Shilpa Commissions Integrated ADC Drug Substance GMP Manufacturing Facility

India-based Shilpa Biologicals commissioned an antibody–drug conjugate (ADC) GMP manufacturing facility, purpose-built and designed to meet global regulatory approval standards including U.S. FDA, EMA, and other major health authority requirements. The facility is fully operational, with GMP qualification protocols now underway.

According to Sridevi Khambhampaty, CEO, Shilpa Biologicals, “The manufacturing of highly potent compounds has been a core pillar of Shilpa’s identity, and this ADC drug substance facility adds a new sophisticated dimension to the capabilities of the Shilpa group. We now offer global biotech and pharma partners a uniquely integrated ADC facility built with the knowledge of our existing high potency manufacturing excellence.”

“India has the scientific talent and now, with this facility, the infrastructure to be a serious and trusted partner in global ADC drug substance manufacturing,” said Vishnukant Bhutada, managing director, Shilpa Medicare. “We are ready to partner with the world’s leading oncology innovators.”

The post Shilpa Commissions Integrated ADC Drug Substance GMP Manufacturing Facility appeared first on GEN – Genetic Engineering and Biotechnology News.

AI agents are not your “coworkers”

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool—one that your company nonetheless calls Alex, an “employee” with a title and defined responsibilities. How well do you think you would work with Alex?

If you’re anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a “coworker” and not a software tool would lead you to do a worse job. Wiles found that people caught 18% fewer errors when the work was said to have come from an agentic “AI employee” rather than a chatbot. It turns out that what’s in a name matters. A lot. 

This is an alarming glimpse of the future Silicon Valley is hurling us toward. Last year Nvidia’s CEO, Jensen Huang, talked about workplaces of “digital humans.” Since April, Microsoft, OpenAI, Anthropic, and Google have all released new tools oriented toward managing teams of AI agents, many of which are explicitly advertised as digital colleagues with the flexibility and cognitive power of actual humans. And nearly a third of the 1,261 managers who participated in Wiles’s study said their companies already frame AI agents as employees (23% even list them on org charts).

The technical progress of agentic AI is not all hot air, of course. Agents, which can effectively be thought of as AI tools programmed to work in a loop until they achieve a goal, have become measurably better at more complicated tasks. But it’s a huge leap to refer to these tools as coworkers or employees, and doing so will set unrealistic expectations for what AI can do while leaving the human employees supposedly responsible for them worse off.

That’s partially because, Wiles’s research suggests, it inverts our sense of who’s in charge. When an AI tool was framed as an employee, participants in the study saw themselves as less responsible for its output. They were also 44% more likely to escalate its questionable work to a manager for further review rather than trusting their own corrections (thus negating the time-saving purpose of using the AI agent in the first place). 

That matters far beyond office culture: As AI agents are embedded into health care, warfare, education, and government, there’s a growing risk they’ll become a convenient place to dump blame for failures that are instead the product of bad human decisions, incentives, and oversight (recall how the bomb strike on a girls’ school in Iran was popularly blamed on Claude, when all signs point to a cascade of human errors).

“AI agents right now are being marketed as things that can replace humans, and I think that’s just a losing proposition,” says Daron Acemoglu, an economist at MIT who won the Nobel Prize in 2024 and studies AI’s impact on the economy. “They should instead be optimized so that they can improve human capabilities, which is not what they have [been] at the moment.”

What could that look like? Consider a new effort at Stanford, where researchers presented 1,500 workers in 104 jobs with information about what tasks AI could potentially do in their work and then asked what would actually be most helpful and productive. Workers did want automation in certain areas: Law clerks thought AI could help ensure that adequate progress was being made across cases, for example. But often the tasks that tech experts deemed most suitable for AI—like verifying customer credit ratings for sales reps—were what the actual workers said they definitely did not want or need an agent to do. 

