Cordica Medical acquires RapidWerks micro-molding capability

NEWS RELEASE: Cordica Medical acquires RapidWerks micro-molding Expanding Cordica Medical’s precision capabilities for the miniaturization of next-generation medical devices KNOXVILLE, Tenn. — Cordica Medical (Cordica), a medical device contract development and manufacturing organization (CDMO), announced that it has acquired RapidWerks’ micro-molding capabilities. The acquisition adds dedicated, fully automated micro-molding for mass production to Cordica’s integrated design…

The post Cordica Medical acquires RapidWerks micro-molding capability appeared first on Medical Design and Outsourcing.

<![CDATA[AI analyzes wearable data to reveal objective biomarkers for ADHD and anxiety, enabling passive tracking and earlier psychiatric detection.]]>

Neonatal Neurological Observation With Video AI

Conditions: Neonatal Encephalopathy; Hypoxic-Ischemic Encephalopathy; Sedation; Sleep

Interventions: Device: Continuous bedside video monitoring with AI anatomic landmark tracking for neurologic monitoring

Sponsors: Artemis AI Labs

Not yet recruiting

STAT+: After hospitals, patients get a turn to bring AI into the doctor’s office

Patients are getting used to being recorded in the doctor’s office. More than a quarter of U.S. practices now use AI-based listening tools called ambient scribes, which capture visits in real time and draft clinical notes for clinicians to enter into patients’ medical records. 

But what happens when it’s the patient doing the recording?

Nearly every patient now has a recording device in their pocket, and commercial large language models have made it easier than ever for them to transcribe and interpret audio files. A growing number of consumer apps — with names like VisitRecall, Advoca Health, and AlignCare — are using AI to do just that, delivering summaries and action items for patients after the fact. One called Kin Health, with backing from the co-founder of GoodRx, announced a $9 million seed round in May. 

Continue to STAT+ to read the full story…

Wearable Sensor–Derived Gait Parameters Across Self-Reported Physical Activity Levels in Individuals With Knee Osteoarthritis and Healthy Controls: Pilot Cross-Sectional Validation Study

Background: Wearable inertial measurement units (IMUs) offer scalable, objective gait assessment, but detailed stride-level validation against motion capture and their ability to reflect physical activity (PA)–related gait differences in knee osteoarthritis (KOA) remain incompletely characterized. Objective: This study aimed to evaluate the technical validity of foot-mounted IMU–derived gait parameters compared with optical motion capture in individuals with KOA and healthy controls. As a secondary exploratory aim, we assessed whether IMU-derived gait parameters differed across self-reported PA levels. Methods: In this pilot cross-sectional validation study, 20 participants (KOA: n=10, 50%; healthy controls: n=10, 50%) completed 3 standardized walking conditions (self-paced, fast-paced, and endurance-equivalent). IMU-derived gait parameters were compared with motion capture at the stride level (≥5000 strides) using Pearson correlation, intraclass correlation coefficients (ICCs), mean absolute error, root mean square error, and Bland-Altman analysis. Participants completed the Stanford Brief Activity Survey to categorize PA level. Secondary analyses emphasized effect sizes and 95% CIs given the pilot design. Feasibility was assessed by protocol completion, data completeness, and tolerability. Results: IMU-derived gait speed demonstrated strong agreement with motion capture (=0.99; ICC=0.98, 95% CI 0.95‐0.99; mean absolute error=0.07 m/s; bias=0.01 m/s; 95% limits of agreement −0.14 to 0.16 m/s). Stride length and cadence showed similarly high agreement (ICC range 0.96‐0.97). All participants completed the protocol with minimal adverse events. Exploratory analyses suggested that participants reporting higher PA demonstrated directionally faster gait speed and longer stride length, with small-to-moderate effect sizes, whereas inactive participants exhibited higher stance-related rhythm parameters. Conclusions: Foot-mounted IMUs demonstrated strong stride-level agreement with motion capture across walking conditions, supporting technical validity in both KOA and healthy populations. Exploratory findings suggest that wearable-derived gait parameters may reflect activity-related differences; however, larger longitudinal studies are required to confirm these preliminary signals.
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Nanotube Sensor Provides Chemical Imaging for Earlier Detection of Bladder Cancer Recurrence

