Based on the Ontology for General Medical Science, we propose definitions for biomarkers of various types of. These definitions provide not only a complete formal representation of what biomarkers are according to the Institute of Medicine (IOM), but also remove the ambiguities and inconsistencies encountered in the documentation provided by the IOM.

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use (...) of clinical biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions. (shrink)

Biomarkers are widely used not only as prognostic or diagnostic indicators, or as surrogate markers of disease in clinical trials, but also to formulate theories of pathogenesis. We identify two problems in the use of biomarkers in mechanistic studies. The first problem arises in the case of multifactorial diseases, where different combinations of multiple causes result in patient heterogeneity. The second problem arises when a pathogenic mediator is difficult to measure. This is the case of the oxidative stress (...) (OS) theory of disease, where the causal components are reactive oxygen species (ROS) that have very short half-lives. In this case, it is usual to measure the traces left by the reaction of ROS with biological molecules, rather than the ROS themselves. Borrowing from the philosophical theories of signs, we look at the different facets of biomarkers and discuss their different value and meaning in multifactorial diseases and system medicine to inform their use in patient stratification in personalized medicine. (shrink)

What makes a high-quality biomarker experiment? The success of personalized medicine hinges on the answer to this question. In this paper, I argue that judgment about the quality of biomarker experiments is mediated by the problem of theoretical underdetermination. That is, the network of biological and pathophysiological theories motivating a biomarker experiment is sufficiently complicated that it often frustrates valid interpretation of the experimental results. Drawing on a case-study in biomarker diagnostic development from neurooncology, I argue that this problem of (...) underdetermination can be overcome with greater coordination across the biomarker research trajectory. I then sketch an account for how coordination across a research trajectory can be evaluated. I ultimate conclude that what makes a high-quality biomarker experiment must be judged by the epistemic contribution it makes to this coordinated research effort. (shrink)

The environment can elicit biological responses such as oxidative stress (OS) and inflammation as a consequence of chemical, physical, or psychological changes. As population studies are essential for establishing these environment-organism interactions, biomarkers of OS or inflammation are critical in formulating mechanistic hypotheses. By using examples of stress induced by various mechanisms, we focus on the biomarkers that have been used to assess OS and inflammation in these conditions. We discuss the difference between biomarkers that are the (...) result of a chemical reaction (such as lipid peroxides or oxidized proteins that are a result of the reaction of molecules with reactive oxygen species) and those that represent the biological response to stress, such as the transcription factor NRF2 or inflammation and inflammatory cytokines. The high-throughput and holistic approaches to biomarker discovery used extensively in large-scale molecular epidemiological exposome are also discussed in the context of human exposure to environmental stressors. We propose to consider the role of biomarkers as signs and to distinguish between signs that are just indicators of biological processes and proxies that one can interact with and modify the disease process. (shrink)

To date researchers planning experiments have always lived by the mantra that 'using equal sample sizes gives the best results' and although unequal groups are also used in experimentation, it is not the preferred method of many and indeed actively discouraged in literature. However, during live study planning there are other considerations that we must take into account such as availability of study participants, statistical power and, indeed, the cost of the study. These can all make allocating equal sample sizes (...) difficult, and sometimes near impossible. This, some might say, means that the study would not adhere to rigorous statistical standard (Rosenbaum and Rubin, 1985). However, here we present evidence that, not only is this a false assumption, but that we may actually gain more power in the study by actually using unequal groups. Here, data from a Sepsis Biomarker study is used, in which the aim is to predict, by biomarker level and presence, whether the patient would go on to develop sepsis. It was found that larger control groups may give more power to studies looking for an effect in the mid range but not for large or small effects. This study shows merit in the hypothesis that more power can be achieved when a larger control group is used. Published by the Ministry of Defence at dstl - Reference DSTLTR92592 P2PP2R-2016-02-23T13:39:45. (shrink)

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward (...) for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction. (shrink)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...) it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)

Precision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates of N = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension (...) of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided. (shrink)

