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Category: biotech/medical – Page 28

Unique immune cell linked to aggressive leukemia may lead to improved treatment outcomes

A new study by Indiana University School of Medicine researchers has revealed a breakthrough in the fight against acute myeloid leukemia, one of the most aggressive and fatal blood cancers in adults. The discovery of a previously unrecognized immune cell could lead to new therapies that are less treatment-resistant than current options for patients—meaning higher survival rates for people with blood cancers.

Acute myeloid leukemia is a cancer that begins in the bone marrow and leads to impaired and function. Currently the sixth-leading cause of cancer-related death in adults, acute myeloid leukemia is resistant to many and relapse is common.

“Despite transformative progress in the treatment of many blood cancers, acute myeloid leukemia therapies have remained largely unchanged for over three decades,” said Reuben Kapur, Ph.D., director and program leader of the Hematologic Malignancies and Stem Cell Biology Program at the IU School of Medicine Herman B Wells Center for Pediatric Research, a researcher with the IU Melvin and Bren Simon Comprehensive Cancer Center and co-author of the study.

Next-gen tech for at-home use can quickly detect endometriosis biomarker in period blood

Almost 200 million people, including children, around the world have endometriosis, a chronic disease in which the lining of the uterus grows outside of the uterus. More severe symptoms, such as extreme pain and potentially infertility, can often be mitigated with early identification and treatment, but no single point-of-care diagnostic test for the disease exists despite the ease of access to the tissue directly implicated.

While Penn State Professor Dipanjan Pan said that the blood and tissue shed from the uterus each month is often overlooked—and even stigmatized by some—as medical waste, menstrual effluent could enable earlier, more accessible detection of biological markers to help diagnose this disease.

Pan and his group have developed a proof-of-concept device capable of detecting HMGB1, a protein implicated in endometriosis development and progression, in menstrual blood with 500% more sensitivity than existing laboratory approaches. The device, which looks and operates much like a pregnancy test in how it detects the protein, hinges on a novel technique to synthesize nanosheets made of the atomically thin 2D material borophene, according to Pan, the Dorothy Foehr Huck & J. Lloyd Huck Chair Professor in Nanomedicine and corresponding author of the study detailing the team’s work.

Tailored deep brain stimulation improves walking in Parkinson’s disease

For patients with Parkinson’s disease, changes in their ability to walk can be dramatic. “Parkinson’s gait,” as it is often called, can include changes in step length and asymmetry between legs. This gait dysfunction reduces a person’s mobility, increases fall risk, and significantly impacts a patient’s quality of life.

While (DBS) is highly effective for lessening symptoms of tremors, rigidity, and bradykinesia (the slowing of movement), its impact on gait has been more variable and less predictable among patients with advanced gait-related problems. Significant challenges in enhancing DBS outcomes for advanced gait disorders have included the lack of a standardized gait metric for clinicians to use during programming, as well as understanding the impact of different stimulation factors on gait.

In a recent study, researchers at UCSF developed a systematic way to quantify key aspects of gait relevant to Parkinson’s and used machine learning to identify the best DBS settings for each individual. These personalized settings led to meaningful improvements in walking, such as faster, more stable steps, without worsening other symptoms.

AI vision, reinvented: Vision-language models gain clearer sight through synthetic training data

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source systems like ChatGPT and Claude currently set the pace. But no one outside their makers knows how those models were trained or what data they used, leaving open-source alternatives scrambling to catch up.

Now, researchers at Penn Engineering and the Allen Institute for AI (Ai2) have developed a new approach to train open-source models: using AI to create scientific figures, charts and tables that teach other AI systems how to interpret complex visual information.

Their tool, CoSyn (short for Code-Guided Synthesis), taps open-source AI models’ coding skills to render text-rich images and generate relevant questions and answers, giving other AI systems the data they need to learn how to “see” and understand scientific figures.

Translating the m6A epitranscriptome for prostate cancer

Mapping the N6-methyladenosine (m6A) transcriptome in prostate cancer has established its clinical potential value as a prognostic biomarker for this disease. A multidisciplinary approach that integrates genomics, transcriptomics, epitranscriptomics, proteomics and clinical oncology is essential to translate the intricacies of m6A modification into tangible benefits for patients.

MethAgingDB: a comprehensive DNA methylation database for aging biology

Scientific Data — MethAgingDB: a comprehensive DNA methylation database for aging biology. MethAgingDB includes 93 datasets, with 11,474 profiles from 13 distinct human tissues and 1,361 profiles from 9 distinct mouse tissues. The database provides preprocessed DNA methylation data in a consistent matrix format, along with tissue-specific DMSs and DMRs, gene-centric aging insights, and an extensive collection of epigenetic clocks. Together, MethAgingDB is expected to streamline aging-related epigenetic research and support the development of robust, biologically informed aging biomarkers.

Suppressing tumor cell stemness might help colon cancer management

Colon cancer remains a major global health concern, ranking third among the most diagnosed cancers and the leading cause of cancer-related death worldwide. One critical factor that makes treating colon cancer challenging is the presence of cancer stem cells.

Though typically present in , these powerful cells drive tumor growth, resist standard treatments, and often contribute to relapse. They achieve this through their “stemness,” a set of properties that enable these cells to self-renew and differentiate into other cell types. Thus, understanding how stemness might be controlled at the is essential for developing effective therapies for colon cancer.

Over the past two decades, researchers have identified several key molecules involved in both the development of the colon and the progression of colon cancer. Among them are CDX1 and CDX2, two homeobox transcription factors that help establish and maintain the identity of intestinal epithelial cells.

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