An adaptable microreactor to investigate the influence of interfaces on Pseudomonas aeruginosa biofilm growth

Biofilms are ubiquitous and notoriously difficult to eradicate and control, complicating human infections and industrial and agricultural biofouling. However, most of the study had used the biofilm model that attached to solid surface and developed in liquid submerged environments which generally have neglected the impact of interfaces. In our study, a reusable dual-chamber microreactor with interchangeable porous membranes was developed to establish multiple growth interfaces for biofilm culture and test. Protocol for culturing Pseudomonas aeruginosa (PAO1) on the air–liquid interface (ALI) and liquid–liquid interface (LLI) under static environmental conditions for 48 h was optimized using this novel device. This study shows that LLI model biofilms are more susceptible to physical disruption compared to ALI model biofilm. SEM images revealed a unique “dome-shaped” microcolonies morphological feature, which is more distinct on ALI biofilms than LLI. Furthermore, the study showed that ALI and LLI biofilms produced a similar amount of extracellular polymeric substances (EPS). As differences in biofilm structure and properties may lead to different outcomes when using the same eradication approaches, the antimicrobial effect of an antibiotic, ciprofloxacin (CIP), was chosen to test the susceptibility of a 48-h-old P. aeruginosa biofilms grown on ALI and LLI. Our results show that the minimum biofilm eradication concentration (MBEC) of 6-h CIP exposure for ALI and LLI biofilms is significantly different, which are 400 μg/mL and 200 μg/mL, respectively. These results highlight the importance of growth interface when developing more targeted biofilm management strategies, and our novel device provides a promising tool that enables manipulation of realistic biofilm growth. Key points • A novel dual-chamber microreactor device that enables the establishment of different interfaces for biofilm culture has been developed. • ALI model biofilms and LLI model biofilms show differences in resistance to physical disruption and antibiotic susceptibility.

Newborn skin maturity models for gestational age prediction

A multicenter clinical trial evaluated the accuracy of a novel device to detect preterm newborns. A portable multiband reflectance photometric device assessed 781 newborns’ skin maturity and used machine learning models to predict reference gestational age, adjusting it to birth weight and antenatal corticosteroid therapy exposure. The day difference between the reference and the test had a median of -1.4 (IQR: -2.1). Using established methods such as comparator ultrasound and last menstrual period (LMP), the medians were 0 (IQR: 4) and 0.01 (IQR: 4), respectively. For prematurity discrimination, the area under the receiver operating characteristic curve (AUROC) was 0.986 (95% CI: 0.977 to 0.994). In newborns with absent or unreliable LMP, the intent-to-discriminate analysis showed that the test generated correct classifications 95.8% of the time. The assessment of the newborn's skin maturity adjusted by learning models promises accurate pregnancy dating at birth without the use of antenatal ultrasound reference.

Performance of a Multisensor Smart Ring to Evaluate Sleep: In-Lab and Home-Based Evaluation Relative to Polysomnography and Actigraphy: Importance of Generalized Versus Personalized Scoring

Study Objectives: Wearable sleep technology has rapidly expanded across the consumer market due to advances in technology and increased interest in personalized sleep assessment to improve health and performance. In this study, we tested the performance of a novel device, alongside other commercial wearables, against in-lab and at-home polysomnography (PSG). Methods: 36 healthy adults were assessed across 77 nights while wearing the Happy Ring, as well as the Actiwatch, Fitbit, Whoop, and Oura Ring devices. Subjects participated in a single night of in-lab PSG and 2 nights of at-home PSG. The Happy Ring includes sensors for skin conductance, movement, heart rate, and skin temperature. Epoch-by-epoch analyses compared the wearable de-vices to both in-lab and at-home PSG. The Happy Ring utilized two machine-learning derived scor-ing algorithms: a generalized algorithm that applied broadly to all users, and a personalized algorithm that adapted to the data of individual subjects. Results: Compared to in-lab PSG, the generalized and personalized algorithms demonstrated good sensitivity (94% and 93%, respectively) and specificity (70% and 83%, respectively). The other wearable devices also demonstrated good sensitivity (89%-94%) but lower specificity (19%-54%), relative to the Happy Ring. Accuracy was 91% for generalized and 92% for personalized algorithms, compared to other devices that ranged from 84%-88%. The generalized algorithm demonstrated an accuracy of 67%, 85%, and 85% for light, deep, and REM sleep, respectively. The personalized algorithm was 81%, 95%, and 92% accurate for light, deep, and REM sleep, re-spectively. Conclusions: The Happy Ring performed well at home and in the lab, especially regarding sleep-wake detection. The personalized algorithm demonstrated improved detection accuracy over the generalized approach and other devices, suggesting that adaptable, dynamic algorithms can enhance sleep detection accuracy.

