P1) and phase-2 (P2) extracts, was evaluated. Several bioactive compounds were positively identified and quantified by liquid chromatography, including quinic acid, released especially after in vitro digestion. The total phenolic content and, regardless of the method, the antioxidant activity of P1 was higher than P2. P1 also showed a lower enzyme inhibitory concentration IC50 than P2, lipase, and α-glucosidase. For cell viability in HCT116 cells, lower concentrations of P1 were found for IC50 compared to P2. In conclusion, bioactive compounds were released mainly during the first phase of the in vitro digestion. The digested samples presented antioxidant activity, enzyme inhibitory activity, and cancer cell cytotoxicity, especially those from the P1 extract. The potential applications of such a by-product in human health are reported.

CHARGE syndrome typically results from mutations in the gene encoding chromodomain helicase DNA-binding protein 7 (CHD7). CHD7 is involved in regulating neural crest development, which gives rise to tissues of the skull/face and the autonomic nervous system (ANS). Individuals with CHARGE syndrome are frequently born with anomalies requiring multiple surgeries and often experience adverse events post-anesthesia, including oxygen desaturations, decreased respiratory rates, and heart rate abnormalities. Central congenital hypoventilation syndrome (CCHS) affects ANS components that regulate breathing. Its hallmark feature is hypoventilation during sleep, clinically resembling observations in anesthetized CHARGE patients. Loss of PHOX2B (paired-like homeobox 2b) underlies CCHS. Employing a chd7-null zebrafish model, we investigated physiologic responses to anesthesia and compared these to loss of phox2b. Heart rates were lower in chd7 mutants compared to the wild-type. Exposure to tricaine, a zebrafish anesthetic/muscle relaxant, revealed that chd7 mutants took longer to become anesthetized, with higher respiratory rates during recovery. chd7 mutant larvae demonstrated unique phox2ba expression patterns. The knockdown of phox2ba reduced larval heart rates similar to chd7 mutants. chd7 mutant fish are a valuable preclinical model to investigate anesthesia in CHARGE syndrome and reveal a novel functional link between CHARGE syndrome and CCHS.

Bitterness is one of the basic tastes, and sensing bitterness plays a significant role in mammals recognizing toxic substances. The bitter taste of food and oral medicines may decrease consumer compliance. As a result, many efforts have been made to mask or decrease the bitterness in food and oral pharmaceutical products. The detection of bitterness is critical to evaluate how successful the taste-masking technology is, and many novel taste-sensing systems have been developed on the basis of various interaction mechanisms. In this review, we summarize the progress of bitterness response mechanisms and the development of novel sensors in detecting bitterness ranging from commercial electronic devices based on modified electrodes to micro-type sensors functionalized with taste cells, polymeric membranes, and other materials in the last two decades. The challenges and potential solutions to improve the taste sensor quality are also discussed.

Bacteriophage (phage) therapy is a promising alternative antimicrobial approach which has the potential to transform the way we treat bacterial infections. Phage therapy is currently being used on a compassionate basis in multiple countries. Therefore, if a patient has an antibiotic refractory infection, they may expect their clinician to consider and access phage therapy with the hope of improvement. The expectations of clinicians may be similar and may also include expectations around data collection. However, there are multiple biological and practical barriers to fulfilling patient and clinician expectations. While it is possible to access phage therapy, the path to acquisition is not straightforward and expectations therefore need to be managed appropriately to avoid raising false hope and undermining confidence in phage therapy. Phage scientists have an important contribution to make in educating clinicians and the broader public about phage therapy. However, it is clinicians that are responsible for managing the expectations of their patients and this relies on clear communication about the barriers and limitations.

Accumulating evidence has demonstrated the association between alcohol overconsumption and the development of insulin resistance. However, the underlying mechanisms are not completely understood. To investigate the requirement and sufficiency of hepatocyte toll-like receptor 4 (TLR4) in alcohol-induced insulin resistance, we used two mouse models (Tlr4fl/fl and Tlr4LoxTB) that allow ablation of TLR4 only in hepatocytes (Tlr4LKO) and restoration of endogenous TLR4 expression in hepatocytes on a TLR4-null background (Tlr4LoxTB × Alb-Cre), respectively. A Lieber-DeCarli feeding model was used to induce glucose intolerance and insulin resistance in mice. Glucose tolerance test, insulin tolerance test, and insulin signaling experiments were performed to examine systemic and tissue-specific insulin sensitivity. We found that alcohol-fed hepatocyte TLR4 deficient mice (Tlr4LKO) had lower blood glucose levels in response to intraperitoneal injection of insulin. Moreover, increased phosphorylation of glycogen synthase kinase-3β (GSK3β) was observed in the liver of Tlr4LKO mice after chronic alcohol intake. In contrast, when hepatic TLR4 was reactivated in mice (Tlr4LoxTB × Alb-Cre), alcohol feeding caused glucose intolerance in these mice compared with littermate controls (Tlr4LoxTB). In addition, AKT phosphorylation was dramatically reduced in the liver and epididymal white adipose tissue (eWAT) of alcohol-fed Tlr4LoxTB × Alb-Cre mice, which was similar to that of mice with whole-body TLR4 reactivation (Tlr4LoxTB × Zp3-Cre). Collectively, these findings suggest that hepatocyte TLR4 is both required and sufficient in the development of insulin resistance induced by alcohol overconsumption.

