A night’s sleep may seem like a quiet break from the day, but the brain remains busy. While we sleep, it sorts through new information, strengthens some memories and prepares us to learn again when we wake up. That nighttime work becomes especially important as people get older. Many older adults notice that the small […]

The post A Hidden Sleep Change May Be Tied to Alzheimer’s Memory Loss appeared first on Knowridge Science Report.

A fourth person in Pennsylvania has died of measles, the state health department confirmed Tuesday. The latest death was in an unvaccinated 18-year-old resident of Mifflin County.

In the announcement, the state health department also confirmed a county coroner's report over the weekend of the death of an unvaccinated 40-year-old woman in Jefferson County. The state had previously reported two deaths in Lancaster County; both were infants—a newborn boy and a 6-week-old girl, both too young to be vaccinated.

According to the Mifflin County coroner, Andrea L. Alcalde, the 18-year-old's cause of death was determined to be acute disseminated encephalomyelitis (ADEM), which is a rare but known severe complication of measles. The condition is characterized by a rapidly progressing autoimmune disorder in which aberrant inflammation from an infection strips away the protective coverings of nerve cells in the brain and spinal cord. Before measles vaccines were widely used, ADEM was commonly associated with measles, though other viral infections can also spur its development.

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Alzheimer’s may begin to unravel the brain when a small group of neurons switches on a receptor it was never meant to use, triggering damage that spreads from synapses to memories. Alzheimer’s disease is often defined by amyloid plaques and tau tangles, but those hallmarks are part of a much wider breakdown. Neurons become overactive, [...]

Dr. Mike Yeadon warns about the alarming findings in Pfizer’s mRNA vaccine report. He cites a confidential document indicating that within 90 days of the vaccine's emergency use authorization, 1,223 deaths and 158,893 adverse reactions were reported globally, with significant implications for women's health.

Idiopathic pulmonary fibrosis, a relentlessly progressive and fatal scarring disease of the lungs, has long frustrated clinicians with only two approved drugs that slow but cannot reverse its course. Now, a team of researchers in Taiwan has identified a surprising new player in the disease’s destructive machinery: doublecortin-like kinase 1, or DCLK1, a kinase better known for its role in cancer stem cells. Their study, published in the Journal of Biomedical Science, demonstrates that DCLK1 drives fibroblast activation in the lung and that blocking it—either genetically or with an oral inhibitor—slows fibrosis and preserves lung function in mice. The findings position DCLK1 as a promising therapeutic target in one of medicine’s most stubborn diseases.

The research, led by Lee-Yuan Lin, Wun-Hao Cheng, Chien-Huang Lin and Bing-Chang Chen of Taipei Medical University, together with collaborators at National Taiwan University Hospital and Universitas Gadjah Mada, began with a question that has lingered in the literature. Gene expression analyses had previously hinted that DCLK1 might be implicated in IPF, and earlier work reported that the kinase is markedly enhanced in the alveolar epithelial cells of patients with pulmonary fibrosis and in mice with bleomycin-induced fibrosis. But its function in fibroblast activation—the cellular engine of fibrosis—had remained unexplained.

To begin untangling that role, the team mined a publicly available single-cell RNA sequencing data set containing more than 312,000 cells from healthy lungs, IPF lungs, and lungs with chronic obstructive pulmonary disease. After stringent quality control filtering, they focused on roughly 240,000 cells from the control and IPF groups and mapped DCLK1 expression across the major lung cell lineages: epithelial, endothelial, lymphoid, myeloid, and stromal cells. The signal was unmistakable. DCLK1 was expressed across many cell populations, but the highest expression appeared in the stromal compartment, particularly in myofibroblasts—the specialized, contractile fibroblasts that churn out the extracellular matrix and stiffen lung tissue in IPF.

Human tissue told the same story. The researchers examined lung samples from eleven patients with IPF, obtained during lung transplantation or surgery, alongside fourteen nonfibrotic control samples. Histological staining with hematoxylin and eosin and Masson trichrome confirmed the expected picture of interstitial consolidation and collagen deposition in the IPF specimens. More importantly, immunohistochemistry revealed that both total DCLK1 and its phosphorylated, activated form were significantly upregulated in the fibrotic lung interstitium compared with control tissue. DCLK1, in other words, was not merely present in scarred lungs—it was switched on.

