AI platforms offering first-line mental health support have proliferated in Nigeria, where health services are sparse and underfunded. AI platforms offering first-line mental health support have proliferated in Nigeria, where health services are sparse and underfunded. 'At 2am, it feels like someone's there': why Nigerians are choosing chatbots to give them advice and therapy O n a quiet evening in her Abuja hotel, Joy Adeboye, 23, sits on her bed clutching her phone, her mind racing and chest tightening. On her screen is yet another abusive message from her stalker - a man she had met nine months earlier at her church. He had asked Adeboye out; when she declined, he began sending her intimidating, insulting and blackmailing messages on social media, as well as spreading false information about her online.

Why personalized gene editing, genetic resurrections and embryo scoring made our list. Earlier this week, published its annual list of Ten Breakthrough Technologies. As always, it features technologies that made the news last year, and which--for better or worse--stand to make waves in the coming years. They're the technologies you should really be paying attention to. This year's list includes tech that's set to transform the energy industry, artificial intelligence, space travel --and of course biotech and health. Our breakthrough biotechnologies for 2026 involve editing a baby's genes and, separately, resurrecting genes from ancient species.

Plus: This company is developing gene therapies for muscle growth, erectile dysfunction, and "radical longevity" For decades, lithium-ion batteries have powered our phones, laptops, and electric vehicles. But lithium's limited supply and volatile price have led the industry to seek more resilient alternatives. They work much like lithium-ion ones: they store and release energy by shuttling ions between two electrodes. But unlike lithium, a somewhat rare element that is currently mined in only a handful of countries, sodium is cheap and found everywhere. Read why it's poised to become more important to our energy future. Sodium-ion batteries are one of 10 Breakthrough Technologies this year.

Four new books grapple with a global mental-health crisis and the dawn of algorithmic therapy. A technician adjusts the wiring inside the Mark I Perceptron. This early AI system was designed not by a mathematician but by a psychologist. More than a billion people worldwide suffer from a mental-health condition, according to the World Health Organization. The prevalence of anxiety and depression is growing in many demographics, particularly young people, and suicide is claiming hundreds of thousands of lives globally each year. Given the clear demand for accessible and affordable mental-health services, it's no wonder that people have looked to artificial intelligence for possible relief.

Combination therapy refers to the use of multiple treatments -- such as surgery, medication, and behavioral therapy - to cure a single disease, and has become a cornerstone for treating various conditions including cancer, HIV, and depression. All possible combinations of treatments lead to a collection of treatment regimens (i.e., policies) with mixed scopes, or what physicians could observe and which actions they should take depending on the context. In this paper, we investigate the online reinforcement learning setting for optimizing the policy space with mixed scopes. In particular, we develop novel online algorithms that achieve sublinear regret compared to an optimal agent deployed in the environment. The regret bound has a dependency on the maximal cardinality of the induced state-action space associated with mixed scopes. We further introduce a canonical representation for an arbitrary subset of interventional distributions given a causal diagram, which leads to a non-trivial, minimal representation of the model parameters.

Technology "Why Did You Do It?" A radical new use of deepfake technology is allowing survivors of abuse to confront their perpetrators. Marina vd Roest hadn't faced the man who abused her in decades when she first sat down in front of the laptop. Confronted with his realistic, blinking, speaking face, she felt "scared like a little child again." "Sometimes I had to close the laptop and get my breath back before opening it and continuing with the conversation," she says. Vd Roest is one of the first people to have tried out a radical new form of therapy that involves putting survivors face-to-face with A.I.-generated deepfakes of their attackers as a means of healing unresolved trauma.

In the past 20 years, mice with glowing cables sprouting from their heads have become a staple of neuroscience. They reflect the rise of optogenetics, in which neurons are engineered to contain light-sensitive proteins called opsins, allowing pulses of light to turn them on or off. The method has powered thousands of basic experiments into the brain circuits that drive behavior and underlie disease. As this research tool matured, hopes arose for using it as a treatment, too. Compared with the electrical or magnetic brain stimulation approaches already in use, optogenetics offers a way to more precisely target and manipulate the exact cell types underlying brain disorders.