Which brings us back to Alex. Calling Alex an employee is easy—and convenient, especially when something goes wrong—but it’s a branding exercise. It doesn’t make the tool more fit for the job, and as Wiles’s research shows, it makes the humans around it worse at theirs. And recall that they are the ones with the agency that AI is trying to replicate. They deserve better than Alex. 

APOE4-Linked Alzheimer’s Risk Lower Than Estimated in Japanese People

Research led by Niigata University suggests that the Alzheimer’s disease risk associated with carriage of the APOE4 gene variant is not as high in Japanese populations as earlier studies reported.

A study published in 1997 suggested that Japanese people who carried two APOE4 alleles had a more than 30-fold increased risk for developing Alzheimer’s disease compared with people with two copies of the more common APOE3 allele.

Writing in the journal Molecular Neurodegeneration, co-lead author Takeshi Ikeuchi, MD, PhD, a professor at Niigata University, and colleagues challenge this earlier statistic. Results from a new meta-analysis carried out by Ikeuchi and team suggest that Japanese APOE4 homozygotes are actually at approximately 12-15-fold increased risk of developing Alzheimer’s compared to those carrying two copies of APOE3.

APOE (apolipoprotein E) is a protein that transports lipids in the blood and brain and helps with neuronal repair after injury. The E4 variant increases Alzheimer’s risk because it alters the way lipids are processed and is associated with greater amyloid‑beta and tau accumulation, more neuroinflammation, and earlier onset of disease symptoms compared with other variants.

Depending on the population, the most common APOE gene variant is E3, which has an average global frequency of around 80%, followed by E4 at around 13% and then E2 at around 7%. While E4 is known to increase the risk for Alzheimer’s disease, E2 is protective in those who carry it with one copy linked to an approximate halving of Alzheimer’s risk and two copies can reduce risks by as much as 85% compared with having two copies of E3.

In European populations, about whom the most genetic information is available, carriage of two copies of the APOE4 allele is linked to an approximate 10-15-fold increase in Alzheimer’s risk. However, this is not the case in all populations. East Asian populations were previously thought to be at higher risk, linked to the earlier Japanese study and also higher estimates in Korean populations. But African or African American populations are thought to have a lower risk linked to being an APOE4 homozygote with an estimated 5-7 fold higher risk than a APOE3 homozygote.

For the current meta-analysis, Ikeuchi and colleagues included 21 Japanese case–control studies that spanned from the early 1990s to the 2010s and reported APOE genotypes in Alzheimer’s patients and controls.

They found that being an APOE4 homozygote substantially increased Alzheimer’s risk in Japanese people, but less than previously thought. Pooled risk increases for E4/E4 vs E3/E3 were 15.5 for early‑onset, 12.5 for late‑onset, and 13.5 for all Alzheimer’s disease, indicating about a 12–15‑fold risk increase for people carrying two copies of APOE4 overall.

Earlier meta-analyses had reported risk increases of 21.8–33.1, so this study revises the Japanese E4 homozygote effect downward to a figure similar to that seen in European populations.

“Accurate risk estimates are essential for both research and clinical practice,” said Ikeuchi in a press statement. “As the field moves toward earlier diagnosis and prevention of Alzheimer’s disease, reliable genetic risk information will become increasingly important.”

The post <i>APOE4</i>-Linked Alzheimer’s Risk Lower Than Estimated in Japanese People appeared first on Inside Precision Medicine.

Brain Messenger Protein May Help Tau Spread in Alzheimer’s Disease

A protein best known for helping neurons communicate may also help Alzheimer’s disease pathology move through the brain, according to new research from University of Utah Health.

The study, published in Cell, identifies the neuronal protein Arc as a key factor that helps toxic tau move from diseased neurons into neighboring healthy cells. In mouse models, removing Arc sharply reduced the transfer of tau between brain cells, pointing to a potential new strategy for slowing disease progression rather than reversing damage that has already occurred.

“I’m excited by the fact that we’ve identified a new way of potentially stopping the progression of Alzheimer’s disease,” said Jason Shepherd, PhD, professor of neurobiology at University of Utah Health and senior author of the study.