At present, psychiatric disorders are characterized descriptively, as the standard within the scientific community for communication and, to a certain extent, for diagnosis, is the DSM, now at its fifth edition. The main reasons for descriptivism are the aim of achieving reliability of diagnosis and improving communication in a situation of theoretical disagreement, and the Ignorance argument, which starts with acknowledgment of the relative failure of the project of finding biomarkers for most mental disorders. Descriptivism has also the advantage (...) of capturing the phenomenology of mental disorders, which appears to be essential for diagnosis, though not exhaustive of the nature of the disease. I argue that if we rely on the distinction between conceptions (procedures of identification) and concepts (reference-fixing representations), which was introduced in the philosophical debate on the nature of concepts, we may understand a limited but valid role for descriptive characterizations, and reply to common objections addressed by those who advocate a theoretically informed approach to nosology. (shrink)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an in- hibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N =96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding (...) constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior. (shrink)

This article analyzes emerging artificial intelligence (AI)-enhanced lie detection systems from ethical and human resource (HR) management perspectives. I show how these AI enhancements transform lie detection, followed with analyses as to how the changes can lead to moral problems. Specifically, I examine how these applications of AI introduce human rights issues of fairness, mental privacy, and bias and outline the implications of these changes for HR management. The changes that AI is making to lie detection are altering the roles (...) of human test administrators and human subjects, adding machine learning-based AI agents to the situation and establishing invasive data collection processes as well as introducing certain biases in results. I project that the potentials for pervasive and continuous lie detection initiatives (“truth machines”) are substantial, displacing human-centered efforts to establish trust and foster integrity in organizations. I argue that if it is possible for HR managers to do so, they should cease using technologically-based lie detection systems entirely and work to foster trust and accountability on a human scale. However, if these AI-enhanced technologies are put into place by organizations by law, agency mandate, or other compulsory measures, care should be taken that the impacts of the technologies on human rights and wellbeing are considered. The article explores how AI can displace the human agent in some aspects of lie detection and credibility assessment scenarios, expanding the prospects for inscrutable, “black box” processes and novel physiological constructs (such as “biomarkers of deceit”) that may increase the potential for such human rights concerns as fairness, mental privacy, and bias. Employee interactions with autonomous lie detection systems rather with than human beings who administer specific tests can reframe organizational processes and rules concerning the assessment of personal honesty and integrity. The dystopian projection of organizational life in which analyses and judgments of the honesty of one’s utterances are made automatically and in conjunction with one’s personal profile provides unsettling prospects for the autonomy of self-representation. (shrink)

The recent explosion in the discovery of exoplanets and our incipient ability to detect atmospheric biomarkers recommend reflection on the conceptual implications of discovering – or not discovering – extrasolar life. I contend that evidence for intelligent extraterrestrial life is evidence against the existence of God, because if there are intelligent extraterrestrials, there are likely to be evils in the universe even greater than those found on Earth. My reasoning is based on Richard Gott's Copernican Principle, which holds that (...) in the absence of information to the contrary, we should take ourselves to be typical observers. (shrink)

Abstract: At present, psychiatric disorders are characterized descriptively, as the standard within the scientific community for communication and, to a cer- tain extent, for diagnosis, is the DSM, now at its fifth edition. The main rea- sons for descriptivism are the aim of achieving reliability of diagnosis and improving communication in a situation of theoretical disagreement, and the Ignorance argument, which starts with acknowledgment of the relative fail- ure of the project of finding biomarkers for most mental disorders. Descrip- (...) tivism has also the advantage of capturing the phenomenology of mental dis- orders, which appears to be essential for diagnosis, though not exhaustive of the nature of the disease. I argue that if we rely on the distinction between conceptions (procedures of identification) and concepts (reference-fixing representations), which was introduced in the philosophical debate on the nature of concepts, we may understand a limited but valid role for descrip- tive characterizations, and reply to common objections addressed by those who advocate a theoretically informed approach to nosology. (shrink)