DCLK1 is an intriguing molecule to find at the center of a fibrotic process. It is a serine/threonine kinase belonging to the calcium/calmodulin-dependent kinase family, distinguished by two microtubule-binding domains. In oncology, DCLK1 overexpression has been documented in colorectal, pancreatic, gastric, renal, and hepatocellular carcinomas, where it correlates with poor prognosis, high recurrence, and metastasis, promoting tumor initiation and the epithelial–mesenchymal transition in cancer stem cells. It has also been linked to inflammatory signaling in SARS-CoV-2 infection, where inhibiting it blocks proinflammatory caspase-1/interleukin-1β signaling. The new study extends this portfolio of mischief to the fibrotic lung.

To test causality rather than mere correlation, the researchers turned to mice. They crossed animals carrying loxP sites flanking exon 3 of the DCLK1 locus with Pgk1-RFP-Cre/ERT2 transgenic mice, generating a system in which tamoxifen administration triggers global deletion of the Dclk1 gene. When these DCLK1 knockout mice and littermate controls were given intratracheal bleomycin, a chemotherapy drug used to induce pulmonary fibrosis in laboratory animals, the difference was striking. Knockout mice showed far less lung infiltration and collagen deposition, reduced numbers of cells staining positive for DCLK1 together with fibroblast surface protein and alpha-smooth muscle actin, and significantly lower levels of the profibrotic proteins fibronectin, α-SMA, and connective tissue growth factor, or CTGF.

The protective effect extended well beyond molecular markers. Using the FlexiVent FX system to measure lung mechanics, the team found that bleomycin treatment significantly reduced respiratory system compliance and pressure–volume performance and increased the normalized work of breathing in control mice—hallmarks of a stiffening, fibrotic lung. In the DCLK1 knockout animals, these functional deficits were substantially attenuated. In vivo microcomputed tomography, acquired at 34.75-micrometer voxel resolution, painted the morphological counterpart: bleomycin caused parenchymal destruction and volume loss in control lungs, while knockout mice retained lung structure and volume. Density histograms shifted toward fibrotic tissue in wild-type animals but stayed largely preserved in the knockouts, and peripheral blood neutrophil percentages, which climbed after bleomycin injury, were significantly reduced in the knockout group.

With the in vivo evidence established, the investigators dissected the molecular wiring in cultured normal human lung fibroblasts. Transforming growth factor beta, the master profibrotic cytokine, induced DCLK1 phosphorylation within 30 minutes and DCLK1 expression within 8 hours. Chromatin immunoprecipitation assays showed that after TGF-β stimulation, both Smad3—the canonical transcriptional mediator of TGF-β signaling—and the nuclear factor kappa B subunit p65 enriched at the DCLK1 promoter, indicating that TGF-β switches on DCLK1 through both Smad-dependent and noncanonical NF-κB pathways. Silencing DCLK1 with small interfering RNA then blunted the fibroblast’s profibrotic response, reducing TGF-β-induced expression of fibronectin, collagen 1A1, α-SMA, and CTGF.

The pathway, however, does not stop there. The team found that TGF-β also phosphorylated Akt, and that transfecting fibroblasts with a dominant-negative Akt construct reduced TGF-β-induced DCLK1 phosphorylation and the expression of fibronectin and CTGF—placing Akt upstream of DCLK1. Downstream, DCLK1 knockdown reduced Smad3 phosphorylation while DCLK1 overexpression enhanced it. Coimmunoprecipitation revealed a physical association between DCLK1 and Smad3, and immunofluorescence microscopy showed the two proteins colocalizing in the nucleus within 30 minutes of TGF-β treatment. A ChIP assay using a DCLK1 antibody pulled down DNA from the Smad3-binding region of the CTGF promoter, and pretreatment with the selective DCLK1 inhibitor DCLK1-IN-1 reduced TGF-β-induced CTGF expression. Together, the results sketch an Akt/DCLK1/Smad3 axis through which TGF-β drives the production of connective tissue growth factor, a potent profibrotic mediator.