A new route for tau spread

Alzheimer’s disease is marked by the accumulation of abnormal protein deposits, including amyloid plaques and tau tangles. While amyloid has historically dominated drug development, tau pathology is closely linked to neurodegeneration and cognitive decline. As tau spreads across connected brain regions, symptoms worsen, making the mechanisms of tau transmission a major focus for therapeutic research.

The new study centers on Arc, a protein involved in synaptic plasticity, memory formation, and communication between neurons. Arc can package itself into extracellular vesicles, small membrane-bound particles that move between cells and carry biological cargo.

The researchers found that tau can use this system to its advantage. In Alzheimer’s mouse models, Arc helped package tau into extracellular vesicles, allowing tau to move from one neuron to another. Once taken up by recipient neurons, tau seeds can corrupt normal tau and trigger new aggregation.

By comparing Alzheimer’s model mice with and without Arc, the team showed that Arc was required for efficient tau release in neuronal extracellular vesicles and for tau transmission between cells.

The ‘glue monster’ problem

Tau is normally present in neurons and helps support microtubules, structures that act like internal transport tracks. In Alzheimer’s disease and related tauopathies, tau becomes abnormally modified, misfolds, and forms aggregates that interfere with neuronal function.

Mitali Tyagi, PhD, first author of the study and now a postdoctoral research associate at Washington University in St. Louis, compared tau tangles to “glue monsters.”

“They glue together and block transportation within the neuron,” Tyagi said. “But they can break down into smaller glue monsters, called tau seeds, which can then get transferred to a new neuron. And once this tau seed comes into contact with healthy tau, it is able to corrupt it. So, the pathology starts all over again in a healthy neuron.”

The researchers found extracellular vesicles containing both Arc and tau in the brains of Alzheimer’s model mice. These vesicles could seed tau aggregation in cell-based assays. But when Arc was absent, the vesicles contained far less tau and had greatly reduced seeding activity.

“When we removed Arc, we saw that the transfer of tau was severely, severely reduced,” Tyagi said. “It was almost gone.”

A double role for Arc

The findings are not as simple as suggesting Arc should be eliminated entirely. Arc appears to play a double-edged role in Alzheimer’s biology.

On one hand, Arc helps neurons export tau, which may reduce toxic buildup inside the original diseased cell. On the other hand, that same export process allows tau to reach and damage neighboring neurons.

“When Arc is absent, tau becomes trapped inside neurons and accumulates to toxic levels. When Arc is present, tau can be released in extracellular vesicles. While this helps reduce tau buildup within the original neuron, the released tau can be taken up by neighboring healthy neurons, promoting the spread of pathology,” Tyagi said.

In mice lacking Arc, tau accumulated inside neurons and was associated with early signs of cell toxicity. Yet tau transfer between cells was markedly reduced. This suggests that simply blocking tau release may not be the best therapeutic approach, because it could worsen toxicity in neurons already burdened by tau.

Instead, the researchers suggest that a more precise strategy may be to intercept tau-containing vesicles after they leave sick neurons but before they enter healthy ones.

Human brain data support the mechanism

Although much of the work was done in mice and cell models, the team also examined human postmortem brain tissue. They found that human brain-derived extracellular vesicles contained both Arc and phosphorylated tau, a disease-associated form of the protein.

The study also reported a positive correlation between Arc levels and phosphorylated tau levels in extracellular vesicles isolated from human brain tissue, supporting the idea that Arc-mediated vesicle biology may be relevant to human disease.

However, the authors caution that the work is still early. The strongest causal evidence comes from mouse models, and more research is needed to determine whether the same mechanism drives tau spread in people with Alzheimer’s disease.

“Most of the work we’ve been doing is in mice, not in humans,” Shepherd said. “We have some clues that whatever is happening in these mice could also be happening in humans, but we don’t know that yet. And we’re far away from saying that we’re developing a treatment for anything. But it could open new avenues to get to that point.”