Researchers at the Massachusetts Institute of Technology (MIT) have developed a catheter-based nanosensor that can detect the recurrence of bladder cancer at an earlier stage by identifying a biomarker released by tumors directly within the bladder. The technology, detailed in Nature Nanotechnology, combines carbon nanotube sensors with a rotating optical imaging device to create what researchers describe as a three-dimensional chemical imaging platform capable of locating cancer-associated biomarkers within tissue.

“It’s like a camera for molecules instead of light,” said Michael Strano, PhD, a professor of chemical engineering at MIT and senior author of the study. “If you have a billion nanosensors in an array, you can use them to make a chemical image that helps you locate their source.”

Roughly 85,000 people in the U.S. are diagnosed with bladder cancer each year, and more than half of patients experience recurrence within five years. The disease also carries among the highest lifetime treatment costs because patients require ongoing surveillance.

The new method addresses a major challenge in detecting bladder cancer recurrence, which currently relies on urinalysis to look for signs cancer has returned. Using urine for detection is hindered since biomarkers of cancer recurrence are diluted, degraded, and are often cleared shortly after they are released by the new tumor.

To address this, the MIT researchers targeted the matrix protein 22 (NMP-22), an FDA-approved biomarker for bladder cancer. While it is possible to detect NMP-22 in urine, the shortcomings of that method often mean that the cancer is often only found at a later stage of development.

To overcome this gap, the MIT team looked for a way to develop a sensor that could work inside the bladder. Their device consists of a urinary catheter coated with specialized nanosensors that detect the presence of NMP-22. A miniature rotating ball lens embedded in the catheter tip emits laser light and collects fluorescent signals generated by the nanotubes when they interact with the target biomarker.

Over the past decade, Strano’s laboratory has focused on developing carbon nanotube-based sensors that can identify specific molecules. The team customizes nanotubes for each application by applying different polymer coatings that function as “synthetic antibodies,” enabling them to bind to disease biomarkers. Previous development efforts in the lab have yielded sensors capable of detecting molecules such as hydrogen peroxide, riboflavin, and viral proteins.

For the bladder cancer application, researchers engineered a phospholipid-containing a synthetic polymer that selectively recognizes NMP-22. The project was partly motivated by earlier computational modeling conducted by the team, which suggested that placing sensors near an emerging bladder tumor could produce “a more than 50,000-fold increase in detection limit by minimizing biomarker dilution and degradation.” That finding pointed toward the potential advantages of measuring biomarkers at their source rather than after they enter urine.

In experimental testing, the platform achieved a 182-fold signal enhancement compared with biofluid sampling. The new technology was tested in multiple ways. The researchers first tested the nanosensors against six bladder cancer cell lines and healthy fibroblast cells and found distinct sensor responses associated with cancer-cell apoptosis. The team also used the chemotherapy drug gemcitabine to induce cancer cell death in vitro and monitored the resulting release of biomarkers. siRNA analysis confirmed that NMP-22 was a major contributor to the detected signals.

Researchers then evaluated the platform in porcine bladder models using a catheter coated with the specially designed nanotubes. Using a rotating ball lens system, they generated chemical maps showing the location of biomarker sources and demonstrated detection at distances up to two centimeters from the source. The researchers also reported a simulated tumor resolution of 16 square millimeters.

The chemical imaging capability is a unique attribute of the new method and the information it can provide should be very useful for treating recurrent cancer. “If you are scanning over a region of tissue, you would like to know not just that there is a signal indicating that a tumor is there, but also its location so that you can treat it or perform a biopsy,” Strano said. “Before an early-stage tumor breaks through the urothelium so that it’s visible, it’s under the surface but still emitting chemical signals that can be imaged.”