The clinical payoff came in the pharmacological arm of the study. Mice receiving oral DCLK1-IN-1 at 10 milligrams per kilogram daily, beginning on day 7 after bleomycin instillation and continuing until day 28, showed visibly reduced fibrotic progression on histology, lower expression of fibronectin, α-SMA, and CTGF in lung tissue and lysates, preserved pulmonary compliance, improved pressure–volume loops, and reduced work of breathing. Serial microCT scans on days 7, 17, and 27 documented less severe fibrotic remodeling in the treated animals, with lung attenuation histograms showing a smaller fraction of dense, nonaerated voxels. Blood neutrophil counts were also lower. In short, a pill-like oral inhibitor measurably slowed the disease in a model that mirrors the human condition.

The implications are significant because the current therapeutic landscape for IPF is so thin. Only nintedanib, a tyrosine kinase inhibitor targeting growth factor receptors, and pirfenidone, which suppresses TGF-β production and activity, are approved by the US Food and Drug Administration, and both merely slow progression. The recent failure of pamrevlumab, a monoclonal antibody against CTGF, in the phase 3 ZEPHYRUS-1 trial suggested that targeting downstream fibrotic end products alone may be insufficient—pointing to the value of upstream signaling regulators such as DCLK1. Adding to the appeal, a DCLK1 inhibitor has already been shown to prevent inflammatory responses in acute lung injury, hinting at dual anti-fibrotic and anti-inflammatory potential.

The authors are careful to note limitations. DCLK1 is expressed across multiple lung cell types, and the tamoxifen-inducible knockout used here was global rather than cell-type-specific, so the contributions of fibroblasts versus epithelial, endothelial, and immune cells could not be fully separated. Human control tissue, as in most fibrosis studies, came from heterogeneous sources, including tumor-adjacent lung. The precise subcellular mechanics of the DCLK1–Smad3 interaction, whether DCLK1 inhibition can promote fibrosis resolution rather than merely slow progression, and the systemic safety of long-term DCLK1 blockade—all relevant given the kinase’s role in cancer and other processes—remain open questions.

Even so, the convergence of evidence is striking: DCLK1 is upregulated in human IPF, amplified in experimental fibrosis, mechanistically coupled to the TGF-β–Smad3 engine of fibroblast activation, and its suppression by both genetics and a small molecule preserves lung structure and function. What began as a cancer stem cell marker has now emerged, unexpectedly, as a central node in the scarring of the lung—offering fresh hope that a disease long considered irreversible may one day be stopped at its molecular source.

Depression in later life may be an early warning from the brain, appearing years before Alzheimer’s begins to affect memory and thinking A new study in JNeurosci found that faster accumulation of tau, a protein closely tied to Alzheimer’s, was associated with worsening depressive symptoms in older adults who remained cognitively healthy. Teodora Markova of [...]

Diseases that cause nerve cells in the brain to die over time are known as neurodegenerative diseases. These cells, known as neurons, are vulnerable to DNA damage because they are highly active cells that require large amounts of energy. Neural DNA damage is a normal part of aging as changes to the DNA sequence, called mutations, build up over time. 

Previous scientists have shown that neurons from people with the neurodegenerative diseases Alzheimer’s disease (AD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS) accumulate unusually high numbers of changes in the DNA sequence, called somatic mutations. However, researchers don’t know what causes the high number of mutations or whether the same process causes them in all 3 diseases. 

To answer these questions, researchers at Boston Children’s Hospital and Harvard Medical School analyzed brain tissue from people who died with and without AD, FTD, or ALS. They compared the processes that cause DNA mutations in the 3 diseases by first accessing the DNA inside individual neurons from healthy and diseased postmortem brain tissue. 

To do this, they broke apart the brain tissue and added a fluorescent marker that identified the center of each neuronal cell where DNA is housed, called its nucleus. They used a sorting machine to separate the nuclei from the rest of the cell material to access the neuron’s DNA. Using a DNA sequencing method called single-cell whole genome sequencing, the team then sequenced each neuron’s DNA to identify mutations. 

They analyzed 159 neurons from people with AD, 61 neurons from people with FTD, 77 neurons from people with ALS, and 232 neurons from healthy individuals. This allowed the team to compare the number and types of DNA mutations between diseased and control (non-diseased) neurons. The researchers found that compared to the control neurons, which typically accumulate only 200 to 300 mutations over an 80-year lifespan, neurons from all 3 diseases contained an unusually high number of 2-base-pair deletions, often exceeding 1,000 mutations per cell. 