Background: Individuals with psychopathic traits demonstrate an attenuated emotional response to aversive stimuli. However, recent evidence suggests heterogeneity in emotional reactivity among individuals with psychopathic or callous-unemotional (CU) traits, the emotional detachment dimension of psychopathy. We hypothesize that primary variants of psychopathy will respond with blunted affect to negatively valenced stimuli, whereas individuals marked with histories of childhood trauma/maltreatment exposure, known as secondary variants, will display heightened emotional reactivity. To test this hypothesis, the present study examined fear-potentiated startle between psychopathy (...) variants while viewing aversive, pleasant, and neutral scenes. Method: 238 incarcerated adolescent (M age = 16.8, SD = 1.11 years) boys completed a picture-startle paradigm and self-report questionnaires assessing CU traits, antisocial-aggressive behavior, and maltreatment. Results: Latent profile analyses identified four classes; primary variants (high CU traits, high aggression, low maltreatment; n = 46), secondary variants (high CU traits, high aggression, high maltreatment; n = 42), and two nonpsychopathic groups differentiated on maltreatment experience (n = 148). Findings from an ANOVA comparing identified groups on startle amplitude difference scores (i.e., aversive-neutral) suggested a main effect for group, F(3,196)=8.91, p<.001, η2 = .12. Primary variants of juvenile psychopathy displayed reduced startle potentiation to aversive images (threat and victim scenes), whereas secondary variants distinguished by high levels of childhood maltreatment did not. Conclusions: Findings add to a rapidly growing body of literature supporting the possibility of multiple developmental pathways to psychopathy (i.e., equifinality), and extend it by finding support for divergent potential biomarkers between primary and secondary psychopathy variants. (shrink)

Objective: The use of neoadjuvant chemotherapy (NACT) in breast cancer is increasing. The management of locally advanced breast cancer differs due to the approach of the center to which the patient applied and the approach of the following physician. From this point of view, we aimed to evaluate the real life data of our region. -/- Methods: The study included 106 patients treated with neoadjuvant chemotherapy in the medical oncology clinic of two different university hospitals. Association between clinicopathological features and (...) pathological complete response (pCR) were analyzed. -/- Results: The pCR rate was higher in patients with negative hormone receptors and this difference was statistically significant (p:0.000). The rate of obtaining pCR increased as the NACT duration increased, and this increase was statistically significant. The mean NACT duration applied to the patients with pCR was 5.48 ± 0.22 months, and the mean NACT duration for those who could not obtain pCR was 5.01 ± 0.1 months (p:0.041). The recurrence rate of patients with pCR was 11.1%, while the recurrence rate of patients who could not obtain pCR was 31.6% (p:0.04). -/- Conclusions: Pathological response to chemotherapy is an important factor in determining prognosis. There appears to be a need for new biomarkers that allow the prediction of pCR and long-term outcomes. (shrink)

Objective: microRNAs (miRNAs) have important potential as biomarkers in the diagnosis and prognosis of ischemia/reperfusion (I/R) injury in coronary artery bypass grafting surgery (CABG). This study investigated the relationship between preoperative (preop) and postoperative (post-op) cardiac parameters and miRNA expressions in CABG. -/- Methods: We analyzed a total of 94 individuals (CABG, n= 46 and healthy control, n=48). Quantitative real-time polymerase chain reaction (qRT) was performed to determine plasma miRNA expressions (miR-21, miR-181a, miR-199a, miR-199b, and miR-320a-5p) in triplicates: before (...) surgery, 1 hour after surgery, and 24 hours after surgery. The target genes and pathways of miRNA were determined using bioinformatic analysis. The biomarker potentials of miRNAs were evaluated with receiver operating characteristic (ROC) curve analysis. -/- Results: All miRNAs were significantly downregulated (p < 0.05). Troponin I, LVEF, CPK, and CK-MB were found to be statistically significant for operation groups (p < 0.05). miRNA expressions and cardiac markers were associated with troponin I and/or CK-MB. In ROC analyses, miR-199a was a good diagnostic marker. CREBRF and ZNF704 genes may be a target for these miRNAs. -/- Conclusions: Downregulation of miR-199a has a regulatory role in ischemia/reperfusion. They may contribute to CABG pathology through these two genes involved in signaling cascades to turn on protein response and ion binding. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...) the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

