Tag: Academic research

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AI Learns to Predict Breast Cancer Risk from How Single Cells Respond to Pressure

A study headed by researchers at City of Hope and the University of California, Berkeley has found that physical and mechanical properties of normal human mammary epithelial cells can offer a “functional readout” of biological age and breast cancer susceptibility.

The team created a novel, high-throughput microfluidic platform that can assess women’s breast cancer risk at the cellular level. The mechano-node-pore sensing (mechano-NPS) platform, which the researchers claim is the first of its kind, squeezes individual breast epithelial cells, creating a taxing environment to measure how they deform, recover, and behave under stress.

Using the platform the researchers uncovered an unexpected insight, which is that breast cells appear to have a “mechanical age” separate from a person’s chronological age, demonstrated by how the cells physically respond to stress. For their study the team developed a machine learning classifier, MechanoAge, to estimate chronological age based on the mechanical phenotypes, and a biological age-based risk index, Mechano-RISQ.

“We learned that the older the mechanical age, as determined by how cells respond to being squeezed through our microfluidic device, the higher the risk for breast cancer,” explained Lydia Sohn, PhD, the Almy C. Maynard and Agnes Offield Maynard Chair in Mechanical Engineering at UC Berkeley. The researchers suggest that, as more than 90% of women lack a known genetic predisposition to or a family history of breast cancer, their innovative approach could fill a critical gap in risk assessment and save countless lives.

Sohn is co-senior author of the team’s published paper in eBioMedicine, titled “MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells,” in which they concluded, “Age-related biomechanical changes may represent a fundamental hallmark of cellular function, with distinct mechanical phenotypes underlying critical processes in aging, cancer, and potentially other diseases. Recognizing and utilizing these biomechanical markers could greatly enhance early detection, refine risk stratification, and improve targeted intervention strategies.”

Breast cancer is one of the most frequently diagnosed cancers worldwide and a leading cause of cancer-related mortality among women, the authors noted, and “… has long been the subject of efforts to improve risk stratification and early-detection strategies.”

About 6% of women who develop breast cancer carry known genetic mutations. But for women outside this group, risk is estimated indirectly based on population models or measurements like breast density. These approaches can both overestimate and underestimate women’s individual breast cancer risk, leading to over-screening, under-screening, unnecessary worry or missed warning signs. And despite significant progress in screening technologies and therapeutic interventions, accurately determining which individuals—particularly among those considered average risk—are most likely to develop breast cancer remains what the team calls “one of the most persistent challenges in oncology and public health.”

For these “ostensibly average-risk individuals,” the team added, “it remains difficult to identify those with latent risk that stems from cellular, molecular, and biophysical alterations that current models are not designed to capture.”

Researchers Mark LaBarge of City of Hope (right) and Lydia Sohn (left) UC Berkeley [City of Hope and UC Berkeley]
Researchers Mark LaBarge of City of Hope (right) and Lydia Sohn (left) UC Berkeley [City of Hope and UC Berkeley]

Currently, there is no non-genetic test available that can identify women at higher risk for breast cancer. A downside to screening mammograms is that they can catch cancer only once it has begun to grow. Co-senior author, Mark LaBarge, PhD, a professor in the Department of Population Sciences at City of Hope, said “For women with a known genetic risk factor for breast cancer, there are things you can do like follow a higher-risk screening protocol. For everybody else, you’re left wondering, ‘Am I at high risk?’”

Emerging evidence links cellular aging and biophysical alterations with cancer susceptibility. For their reported study the researchers used the mechano-NPS platform to profile primary human mammary epithelial cells (HMECs) from women of different ages and risk backgrounds. They also developed a machine learning algorithm that identifies and measures cells that show signs of accelerated aging, quantifying an individual breast cancer risk score.

In this type of mechano-node-pore sensing, an electrical current is measured across a liquid-filled channel, much like how current is measured across a wire. As cells pass through, they disrupt the current, generating measurements about the cells’ size and shape. By making parts of the channel very narrow, researchers squeeze cells, then measure how long it takes each cell to recover its normal shape.

Machine-learning algorithms developed by the researchers were then used to detect differences in cells from older and younger women. The researchers found that the physical properties of breast cells changed with age; cells from older women were stiffer and took longer to bounce back after being squeezed.