Human milk is influenced by maternal habitual diet, yet we do not fully understand the short-term effects of dietary variations on breast milk macronutrient concentrations. This study aimed to determine if increasing sugar and fat consumption would impact breast milk protein, lactose and lipids. Nine mothers who were exclusively breast-feeding consumed three diets; a control, a higher fat diet and a higher sugar diet at least 1 week apart. Breast milk samples were collected hourly and analysed for concentrations of protein, lactose, triglycerides and cholesterol. Breast milk triglycerides responded to both intervention diets with significantly higher concentrations in comparison to the control diet (p < 0.001). Cholesterol concentrations increased more in response to the higher sugar diet than the higher fat diet (p < 0.005). Lactose concentrations increased in response to the higher fat diet (p = 0.006), and protein decreased in response to the higher fat diet (p = 0.05). Variations in breast milk composition were observed over the day with triglyceride and cholesterol concentrations highest at the end of day (p < 0.001), and lactose and protein concentrations peaking at hour 10 (p < 0.001). Manipulating maternal consumption of fat and sugar impacted concentrations of human milk triglycerides, cholesterol, lactose and protein. Fluctuations were also seen in milk macronutrients in response to time of day.

The human akna gene encodes an AT-hook transcription factor, the expression of which is involved in various cellular processes. The goal of this study was to identify potential AKNA binding sites in genes that participate in T-cell activation and validate selected genes. Here we analyzed ChIP-seq and microarray assays to determine AKNA-binding motifs and the cellular process altered by AKNA in T-cell lymphocytes. In addition, we performed a validation analysis by RT-qPCR to assess AKNA’s role in promoting IL-2 and CD80 expression. We found five AT-rich motifs that are potential candidates as AKNA response elements. We identified these AT-rich motifs in promoter regions of more than a thousand genes in activated T-cells, and demonstrated that AKNA induces the expression of genes involved in helper T-cell activation, such as IL-2. The genomic enrichment and prediction of AT-rich motif analyses demonstrated that AKNA is a transcription factor that can potentially modulate gene expression by recognizing AT-rich motifs in a plethora of genes that are involved in different molecular pathways and processes. Among the cellular processes activated by AT-rich genes, we found inflammatory pathways potentially regulated by AKNA, suggesting AKNA is acting as a master regulator during T-cell activation.

Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level, long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are re-visited in this concept paper on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics.

New technologies for monitoring grip forces during hand and finger movements in non-standard task contexts have provided unprecedented functional insights into somatosensory cognition. Somatosensory cognition is the basis of our ability to manipulate and transform objects of the physical world and to grasp them with the right amount of force. In previous work, the wireless tracking of grip-force signals recorded from biosensors in the palm of the human hand has permitted us to unravel some of the functional synergies that underlie perceptual and motor learning under conditions of non-standard and essentially unreliable sensory input. This paper builds on this previous work and discusses further, functionally motivated, analyses of individual grip-force data in manual robot control. Grip forces were recorded from various loci in the dominant and non-dominant hands of individuals with wearable wireless sensor technology. Statistical analyses bring to the fore skill-specific temporal variations in thousands of grip forces of a complete novice and a highly proficient expert in manual robot control. A brain-inspired neural network model that uses the output metric of a self-organizing pap with unsupervised winner-take-all learning was run on the sensor output from both hands of each user. The neural network metric expresses the difference between an input representation and its model representation at any given moment in time and reliably captures the differences between novice and expert performance in terms of grip-force variability.Functionally motivated spatiotemporal analysis of individual average grip forces, computed for time windows of constant size in the output of a restricted amount of task-relevant sensors in the dominant (preferred) hand, reveal finger-specific synergies reflecting robotic task skill. The analyses lead the way towards grip-force monitoring in real time. This will permit tracking task skill evolution in trainees, or identify individual proficiency levels in human robot-interaction, which represents unprecedented challenges for perceptual and motor adaptation in environmental contexts of high sensory uncertainty. Cross-disciplinary insights from systems neuroscience and cognitive behavioral science, and the predictive modeling of operator skills using parsimonious Artificial Intelligence (AI), will contribute towards improving the outcome of new types of surgery, in particular the single-port approaches such as NOTES (Natural Orifice Transluminal Endoscopic Surgery) and SILS (Single-Incision Laparoscopic Surgery).

The physiological state of the human macrophage may impact the metabolism and the persistence of Mycobacterium tuberculosis. This pathogen senses and counters the levels of O2, CO, reactive oxygen species (ROS), and pH in macrophages. M. tuberculosis responds to oxidative stress through WhiB3. The goal was to determine the effect of NADPH oxidase (NOX) modulation and oxidative agents on the expression of whiB3 and genes involved in lipid metabolism (lip-Y, Icl-1, and tgs-1) in intracellular mycobacteria. Human macrophages were first treated with NOX modulators such as DPI (ROS inhibitor) and PMA (ROS activator), or with oxidative agents (H2O2 and generator system O2•−), and then infected with mycobacteria. We determined ROS production, cell viability, and expression of whiB3, as well as genes involved in lipid metabolism. PMA, H2O2, and O2•− increased ROS production in human macrophages, generating oxidative stress in bacteria and augmented the gene expression of whiB3, lip-Y, Icl-1, and tgs-1. Our results suggest that ROS production in macrophages induces oxidative stress in intracellular bacteria inducing whiB3 expression. This factor may activate the synthesis of reserve lipids produced to survive in the latency state, which allows its persistence for long periods within the host.

