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Alzheimer’s disease (AD) is a complex neurodegenerative illness with genetic and environmental origins. Females experience faster cognitive decline and cerebral atrophy than males, while males have greater mortality rates. Using a new machine-learning method they developed called “Evolutionary Action Machine Learning (EAML),” researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital have discovered sex-specific genes and molecular pathways that contribute to the development and progression of this condition. The study was published in Nature Communications.

“We have developed a unique machine-learning software that uses an advanced computational predictive metric called the evolutionary action (EA) score as a feature to identify genetic factors that influence AD risk separately in males and females,” Dr. Olivier Lichtarge, MD, Ph.D., professor of biochemistry and molecular biology at Baylor College of Medicine, said. “This approach lets us exploit a massive amount of evolutionary data efficiently, so we can now probe with greater accuracy smaller cohorts and identify genes involved in sex-specific differences in AD.”

EAML is an ensemble computational approach that includes nine machine learning algorithms to analyze the functional impact of non-synonymous coding variants, defined as DNA mutations that affect the structure and function of the resulting protein, and estimates their deleterious effect on biological processes using the evolutionary action (EA) score.

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD) but its neural basis is poorly understood. Using structural magnetic resonance imaging (MRI), the present study provides the whole-brain comparison of both volume-and surface-based characteristics between groups of children with and without ASD and investigates the relationships between these characteristics in language-related areas and the language abilities of children with ASD measured with standardized tools. A total of 36 school-aged children participated in the study: 18 children with ASD and 18 age-and sex-matched typically developing controls. The results revealed that multiple regions differed between groups of children in gray matter volume, gray matter thickness, gyrification, and cortical complexity (fractal dimension).

When people pay for sexual media, they’re seeking more than an anonymous image. AI cannot replicate the underlying desires that drive sex work.

As one of the OMICS in systems biology, metabolomics defines the metabolome and simultaneously quantifies numerous metabolites that are final or intermediate products and effectors of upstream biological processes. Metabolomics provides accurate information that helps determine the physiological steady state and biochemical changes during the aging process. To date, reference values of metabolites across the adult lifespan, especially among ethnicity groups, are lacking. The “normal” reference values according to age, sex, and race allow the characterization of whether an individual or a group deviates metabolically from normal aging, encompass a fundamental element in any study aimed at understanding mechanisms at the interface between aging and diseases.

Chronic anxiety is prevalent and associated with an increased risk of cardiovascular disease. Prior studies that have reported a relationship between muscle sympathetic nerve activity (MSNA) and anxiety have focused on participants with anxiety disorders and/or metabolic syndrome. The present study leverages a large cohort of healthy adults devoid of cardiometabolic disorders to examine the hypothesis that trait anxiety severity is positively associated with resting MSNA and blood pressure. Resting blood pressure (BP) (sphygmomanometer and finger plethysmography), MSNA (microneurography), and heart rate (HR; electrocardiogram) were collected in 88 healthy participants (52 males, 36 females, 25 ± 1 yr, 25 ± 1 kg/m²). Multiple linear regression was performed to assess the independent relationship between trait anxiety, MSNA, resting BP, and HR while controlling for age and sex. Trait anxiety was significantly correlated with systolic arterial pressure (SAP; r = 0.251, P = 0.018), diastolic arterial pressure (DAP; r = 0.291, P = 0.006), mean arterial pressure (MAP; r = 0.328, P = 0.002), MSNA burst frequency (BF; r = 0.237, P = 0.026), and MSNA burst incidence (BI; r = 0.225, P = 0.035). When controlling for the effects of age and sex, trait anxiety was independently associated with SAP (β = 0.206, P = 0.028), DAP (β = 0.317, P = 0.002), MAP (β = 0.325, P = 0.001), MSNA BF (β = 0.227, P = 0.030), and MSNA BI (β = 0.214, P = 0.038). Trait anxiety is associated with increased blood pressure and MSNA, demonstrating an important relationship between anxiety and autonomic blood pressure regulation.

NEW & NOTEWORTHY Anxiety is associated with development of cardiovascular disease. Although the sympathetic nervous system is a likely mediator of this relationship, populations with chronic anxiety have shown little, if any, alteration in resting levels of directly recorded muscle sympathetic nerve activity (MSNA). The present study is the first to reveal an independent relationship between trait anxiety, resting blood pressure, and MSNA in a large cohort of healthy males and females devoid of cardiometabolic comorbidities.

Listen to this article’s corresponding podcast at https://ajpheart.podbean.com/e/anxiety-and-muscle-sympathetic-nerve-activity/.

Functional movement/conversion disorder (FMD), part of the spectrum of Functional Neurological Disorder (FND), is a neuropsychiatric condition marked by a range of neurological symptoms, including tremors, muscular spasms and cognitive difficulties. Despite being the second-most common cause of referrals to neurology outpatient clinics after headache, scientists have struggled to pin down the disorder’s root cause. Female sex and a history of childhood trauma are factors associated with higher risk of developing FMD, but it’s been unclear why.

A new study from investigators of the Brigham and Women’s Hospital, in collaboration with researchers at the National Institute of Neurological Disorders and Stroke, demonstrated that FMD is characterized by epigenetic changes, and that women and childhood abuse survivors with FMD have different epigenetic profiles linked to this condition. Their study, which examined the genomes of over 100 individuals and was recently published in Progress in Neuro-Psychopharmacology and Biological Psychiatry, is the first to demonstrate the occurrence of epigenetic changes in FMD.

“This study finally takes FMD out of a cloud of confusion and provides a neuroscientifically grounded explanation for why childhood trauma and female sex are associated with this disorder,” said lead author Primavera A. Spagnolo, MD, Ph.D., scientific director of the Mary Horrigan Connors Center for Women’s Health and Gender Biology and assistant professor of psychiatry at HMS.

I propose to consider the question, ‘Can machines think?’ This should begin with definitions of the meaning of the terms ‘machine’ and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.

The new form of the problem can be described in terms of a game which we call the ‘imitation game’. It is played with three people, a man (A), a woman (B), and an interrogator © who may be of either sex. The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either ‘X is A and Y is B’ or ‘X is B and Y is A’. The interrogator is allowed to put questions to A and B thus:

C: Will X please tell me the length of his or her hair? Now suppose X is actually A, then A must answer. It is A’s object in the game to try and cause C to make the wrong identification. His answer might therefore be.

Female robots are a technological marvel, and many of us could not even tell the difference between a real woman and a female robot. Have you seen female robots such as Harmony and Erica? You cannot spot a distinction to tell that they are robots. But are they created just to satisfy the needs of men?

Have you ever thought of a civilization where human robots rule? Such a situation is not very far away if the current AI trends continue. Experts are expecting such a dramatic change within the mid-2030s. Today we will discuss the scary situation when robots act smarter than humans. An apt movie showing this situation is the 2014 award-winning science fiction movie Ex Machina where the robots become more competent and, in the end, dangerous.

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This video gets into two significant reasons why women dread the rise of sexbots. Sex robots are a mystique and a new innovation that will revolutionize how we consider sexual dynamics. Due to today’s gender war and rise of sexless men AI technologies are now hitting the market with a boom. While still overpriced an uncommon here in the U.S the artificial intelligence technogies are sure to make your experience more lifelike.

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