When a biological process damages DNA, it leaves behind its own unique signature. By identifying these signatures, scientists can identify the biological process that likely caused the damage. Since these 2-base-pair deletions were so frequent in diseased neurons, the researchers wanted to know whether they were left behind by a biological process. The researchers used a machine learning algorithm to scan DNA sequences for recurring mutation patterns and identified a signature in neuronal DNA, which they named ID-4.

When the researchers compared the ID-4 signature with a database of previously characterized signatures, they found that it was associated with a DNA repair protein called TOP1. TOP1 temporarily cuts and rejoins DNA to relieve the tension that builds up during normal cellular activity. TOP1 typically detaches from the DNA after completing this process. However, if TOP1 fails to detach, it breaks one of the two DNA strands. 

To test whether abnormal TOP1 activity was breaking the DNA, the researchers isolated DNA from control and diseased neurons. They visualized the DNA on a gel, where intact DNA forms bands while broken DNA spreads out into smears. The more fragmented the DNA is, the more intense the smear appears. Using a machine that quantified the intensity of smears, the researchers found that DNA from diseased neurons produced smears that were up to 3.2 times more intense than those from control neurons. They also found that neurons with more DNA fragmentation had more ID-4 signatures. 

Based on these findings, the researchers concluded that abnormal TOP1 activity created frequent single-strand DNA breaks. They proposed that some of these breaks are repaired incorrectly, eventually leading to widespread DNA breaks in all 3 neurodegenerative diseases.

Overall, the researchers found that neurons from these 3 neurodegenerative diseases accumulated excessive DNA mutations despite differences in the disease symptoms and underlying causes. Their findings also provided evidence that abnormal TOP1 activity contributes to this mutation accumulation. Based on these findings, they stated that preventing TOP1 from becoming trapped on DNA, or improving the DNA repair process that removes trapped TOP1, could be a promising way to treat a wide range of neurodegenerative diseases.

The post Common DNA damage could cause neurodegenerative diseases appeared first on Sciworthy.

Scientists in Arkansas have developed a machine-learning approach that can identify potentially disease-causing strains of a poultry bacterium by analyzing not only which genes are present, but also how those genes are arranged across the genome. The method focuses on the “genetic neighborhoods” surrounding genes, offering a new way to distinguish harmful strains of Enterococcus cecorum from closely related strains that do not cause disease.

E. cecorum is commonly found in poultry environments, and many of its strains are harmless. However, pathogenic strains can cause arthritis, bone infections and lameness, creating serious animal-welfare problems and economic losses for poultry producers. Because pathogenic and nonpathogenic strains can share many of the same genes, identifying the genetic features associated with disease has been challenging.

The research team, led by Aranyak Goswami of the Arkansas Agricultural Experiment Station’s Center for Agricultural Data Analytics, examined the organization of genes within genomic islands. These are segments of DNA that bacteria often acquire from other microorganisms through horizontal gene transfer. Genomic islands can carry genes involved in antibiotic resistance, bacterial survival, movement of DNA and virulence, making them important regions for understanding how pathogens emerge.

Rather than treating the bacterial genome as a simple list of genetic components, the researchers analyzed it as a structured map. They investigated which genes occurred near one another, the order in which they appeared and the way groups of neighboring genes formed recurring units known as genomic-island cassettes. This architecture provided information that could be missed when genes are examined individually.

“The machine-learning model recognizes patterns in gene order much like it recognizes patterns in language,” Goswami said. In the same way that a language model can learn that certain words frequently appear together, the computational system learned that particular combinations and arrangements of bacterial genes were associated with pathogenic strains. The approach therefore captures relationships among genes rather than relying only on the presence or absence of individual DNA sequences.

For the proof-of-concept study, the researchers analyzed the genomes of 145 E. cecorum strains isolated from poultry. The dataset included 95 nonpathogenic strains and 50 pathogenic strains capable of causing illness. The analysis found that disease-associated strains were more likely to contain genomic islands enriched in genes linked to antimicrobial resistance and the transfer of genetic material between bacteria.

Those findings do not mean that every bacterium carrying such genes will necessarily cause disease. Instead, the researchers describe the system as an exploratory classification and research tool. It identifies patterns that may help scientists investigate why some bacterial lineages become harmful, while also providing clues about how resistance and virulence traits move through bacterial populations.