Then came a surprising finding: a subset of younger women had cells that behaved like they came from older women. These cells came from women with genetic mutations that put them at high risk of breast cancer. Researchers then refined the algorithm to assign a risk score based on all the mechanical and physical properties measured in the cells. This algorithm successfully identified women with known genetic risks. Next the team used it to compare cells from healthy women, women who had family history of breast cancer and cells taken from the healthy breast of women with breast cancer in the other breast. “Normal epithelial cells from women with germline mutations, strong family history of cancer, or contralateral breast cancer exhibit mechanically aged phenotypes despite normal histology,” the investigators stated. “Together with prior molecular and epigenetic studies, these findings support a model in which accelerated biological aging of mammary epithelia may underpin breast cancer susceptibility across genetic and non-genetic risk groups.”

Using the MechanoAge platform, researchers shifted the scientific lens to the cellular level, calculating risk by looking for physical changes in individual cells. “Mechanical phenotyping captures an integrative cellular state that reflects underlying molecular networks rather than single biomarkers,” the team noted. “Mechano-RISQ offers a proof of principle approach for identifying individuals at elevated risk of breast cancer, especially among average-risk populations, and may complement existing risk models by incorporating biophysical measures of mammary epithelial cell aging.”

“With accuracy, we were able to figure out which women were at high risk of breast cancer and which women didn’t seem to be,” LaBarge said. “By translating physical changes in cells into quantifiable data, this tool gives women something tangible to discuss with their doctors—not just risk estimates, but evidence drawn directly from their own cells.” In their paper the scientists further stated, “This approach could enable earlier, individualized risk stratification, particularly for women who lack identifiable high-risk mutations yet harbor susceptible tissue states.”

Importantly, the AI platform uses simple electronics that would be easy and affordable to replicate on a large scale. “Our team isn’t the first to measure the mechanical properties of cells; however, other approaches require advanced imaging technology that’s expensive, cumbersome and has limited availability,” said Sohn. “In contrast, MechanoAge uses computer chips that are simpler than an Apple Watch and ‘Radio Shack parts’ that are cheap and easy to assemble, potentially making the device highly scalable.”

While engineers study the aging of materials such as metals, concrete and polymers, this is the first time that mechanical age has been quantified in biological cells. The finding that cells have a “mechanical age” separate from the individual’s chronological age would not have been possible without MechanoAge.

This work grew out of more than 12 years of collaboration between the two labs, combining engineering innovation with cancer and aging biology. The long-term partnership enabled discoveries that neither group could have reached alone.  “It’s a true collaboration. We’ve learned a lot from each other,” Sohn said. “In my view, this is what happens when you have a real collaboration that develops over a long time,” LaBarge added. “This result is not what we imagined at the beginning.”

The post AI Learns to Predict Breast Cancer Risk from How Single Cells Respond to Pressure appeared first on GEN – Genetic Engineering and Biotechnology News.

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Single-Cell Atlas of the Prenatal Brain Reveals How Down Syndrome Reshapes Development

A cellular-resolution molecular map details how Down syndrome alters human brain development before birth. The study analyzed more than 100,000 nuclei from human prenatal neocortex samples collected across 26 pre-genotyped donors during gestational weeks 13 to 23—the only window during which all the cortical neurons a person will carry for their entire life are generated. The findings suggest that Down syndrome disrupts the developmental sequence of that process, creating shifts that may help explain later differences in cognition, learning, and sensory processing.

This work is published in Science in the paper, “A single-cell multiomic analysis identifies molecular and gene-regulatory mechanisms dysregulated in developing Down syndrome neocortex.“

“There’s a new level of detail here that had never existed before,” said Luis de la Torre-Ubieta, PhD, an assistant professor of psychiatry and biobehavioral sciences at UCLA and a member of the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research. “For the first time, we can really try to understand systematically what’s going on in the developing brain of individuals with Down syndrome.”

“No one had looked at the developing human brain in Down syndrome directly using single-cell genomics,” he continued.

The Down syndrome research field has historically focused on two areas: the adult brain and the disorder’s connection to neurodegeneration. What remained largely unexamined, despite clear indicators that Down syndrome is a developmental condition, was how the condition shapes the developing brain itself.