Vascular endothelial cells have a critical role in the maintenance of cardiovascular function. Evidence suggests that endothelial function may be compromised under conditions of magnesium deficiency, which increases vulnerability to inflammation. Whole genome transcription analysis was used to explore the acute (24 h) effects of magnesium on human umbilical vascular endothelial cells (HUVEC) cultured in low (0.1 mM) or high (5 mM) concentrations. With low magnesium 2728 transcripts were differentially expressed compared to the 1 mM control cultures and 3030 were differentially expressed with high magnesium. 615 transcripts were differentially expressed under both conditions, of which only 34 showed a concentration-dependent response. Analysis indicated that cellular organisation and biogenesis and key cellular processes such as apoptosis were impacted by both low and high conditions. High magnesium also influenced protein binding functions, intracellular signal transduction, metabolic and catalytic processes. Both conditions impacted on stress-related processes, in particular the inflammatory response. Key mediators of calcium-dependent regulation of gene expression were responsive to both high and low magnesium conditions. The HUVEC transcriptome is highly sensitive to acute changes in the concentration of magnesium in culture medium. The findings of this study support the view that whilst inflammation is an important process that is responsive to magnesium, the function of the endothelium may be impacted by other magnesium-induced changes including maintenance of cellular integrity, receptor expression and metabolic functions. The high proportion of transcripts that did not show a concentration-dependent response suggests variation in magnesium may elicit indirect changes, possibly mediated by other ions.

Symmetry in nature is a result of biological self-organization, driven by evolutionary processes. Detected by the visual systems of various species, from invertebrates to primates, symmetry determines survival relevant choice behaviors and supports adaptive function by reducing stimulus uncertainty. Symmetry also provides a major structural key to bio-inspired artificial vision and shape or movement simulations. In this psychophysical study, local variations in color covering the whole spectrum of visible wavelengths are compared to local variations in luminance contrast across an axis of geometrically perfect vertical mirror symmetry. The chromatic variations are found to delay response time to shape symmetry to a significantly larger extent than achromatic variations. This effect depends on the degree of variability, i.e., stimulus complexity. In both cases, we observe linear increase in response time as a function of local color variations across the vertical axis of symmetry. These results are directly explained by the difference in computational complexity between the two major (magnocellular vs. parvocellular) visual pathways involved in filtering the contrast (luminance vs. luminance and color) of the shapes. It is concluded that color variability across an axis of symmetry proves detrimental to the rapid detection of symmetry, and, presumably, other structural shape regularities. The results have implications for vision-inspired artificial intelligence and robotics exploiting functional principles of human vision for gesture and movement detection, or geometric shape simulation for recognition systems, where symmetry is often a critical property.

The smuggling of illicit drugs urges the development of new tools for rapid on-site identification in cargos. Current methods rely on presumptive color tests and portable spectroscopic techniques. However, these methods sometimes exhibit inaccurate results due to commonly used cutting agents, the colorful nature of the sample or because the drugs are smuggled in common goods. Interestingly, electrochemical sensors can deal with these specific problems. Herein, an electrochemical device is presented that uses affordable screen-printed electrodes for the electrochemical profiling of several illicit drugs by square-wave voltammetry (SWV). The identification of the illicit compound is based on the oxidation potential of the analyte. Hence, a library of electrochemical profiles is built upon the analysis of illicit drugs and common cutting agents. This library allows the design of a tailor-made script that enables the identification of each drug through a user-friendly interface (laptop or mobile phone). Importantly, the electrochemical test is compared by analyzing 48 confiscated samples with other portable devices based on Raman and FTIR spectroscopy as well as a laboratory standard method (i.e., gas chromatography–mass spectrometry). Overall, the electrochemical results, obtained through the analysis of different samples from confiscated cargos at an end-user site, present a promising alternative to current methods, offering low-cost and rapid testing in the field.

The Valparaiso region in Chile was decreed a zone affected by catastrophe in 2019 as a consequence of one of the driest seasons of the last 50 years. In this study, three varieties (‘Alfa-INIA’, ‘California-INIA’, and one landrace, ‘Local Navidad’) of kabuli-type chickpea seeds produced in 2018 (control) and 2019 (climate-related catastrophe, hereafter named water stress) were evaluated for their grain yield. Furthermore, the flavonoid profile of both free and esterified phenolic extracts was determined using liquid chromatography-mass spectrometry, and the concentration of the main flavonoid, biochanin A, was determined using liquid chromatography with diode array detection. The grain yield was decreased by up to 25 times in 2019. The concentration of biochanin A was up to 3.2 times higher in samples from the second season (water stress). This study demonstrates that water stress induces biosynthesis of biochanin A. However, positive changes in the biochanin A concentration are overshadowed by negative changes in the grain yield. Therefore, water stress, which may be worsened by climate change in the upcoming years, may jeopardize both the production of chickpeas and the supply of biochanin A, a bioactive compound that can be used to produce dietary supplements and/or nutraceuticals.