Toward therapies that slow progression

The findings arrive as Alzheimer’s treatment is beginning to shift from symptom management toward disease modification. Anti-amyloid therapies have shown that changing disease biology is possible, but there remains a major need for treatments that slow tau-driven neurodegeneration and preserve cognition for longer.

Targeting tau spread could be one way to do that. A therapy aimed at tau-containing extracellular vesicles would not be expected to restore neurons already lost to disease. But it could potentially slow the movement of pathology through the brain, especially in early disease stages.

“If we could target these particular EVs, that would be a really useful therapy strategy,” Shepherd said. “For someone with early-onset Alzheimer’s or dementia, if we could stop the spread, then we could prevent further damage and cognitive decline.”

The study positions Arc not only as a messenger of normal brain communication, but also as a possible vehicle for pathological tau spread. The next challenge will be determining whether that vehicle can be safely intercepted without disrupting Arc’s essential roles in memory and synaptic function.

The post Brain Messenger Protein May Help Tau Spread in Alzheimer’s Disease appeared first on Inside Precision Medicine.

HeartMap Atlas Offers New Single-Cell View of Human Heart Disease

Cardiovascular disease is often managed through broad clinical categories: heart failure, cardiomyopathy, ischemic injury, arrhythmia risk. These categories are essential for diagnosis and treatment, but they do not fully explain why patients with similar clinical presentations can progress differently or respond unevenly to therapy.

A new single-nucleus atlas of the adult human heart aims to bring that biology into sharper focus. In a study published in Nature Cardiovascular Research, researchers from the Broad Institute of MIT and Harvard and Mass General Brigham developed HeartMap, an integrated atlas spanning more than 2.4 million cardiac nuclei from 209 individuals.

The resource brings together data from nine studies and includes eight anatomical regions and seven healthy or disease states. Its value lies not only in scale, but in its attempt to make cardiac single-cell data more comparable across studies.

Why cardiology needs cellular resolution

Precision medicine depends on identifying the biological mechanisms that matter for a specific patient or disease subtype. In oncology, this has increasingly meant matching molecular alterations to targeted therapies. Cardiology has made important progress with genetics, imaging, biomarkers, and risk stratification, but many therapeutic decisions still operate at a relatively high level of disease classification.

Heart disease is not driven by cardiomyocytes alone. Fibroblasts, endothelial cells, immune cells, vascular smooth muscle cells, pericytes, and other populations all contribute to remodeling, inflammation, fibrosis, and tissue dysfunction. A patient’s clinical phenotype may therefore reflect different combinations of cellular programs.

HeartMap was designed to help researchers interrogate those programs. The authors write that differentiating transcriptional signatures between cardiovascular disease groups using HeartMap “may aid in precision medicine approaches” by informing biomarker and therapeutic target discovery.

Separating robust disease signals from dataset noise

Single-cell and single-nucleus sequencing have already revealed important differences between healthy and diseased cardiac tissue. However, individual studies vary in how samples are collected, processed, sequenced, and analyzed. Those differences can obscure whether a signal is truly disease-related or specific to a cohort or protocol.

To address this, the HeartMap team reprocessed and harmonized published datasets, using computational integration to reduce technical variation while preserving biological signal. The final atlas resolved 14 broad cardiac cell types and 52 clusters.

Across the atlas, diseased and non-failing hearts separated by gene expression patterns. Disease-versus-control comparisons produced more differentially expressed genes than comparisons between disease states, suggesting that different cardiovascular conditions share broad remodeling programs while retaining more specific molecular features.

That distinction is important for translation. Shared injury programs may help explain common features of heart failure progression, while disease-specific or cell-state-specific programs may point to more selective therapeutic opportunities.

Fibroblasts show why cell state matters

One of the most clinically relevant findings involves fibroblasts. These cells are central to fibrosis and cardiac remodeling, but they are not a single uniform target. Some fibroblast activity may be part of necessary repair, while other states may contribute to scar formation, tissue stiffening, inflammation, and progressive dysfunction.