The development of the prenatal neocortex typically follows a tightly orchestrated sequence. Progenitor cells must first divide repeatedly to expand their own pool, building up a sufficient base for all future neurons. Only then do they begin differentiating into neurons, starting with deep-layer cell types and progressing toward upper-layer cells in a carefully timed order.

The study found that progenitor cells appear to rush prematurely into neuron production, depleting their own pool and skewing the balance of neuron types generated. Specifically, the researchers observed a relative increase in upper-layer intratelencephalic neurons and a reduction in deep-layer corticothalamic neurons.

Those two cell populations play fundamentally different roles: CT neurons project outward from the cortex—connecting to brain structures and to the spinal cord to govern sensation and movement; IT neurons wire within the cortex, connecting the two hemispheres and contributing to information processing. This finding offers a new hypothesis for how early developmental changes might contribute to the cognitive profile of the condition.

The finding also offers a new answer to a longstanding question in the field: Why do people with Down syndrome tend to have smaller brains? Earlier theories centered on elevated rates of cell death. The current study found less evidence of widespread neuronal death and instead points to the depletion of the progenitor pool.

The study employed paired single-nucleus multiomics to reconstruct not just a snapshot of which cells are present, but the regulatory programs that guide cell fate—and how those programs are disrupted in Down syndrome. Systems-level approaches also led them to uncover alterations in cell metabolism and changes in how the vasculature interacts with the developing nervous system, both of which could speed up neuron production.

The study’s significance extends beyond Down syndrome. The researchers specifically tested for overlap between the molecular disruptions they identified and the genetic risk signatures associated with other neurodevelopmental and neuropsychiatric conditions, including autism, epilepsy, and developmental delay. They found substantial convergence, particularly in the gene-regulatory networks governing the specification of IT versus CT neurons.

“Down syndrome could be a model to understand intellectual disability and neuropsychiatric disorders more broadly,” de la Torre-Ubieta said. “Also to uncover the shared biology underlying these conditions—because the mechanisms are often still unknown.”

The publication coincides with a companion paper from researchers at the University of Wisconsin-Madison, appearing in the same issue of Science. While the UCLA study focuses on the prenatal period, the Wisconsin team examined the postnatal brain, studying Down syndrome between approximately one and five years of age.

Together, the two papers provide a continuous molecular view of Down syndrome brain development from mid-gestation through infancy—a resource that did not previously exist and that the researchers expect will serve as a reference for their field for years to come.

While the researchers are careful to emphasize that the findings do not point to a near-term clinical application, the study provides the clearest picture yet of the cellular and molecular events that distinguish the Down syndrome brain during development, and a framework for identifying future therapeutic targets.

The post Single-Cell Atlas of the Prenatal Brain Reveals How Down Syndrome Reshapes Development appeared first on GEN – Genetic Engineering and Biotechnology News.

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Epigenetic Mapping in Pancreatic Cells Identifies New Diabetes Target

Researchers at Lund University in Sweden have conducted the first study looking at epigenetic changes associated with type 2 diabetes in alpha and beta pancreatic cells. Published today in Nature Metabolism, their findings show that the ONECUT2 gene plays a key role in the development of type 2 diabetes by altering insulin production. 

“The study shows that many genes central to insulin and glucagon production are regulated by differences in DNA methylation,” says Charlotte Ling, PhD, professor of epigenetics at Lund University and lead author of the study. “It has made it possible, for the first time, to describe detailed, cell-specific epigenetic patterns.”

The number of people living with diabetes is rapidly increasing worldwide, with approximately 95% of cases attributed to type 2 diabetes. This condition develops gradually and is characterized by a reduced ability to use insulin effectively, leading to elevated blood sugar levels. Over time, high blood sugar can lead to a range of complications that significantly impact the patient’s quality of life. 

Lifestyle factors like diet and physical activity are major drivers of this condition; however, genetics can also contribute to the development of type 2 diabetes, increasing the risk for some people over others. While genome- and epigenome-wide studies on diabetes have identified genetic and epigenetic mechanisms involved in type 2 diabetes, previous epigenetics studies had only looked at whole tissues and none had investigated epigenetic changes within specific cell types that are involved in blood sugar regulation. 