While the study focused on bladder cancer, the researchers indicated that the underlying platform may have broader applications. By replacing the nanosensors with versions designed to recognize other biomarkers, the system could potentially be adapted for additional cancers or for diseases affecting the cardiovascular or gastrointestinal systems.

“The beauty of polymer chemistry is that if we understand the molecular structures of target biomarkers and the design principles of binding sites, we can develop new sensors tailored to different diseases,” said lead author Wonjun Yim, PhD.

Future work will focus on expanding the range of detectable analytes, developing multiplexed sensor arrays, conducting omics-based biomarker validation studies, and improving optical engineering. The researchers also aim to miniaturize the imaging system and integrate the technology into cystoscopes already used in clinical practice.

The post Nanotube Sensor Provides Chemical Imaging for Earlier Detection of Bladder Cancer Recurrence appeared first on Inside Precision Medicine.

Feasibility of Technology-Assisted Lifestyle Self-Monitoring in Older Adults With Type 2 Diabetes: Mixed Methods Pilot Study

Background: Type 2 diabetes is a major public health concern in older adults. Healthy lifestyles, such as physical activity and healthy eating, are effective strategies for diabetes self-management. Increasing evidence shows that health technologies can promote healthy lifestyles for diabetes management. However, limited research has evaluated their use among older adults with type 2 diabetes. Objective: This study evaluated the feasibility and preliminary health outcomes of technology-assisted lifestyle monitoring for diabetes management in older adults with type 2 diabetes. The study also examined participants’ experiences to identify barriers and facilitators to sustained technology-assisted lifestyle modification. Methods: This 12-week pilot study used a pretest and posttest design. Feasibility was assessed by recruitment, retention, and adherence to device-based self-monitoring, including the percentage of days with tracked steps (PDWTs) and the percentage of days with food logs (PDWFLs). Fitbit fitness trackers paired with smartphone apps were used to track physical activity and food intake in 15 overweight/obese older adults with type 2 diabetes (mean age 70.5, SD 4.8 y). Self-monitoring behaviors were tracked throughout the study. Baseline and 12-week health outcomes (eg, hemoglobin A [HbA] and physical function) were compared using paired 2-tailed tests or Wilcoxon signed rank tests, as appropriate; effect sizes were calculated using Cohen . Associations between self-monitoring data (PDWTs, average daily steps, PDWFL) and health outcomes were examined using Pearson or Spearman correlations. Semistructured interviews were conducted at the study completion, and thematic analysis was used to analyze qualitative data. Results: The target sample (n=15) was successfully enrolled over 6 months, with 100% retention at 12 weeks. Feasibility was supported by consistent use of wearable devices for self-monitoring of physical activity, although dietary logging adherence varied. HbA decreased from baseline to 12 weeks (effect size −0.49, 95% CI –1.15 to –0.04; =.04), and PDWFL was inversely correlated with HbA (=−0.53; =.04) at follow-up. The qualitative findings indicated that barriers and facilitators to technology-assisted lifestyle self-monitoring and diabetes management through lifestyle modifications exist across multiple levels, including the individual, interpersonal, organizational or community, and societal levels in older adults with type 2 diabetes. Factors at one level interacted with those at other levels. For example, limited technological proficiency challenged lifestyle tracking, while interpersonal and organizational support helped mitigate barriers. Conclusions: Technology-assisted self-monitoring of lifestyle behaviors was feasible in this sample of older adults with type 2 diabetes and was associated with favorable signals in glycemic control. While causal inferences cannot be drawn from this single-arm pilot study, observed within-subject changes and behavioral-clinical correlations support further evaluation of technology-assisted lifestyle self-monitoring. The findings also highlight the importance of addressing interconnected factors at multiple levels, tailored to older adults’ unique needs and capacities in diabetes self-management.
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