HeartMap identified 29 fibroblast subclusters, including activated fibroblast populations that differed across cardiomyopathies. Two activated populations, enriched for COL22A1 or TNC, were validated in human heart tissue using RNAscope.

This matters because anti-fibrotic drug development has long faced a precision problem: suppressing fibrosis broadly may not be the same as targeting the cell states that drive pathological remodeling. The authors note that identifying these activated fibroblast populations brings the field closer to understanding which subpopulations are “ideal candidates for therapeutic intervention.”

A research reference, not a clinical test

HeartMap is not a diagnostic assay and is not ready to guide care for individual patients. The atlas is built from previously generated datasets, so the researchers could not fully control sample collection, nuclei isolation, sequencing methods, or clinical metadata. The study also notes limited ancestral diversity, with samples largely from White or unclassified ethnic backgrounds. Most disease samples represented chronic or end-stage disease, limiting insight into early disease initiation.

Even so, the atlas points to an important direction for precision cardiology. Future patient datasets could be compared against resources such as HeartMap to determine which cellular programs are active in a given disease context. Over time, that could help connect clinical phenotypes with cell-specific biomarkers, drug targets, and mechanisms of progression.

Rather than treating the diseased heart as a single failing organ, HeartMap frames it as a dynamic cellular system. That shift may be essential if cardiovascular medicine is to move beyond broad disease labels toward therapies guided by the cells and pathways driving disease in individual patients.

The post HeartMap Atlas Offers New Single-Cell View of Human Heart Disease appeared first on Inside Precision Medicine.

Agent confidence on the technical frontier

Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial outcomes their businesses seek.

A prime opportunity for AI agents exists in the tech function, where IT infrastructure costs are projected to grow two to three times by 2030, even as budgets remain unchanged, according to McKinsey. And in the last 18 months, tech teams—the engineers, developers, architects, and other practitioners who are building, deploying, and continually improving their organizations’ infrastructure and applications—are clearly putting agents to work.

The ultimate promise of agents is not only to automate tasks but to manage and coordinate entire workflows, pursuing business goals in a way that allows humans and agents to work together. Given the risks involved in automated decision-making, teams cannot delegate the work that agents do without confidence that they are fully capable of performing the task and that it will do so in a safe, reliable, and secure manner.

Among technology experts, our research shows that teams are exceedingly confident about using agentic AI across a significant amount of AI, data, and cloud tasks.

Where agent readiness drops is largely due to a lack of business context being supplied to agentic systems. The more complex the task, the more reasoning capability an agent requires and the greater its need for business context. Such context-generation capabilities for agents are still at an early stage of development, especially in situations where enterprise data is difficult to wrangle and connect into the agent lifecycle at the speed and quality in which developers and executives need it. Human oversight is a key factor of success in deploying agentic AI.

Knowing that tech teams are in a pivotal position to lead this transformation, the experts we interviewed expect agent confidence to accelerate as experience with agents deepens and business environments mature. “As we design agents to operate within the same operational boundaries, identity systems, and governance models that teams already use, they start to behave more like the systems organizations already trust,” says Jeremy Winter, corporate vice president and chief product officer at Microsoft Azure Platform.

This report, based on a survey of 300 global technology experts, ranks 101 tasks across AI, data, and cloud workflows based on respondents’ confidence in agents acting on their behalf. It also examines how technology teams view the opportunities and challenges related to agentic AI, along with the potential for the technology to enhance their careers.

Key findings from the report include:

Confidence in agents is surging for measurable tasks and growing in areas of complex judgment. Technology experts overwhelmingly believe agents help with everyday work including streamlining processes, improving performance, and reducing repetitive tasks. Confidence is highest for processes like generating reports and boilerplate code, and there is clear opportunity where tasks involve multistep workflows and advanced reasoning to make decisions.