Ling’s team focused on alpha and beta pancreatic cells, which secrete insulin and glucagon hormones, respectively, to regulate blood sugar levels. By analyzing hundreds of thousands of cells from 24 people, with and without diabetes, the researchers created the most detailed epigenetics mapping of pancreatic cells to date. This allowed them to discover over 22,000 regions in nearly 8,000 genes that were differentially methylated between alpha and beta cells. 

“Here, for the first time, we show exactly which regions regulate insulin and glucagon production through DNA methylation, which gives us the opportunity to develop future treatments based on epigenetics,” says Ling.    

They then used CRISPR epigenetic editing to alter DNA methylation around the genes encoding for insulin and glucagon, which revealed that levels of the ONECUT2 transcription factor were elevated in beta cells from type 2 diabetes patients. This epigenetic upregulation was found to impair the ability of beta cells to release insulin, which in turn disrupted glucose regulation and reduced energy production within the cell.

Based on their findings, the researchers developed a web tool intended as a comprehensive resource available to researchers investigating the impact of age, sex, and type 2 diabetes on DNA methylation and gene expression in alpha and beta cells. 

“We now want to understand which of these changes can actually be reversed, and whether this can help beta cells regain their function in diabetes,” says Ling. “A key aspect is to see whether the effects of editing DNA methylation can be sustained in the cell over time.” 

The post Epigenetic Mapping in Pancreatic Cells Identifies New Diabetes Target appeared first on Inside Precision Medicine.

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Fibroblast Subset Directs Immune Cell Positioning in Lymph Nodes

Researchers at the University of Lausanne have identified a specialized fibroblast population that actively organizes immune cell interactions within lymph nodes, revealing a key mechanism underlying effective T cell responses to infection and cancer.

The study, published in Immunity, shows that stromal cells, long considered primarily structural, play a central role in orchestrating where and how immune cells meet, with direct consequences for immune activation and memory formation.

Spatial organization drives immune efficiency

Lymph nodes act as surveillance hubs of the immune system, filtering lymphatic fluid and coordinating responses to pathogens or tumor cells. Within these small, highly organized structures, immune cells are not randomly distributed. Instead, they occupy defined niches that facilitate efficient communication.

Cytotoxic T lymphocytes (CTLs), for example, are typically positioned in central regions of the lymph node, where they interact with type 1 dendritic cells (cDC1s) that present antigen and initiate activation. As explained by the study authors, “cytotoxic T lymphocytes are typically found in central regions of the lymph node, where they colocalize and interact with specialized cells called type 1 dendritic cells that present danger signals to them.”

While the importance of this organization has long been appreciated, the mechanisms guiding immune cells to the correct locations have remained incompletely understood.

A fibroblast niche organizes T cell positioning

To address this question, the Lausanne team focused on fibroblasts, a class of stromal cells that form the structural backbone of lymphoid tissues. Using mouse models and human lymph node samples, they identified a distinct subset of fibroblasts located in the central compartment.

These fibroblasts are characterized by expression of MAdCAM1 and by their production of high levels of the chemokine CCL19. This signaling molecule acts as an attractant that guides cytotoxic T cells into proximity with dendritic cells, enabling productive immune interactions. As the researchers note, CCL19 “acts as an ‘attractant signal’ for cytotoxic T lymphocytes, bringing them into physical contact with type 1 dendritic cells.”

By shaping this spatial organization, the fibroblast subset creates a functional niche that promotes T cell activation. When this system was disrupted, cytotoxic T cells failed to position correctly and showed impaired differentiation into memory T cells, highlighting the importance of tissue architecture for long-term immunity.

Notch signaling maintains the stromal network

The researchers also identified the molecular pathway that sustains this fibroblast population. A signaling axis involving Notch2 and its downstream mediator RBPj was found to be essential for maintaining the identity and activity of the CCL19-producing fibroblasts.

In addition, Jagged-1, a ligand produced primarily by dendritic cells, appears to initiate or reinforce this signaling loop. This suggests a feedback mechanism in which immune cells and stromal cells cooperate to maintain the lymph node architecture.