Olive lace bugs (Hemiptera: Tingidae) are small sap-sucking insects that feed on wild and cultivated Olea europaea. The diversity of olive lace bug species in South Africa, the most important olive producer on the continent, has been incompletely surveyed. Adult specimens were collected in the Western Cape province for morphological and DNA-based species identification, and sequencing of complete mitogenomes. Cysteochila lineata, Plerochila australis, Neoplerochila paliatseasi and Neoplerochila sp. were found at 12 sites. Intra- and interspecific genetic divergences and phylogenetic clustering in 30 species in 18 genera of Tingidae using new and publicly available DNA barcodes showed high levels of congruity between taxonomic and genetic data. The phylogenetic position of the four species found in South Africa was inferred using new and available mitogenomes of Tingidae. Notably, olive lace bugs formed a cluster of closely related species. However, Cysteochila was non-monophyletic as C. lineata was recovered as a sister species to P. australis whereas Cysteochila chiniana, the other representative of the genus, was grouped with Trachypeplus jacobsoni and Tingis cardui in a different cluster. This result suggests that feeding on O. europaea may have a common origin in Tingidae and warrants future research on potential evolutionary adaptations of olive lace bugs to this plant host.

Neutrophil–lymphocyte ratio (NLR) is a biomarker of the systemic inflammatory response. The objective of this systematic scoping review was to examine the literature on NLR and inflammatory bowel disease (IBD). PubMed, Embase, Cochrane CENTRAL, CINAHL, ClinicalTrials.gov, Cochrane Specialized Register, DOAJ, PDQT, Biosis Citation Index, Scopus, and Web of Science were systematically searched. A total of 2621 citations yielding 62 primary studies were synthesized under four categories: distinguishing patients with IBD from controls, disease activity differentiation, clinical outcome prediction, and association of NLR with other IBD biomarkers. Thirty-eight studies employed receiver operating characteristic (ROC) curve analysis to generate optimal NLR cutpoints for applications including disease activity differentiation and prediction of response to treatment. Among the most promising findings, NLR may have utility for clinical and endoscopic disease activity differentiation and prediction of loss of response to infliximab (IFX). Overall findings suggest NLR may be a promising IBD biomarker. Assessment of NLR is non-invasive, low cost, and widely accessible given NLR is easily calculated from blood count data routinely and serially monitored in patients with IBD. Further research is justified to elucidate how evaluation of NLR in research and clinical practice would directly impact the quality and cost of care for patients living with IBD.

Magnetic nanoparticles (MNPs) have a wide range of applications; an area of particular interest is magnetic particle imaging (MPI). MPI is an imaging modality that utilizes superparamagnetic iron oxide particles (SPIONs) as tracer particles to produce highly sensitive and specific images in a broad range of applications, including cardiovascular, neuroimaging, tumor imaging, magnetic hyperthermia and cellular tracking. While there are hurdles to overcome, including accessibility of products, and an understanding of safety and toxicity profiles, MPI has the potential to revolutionize research and clinical biomedical imaging. This review will explore a brief history of MPI, MNP synthesis methods, current and future applications, and safety concerns associated with this newly emerging imaging modality.

Purpose: (1) To determine the contribution of diet, time spent outdoors, and habitual physical activity (PA) on vitamin D status in men with cerebral palsy (CP) compared to physical activity matched controls (TDC) without neurological impairment; (2) to determine the role of vitamin D on musculoskeletal health, morphology, and function in men with CP compared to TDC. Materials and methods: A cross-sectional comparison study where 24 active, ambulant men with CP aged 21.0 ± 1.4 years (Gross Motor Function Classification Score (I–II) and 24 healthy TDC aged 25.3 ± 3.1 years completed in vivo assessment of musculoskeletal health, including: vastus lateralis anatomical cross-sectional area (VL ACSA), isometric knee extension maximal voluntary contraction (KE iMVC), 10 m sprint, vertical jumps (VJ), and radius and tibia bone ultrasound (US) Tus and Zus scores. Assessments of vitamin D status through venous samples of serum 25-hydroxyvitamin D (25(OH)D) and parathyroid hormone, dietary vitamin D intake from food diary, and total sun exposure via questionnaire were also taken. Results: Men with CP had 40.5% weaker KE iMVC, 23.7% smaller VL ACSA, 22.2% lower VJ, 14.6% lower KE iMVC/VL ACSA ratio, 22.4% lower KE iMVC/body mass (BM) ratio, and 25.1% lower KE iMVC/lean body mass (LBM) ratio (all p < 0.05). Radius Tus and Zus scores were 1.75 and 1.57 standard deviations lower than TDC, respectively (p < 0.05), whereas neither tibia Tus nor Zus scores showed any difference compared to TDC (p > 0.05). The 25(OH)D was not different between groups, and 90.9% of men with CP and 91.7% of TDC had low 25(OH)D levels when compared to current UK recommendations. The 25(OH)D was positively associated with KE iMVC/LBM ratio in men with CP (r = 0.500, p = 0.020) but not in TDC (r = 0.281, p = 0.104). Conclusion: Musculoskeletal outcomes in men with CP were lower than TDC, and despite there being no difference in levels of 25(OH)D between the groups, 25 (OH)D was associated with strength (KE iMVC/LBM) in the CP group but not TDC. The findings suggest that vitamin D deficiency can accentuate some of the condition-specific impairments to musculoskeletal outcomes.