Current monitoring methods for E. cecorum often depend on culturing the bacterium or screening for specific genes. Such techniques remain valuable, but they may overlook broader genomic relationships. The new pipeline could complement these approaches by evaluating the wider context in which genes occur. Additional testing with larger and more geographically diverse datasets will be necessary before the method can be used for routine flock surveillance or diagnostic decision-making.

The researchers believe the strategy could eventually be adapted to other bacterial species affecting animals, humans, wildlife and plants. Goswami’s team is beginning to examine Enterococcus faecalis, a close relative of E. cecorum and a frequent cause of hospital-acquired infections in humans. They also plan to apply the pipeline to Escherichia coli and other bacteria to study how nonpathogenic lineages acquire the genomic configurations associated with disease. The study, published in Frontiers in Microbiology, demonstrates how machine learning and comparative genomics can reveal hidden signals in bacterial DNA and may help researchers track the evolution of emerging pathogens.

Subject of Research: Animals

Article Title: Genomic-island cassette architecture provides interpretable signal for exploratory classification of poultry-associated Enterococcus cecorum lineages

News Publication Date: 7-Jul-2026

Web References: https://doi.org/10.3389/fmicb.2026.1882753

References: Frontiers in Microbiology, DOI: 10.3389/fmicb.2026.1882753

Image Credits: UA University Relations photo by Chieko Hara

Keywords: artificial intelligence, machine learning, deep learning, computational biology, bacterial pathogens, Enterococcus cecorum, genomic islands, genomic architecture, antibiotic resistance, poultry disease, pathogen surveillance, comparative genomics

Cardiovascular health in midlife may influence mental function later in life. A person’s activity level and blood sugar in middle age may help shape how quickly thinking skills decline decades later. Research from UT Health San Antonio, the academic health center of The University of Texas at San Antonio, found that physical activity and better [...]

Clearing amyloid plaques may break the chain reaction that fuels brain cell destruction in Alzheimer’s disease. One Alzheimer’s brain offered researchers something they almost never get to see: a natural side-by-side experiment. In some regions, years of anti-amyloid treatment had removed most of the sticky plaques associated with Alzheimer’s disease (AD). Those areas contained little [...]

Ancient scourges still infect, disable and kill people across the modern world.

A battery-free sweat sensor could make levodopa monitoring faster and more personalized for people with Parkinson’s disease. For people with Parkinson’s disease, the effect of a levodopa dose can fade abruptly, allowing movement problems to return before the next scheduled dose. Engineers and neuroscientists at the University of California San Diego have developed a soft [...]

Scientists are making progress understanding how a fiber-rich diet can help with chronic disease

In a perspective paper published in The American Journal of Clinical Nutrition, a team of researchers and health experts calls for a ‘paradigm shift’ in how public health agencies address hypertension.

The post Scientists Propose New Strategy in Fight against High Blood Pressure appeared first on Sci.News: Breaking Science News.

Scientists have discovered that the sleep problems seen in Alzheimer’s disease may not be caused directly by harmful protein plaques as previously believed. Instead, the brain’s own immune system may be playing a much larger role, opening the door to new treatment possibilities. Sleep problems are one of the earliest and most common symptoms of […]

The post Study Finds Hidden Cause of Sleep Issue in Alzheimer’s Disease appeared first on Knowridge Science Report.

Alzheimer’s disease may be leaving a more precise anatomical signature in the brain than scientists once realized. A new study published in Translational Psychiatry investigates regional changes in the fine structure of brain tissue immediately beneath the cerebral cortex, known as the juxtacortical region, and links those changes to patterns of gene expression associated with neurodegeneration. The work, led by J. Zhang, L. Sun, X. Yang and colleagues, offers a combined view of Alzheimer’s biology that connects what can be detected through brain imaging with the molecular programs active inside vulnerable neural tissue.

The juxtacortical zone is a narrow but biologically important interface. It lies directly beneath the cortex, the outer layer responsible for functions including memory, language, perception and decision-making. Although much Alzheimer’s research has focused on cortical thinning, large-scale tissue loss and abnormalities in deeper brain structures, the tissue bordering the cortex may reveal earlier or more regionally specific changes. Its organization includes densely packed axons, dendrites, neurons, glial cells and blood vessels, all of which can be affected as the disease progresses. Subtle disruption in this area could therefore provide clues before dramatic anatomical damage becomes visible.