According to the scientists, this pathway must remain active throughout life. When Notch2 signaling was disrupted in fibroblasts, the structural integrity of the niche was lost, leading to defective T cell responses and reduced formation of memory cells.

A conserved mechanism across immune tissues

Although the study focused on lymph nodes, the same organizational principles appear to extend to other immune organs. The researchers observed similar regulation of CCL19 production in the spleen and Peyer’s patches, which are involved in blood filtration and intestinal immunity.

Comparable fibroblast populations were also identified in human lymph nodes, suggesting that this mechanism is conserved across species and relevant to human immune function.

Implications for immunotherapy and vaccines

The findings add to a growing body of evidence that stromal cells play active roles in shaping immune responses. Rather than acting as passive scaffolds, fibroblasts help define where immune interactions occur and how effectively they proceed.

This has important implications for disease. In cancer, for example, ineffective T cell responses may result not only from intrinsic immune dysfunction but also from disrupted tissue organization that prevents optimal cell–cell interactions.

In vaccination, enhancing the formation or function of such stromal niches could improve immune activation and the development of long-lasting memory responses.

Looking ahead

The identification of a fibroblast-driven mechanism for organizing immune cell positioning provides a new foundation for understanding how immune responses are initiated and maintained.

Future research will be needed to explore whether targeting stromal signaling pathways, such as Notch2, can be used to modulate immune responses in therapeutic settings. While such approaches remain speculative, they highlight the potential of integrating tissue architecture into the design of next-generation immunotherapies.

“Overall, these findings deepen our understanding of the organization of the immune system and how effective T cell responses against infections and cancer are initiated,” said Sanjiv Luther, PhD, senior author of the study. “In the future, this knowledge could help improve vaccine design and clarify why immune defenses sometimes fail against certain pathogens or tumors.”

The post Fibroblast Subset Directs Immune Cell Positioning in Lymph Nodes appeared first on Inside Precision Medicine.

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AI in Oncology Takes Off, Tackling HIV and Liver Disease, Pharma’s Recent Gains

Some GEN editors were in sunny San Diego covering the hottest research, trends, and products from the American Association for Cancer Research meeting. We kick things off with news from America’s Finest City, particularly around the growing role of AI in oncology. Then we dive into two new research studies. In the first, scientists used CRISPR to identify genes in primary CD4+ T cells that promote or restrict HIV infection. The second study described engineered implantable liver constructs that could eventually serve as a stopgap for patients waiting for donor transplants. Finally, the acquisitions keep coming as Eli Lilly scoops up CAR T cell therapy developer Kelonia for $7B. Also, Revolution Medicines has shared some impressive data from a Phase III trial of its pancreatic cancer drug.

Listed below are links to the GEN stories referenced in this episode of Touching Base:

AACR 2026: A Video Update from San Diego
By Julianna LeMieux, PhD, and Damian Doherty, GEN, April 21, 2026

AACR 2026 Video Update: Cancer Research Edges Toward an AI-Driven Era
By Fay Lin, PhD, and Jonathan Grinstein, PhD, GEN, April 22, 2026

Using AI in Healthcare Ethically by Considering Humanity
By Corinna Singleman, PhD, IPM, November 18, 2025

10x Genomics Unveils Atera Spatial Platform at AACR Meeting
By Julianna LeMieux, PhD, GEN, April 19, 2026

CRISPR Screens Map Human T‑Cell Genes That Promote or Block HIV Infection
GEN, April 20, 2026

Synthetic Biology and Tissue Engineering Grow Liver Tissue In‑Body
GEN, April 20, 2026

StockWatch: Revolution’s Phase III Pancreatic Cancer Data Dazzles Investors, Analysts
By Alex Philippidis, GEN Edge, April 19, 2026

Lilly to Acquire Kelonia for Up to $7B, Expanding Cancer Cell Therapy Pipeline
By Alex Philippidis, GEN Edge, April 20, 2026

Touching Base Podcast
Hosted by Corinna Singleman, PhD

Behind the Breakthroughs
Hosted by Jonathan D. Grinstein, PhD

The post AI in Oncology Takes Off, Tackling HIV and Liver Disease, Pharma’s Recent Gains appeared first on GEN – Genetic Engineering and Biotechnology News.

