The PolyU research team has developed TRUECAM, an integrated AI framework that ensures data and model trustworthiness in cancer diagnosis. The framework can assess the level of an AI's confidence in its diagnostic outputs and proactively prompts pathologists to review cases when uncertainty is high.
Researchers have discovered lymph node-like structures in the skull bone marrow of mice that act as rapid first responders against brain cancer and neurodegenerative diseases. The discovery offers a new way to fight brain cancer and other neurological diseases.
Advincula, a Governor's Chair Professor at ORNL and University of Tennessee, recognized for research advancing applied chemistry and translating scientific discoveries into practical applications. His work helps strengthen American innovation and industrial competitiveness.
A team of Penn State researchers has developed a synthetic enzyme mimic that can drive chemical reactions using oxygen, producing only water as waste. This breakthrough could potentially be used in sustainable industrial chemical syntheses and pharmaceutical drug development.
The article highlights the need for AI tools to provide interpretable and reportable results, with a focus on improving turnaround time, diagnostic consistency, and clinical decision-making. While AI is unlikely to replace pathologists, it can help convert tissue morphology into actionable evidence for better patient care
A new AI tool developed by La Trobe University researchers can analyze routine pathology slides to predict stage-two bowel cancer patients at risk of relapse. The study analyzed over 1600 pathology slides and validated the findings across 1220 patients in three independent cohorts.
A vaccine targeting KRAS mutations was safe and stimulated durable immune responses in high-risk individuals. After a median follow-up of 16.5 months, none of the participants developed pancreatic cancer, and some precancerous lesions shrank or stopped growing.
Elaine S. Jaffe, a distinguished investigator at the NCI Center for Cancer Research, has transformed our understanding of lymphoid malignancies through her groundbreaking research. Her work has led to significant advancements in disease classifications, diagnosis, and treatment.
Dr. Elaine S. Jaffe receives AMP's highest honor for pioneering contributions to lymphoma diagnosis and treatment. Dr. Laura J. Tafe is recognized for her leadership and service to the organization, while Dr. Daniel E. Sabath receives the Meritorious Service Award for his dedication to scientific excellence and organizational service.
The Association for Molecular Pathology recognizes Dartmouth Health medical director Laura J. Tafe for her exceptional leadership and dedication to the field of molecular diagnostics. She has been a member of the organization since 2007 and has held various positions, including president in 2023.
Daniel E. Sabath, a professor at UW Department of Laboratory Medicine and Pathology, has won the Association for Molecular Pathology's 2026 Meritorious Service Award for his dedication and effort over three decades. He is being honored for his leadership roles, scientific expertise, and collaborative spirit in advancing education and s...
The Association for Molecular Pathology has elected new leaders for several committees, including Genetics, Hematopathology, Infectious Diseases, Informatics, and Solid Tumors. The newly elected leaders will work together to drive the organization's mission forward.
A new study reveals IL-6 plays a crucial role in regulating neuroinflammation and protecting the nigrostriatal pathway in Parkinson's disease. The research found that restoring IL-6 levels can reverse aggravated pathology and partially ameliorate motor dysfunction in mice.
Researchers found that patients with Parkinson's disease showing little to no Lewy bodies despite long-standing, clinically advanced disease. The study provides new insight into the relationship between clinical symptoms and neuropathological progression.
Researchers discovered how ATRX mutations reprogram gene regulation architecture to fuel glioma growth and progression. Targeting genes downstream of ATRX slowed cancer progression in preclinical models.
A lifecycle framework helps laboratories overcome barriers to digital pathology adoption by integrating infrastructure, workflow redesign, validation, interoperability, and AI readiness. The framework addresses institutional governance, cybersecurity, education, and performance monitoring to ensure durable success.
The review discusses key AI concepts, including algorithms, models, architectures, machine learning, deep learning, and multimodal models. It highlights their clinical applications, such as detection of lymph node metastases, Nottingham grading, biomarker quantification, risk stratification, and prognostic prediction.
A cohort study found that a dietary pattern with lower inflammatory potential was associated with lower dementia risk among individuals with Alzheimer disease pathology. Targeted dietary strategies may help prevent dementia in those already at elevated risk.
Researchers developed a compact, cost-effective diagnostic platform combining lensfree holography and deep learning for automated HER2 scoring. The system reached 84.9% accuracy for four-level HER2 classification and 94.8% accuracy for binary scoring, effectively lowering diagnostic risks.
Researchers have developed a versatile uncertainty-aware AI framework called TRUECAM that provides customizable accuracy guarantees for cancer subtype classifications. TRUECAM outperforms existing approaches to digital pathology AI uncertainty quantification, detecting out-of-scope inputs and improving fairness across sex and race.