Polycyclic aromatic hydrocarbons (PAHs) are chemical compounds comprised of carbon and hydrogen molecules in a cyclic arrangement. PAHs are associated with risks to human health, especially carcinogenesis. One form of exposure to these compounds is through ingestion of contaminated food, which can occur during preparation and processing involving high temperatures (e.g., grilling, smoking, toasting, roasting, and frying) as well as through PAHs present in the soil, air, and water (i.e., environmental pollution). Differently from changes caused by microbiological characteristics and lipid oxidation, consumers cannot sensorially perceive PAH contamination in food products, thereby hindering their ability to reject these foods. Herein, the occurrence and biological effects of PAHs were comprehensively explored, as well as analytical methods to monitor their levels, legislations, and strategies to reduce their generation in food products. This review updates the current knowledge and addresses recent regulation changes concerning the widespread PAHs contamination in several types of food, often surpassing the concentration limits deemed acceptable by current legislations. Therefore, effective measures involving different food processing strategies are needed to prevent and reduce PAHs contamination, thereby decreasing human exposure and detrimental health effects. Furthermore, gaps in literature have been addressed to provide a basis for future studies.

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this end, we exploit a neural network metric in the output of a biologically inspired Self-Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data.

Understanding the genomic and environmental basis of cold adaptation is key to understand how plants survive and adapt to different environmental conditions across their natural range. Univariate and multivariate genome-wide association (GWAS) and genotype-environment association (GEA) analyses were used to test associations among genome-wide SNPs obtained from whole-genome resequencing, measures of growth, phenology, emergence, cold hardiness, and range-wide environmental variation in coastal Douglas-fir (Pseudotsuga menziesii). Results suggest a complex genomic architecture of cold adaptation, in which traits are either highly polygenic or controlled by both large and small effect genes. Newly discovered associations for cold adaptation in Douglas-fir included 130 genes involved in many important biological functions such as primary and secondary metabolism, growth and reproductive development, transcription regulation, stress and signaling, and DNA processes. These genes were related to growth, phenology and cold hardiness and strongly depend on variation in environmental variables such degree days below 0c, precipitation, elevation and distance from the coast. This study is a step forward in our understanding of the complex interconnection between environment and genomics and their role in cold-associated trait variation in boreal tree species, providing a baseline for the species’ predictions under climate change.

Deep learning has provided new ways of manipulating, processing and analyzing data. It sometimes may achieve results comparable to, or surpassing human expert performance, and has become a source of inspiration in the era of artificial intelligence. Another subfield of machine learning named reinforcement learning, tries to find an optimal behavior strategy through interactions with the environment. Combining deep learning and reinforcement learning permits resolving critical issues relative to the dimensionality and scalability of data in tasks with sparse reward signals, such as robotic manipulation and control tasks, that neither method permits resolving when applied on its own. In this paper, we present recent significant progress of deep reinforcement learning algorithms, which try to tackle the problems for the application in the domain of robotic manipulation control, such as sample efficiency and generalization. Despite these continuous improvements, currently, the challenges of learning robust and versatile manipulation skills for robots with deep reinforcement learning are still far from being resolved for real-world applications.

Wearable sensor systems with transmitting capabilities are currently employed for the biometric screening of exercise activities and other performance data. Such technology is generally wireless and enables the non-invasive monitoring of signals to track and trace user behaviors in real time. Examples include signals relative to hand and finger movements or force control reflected by individual grip force data. As will be shown here, these signals directly translate into task, skill, and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. The present study draws from thousands of such sensor data recorded from multiple spatial locations. The individual grip force profiles of a highly proficient left-hander (expert), a right-handed dominant-hand-trained user, and a right-handed novice performing an image-guided, robot-assisted precision task with the dominant or the non-dominant hand are analyzed. The step-by-step statistical approach follows Tukey’s “detective work” principle, guided by explicit functional assumptions relating to somatosensory receptive field organization in the human brain. Correlation analyses (Person’s product moment) reveal skill-specific differences in co-variation patterns in the individual grip force profiles. These can be functionally mapped to from-global-to-local coding principles in the brain networks that govern grip force control and its optimization with a specific task expertise. Implications for the real-time monitoring of grip forces and performance training in complex task-user systems are brought forward.

The video-capabilities of smartphones are rapidly improving both in pixel resolution and frame-rates. Herein we use four smartphones in the “slow-mo” option to perform time-resolved Tomographic Particle Shadow Velocimetry of a vortex ring, using 960 fps. We use background LED-illuminated diffusers, facing each camera, for shadow particle imaging. We discuss in-depth the challenges present in synchronizing the high-speed video capture on the smartphones and steps to overcome these challenges. The resulting 3-D velocity field is compared to an instantaneous, concurrent, high-resolution snapshot with four 4k-video cameras using dual-color to encode two time-steps on a single frame. This proof-of-concept demonstration, supports realistic low-cost alternatives to conventional 3-D experimental systems.

Influenza virus infection causes severe respiratory illness in people worldwide, disproportionately affecting infants. The immature respiratory tract coupled with the developing immune system, and lack of previous exposure to the virus is thought to synergistically play a role in the increased disease severity in younger age groups. No influenza vaccines are available for those under six months, although maternal influenza immunization is recommended. In children aged six months to two years, vaccine immunogenicity is dampened compared to older children and adults. Unlike older children and adults, the infant immune system has fewer antigen-presenting cells and soluble immune factors. Paradoxically, we know that a person’s first infection with the influenza virus during infancy or childhood leads to the establishment of life-long immunity toward that particular virus strain. This is called influenza imprinting. We contend that by understanding the influenza imprinting event in the context of the infant immune system, we will be able to design more effective influenza vaccines for both infants and adults. Working through the lens of imprinting, using infant influenza animal models such as mice and ferrets which have proven useful for infant immunity studies, we will gain a better understanding of imprinting and its implications regarding vaccine design. This review examines literature regarding infant immune and respiratory development, current vaccine strategies, and highlights the importance of research into the imprinting event in infant animal models to develop more effective and protective vaccines for all including young children.