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Lithuanian children’s trauma characteristics and correlates: comparison of clinical and non-clinical samples

IntroductionPrevious studies have shown that children’s exposure to potentially traumatic events and their trauma−related symptoms may not always be consistently identified. This study aims to examine differences in trauma exposure and related psychological outcomes between clinical and non−clinical Lithuanian children.MethodsThis cross-sectional study included 10–17−year−old children and adolescents recruited from a clinical inpatient setting (Vilnius University Hospital Santaros Klinikos) and general−education schools in Vilnius and nearby districts. After parental consent and child assent, participants completed a secure mobile assessment covering exposure to potentially traumatic events (CATS), dissociation (A−DES), mood and feeling (SMFQ), post−traumatic cognitions (CPTCI), PTSD symptoms (CATS; PCL−5 for convergent validation), and perceived social support (CASSS). Data were collected in 2023–2024. Group differences were examined using Welch’s t−tests (with Mann–Whitney U as robustness checks), and associations were assessed using Pearson correlations.ResultsIn the clinical sample over 40% of children experienced physical violence, while in the non−clinical sample 82.9% children reported exposure to multiple traumatic events. The clinical sample showed significantly higher dissociation, negative mood, and PTSD symptoms compared to the non−clinical sample. However, among children exposed to more than one traumatic event, differences in dissociation, PTSD symptoms, and close−friend support were not significant. Across both samples, exposure to potentially traumatic events was strongly associated with PTSD symptoms, dissociation, and post−traumatic cognitions, and moderately associated with mood symptoms. In the non−clinical sample, parental support showed moderate negative associations with dissociation, mood symptoms, post−traumatic cognitions, and PTSD symptoms.DiscussionThis study identified between−sample differences in exposure to potentially traumatic events and trauma−related psychological outcomes among Lithuanian children in inpatient and community settings, highlighting the need for trauma−informed assessment and attention to social support within child mental health and welfare services.
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A longitudinal inquiry into the vicious cycle of social media addiction and self-injury: the moderating role of resilience

BackgroundThe reciprocal relationship between social networking addiction (SNA) and non-suicidal self-injury (NSSI) represents a critical, yet poorly understood, feedback loop in adolescent psychopathology. This study aimed to longitudinally test a “vicious cycle” model, examining the bidirectional effects between SNA and NSSI, and to investigate psychological resilience as a potential protective factor that could disrupt this harmful dynamic.MethodsA three-wave longitudinal study was conducted with a large cohort of 2,628 Chinese high school students (mean age = 16.1 years; 53.1% female) over a 12-month period. Participants completed measures of SNA, NSSI frequency, and psychological resilience at each wave. A cross-lagged panel model (CLPM) was used to examine the reciprocal, prospective relationships between SNA and NSSI. A multi-group CLPM was then employed to test the moderating role of resilience.ResultsThe CLPM revealed significant, positive, and reciprocal cross-lagged effects. SNA at T1 and T2 prospectively predicted increases in NSSI at T2 and T3, respectively (βs = .19 and.17). Conversely, NSSI at T1 and T2 prospectively predicted increases in SNA at T2 and T3 (βs = .14 and.12), providing robust evidence for a vicious cycle. Furthermore, resilience significantly moderated the pathway from SNA to NSSI. For adolescents with low resilience, the effect was strong and significant (β = .25), whereas for those with high resilience, the effect was rendered non-significant (β = .07).ConclusionsSocial networking addiction and non-suicidal self-injury are not merely comorbid but are locked in a mutually reinforcing developmental spiral over time. However, this dangerous cycle is not deterministic. Psychological resilience acts as a powerful protective buffer, effectively uncoupling the link from addictive social media use to self-harm. These findings underscore the urgent need for integrated, dual-focus interventions that address both online and offline maladaptive behaviors, while championing resilience-building as a primary strategy for prevention.
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Sex-specific impact of vitamin D and B9 concentrations on neuroticism: a polygenic score-based study