Objective: Inflammation is one of several etiopathological mechanisms contributing to bipolar disorder. Neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) are relatively cheap hematological parameters recommended to measure the level of inflammation. In this study, the NLR, MLR, and PLR values of the same patients during manic and euthymic periods were compared to a healthy control group. -/- Methods: This retrospective study was conducted on inpatients with bipolar disorder manic episodes at the University Faculty of Medicine psychiatry clinic. (...) Ninety-nine patients with manic episodes of bipolar disorder and age and gender-matched 101 volunteers without prior psychiatric illness were included in the study. Neutrophil, lymphocyte, monocyte, and platelet counts during the disease period were recorded, and NLR, MLR, and PLR values were calculated from these values. Similar hematological parameters of the same patients in the euthymic period after discharge were compared. -/- Results: Patients with manic episodes were shown to have significantly higher neutrophil, platelet, NLR, MLR, and PLR levels than the control group (p<0.001). Monocyte count was significantly lower in manic episode patients compared to controls (p<0.001). Neutrophil and monocyte counts were significantly lower during the euthymic period compared to the control group, while NLR, MLR, and PLR levels were higher (p<0.001). -/- Conclusions: The fact that NLR, MLR, and PLR are higher in BD patients compared to the healthy control group in both manic and euthymic periods indicates that they can be used as trait biomarkers. (shrink)

Objective: to evaluate CANLPH score and systemic immune inflammation index (SII) in patients with symptomatic rheumatic mitral stenosis (MS) undergoing percutaneous mitral balloon valvuloplasty (PMBV). -/- Methods: 62 patients who underwent PMBV in our clinic between 2018 and 2021 were included retrospectively. The patients were divided into 2 groups according to echo score. The CANLPH score was calculated from the cut-off values of C-reactive protein to albumin ratio (CAR), neutrophil to lymphocyte ratio (NLR) and platelet to hemoglobin ratio (PHR), determined (...) with the Youden index and SII by the formula platelet x neutrophil/lymphocyte. P <0.05 was considered statistically significant. -/- Results: The mean age of the patients was 44.5±10.4 years (40 female, 64.5%). The mean values of SII and CANLPH scores were higher in the Echo score >8 group (p <0.001, both). The mean mitral gradient before and after PMBV was 12.6±5.7mm Hg and 5.0±2.4 mm Hg, and the mean valve area was 1.12±0.27 cm2 and 1.85±0.29 cm2. A statistically significant and negative correlation was observed between the gradient decrease after the procedure and the CANLPH score and SII (r=-0.426, p=0.001 and r=-0.418, p=0.001, respectively). In receiver operating characteristic (ROC) curve analysis, it was concluded that the ability of CANPLH score to predict the higher Echo scores was noninferior to SII with an area under curve (AUC:0.820 (0.701-0.906) and AUC:0.786 (0.664-0.880), z statistics 0.576 and p=0.564. -/- Conclusion: SII and CANLPH scores are correlated with Echo score. A significant negative relationship was found with both biomarkers and gradient decrease after the PMBV. (shrink)

Neuroscientists have in recent years turned to building models that aim to generate predictions rather than explanations. This “predictive turn” has swept across domains including law, marketing, and neuropsychiatry. Yet the norms of prediction remain undertheorized relative to those of explanation. I examine two styles of predictive modeling and show how they exemplify the normative dynamics at work in prediction. I propose an account of how predictive models, conceived of as technological devices for aiding decision-making, can come to be adequate (...) for purposes that are defined by both their guiding research questions and their larger social context of application. (shrink)

