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Invisible threads: How our environment quietly shapes disease

From the air we breathe to the food we eat, we are constantly exposed to thousands of chemicals—yet how these exposures affect our health has remained surprisingly difficult to understand. A new study led by researchers at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences and the Ludwig Boltzmann Institute for Network Medicine at the University of Vienna, published in Nature Communications, offers a unifying view: Diverse substances can disrupt the same biological systems and thereby contribute to disease risk in predictable ways.

Environmental pollution is estimated to contribute to around one in six deaths worldwide, but scientists have long struggled to connect specific exposures to specific diseases. One reason is the sheer complexity of the “exposome” —the totality of all environmental influences a person encounters over a lifetime. Traditionally, chemicals have been grouped by their structure or origin, but this says little about what they actually do inside the body. Two nearly identical molecules can have completely different effects, while entirely unrelated substances may trigger the same illness. This has made it difficult to move from observation to understanding.

A new study, led by Jörg Menche, CeMM adjunct PI and director of the Ludwig Boltzmann Institute for Network Medicine, and first authored by former Ph.D. student at CeMM and LBI NetMed (now a postdoc at Harvard Medical School) Salvo Danilo Lombardo, takes a different route: Instead of asking what chemicals look like, the researchers asked what they do. They compiled nearly 10,000 environmental exposures, ranging from pollutants and food components to medications, and mapped how each affects human genes. The result is a large-scale network that links exposures based on shared biological effects.

New “Bad Epoll” Linux Kernel Flaw Lets Unprivileged Users Gain Root, Hits Android

A newly disclosed Linux kernel flaw called Bad Epoll (CVE-2026–46242) lets an ordinary user with no special access take full control of a machine as root. It affects Linux desktops, servers, and Android, and a fix is out.

Bad Epoll sits in the same small stretch of kernel code where Anthropic’s most powerful AI model, Mythos, recently found a different bug.

The AI caught one flaw and missed this one. A researcher, Jaeyoung Chung, found it and built a working attack.

NetNut proxy network disrupted, 2 million infected devices cut off

A joint operation involving Google has disrupted NetNut, a residential proxy network that gave access to millions of compromised Android devices, including smart TVs and streaming boxes.

Also known as Popa, the NetNut botnet allowed cybercriminals and espionage groups to hide behind legitimate home internet addresses when launching attacks.

According to the Google Threat Intelligence Group (GTIG), the residential proxy botnet is estimated to comprise at least two million compromised devices.

ARToken PhaaS exposes EvilTokens’ Microsoft 365 phishing toolkit

A new phishing-as-a-service (PhaaS) platform dubbed “ARToken” appears to operate as an affiliate of the EvilTokens phishing platform, giving researchers a glimpse into an extensive toolkit designed to compromise Microsoft 365.

Cisco Talos researchers discovered the platform while investigating phishing infrastructure used in an incident response engagement and identified a React-based management panel called “ARToken Panel” that exposed more than 80 API endpoints.

Reverse engineering the client-side JavaScript code revealed previously undocumented capabilities that extend well beyond what you would normally find in a phishing platform.

An artificial neuromorphic interface for auditory restoration

Hearing loss affects millions of people, requiring technology to repair their auditory pathway. A biohybrid interface is developed that combines a self-powered acoustic device and an artificial auditory neural circuit, enabling restoration of auditory function in a rabbit model of hearing impairment.

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