Omega-3 long-chain polyunsaturated fatty acids (LCPUFA) have been shown to inhibit lipogenesis and adipogenesis in adult rats. Their possible early life effects on offspring fat deposition, however, remain to be established. To investigate this, female Wistar rats (n = 6–9 per group) were fed either a 9:1 ratio of linoleic acid (LA) to alpha-linolenic acid (ALA) or a lower 1:1.5 ratio during pregnancy and lactation. Each ratio was fed at two total fat levels (18% vs. 36% fat w/w) and offspring were weaned onto standard laboratory chow. Offspring exposed to a 36% fat diet, irrespective of maternal dietary LA:ALA ratio, were lighter (male, 27 g lighter; female 19 g lighter; p < 0.0001) than those exposed to an 18% fat diet between 3 and 8 weeks of age. Offspring exposed to a low LA (18% fat) diet had higher proportions of circulating omega-3 LCPUFA and increased gonadal fat mass at 4 weeks of age (p < 0.05). Reduced Srebf1 mRNA expression of hepatic (p < 0.01), gonadal fat (p < 0.05) and retroperitoneal fat (p < 0.05) tissue was observed at 4 weeks of age in male and female offspring exposed to a 36% fat diet, and hepatic Srebf1 mRNA was also reduced in male offspring at 8 weeks of age (p < 0.05). Thus, while offspring fat deposition appeared to be sensitive to both maternal dietary LA:ALA ratio and total fat content, offspring growth and lipogenic capacity of tissues appeared to be more sensitive to maternal dietary fat content.

All too often, organizations embrace standards for health technology assessment that fail to meet those of normal science. A value assessment framework has been endorsed that is patently in the realm of pseudoscience. If a value assessment framework is to be accepted, then claims for the value of competing products must be credible, evaluable and replicable. If not, for example, when the assessment relies on the construction of an imaginary lifetime incremental cost-per-quality-adjusted-life-year (QALY) world, then that assessment should be rejected. Such an assessment would fail one of the central roles of normal science: the discovery of new facts through an ongoing process of conjecture and refutation where provisional claims can be continually challenged. It is no good defending an endorsement of a value framework that fails expected standards on the grounds that it has been endorsed by professional groups and reflects decades of development. This is intellectually lazy. If this is the case, then the scientific revolution of the 17th century need not have happened. The purpose of this commentary is to consider the recommended standards for health technology assessment of the National Pharmaceutical Council (NPC), with particular reference to proposed methodological standards in value assessment and the commitment to mathematically impossible QALYs.

The reporting of U wave abnormalities is clinically important, but the measurement of this small electrocardiographic (ECG) feature is extremely difficult, especially in challenging recording conditions, such as stress exercise, due to contaminating noise. Furthermore, it is widely stated that ECG U waves are rarely observable at heart rates greater than 90 bpm. The aims of the study were (i) to assess the ability of multi-beat averaging to reveal the presence of U waves in ECGs contaminated by noise following exercise and (ii) to quantify the effect of exercise on U wave amplitude. The multi-beat averaging algorithm was applied to recover U waves in 20 healthy subjects in pre- and post-exercise recordings. Average beats were generated from 30 beat epochs. The prevalence of U waves and their amplitudes were measured in pre- and post-exercise recordings and changes in amplitude due to exercise were quantified. U waves were present in all subjects in pre-exercise recordings. Following exercise, U waves could not be seen in standard ECG but were observable in all 20 subjects by multi-beat averaging and despite significantly increased mean (±SD) heart rate (63 ± 8 bpm vs. 100 ± 9 bpm, p < 0.0001). Furthermore, U waves were observable in all subjects with heart rates greater than 90 bpm. U waves significantly increased in amplitude following exercise (38 ± 15 μV vs. 80 ± 48 μV, p = 0.0005). Multi-beat averaging is effective at recovering U waves contaminated by noise due to exercise. U waves were measurable in all subjects, dispelling the myth that U waves are rarely seen at elevated heart rates. U waves exhibit increased amplitudes at elevated heart rates following exercise.

Inactivated influenza vaccines efficacy is variable and often poor. We conducted a phase 1 trial (NCT02188810), to assess the safety and immunogenicity of a novel nanoparticle Toll-like receptor 7/8 agonist adjuvant (Papaya Mosaic Virus) at different dose levels combined with trivalent influenza vaccine in healthy persons 18–50 years of age. Hemagglutination-inhibition assays, antibody to Influenza A virus nucleoprotein and peripheral blood mononuclear cells for measurement of interferon-gamma ELISPOT response to influenza antigens, Granzyme B and IFNγ:IL-10 ratio were measured. The most common adverse events were transient mild to severe injection site pain and no safety signals were observed. A dose-related adjuvant effect was observed. Geometric mean hemagglutination-inhibition titers increased at day 28 in most groups and waned over time, but fold-antibody responses were poor in all groups. Cell mediated immunity results were consistent with humoral responses. The Papaya Mosaic Virus adjuvant in doses of 30 to 240 µg combined with reduced influenza antigen content was safe with no signals up to 3 years after vaccination. A dose-related adjuvant effect was observed and immunogenicity results suggest that efficacy study should be conducted in influenza antigen-naïve participants.