In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently (...) living people reach longevity escape velocity and survive until more advanced AI appears. When AI comes close to human level, the main contribution to life extension will come from AI integration with humans through brain-computer interfaces, integrated AI assistants capable of autonomously diagnosing and treating health issues, and cyber systems embedded into human bodies. Lastly, we speculate about the more remote future, when AI reaches the level of superintelligence and such life-extension methods as uploading human minds and creating nanotechnological bodies may become possible, thus lowering the probability of human death close to zero. We suggest that medical AI based superintelligence could be safer than, say, military AI, as it may help humans to evolve into part of the future superintelligence via brain augmentation, uploading, and a network of self-improving humans. Medical AI’s value system is focused on human benefit. (shrink)

The observation that a crisis of confidence regarding Psychiatry exists is a notion shared even among psychiatrists themselves. Psychiatry has a checkered history and its alliance with the pharmaceutical industry, aka Big-Pharma, continues to reinforce a need for healthy skepticism. Why? Mainly, an over-reliance on the questionable expertise and authority afforded psychiatry as the specialists of mental health. I contend that the authority of psychiatry is misplaced and too often harmful. Since the criteria required to justify and satisfy psychiatric expertise (...) is not fully established as can be substantiated by compelling reasons to rethink its authority as a reliable profession in its current form. Psychiatric expertise is not particularly scientific and this is especially dangerous in a sector that prescribes mind-altering drugs. There are a number of identified criteria that would otherwise substantiate psychiatric expertise and whilst partially existent, are nonetheless deficient. These major yet deficient aspects of psychiatric practice concern diagnostic problems – reliability and verification of diagnoses and accurate testable validity of diagnoses - mainly due to an absence of identifiable underlying biomarkers ordinarily related to disease or biological conditions. Psychiatrists often fail to distinguish between reactive-depression (reaction to external event or circumstance) and endogenous-depression (biological) resulting, in part, from incorrectly distinguishing between conditions constitutive of ‘trait’ (endogenous) and of those of ‘state’ (e.g. reactive depression; adverse effects from medication, etc.). (shrink)

In this article, we consider music and noise in terms of vibrational and transferable energy as well as from the evolutionary significance of the hearing system of Homo sapiens. Music and sound impinge upon our body and our mind and we can react to both either positively or negatively. Much depends, in this regard, on the frequency spectrum and the level of the sound stimuli, which may sometimes make it possible to set music apart from noise. There are, however, two (...) levels of description: the physical-acoustic description of the sound and the subjective-psychological reactions by the listeners. Starting from a vibrational approach to sound and music, we first investigate how sound may activate the sense of touch and the vestibular system of the inner ear besides the sense of hearing. We then touch upon distinct issues such as the relation between low-frequency sounds and annoyance, the harmful effect of loud sound and noise, the direct effects of overstimulation with sound, the indirect effects of unwanted sounds as related to auditory neurology, and the widespread phenomenon of liking loud sound and music, both from the point of view of behavioral and psychological aspects. (shrink)

Importance: Patients with remitted major depressive disorder (MDD) were previously found to display abnormal functional magnetic resonance imaging connectivity (fMRI) between the right superior anterior temporal lobe (RSATL) and the subgenual cingulate cortex and adjacent septal region (SCSR) when experiencing self-blaming emotions relative to emotions related to blaming others (eg, "indignation or anger toward others"). This finding provided the first neural signature of biases toward overgeneralized self-blaming emotions (eg, "feeling guilty for everything"), known to have a key role in cognitive (...) vulnerability to MDD. It is unknown whether this neural signature predicts risk of recurrence, a crucial step in establishing its potential as a prognostic biomarker, which is urgently needed for stratification into pathophysiologically more homogeneous subgroups and for novel treatments. -/- Objective: To use fMRI in remitted MDD at baseline to test the hypothesis that RSATL-SCSR connectivity for self-blaming relative to other-blaming emotions predicts subsequent recurrence of depressive episodes. -/- Design, setting, and participants: A prospective cohort study from June 16, 2011, to October 10, 2014, in a clinical research facility completed by 75 psychotropic medication-free patients with remitted MDD and no relevant comorbidity. In total, 31 remained in stable remission, and 25 developed a recurring episode over the 14 months of clinical follow-up and were included in the primary analysis. Thirty-nine control participants with no personal or family history of MDD were recruited for further comparison. -/- Main outcomes and measures: Between-group difference (recurring vs stable MDD) in RSATL connectivity, with an a priori SCSR region of interest for self-blaming vs other-blaming emotions. -/- Results: We corroborated our hypothesis that during the experience of self-blaming vs other-blaming emotions, RSATL-SCSR connectivity predicted risk of subsequent recurrence. The recurring MDD group showed higher connectivity than the stable MDD group (familywise error-corrected P < .05 over the a priori SCSR region of interest) and the control group. In addition, the recurring MDD group also exhibited RSATL hyperconnectivity with the right ventral putamen and claustrum and the temporoparietal junction. Together, these regions predicted recurrence with 75% accuracy. -/- Conclusions and relevance: To our knowledge, this study is the first to provide a robust demonstration of an fMRI signature of recurrence risk in remitted MDD. Additional studies are needed for its further optimization and validation as a prognostic biomarker. (shrink)