Data workflows are the breakthrough domain. Tech teams trust agents most where structure can provide a reliable foundation for decisions. This includes areas such as data quality monitoring, visualization anomaly detection, real-time data stream monitoring, and data profiling. This is where domain experts closest to the point of data generation can provide context to allow agents to act and deliver trusted outcomes.

Download the full report.

Read the Microsoft Cloud blog by Amanda Silver, corporate vice president of Microsoft 365 Core and Work IQ, which underscores the importance of keeping humans in the loop and how systems thinking advances careers. And for a deeper dive into data workflows as a breakthrough use case for agents, check out the Fabric blog to hear from Kim Manis, corporate vice president of Product for Microsoft Fabric.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

<![CDATA[Largest real-world analysis shows Deep TMS cuts PTSD and depression symptoms in comorbid patients; promising but not FDA-cleared yet.]]>

The Download: metric weaknesses and AI elephant warnings

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

The inevitable weakness of metrics

There are plenty of useful things a metric can reveal. There are even more that it can obscure or corrupt.

Like a lot of people bitten by the self-quantifying bug, I started gathering personal data to pursue a nebulous collection of goals and desires. I wanted to feel better physically and emotionally, get outside more, and bring order to the messiness and uncertainty of my daily existence.

But external metrics and data can never capture what’s truly important. Worse, they inevitably redefine your core sense of what’s important, whether you’re aware of the trap or not.

Dive into the dangers of quantifying our lives with metrics.

—Bryan Gardiner

This story is from the next edition of our magazine, which is all about engineering. Subscribe now to get a copy when it lands!

Elephant alert! AI warning systems aim to avoid deadly clashes

India is home to about 60% of the world’s wild Asian elephants, and around 80% of their habitat lies outside protected areas. That brings them into close contact with people, and clashes can turn lethal: there have been some 3,000 human casualties in the last five years and over 1,000 elephant deaths since 2014.

In response, state forest departments, NGOs, and locals are designing, testing, and deploying a range of AI systems that cut response and warning times to minutes—or even seconds. They range from wildlife eyes in Maharashtra to infrared drones in Chhattisgarh.

Find out how they work in our interactive map.

—Kanika Gupta

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US has allowed Anthropic to release Mythos 5 to “trusted” orgs
About 100 US companies and federal agencies now have access. (Semafor)
+ The White House said appropriate safeguards were now in place. (WSJ $)
+ The US had restricted both models over national security concerns. (BBC)
+ Which raised new questions about AI safety. (MIT Technology Review
 
2 A Chinese AI model has matched Mythos in finding security bugs
Security researchers say Zhipu AI is poised to reset the AI race. (WSJ $)
+ It’s sparked alarm that US restrictions are boosting China’s progress. (NYT $)
+ Although it still can’t match Anthropic or OpenAI on general tasks. (Verge)
+ In the AI race, China is eyeing a come-from-behind victory. (WP $)
 
3 Apple is seeking approval to buy chips from a blacklisted Chinese firm
It’s lobbying the White House for clearance to buy from ChangXin. (FT $)
+ ChangXin is on a Pentagon list of firms with Chinese military ties. (WP $)
+ Chipmakers are profiting off AI at the expense of everyone else. (WSJ $)
+ The US is banning imports of more Chinese technology. (Reuters $)
+ But Chinese tech companies feel optimistic. (MIT Technology Review)
 
4. South Korea plans to train its entire military as “drone warriors”
It wants to train all 500,000 personnel. (Reuters $)
+ And produce 110,000 drones by 2029. (Ars Technica)
 
5 Google has limited Meta’s use of its Gemini AI models
Meta wanted more compute than Google could provide. (FT $)
+ The cap has disrupted and delayed some Meta AI projects. (Bloomberg $)

6 Zuckerberg wants Meta to work with Polymarket and Kalshi
Meta wants its own prediction market, but without real-money bets. (NYT $)
+ The partnerships could hedge risks and accelerate development. (Reuters $)
 
