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Curr Opin Biotechnol. 2025 Feb 5;92:103267. doi: 10.1016/j.copbio.2025.103267. Online ahead of print.

ABSTRACT

Intermolecular relationships at the cell surface dictate the behavior and regulatory network of cells. Such interactions often require precise spatial control for optimal response. By binding simultaneously to two different target sites, bispecific binders can bridge molecules of interest. Despite decades of bispecific development, only recently have bispecifics been engineered with programmable, tuneable geometries to replicate natural interaction geometries or achieve new responses from unnatural arrangements. This review highlights emerging methods of protein engineering and modular bioconjugation to control pairing and orientation of binders in bispecific scaffolds. We also describe novel biophysical and phenotypic assays, which reveal how bispecific geometries change cell fate. These approaches are informing design of next-generation precision therapeutics, as well as uncovering fundamental features of signal integration.

PMID:39914134 | DOI:10.1016/j.copbio.2025.103267

Health Promot J Austr. 2025 Apr;36(2):e951. doi: 10.1002/hpja.951.

ABSTRACT

ISSUE ADDRESSED: Adolescent e-cigarette use is increasing and is associated with subsequent smoking. This study examines potential protective factors associated with not vaping among First Nations adolescents in Australia to inform community programs.

METHODS: The 'Next Generation: Youth Wellbeing Study' is a cohort study of First Nations adolescents aged 10-24 years from urban, rural and remote communities in Central Australia, Western Australia and New South Wales. Analysis of self-reported vaping from 16 to 24-year-olds, collected 2018-2020, using multi-level mixed-effects Poisson regression to estimate age-site-adjusted prevalence ratios (PRs) for never-vaping in relation to various factors.

RESULTS: Among 419 participants, 65% were female, 75% had never vaped, 49% had never smoked and 82% lived in smoke-free homes. Never vaping was more common among those who had: never-smoked (PR = 1.78, 95%CI: 1.56-2.04); never used cannabis (1.89, 1.60-2.24); non-smoking friends (1.38, 1.26-1.51); good mental health (1.15, 1.01-1.30), never diagnosed with depression (1.21, 1.01-1.46) or anxiety (1.31, 1.08-1.57); and no experiences of racism (1.21, 1.08-1.36), no negative criminal justice system experiences (1.25, 1.11-1.41), or vicarious racism through negative media (1.24, 1.10-1.39).

CONCLUSIONS: Most First Nations adolescents have never vaped, with potential protective factors being better mental health, no other substance use and fewer experiences of racism and justice system interactions. Comprehensive community adolescent prevention programs are needed to prevent vaping and protect future health, including preventing nicotine addiction and future smoking. SO WHAT?: Policies and programs must address e-cigarettes directly as well as structural factors, promoting broader adolescent wellbeing, centring culture and family in a strengths-based approach.

PMID:39912122 | DOI:10.1002/hpja.951

Eur J Med Res. 2025 Jan 31;30(1):61. doi: 10.1186/s40001-025-02339-3.

ABSTRACT

Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, characterised by rapid progression and a poor prognosis. Survival analysis is an essential aspect of glioma management and research, as most studies use time-to-event outcomes to assess overall survival (OS) and progression-free survival (PFS) as key measures to evaluate patients. However, predicting survival using traditional methods such as the Kaplan-Meier estimator and the Cox Proportional Hazards (CPH) model has faced many challenges and inaccuracies. Recently, advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), have enabled significant improvements in survival prediction for glioma patients by integrating multimodal data such as imaging, clinical parameters and molecular biomarkers. This study highlights the comparative effectiveness of imaging-based, non-imaging and combined AI models. Imaging models excel at identifying tumour-specific features through radiomics, achieving high predictive accuracy. Non-imaging approaches also excel in utilising clinical and genetic data to provide complementary insights, whilst combined methods integrate multiple data modalities and have the greatest potential for accurate survival prediction. Limitations include data heterogeneity, interpretability challenges and computational demands, particularly in resource-limited settings. Solutions such as federated learning, lightweight AI models and explainable AI frameworks are proposed to overcome these barriers. Ultimately, the integration of advanced AI techniques promises to transform glioma management by enabling personalised treatment strategies and improved prognostic accuracy.

PMID:39891313 | DOI:10.1186/s40001-025-02339-3

Crit Care Nurse. 2025 Feb 1;45(1):52-60. doi: 10.4037/ccn2025452.

ABSTRACT

BACKGROUND: For patients receiving extracorporeal membrane oxygenation, early mobility decreases mechanical ventilation time, delirium incidence, and length of intensive care unit stay and improves physical functioning. Individual centers use institutional guidelines to develop ambulation protocols. Local Problem A quality improvement initiative was used to evaluate an ambulation protocol for adult intensive care unit patients receiving extracorporeal membrane oxygenation.

METHODS: Adult patients receiving extracorporeal membrane oxygenation who walked according to the protocol were compared with a historical control group of patients who walked without the protocol. Data analysis included descriptive statistics and independent t tests. Outcomes included adverse safety events, number of patients and ambulation sessions, standing and ambulation time, and distance.

RESULTS: From January to March 2021, 13 of 46 patients receiving extracorporeal membrane oxygenation (28%) walked according to the protocol. In the control group, 14 of 147 patients (10%) walked in 2019; 21 of 144 patients (15%) walked in 2020. Some characteristics of the control group (hospitalized before the COVID-19 pandemic) differed from those of the protocol group (hospitalized during the pandemic). Mean number of ambulation sessions was not significantly different between groups (protocol group, 10; control group, 9). Differences in mean standing time (protocol group, 121.23 minutes; control group, 210.80 minutes), ambulation time (protocol group, 11.77 minutes; control group, 198.70 minutes), and ambulation distance were not significant.

CONCLUSIONS: Standing time, ambulation time, and distance were not significantly different between the groups. The extracorporeal membrane oxygenation ambulation protocol demonstrated clinical significance by increasing the number of patients walking.

PMID:39889799 | DOI:10.4037/ccn2025452

Biomimetics (Basel). 2025 Jan 10;10(1):40. doi: 10.3390/biomimetics10010040.

ABSTRACT

In this preliminary study, the long-term effects of calcium chloride crosslinking concentration on viability of 16HBE14o- human bronchial epithelial cells embedded in alginate-extracellular matrix (ECM) or alginate-methylcellulose-ECM hydrogels have been investigated. There is currently a limited understanding regarding the effects of crosslinking solution concentration on lung epithelial cells embedded in hydrogel. Furthermore, the effects of calcium chloride concentration in crosslinking solutions on other cell types have not been reported regarding whether the addition of viscosity and stiffness tuning agents such as methylcellulose will alter the responses of cells to changes in calcium chloride concentration in crosslinking solutions. While there were no significant effects of calcium chloride concentration on cell viability in alginate-ECM hydrogels, there is a decrease in cell viability in alginate-methylcellulose-ECM hydrogels crosslinked with 300 mM calcium chloride crosslinking solution. These findings have implications in the maintenance of 16HBE14o- 3D cultures with respect to the gelation of alginate with high concentrations of ionic crosslinking solution.

PMID:39851756 | DOI:10.3390/biomimetics10010040