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: (1) modular connectivity, (2) unsupervised learning, (3) adaptive ability, (4) functional resiliency, (5) functional plasticity, (6) from-local-to-global functional organization, and (7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward.

Cancer cells exhibit exacerbated metabolic activity to maintain their accelerated proliferation and microenvironmental adaptation in order to survive under nutrient-deficient conditions. Tumors display an increase in glycolysis, glutaminolysis and fatty acid biosynthesis, which provide their energy source. Glutamine is critical for fundamental cellular processes, where intermediate metabolites produced through glutaminolysis are necessary for the maintenance of mitochondrial metabolism. These include antioxidants to remove reactive oxygen species, and the generation of the nonessential amino acids, purines, pyrimidines and fatty acids required for cellular replication and the activation of cell signaling. Some cancer cells are highly dependent on glutamine consumption since its catabolism provides an anaplerotic pathway to feed the Krebs cycle. Intermediate members of the glutaminolysis pathway have been found to be deregulated in several types of cancers and have been proposed as therapeutic targets and prognostic biomarkers. This review summarizes the main players in the glutaminolysis pathway, how they have been found to be deregulated in cancer and their implications for cancer maintenance. Furthermore, non-coding RNAs are now recognized as new participants in the regulation of glutaminolysis; therefore, their involvement in glutamine metabolism in cancer is discussed in detail.

Pieron’s and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the forefront the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations based on physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative, forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results showed that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by audio-visual probability summation.

STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. Pre-clinical testing of STRAS has recently permitted to demonstrate major advantages of the system in comparison with classic procedures. Benchmark methods permitting to establish objective criteria for ‘expertise’ need to be worked out now to effectively train surgeons on this new system in the near future. STRAS consists of three cable-driven sub-systems, one endoscope serving as guide, and two flexible instruments. The flexible instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this study, small force sensors sewn into a wearable glove to ergonomically fit the master handles of the robotic system were employed for monitoring the forces applied by an expert and a trainee (complete novice) during all the steps of surgical task execution in a simulator task (4-step-pick-and-drop). Analysis of grip-force profiles is performed sensor by sensor to bring to the fore specific differences in handgrip force profiles in specific sensor locations on anatomically relevant parts of the fingers and hand controlling the master/slave system.

A cyclam (1,4,8,11-tetraazacyclotetradecane)-based macrocycle bearing two benzyl and two 2-hydroxy-3,5-di-tert-butylbenzyl pendent arms was synthesized and characterized using spectroscopic techniques and single crystal X-ray diffraction. The macrocycle crystallizes in the triclinic space group P-1, with the asymmetric unit containing one-half of the molecule. The structure is stabilized by hydrogen-bonding which exists between the phenolic protons and the nitrogen atoms of the macrocyclic ring. The presence of this hydrogen bonding is observed in the 1H-NMR due to the deshielded nature of the phenolic OH peak (δ 9.99). Cyclic voltammetry of the ligand revealed a single quasi-reversible peak at −0.58 V (Epc = −0.48 V and Epa = −0.68 V), which is due to the electrochemical oxidation of the phenol to the phenoxyl radical.

Although attention-deficit hyperactivity disorder (ADHD) has been linked to emotion dysregulation, few studies have experimentally investigated this whilst controlling for the effects of comorbid conduct disorder (CD). Economic decision-making games that assess how individuals respond to offers varying in fairness have been used to study emotion regulation. The present study compared adolescent boys with ADHD (n = 90), ADHD + CD (n = 94) and typical controls (n = 47) on the Ultimatum Game and examined the contribution of ADHD and CD symptom scores and callous and unemotional traits to acceptance levels of unfair offers. There were no significant differences in acceptance rates of fair and highly unfair offers between groups, and only boys with ADHD did not significantly differ from the controls. However, the subgroup of boys with ADHD and additional high levels of aggressive CD symptoms rejected significantly more ambiguous (i.e., moderately unfair) offers than any other subgroup, suggesting impaired emotion regulation in those with ADHD and aggressive CD. Correlations within the CD group showed that the rejection rate to moderately unfair offers was predicted by aggressive CD symptom severity, but not callous and unemotional traits. These findings highlight the fact that ADHD is a heterogeneous condition from an emotion regulation point of view.

A novel method of quantifying the effectiveness of the suppression of ventricular activity from electrocardiograms (ECGs) in atrial fibrillation is proposed. The temporal distribution of the energy of wavelet coefficients is quantified by wavelet entropy at each ventricular beat. More effective ventricular activity suppression yields increased entropies at scales dominated by the ventricular and atrial components of the ECG. Two studies are undertaken to demonstrate the efficacy of the method: first, using synthesised ECGs with controlled levels of residual ventricular activity, and second, using patient recordings with ventricular activity suppressed by an average beat template subtraction algorithm. In both cases wavelet entropy is shown to be a good measure of the effectiveness of ventricular beat suppression.

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns and generate new information, or simply store and further process large amounts of sensor data is then reviewed, and examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence (AI) aimed at coping with the big data deluge in the near future.