A large-scale study developed a predictive model for Lymph Node Metastasis (LNM) status in T1b gastric cancer using digital pathology and deep learning. The DL-T1 nomogram achieved an AUC of 0.910, indicating high accuracy in predicting LNM risk.
A research team has discovered that complex chemical signals merge in the environment to form dynamic 'chemodiversity landscapes' with emergent properties. These patterns can generate novel ecological effects, shaping entire ecosystems and influencing interactions between organisms.
A study by Southeast University and Korea University provides a roadmap for converting biomass into renewable energy and chemicals. The researchers highlight the potential of biomass chemical looping (BCL) for producing hydrogen, methanol, and other low-carbon products.
The study proposes a three-stage maturity model for AI integration in pathology, highlighting key barriers to clinical translation: data fragility, workflow misalignment, and institutional trust deficits. Infrastructure-first AI, workflow-embedded intelligence, and adaptive governance are proposed pathways toward sustainable clinical i...
A new study found that an mRNA influenza vaccine helps the immune system recognize a wider range of viruses, offering stronger protection. The vaccine is currently under review by the FDA and could offer benefits in reducing hospitalizations and deaths if approved.
A new staining-free imaging platform has been developed to analyze tissue samples more quickly and consistently, supporting future AI-assisted cancer diagnostics. The platform achieved a 99% agreement rate with conventional pathology assessments when analyzing colorectal tissue samples.
The Aileen Wee Professorship in Liver Diseases aims to catalyse partnerships between experts and address cancer and healthcare challenges. Prof Aileen Wee, a renowned authority in hepatobiliary pathology, will lead the professorship.
Professor Tony James has been awarded Honorary Fellow of the Chinese Chemical Society in recognition of his significant contributions to fluorescence chemical sensing, molecular identification, and diagnostic chemistry. He is a renowned expert in supramolecular chemistry and chemical sensing with broad international influence.
Airborne levels of formaldehyde regularly exceed EU limits in 70% of NHS pathology departments, with poor monitoring and control contributing to the risk. The researchers call for national regulatory intervention to protect NHS employees' health, citing increased risks of respiratory and reproductive problems, as well as cancers.
Researchers used tissue samples, pathology images, and clinical data from 672 patients to train AI models to classify meningioma subtypes and predict recurrence risk. The findings suggest that AI can help clinicians obtain more detailed tumor information without requiring advanced genetic testing.
A study published in Nature Medicine reveals that distinct cellular programs and immune-cell states are associated with Alzheimer's disease progression and resilience. Microglial responses were found to be critical in determining whether Alzheimer's pathology leads to dementia, suggesting new avenues for therapies to prevent neurodegen...
A new leishmaniasis vaccine, developed using CRISPR gene-editing technology, is set to begin testing in healthy people for its safety and immune response. The vaccine has shown strong results in mice and has cleared a key FDA hurdle, paving the way for Phase 2 trials aiming to understand its effectiveness.
A European research team is developing bacteria that can produce important chemical base materials from sustainable methanol, aiming to replace fossil resources in the chemical industry. The goal is to make chemical production more sustainable without jeopardizing food security.
Researchers highlight latest developments in pathology, diagnosis, and treatment of MASLD and IPFD, revealing correlations with chronic diseases like liver cancer and pancreatic cancer. Innovative treatments, such as AI-driven approaches and organ-targeted therapies, show promise for precision prevention and therapy.
A new brain imaging test can detect Alzheimer's disease pathology in twice as many people before symptoms appear. The test uses a new tau PET tracer that identifies more tau-positive cases than the current standard, leading to better decisions about who is on an Alzheimer's trajectory.
Benjamin L. Wolozin and his team will examine RNA binding proteins, RNA metabolism, and membraneless organelles in Parkinson's disease pathology and co-pathologies. They will also test a novel compound AQV-3 to break up toxic protein aggregates.
A large multisite study found that Black and Hispanic people with cognitive impairment are less likely to show Alzheimer's pathology on brain scans compared to other racial and ethnic groups. The study highlights ethnoracial differences in dementia and underscores the need for further research into underlying causes of dementia symptoms.
A study published in Acta Neuropathologica found that APOE ε4 is associated with widespread TDP-43 pathological subtype in sporadic ALS. This discovery suggests a new perspective on why ALS pathology spreads differently among patients.
A new AI system, SPARK, enables autonomous scientific discovery in cancer pathology by generating biological hypotheses and translating them into analytical tools. The system identifies clinically relevant tissue markers linked to disease course, treatment response, and tumour progression.
Researchers at Mass General Brigham developed an ultrasensitive test to detect abnormal clumps of TDP-43 protein in cerebrospinal fluid, a biomarker for specific form of dementia called FTLD-TDP. The test shows promise in diagnosing patients with the correct pathology and tracking disease progression.