IntroductionNeuroticism is a personality domain with prognostic value for physical and mental health. To properly inform public health policy, it is crucial to uncover the mechanisms underlying high neuroticism. Many internal and external factors that affect brain development and functioning and therefore might contribute to the variability of neuroticism remain understudied. Among them, the impact of vitamin sufficiency is of great interest, as it is a modifiable factor. This study aimed to evaluate the associations of neuroticism with vitamin D (VD) and vitamin B9 (VB9) using polygenic scores (PGS) in a nonclinical cohort.MethodsWe analyzed data from 348 healthy unrelated individuals, including neuroticism scores on the Eysenck Personality Inventory, VD-PGS, VB9-PGS and PGS for neuroticism-related traits.ResultsThe analysis controlling for demographic and genetic confounders revealed a negative association between VB9-PGS and neuroticism scores in women and a positive association between VD-PGS and neuroticism scores in men. The highest values of the VD-PGS were observed in men, who scored high on both neuroticism and extraversion. In men, unlike women, neuroticism scores were not correlated with PGS for neuroticism but were associated with PGS for bipolar disorder type 1 and alcohol use disorders.ConclusionThe results suggest that the effects on neuroticism of genetic propensity for suboptimal vitamin D and B9 concentrations might differ across the two sexes. The findings are consistent with the idea of the importance of vitamin B9 for emotional stability in women and indicate the involvement of genetic factors predisposing to higher vitamin D levels in excitability-related components of neuroticism in men.
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Impact of extremely low frequency electromagnetic fields exposure on sleep quality and mental health in a Tunisian power plant: a cross-sectional study

IntroductionExtremely low-frequency electromagnetic fields (ELF-EMFs) are ubiquitous in our daily life. They may have an impact not only on physical health but also on mental health.ObjectivesTo assess the impact of occupational exposure to the ELF-EMFs on sleep quality, depression, anxiety and stress among workers at the Tunisian Electricity and Gas Company (TEGC).MethodsThis was a cross-sectional study. The study population included two groups: an exposed group (EG), consisting of power plant employees, and a non-exposed group (NEG), consisting of administrative workers. Exposure to ELF-EMFs was assessed via spot measurements using a magnetometer. Sleep quality, depression, anxiety and stress were assessed by the French versions of the Pittsburgh Sleep Quality Index (PSQI) and the Depression, Anxiety and Stress Scale (DASS-21).ResultsSeventy-seven participants in the EG and 88 participants in the NEG were included in the study. The median value of the ELF-EMFs was 5.86 μT at the power plant [min 0.1, max 40.34 μT]. According to the PSQI global score, 64.9% of the EG had poor sleep quality versus 29.5% of the NEG. Depression was registered in 24.7% of EG and in 3.4% of NEG. Anxiety was noted in 23.4% of the EG and in none of the NEG. Stress was found in 46.8% of the EG and none of the NEG. After multivariate analysis, ELF-EMF exposure was significantly associated with poor sleep quality and depression.ConclusionThe present study revealed that ELF-EMFs can affect sleep and mental health. Further studies are needed to explain the mechanism involved.
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Mental health in the time of polycrisis: geopolitical determinants and modern psychiatry

Psychiatry is increasingly being practised in environments affected by geopolitical instabilities, including economic fragmentation, democratic backsliding, and widening inequities. The confluence of these phenomena contributes to what has been described as a contemporary polycrisis, encompassing synchronous disruptions that reinforce one another and threaten collective wellbeing. Nevertheless, psychiatric research and clinical work have generally remained oriented towards immediate determinants and risk factors, overlooking the macro-level political and institutional dynamics that can condition stressor exposure and mental health disparities. Amidst, interconnected crises, this paper advances geopsychiatry as a framework for understanding how distal geopolitical determinants translate into psychiatric vulnerabilities across communities and societies. Focussing on armed conflicts, climate change, and forced migration as emblematic domains of polycrisis, it highlights how these compounding phenomena are generating direct mental health burdens and may amplify harms via secondary pathways. Moreover, it contends that the psychiatric consequences of polycrisis are unlikely to be ameliorated through patient-centred interventions alone, but also require innovative approaches responsive to structural inequalities and material forces that transcend borders. In this context, work from geopsychiatry can offer important implications for modern psychiatry, highlighting a need for a more globally representative evidence base, potential clinical adaptations, and policy engagement that better attends to the geopolitical determinants of mental health.