The study’s central idea is that Alzheimer’s disease does not alter every brain region in the same way. Instead, neurodegeneration follows a complex geography shaped by cellular composition, connectivity, metabolism and genetic vulnerability. By examining regional juxtacortical microstructural changes, the researchers seek to move beyond a simple question of whether tissue has shrunk. Microstructure refers to the organization of brain components at scales smaller than conventional anatomical imaging can directly resolve. Variations in water diffusion, tissue organization and local architecture can serve as indirect markers of changes to axons, membranes, extracellular space and other microscopic features.

This regional perspective matters because the same imaging signal can arise from different biological processes. A change in tissue organization may reflect loss of neuronal connections, damage to myelinated fibers, altered glial activity, inflammation or shifts in the balance of cellular compartments. Imaging alone can reveal where abnormalities are concentrated, but it cannot always explain why they occur. The researchers therefore paired their investigation of juxtacortical structure with gene-expression information, creating a bridge between regional anatomy and molecular biology. That combination can help identify which biological pathways may underlie the imaging patterns seen in Alzheimer’s disease.

Gene expression describes the activity of genes within cells and tissues: which genetic instructions are being read, and at what levels. In the Alzheimer’s brain, these molecular signatures can point toward processes such as synaptic dysfunction, immune activation, impaired energy production, protein handling and cellular stress. Mapping gene-expression patterns onto regions showing microstructural alterations may reveal whether vulnerable areas share particular molecular characteristics. It may also help distinguish tissue changes related directly to neurodegeneration from those associated with aging or general brain atrophy. The result is a more layered portrait of disease, linking microscopic organization to the biological machinery that maintains it.

The findings described by the paper’s title suggest that these two forms of evidence—regional microstructure and gene activity—provide complementary insights into Alzheimer’s pathology. Rather than treating the brain as a uniform organ undergoing gradual damage, the research emphasizes a mosaic of vulnerability. Some areas may show distinctive structural disruption alongside gene-expression profiles associated with neuronal injury or altered support-cell function, while other regions may be relatively resilient. Such differences could help explain why symptoms vary between individuals and why memory, language, attention and other abilities can deteriorate along different trajectories.

The work could also influence how scientists think about biomarkers. A biomarker is a measurable biological feature that helps indicate disease presence, progression or response to treatment. Traditional markers of Alzheimer’s include abnormal amyloid and tau proteins, brain volume loss and changes in metabolism. Juxtacortical microstructural measures, especially when interpreted alongside molecular data, could eventually add regional detail to this toolkit. They might help researchers identify tissue at risk, track the spread of degeneration or evaluate whether an experimental therapy is protecting neural architecture even before clinical improvement becomes obvious.

However, the study should not be interpreted as proof that a single imaging signature can diagnose Alzheimer’s disease or predict an individual’s future with certainty. Microstructural measurements are indirect, and gene-expression data often come from specialized datasets that may not capture every cell type or every stage of disease. Differences in age, disease severity, medication, vascular health and individual brain organization can also influence results. The strength of the approach lies not in one isolated measurement, but in the convergence of regional imaging and molecular evidence. Together, these methods can generate testable hypotheses about how and where neurodegeneration unfolds.

The broader message is that Alzheimer’s research is moving toward increasingly integrated maps of the human brain. The study by Zhang, Sun, Yang and colleagues presents the juxtacortical region as a potentially informative frontier, where microscopic tissue organization and gene regulation intersect. If future research confirms these relationships in larger and more diverse groups, the approach could sharpen disease staging and improve the design of targeted therapies. For now, the findings add weight to a crucial principle in neuroscience: understanding Alzheimer’s requires knowing not only which brain regions are damaged, but also how their cellular architecture and molecular identity make them vulnerable.

Subject of Research: Regional juxtacortical microstructural changes and gene expression in Alzheimer’s disease

Article Title: Regional juxtacortical microstructural changes and gene expression provide insights into neurodegeneration in Alzheimer’s disease

Article References: Zhang, J., Sun, L., Yang, X. et al. “Regional juxtacortical microstructural changes and gene expression provide insights into neurodegeneration in Alzheimer’s disease.” Translational Psychiatry (2026). https://doi.org/10.1038/s41398-026-04292-z

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41398-026-04292-z

Keywords: Alzheimer’s disease, neurodegeneration, juxtacortical microstructure, gene expression, brain imaging, neuroscience, biomarkers, translational psychiatry