Abstract: Background: Vitamin D insufficiency/deficiency prevalent in all age groups across the world is common in obesity and may play an important role in the risk factors of metabolic syndrome (MS). Objectives: This cross-sectional study is to evaluate the relationship between levels of adiponectin and circulating 25(OH)D, and its effect on metabolic biomarker among overweight/obese female students. Methods: Three hundred female students; with mean age 20.9 ± 3.2 years were attending the Aljouf University, Sakaka, Saudi Arabia. They were randomly selected (...) from university during the studying year 2015 – 2016. Anthropometric and biochemical indices were determined. Results: The study showed 19% of the female’s student were either overweight or obese (15% and 4%, respectively). The frequency of MS diagnosis among the students was 17%, with 13% and 4% had either three or four risk factors, respectively. Overweight/obese subjects had significantly worse anthropometric and biochemical characteristics, including waist/hip ratio, blood pressure (BP), fasting blood glucose (BG), insulin, insulin resistance (HOMA-IR), triglyceride levels (TG), low-density lipoprotein cholesterol levels (LDL-C), leptin, adiponectin, leptin/adiponectin ratio and high-density lipoprotein cholesterol levels (HDL-C) compared to normal weight. Of the subjects diagnosed with MS, 59% had mild and 8.6% had severe 25(OH)D deficiency. There was negative association between 25(OH)D and both FBG and HOMA-IR among young women obese/overweight. Conclusion: In our study, it suggested that low level of adiponectin was strongly correlated with low 25(OH)D levels. Also, the prevalence of MS tends to increase with high occurrence rate of low circulating 25(OH)D levels that is, known cause poor glycemic control and prediction of cardiovascular outcomes. (shrink)

The present investigation has been designed to study the effect of sub lethal concentrations of Nickel on the serum metabolites of Channa punctatus after exposure to 45 days. The present study shows that serum metabolites such as glucose and protein were significantly decreased while lipid was significantly increased. Thus, the result provides an overview of the manipulation of fish, Channa punctatus as a biomarker of heavy metals through alternation in serum biochemical parameters.

The proposed project is based on a Dietitian app. The proposed app lets us discover what should we eat based on our weight, height, age, sex, and physical activity. It calculates BMI and BMR and tells us how many calories should we ideally need to intake per day. The calories we should intake will be feed in and based on the RETE algorithm the amount of food intake for the day will be decided. The proposed application is for any type (...) of body person, it is also suited for any range of weight people. It will ideally inform how should we cut down the weight using target programs such as 1LB per week gain/loss. The given system will suggest a food list according to the meal that is if it’s breakfast lunch or dinner. It will accordingly organize heavy calorie food & light calorie food. The system will give more accurate results as it accepts the data entered by the user and processes it depending on some metrics already known to the application on the basis of which a diet plan is generated and ask the user if the user accepts the diet plan. If not accepted the system may also give an alternative diet plan. (shrink)