The potential association between running foot strike analysis and performance and injury metrics has created the need for reliable methods to quantify foot strike pattern outside the laboratory. Small, wireless inertial measurement units (IMUs) allow for unrestricted movement of the participants. Current IMU methods to measure foot strike pattern places small, rigid accelerometers and/or gyroscopes on the heel cap or on the instep of the shoe. The purpose of this study was to validate a thin, conformable IMU sensor placed directly on the dorsal foot surface to determine foot strike angles and pattern. Participants (n = 12) ran on a treadmill with different foot strike patterns while videography and sensor data were captured. Sensor measures were compared against traditional 2D video analysis techniques and the results showed that the sensor was able to accurately (92.2% success) distinguish between rearfoot and non-rearfoot foot strikes using an angular velocity cut-off value of 0°/s. There was also a strong and significant correlation between sensor determined foot strike angle and foot strike angle determined from videography analysis (r = 0.868, p < 0.001), although linear regression analysis showed that the sensor underestimated the foot strike angle. Conformable sensors with the ability to attach directly to the human skin could improve the tracking of human dynamics and should be further explored.

Failure to cure ovarian cancer relates to the persistence of dormant, drug-resistant cancer cells following surgery and chemotherapy. “Second look” surgery can detect small, poorly vascularized nodules of persistent ovarian cancer in ~50% of patients, where >80% are undergoing autophagy and express DIRAS3. Autophagy is one mechanism by which dormant cancer cells survive in nutrient poor environments. DIRAS3 is a tumor suppressor gene downregulated in >60% of primary ovarian cancers by genetic, epigenetic, transcriptional and post-transcriptional mechanisms, that upon re-expression can induce autophagy and dormancy in a xenograft model of ovarian cancer. We examined the expression of DIRAS3 and autophagy in ovarian cancer cells following nutrient deprivation and the mechanism by which they are upregulated. We have found that DIRAS3 mediates autophagy induced by amino acid starvation, where nutrient sensing by mTOR plays a central role. Withdrawal of amino acids downregulates mTOR, decreases binding of E2F1/4 to the DIRAS3 promoter, upregulates DIRAS3 and induces autophagy. By contrast, acute amino acid deprivation did not affect epigenetic regulation of DIRAS3 or expression of miRNAs that regulate DIRAS3. Under nutrient poor conditions DIRAS3 can be transcriptionally upregulated, inducing autophagy that could sustain dormant ovarian cancer cells.

Estrogen receptor alpha (ERα) has an established role in breast cancer biology. Transcriptional activation by ERα is a multistep process modulated by coactivator and corepressor proteins. Breast Cancer Amplified Sequence 2 (BCAS2), is a poorly studied ERα coactivator. In this work, we characterize some of the mechanisms through which this protein increases ERα activity and how this promotes carcinogenic processes in breast cancer cells. Using protein-protein interaction and luciferase assays we show that BCAS2 interacts with ERα both in vitro and in vivo and upregulates transcriptional activation of ERα directly through its N-terminal region (AF-1) and indirectly through its C-terminal (AF-2) region, acting in concert with AF-2 interacting coactivators. Elevated expression of BCAS2 positively affects proliferation, clonogenicity and migration of breast cancer cells and directly activates ERα regulated genes which have been shown to play a role in tumor growth and progression. Finally, we used signal transduction pathway inhibitors to elucidate how BCAS2 is regulated in these cells and observed that BCAS2 is preferentially regulated by the PI3K/AKT signaling pathway. BCAS2 is an AF-1 coactivator of ERα whose overexpression promotes carcinogenic processes, suggesting an important role in the development of estrogen-receptor positive breast cancer.

Although symmetry has been discussed in terms of a major law of perceptual organization since the early conceptual efforts of the Gestalt school (Wertheimer, Metzger, Koffka and others), the first quantitative measurements testing for effects of symmetry on processes of Gestalt formation have seen the day only recently. In this study, a psychophysical rating study and a “foreground„-“background„ choice response time experiment were run with human observers to test for effects of bilateral symmetry on the perceived strength of figure-ground in triangular Kanizsa configurations. Displays with and without bilateral symmetry, identical physically-specified-to-total contour ratio, and constant local contrast intensity within and across conditions, but variable local contrast polarity and variable orientation in the plane, were presented in a random order to human observers. Configurations with bilateral symmetry produced significantly stronger figure-ground percepts reflected by greater subjective magnitudes and consistently higher percentages of “foreground„ judgments accompanied by significantly shorter response times. These effects of symmetry depend neither on the orientation of the axis of symmetry, nor on the contrast polarity of the physical inducers. It is concluded that bilateral symmetry, irrespective of orientation, significantly contributes to the, largely sign-invariant, visual mechanisms of figure-ground segregation that determine the salience of figure-ground in perceptually ambiguous configurations.

Simulator training for image-guided surgical interventions would benefit from intelligent systems that detect the evolution of task performance, and take control of individual speed⁻precision strategies by providing effective automatic performance feedback. At the earliest training stages, novices frequently focus on getting faster at the task. This may, as shown here, compromise the evolution of their precision scores, sometimes irreparably, if it is not controlled for as early as possible. Artificial intelligence could help make sure that a trainee reaches her/his optimal individual speed⁻accuracy trade-off by monitoring individual performance criteria, detecting critical trends at any given moment in time, and alerting the trainee as early as necessary when to slow down and focus on precision, or when to focus on getting faster. It is suggested that, for effective benchmarking, individual training statistics of novices are compared with the statistics of an expert surgeon. The speed⁻accuracy functions of novices trained in a large number of experimental sessions reveal differences in individual speed⁻precision strategies, and clarify why such strategies should be automatically detected and controlled for before further training on specific surgical task models, or clinical models, may be envisaged. How expert benchmark statistics may be exploited for automatic performance control is explained.