7 Extreme heat is putting already hot data centers under pressure
Severe weather is now the leading cause of loss for data centers. (CNBC)
+ Heat waves also mess with your brain. (MIT Technology Review)

8 Android phones alerted millions moments before Venezuela’s earthquakes
They gave users between seconds and up to two minutes’ notice. (NYT $)

9 Scientists think Uranus and Neptune may not be the icy giants we imagined
They may have a magma ocean brewing on the inside. (Gizmodo)

10 Too much sleep may be as harmful as too little
A new study suggests 6.4–7.8 hours is the sweet spot. (Economist $)

Quote of the day

“This kind of powerful weapon that can alter the landscape of cyberwarfare can’t remain solely in American hands.” 

—360 Security CEO Zhou Hongyi tells a cybersecurity conference in Beijing why Chinese AI firms need to match the capabilities of their rivals in the US, The Wall Street Journal reports.

One More Thing

teenage girls on their phones

GETTY


Why Generation Z falls for online misinformation

Research shows that young people are more likely to believe and pass on misinformation if they feel a sense of common identity with the person who shared it in the first place. 

Offline, teenagers are likely to draw on the context that their communities provide. Social media, however, promotes credibility based on identity rather than community. And when trust is built on identity, authority shifts to influencers.

As young people participate in more political discussions online, those who have successfully cultivated identity-based credibility could become de facto community leaders, attracting like-minded people and steering the conversation. While that has the potential to empower marginalized groups, it also exacerbates the threat of misinformation.

Find out what we can all learn about how young people evaluate truth online.

—Jennifer Neda John

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ The Euclid space telescope has captured the most detailed image yet of the Milky Way.
+ Here’s a lovely, lilting medieval bardcore cover of Daft Punk’s electronic classic Veridis Quo.
+ A toilet plunger becomes an unlikely engineering breakthrough in this quest to build a better blowgun.

Association of MAP2 gene polymorphisms and altered expression with schizophrenia risk in a Chinese Han population

BackgroundSchizophrenia (SCZ) is a highly heritable primary psychotic disorder. The microtubule-associated protein 2 (MAP2) gene is essential for dendritic integrity and synaptic plasticity, positioning it as a key candidate for bridging genetic risk and neuropathology. Nevertheless, the role of common genetic variations within MAP2 in SCZ susceptibility remains to be elucidated.MethodsWe conducted a candidate gene association study of MAP2 in a Han Chinese cohort comprising 418 SCZ patients and 418 matched healthy controls. Targeted sequencing was used to genotype single nucleotide polymorphisms (SNPs). MAP2 mRNA levels were quantified by RT-qPCR and correlated with genotypes and clinical symptoms. Bioinformatic tools (such as GTEx, BrainSeq, 3DSNP, HaploReg, RegulomeDB and SNP2TFBS database) were employed for functional annotation of risk loci.ResultsWe identified multiple MAP2 SNPs associated with SCZ risk in a Han Chinese cohort. Specifically, the AA genotype of rs288057 and the GG genotype of rs288087 were significantly associated with increased disease risk (OR = 2.393 and 2.258, respectively). Expression analysis revealed a marked reduction in peripheral MAP2 mRNA levels in patients compared to controls. This downregulation was genotype-dependent: the risk AA at rs288057 and GG at rs288087 were correlated with lower mRNA levels, a finding supported by its significant eQTL effect in the GTEx and BrainSeq database. In silico annotation suggested rs288087 resides within a putative enhancer region, while rs288057 may affect a promoter-proximal regulatory site. Clinically, MAP2 expression showed a significant positive correlation with the severity of negative symptoms (SANS score). Furthermore, ROC analysis indicated that MAP2 expression levels distinguished patients from controls with an AUC of 0.728.ConclusionThis study identifies MAP2 as a schizophrenia risk gene, wherein non-coding variants likely reduce its expression via distinct regulatory mechanisms, linking this downregulation to core negative symptoms. These findings highlight MAP2’s pathophysiological and translational relevance.