A new study combines dynamic full-field optical coherence tomography with deep learning to generate real-time virtual pathology images of fresh lymph nodes during surgery. The approach achieved high accuracy and sensitivity, reducing tissue consumption and manual workload.
The research team developed a novel AI pathology analysis system named PRET that can accurately recognize multiple types of cancer using only a minimal number of samples. PRET outperformed existing methods in 20 tasks, achieving high diagnostic accuracy rates and stable generalizability across different populations and regions.
A new AI framework combines digital pathology and structured clinical data to predict PIK3CA mutation status in breast cancer. The Multimodal PIK3CA Model outperformed single-modality models, achieving an AUC of 0.745, with strong performance across multiple clinical datasets.
Researchers developed a pathomics framework using a deep learning survival prediction model that analyzes pathology slide images and study patterns to predict patient outcomes. The model correctly stratified patients into high- and low-risk groups with significantly different outcomes.
Researchers at WashU Medicine discovered that mRNA vaccines can trigger strong anti-tumor responses even without certain immune cell subtypes, suggesting a novel pathway for cancer treatment. The study found that both cDC1 and cDC2 dendritic cells play a role in stimulating T-cell responses.
Blake Warner, a renowned expert in salivary disorders, has been awarded the 2026 AADOCR National Student Research Group Mentor Award. He leads an integrated clinic and research laboratory focused on deep characterization of disorders affecting the salivary glands. The award recognizes his outstanding mentorship in dental research.
Several open-source AI models consistently produced summaries that were more comprehensive than physician-written versions, particularly in capturing molecular and genetic findings. The study found that Llama 3.1 and DeepSeek performed best among the six evaluated models.
Researchers have developed an integrated reiterative pipeline that uses machine learning and structural biology to identify promising vaccine targets across multiple related viruses simultaneously. The system evaluates viral proteins to identify short fragments called epitopes that can trigger a strong immune response.
Alexander Kerr, NYU Clinical Professor, recognized for outstanding research on oral cavity squamous cell carcinoma and oral potentially malignant disorders. The IADR Distinguished Scientist Award is one of the highest honors bestowed by IADR, recognizing contributions to understanding oral health and disease mechanisms.
The BiliSeq test detected approximately 82% of bile duct cancers, compared to 44% with pathology alone, and increased cancer detection to nearly 90% when combined with pathology. This improved accuracy enables physicians to provide more personalized medicine and treatment options for patients.
Researchers developed an AI model that analyzes routine pathology slides to predict breast cancer recurrence and chemotherapy benefit. The model was validated in a large clinical trial and demonstrates fast, accessible, and globally scalable diagnostic capabilities.
Researchers found that breast cancer cells trigger the lung's natural repair system, leading to chronic inflammation and promoting tumor growth. A repurposed drug, roflumilast, may slow this process by preventing the lung environment from aiding tumor growth.
UL Research Institutes' Chemical Insights will present findings on chemical exposures and health risks, highlighting new methods for faster, more transparent science. The institute aims to protect people and communities through open science, education, and collaboration.
LazySlide enables systematic whole-slide image analysis using AI models and links visual patterns to text concepts. The study demonstrates its potential in analyzing tissue samples, identifying biological pathways, and reducing the barrier for applying advanced image analysis methods.
Researchers from the University of Amsterdam developed a novel computational framework, Measurable Feature Prediction, to quantify the gaps in nontargeted chemical analysis. The study shows that environmental screening methods leave massive blind spots in the data, with only 0.01% of the chemical space being measurable.
Researchers at Boston University School of Medicine have discovered protein and sugar level changes that occur with aging and Alzheimer's disease brains. The study uses a unique mass spectrometry technique to capture detailed molecular information, providing new avenues for biomarker discovery and potential treatments.
New research warns that popular AI systems for predicting cancer biology may rely on visual shortcuts, raising concerns about their reliability for real-world patient care. Despite achieving high accuracy, these models often fail when conditions change or confounding factors are controlled.
This systematic review found that both chemical and non-chemical denture cleansers effectively reduce Candida species, with chemical agents demonstrating more consistent antifungal action. Non-chemical agents preserve material integrity and are preferred by patients for their taste and ease of use.
A University of Barcelona study using animal models found that early and sustained cognitive stimulation preserves brain connectivity and memory in Alzheimer's disease. Males respond better to cognitive intervention than females, which can delay the onset of the disease.
Researchers at Jeonbuk National University have developed a new dual-chemical looping process that improves the efficiency of ammonia synthesis by 8.4% and reduces global warming potential by up to 15.85 kg CO2-equivalent per kilogram of ammonia produced.