Safety and Performance Evaluation of Su2ura Approximation, a New Suturing Device, in Pigs

One of the challenging aspects of minimal invasive surgery (MIS) is intracorporal suturing, which can be significantly time-consuming. Therefore, there is a rising need for devices that can facilitate the suturing procedure in MIS. Su2ura Approximation Device (Su2ura Approximation) is a novel device developed to utilize the insertion of anchors threaded with stitches to allow a single action placement of a suture. The objective of this study was to evaluate the long-term safety and tissue approximation of Su2ura Approximation in comparison to Endo Stitch + Surgidac sutures in female domestic pigs. All incision sites were successfully closed by both methods. Firm consolidation within and around the incision site was noted in several animals in both treatment groups, which corresponded histopathologically to islands of ectopic cartilage or bone spicules within the fibrotic scar. These changes reflect heterotopic ossification that is commonly seen in the healing of abdominal operation sites in pigs. No other abnormal findings were observed throughout the study period. In conclusion, the use of Su2ura Approximation under the present experimental conditions revealed no safety concerns.

Newborn skin maturity models for gestational age prediction

A multicenter clinical trial evaluated the accuracy of a novel device to detect preterm newborns. A portable multiband reflectance photometric device assessed 781 newborns’ skin maturity and used machine learning models to predict reference gestational age, adjusting it to birth weight and antenatal corticosteroid therapy exposition. The day difference between the reference and the test had a median of -1.4 (IQR: -2.1). Using established methods such as comparator ultrasound and last menstrual period (LMP), the medians were 0 (IQR: 4) and 0.01 (IQR: 4), respectively. For prematurity discrimination, the area under the receiver operating characteristic curve (AUROC) was 0.986 (95% CI: 0.977 to 0.994). In newborns with absent or unreliable LMP, the intent-to-discriminate analysis showed that the test generated correct classifications 95.8% of the time. The assessment of the newborn's skin maturity adjusted by learning models promises accurate pregnancy dating at birth without the use of antenatal ultrasound reference.

A Review of Cold Atmospheric Pressure Plasmas for Trauma and Acute Care

Despite the high overall survival rates of severely injured military and civilian personnel requiring trauma and acute care, the challenges of treating infections and healing-resistant wounds have grown. Exposure to unknown environmental pathogens at the wound, including parasites and antibiotic resistant microorganisms, hinders timely and effective treatment using traditional techniques. Cold atmospheric pressure plasma (CAPP) provides a promising biophysical tool to address these issues by applying physically created modalities that cannot be circumvented by bioresistance to inactivate microorganisms and enhance wound healing. CAPPs generate charged particles and numerous reactive oxygen species (ROS) and reactive nitrogen species (RNS) that act on biological cells and tissues, often through plasma membrane interactions. This review fills a gap in the plasma medicine literature by specifically focusing on applying CAPPs for acute trauma, such as surgery, wound treatment, and disinfection. After briefly highlighting the areas of opportunity for improving acute trauma treatment and the fundamentals of CAPP generation, this review details emerging applications of CAPPs for enhanced wound healing, burn treatment, transdermal delivery, and surgical applications. We also discuss CAPP optimization through novel device design and synergistic combination with traditional treatment technologies to transition this biophysical technology to the battlefield and acute care settings.