Neurorehabilitation conventionally relies on the interaction between a patient and a physical therapist. Robotic systems can improve and enrich the physical feedback provided to patients after neurological injury, but they under-utilize the adaptability and clinical expertise of trained therapists. In this position paper, we advocate for a novel approach that integrates the therapist's clinical expertise and nuanced decision-making with the strength, accuracy, and repeatability of robotics: Robot-mediated physical Human-Human Interaction. This framework, which enables two individuals to physically interact through robotic devices, has been studied across diverse research groups and has recently emerged as a promising link between conventional manual therapy and rehabilitation robotics, harmonizing the strengths of both approaches. This paper presents the rationale of a multidisciplinary team-including engineers, doctors, and physical therapists-for conducting research that utilizes: a unified taxonomy to describe robot-mediated rehabilitation, a framework of interaction based on social psychology, and a technological approach that makes robotic systems seamless facilitators of natural human-human interaction.

Wellness brand Therabody's Theragun Black Friday deals are live until December 6. The company is mostly known for its percussive massage guns--which are on sale, too--but don't overlook the rest of Therabody's inventory. From skincare facial devices and compression boots to sleep aids and hot and cold wearables, there is a gadget for every concern. Most of these products are HSA/FSA eligible, too. We've rounded up the best Therabody and Theragun Black Friday deals worth your attention (and money).

Clinical antimicrobial therapy requires the dynamic integration of pathogen profiles, host factors, pharmacological properties of antimicrobials, and the severity of infection.This complexity imposes fundamental limitations on the applicability of Large Language Models (LLMs) in high-stakes clinical decision-making including knowledge gaps, data privacy concerns, high deployment costs, and limited reasoning capabilities. This is the first author footnote. A hierarchical evaluation employing diverse teacher-model proxies reduces assessment costs, while modular interface design facilitates seamless system updates. Experimental results demonstrate that KRAL significantly outperforms traditional Retrieval-Augmented Generation (RAG) and Supervised Fine-Tuning (SFT) methods. It improves knowledge question-answering capability (Accuracy@1 on the external open-source benchmark MEDQA increased by 1.8% vs. SFT and 3.6% vs. RAG) and reasoning capability (Pass@1 on the external benchmark PUMCH Antimicrobial increased by 27% vs. SFT and 27.2% vs. RAG), achieved at 20% of SFT's long-term training costs. This establishes KRAL as an effective solution for enhancing local LLMs' clinical diagnostic capabilities, enabling low-cost, high-safety deployment in complex medical decision support. Introduction Antimicrobial therapy constitutes a cornerstone of modern clinical practice. The formulation of an effective regimen necessitates the integration of pathogen-specific factors, host characteristics, pharmacokinetic pharma-codynamic (PK/PD) properties of antimicrobials, and infection severity, all of which are dynamic and interrelated. This places significant cognitive load on clinicians, especially for non-infectious disease specialists or in situations where pathogens are unknown and time is limited, which may result in sub-optimal prescribing decisions, thereby increasing the likelihood of therapeutic failure, antimicrobial toxicity, and the emergence of multidrug-resistant (MDR) pathogens. Large language models (LLMs) have recently emerged as promising tools for enhancing clinical decision support systems (CDSS), owing to their advanced natural language understanding and generation capabilities. Nevertheless, the direct deployment of general-purpose LLMs in high-stakes clinical domains such as antimicrobial therapy is fraught with limitations, including: Knowledge bias: Medical content constitutes <0.3 % of the pre-training corpora[1] in mainstream LLMs (e.g., GPT-3), resulting in limited coverage of rare or emerging pathogens[2-4], outdated guideline adherence[5-9](Appendix A1), and suboptimal performance on atypical presentations. 2 Data privacy and compliance risks: The use of closed-source, cloud-based LLMs (e.g., GPT-4) for processing unencrypted protected health information (PHI) may violate HIPAA/GDPR-equivalent regulations, even under private deployment scenarios if online guideline updates are required[10-12].