Protective Proteins Can Improve Cell-Free System Performance in Austere Environments

Cell-free gene expression (CFE) technology is an appealing expression chassis for fieldable synthetic biology. Reagents for cell-free protein expression can be preserved, transported, or stored over long periods, even at elevated temperatures. Therefore, cell-free synthetic biology efforts are practical for applications such as fieldable biosensing and decentralized or on-demand therapeutics production in austere environments and at emergency or natural disaster sites. However, these systems still require incubation to operate under standard conditions (e.g., 16 °C to 37 °C), whereas the conditions in the application environment often lie outside these limits. To address this technological gap, we propose adding heat-shock chaperones from diverse organisms to expand the cell-free system’s operating range. We present a method for assessing protective protein candidates, and we demonstrate a 100-fold improvement in fluorescent reporter expression at non-standard temperatures and a widening of the temperature range for system operation by more than 4 °C, as measured by fluorescence from reporter expression. Moreover, we show that dual-chaperone systems can yield higher fluorescence output compared to single-chaperone ones. These chaperone-inspired systems may perform in environments where standard ones fall short, expanding their usability and application potential.

Rose Genomics Research Associated with Important Agronomic and Ornamental Traits for Biobreeding: Progress, Challenges and Prospects

Rose is a globally significant ornamental crop and an emerging genomics system for woody ornamental plants. In recent decades, the rapid evolution of high-throughput sequencing and robust technical platforms has yielded high-quality reference genomes and been propelling our understanding of rose biology to unprecedented depths. This review systematically synthesizes the current landscape of rose genomics, recent development of technical and resource platforms, and the molecular mechanisms underlying pivotal agronomic traits such as floral development, scent biosynthesis, petal lifespan, and stress resilience. Despite these strides, high genome heterozygosity, polyploidy, and recalcitrance to genetic transformation remain significant barriers. We discuss how integrating cutting-edge technologies, such as pangenomics, single-cell transcriptomics, AI-assisted genomic selection, and precise CRISPR-based editing, can bridge the gap between fundamental research and practical applications. Collectively, this review provides a strategic roadmap for accelerating the development of next-generation rose cultivars through trait-based biobreeding.

Flood Vulnerability, Social Risk, and Economic Damage Assessment in the Lower Karnali River Basin, Nepal

The lower Karnali River basin is one of Nepal’s most flood-prone regions, yet it has lacked an integrated risk assessment. This study presents the first comprehensive analysis combining physical vulnerability, social vulnerability, and economic damage assessment for the corridor. Utilizing a validated 2D HEC-RAS model across eight return periods (2–500 years), we quantified impacts on 23,929 buildings, 477 km of roads, and 16,065 hectares of paddy cropland using locally calibrated depth-damage curves. Those calibrations were mainly focused on three building typologies, two road surface classes, and paddy crops at the maturity stage. A Social Vulnerability Index (SVI) was developed for 27 wards, integrating demographics, healthcare access, and education. Findings indicate total economic damages range from NPR 395 million (2-year) to NPR 3538 million (500-year), with buildings consistently accounting for the largest share (41–42%). Madhuwan Ward 6, Geruwa Ward 1, and Rajapur Ward 7 emerged as the highest combined flood risk hotspots through the integration of social vulnerability and physical hazard. The results prove that social infrastructure investment, particularly in healthcare, serves as a direct flood risk reduction measure. This research provides a spatially explicit evidence base to guide targeted mitigation, land-use policy, and social protection in the basin.

Diabetes Knowledge, Self-Management, and Belonging: A Community of Practice Perspective on Camp for Youth with Type 1 Diabetes

Youth with type 1 diabetes (T1D) often face barriers to recreation participation, disease self-management, and peer connection. This research note examined how a university-based diabetes camp, grounded in a Community of Practice (CoP) model, supported youth learning, self-management, and belonging. Participants were 33 youth, ages 11 to 18, attending a university-based diabetes day camp in Northern Utah. Self-reported, open-ended post-camp evaluation responses were analyzed using Braun and Clarke’s reflexive thematic analysis. Three themes were identified: applied diabetes knowledge, intentional self-management in active settings, and belonging through shared experience. Findings suggest that recreation-based camp programming supported practical diabetes learning, more deliberate self-management behaviors, and meaningful peer relationships, thereby reducing isolation and normalizing living with T1D. Results highlight the value of interdisciplinary, recreation-centered CoP models for creating supportive recreation spaces for youth with chronic health conditions.

Neurotechnology in Stroke Neurorehabilitation: Towards Precision and Personalized Rehabilitation Treatment

Given the large global population of stroke survivors and limited rehabilitation resources, efficient treatments are urgently needed to help patients regain independence and reintegrate into society. In this review, we discuss how artificial intelligence and neurotechnology can be used to accelerate neurorehabilitation after stroke. First, we introduce neurorehabilitation mechanisms that provide the basis for neurotechnology development. Next, we describe how neurophysiological and neuroimaging biomarkers can be used for multimodal assessment and prognostic prediction. We then provide examples of brain-computer interface (BCI)-driven rehabilitation robots and BCI-triggered transcranial and peripheral neuromodulation for closed-loop rehabilitation training.

Trait Number and Coding Shape Estimates of Functional Diversity

Functional diversity estimates increasingly inform ecological research, yet how methodological choices such as trait number and coding affect common metrics remains poorly quantified. Here, we systematically evaluate the effects of trait number and coding strategy on functional diversity metrics using benthic macroinvertebrate traits. Across 14 functional diversity indices representing functional richness, evenness, dispersion, and redundancy, we showed that metric responses to trait number are highly facet-dependent. Functional richness and evenness indices were particularly sensitive to trait number, whereas dispersion and redundancy metrics were comparatively stable. Estimation uncertainty was minimized at intermediate trait number, indicating a potential balance between functional space resolution and statistical robustness. Despite broad consistency between binary and fuzzy coding approaches for several metrics, redundancy metrics showed substantial divergence between coding schemes. These results demonstrate that hidden methodological decisions can substantially influence functional diversity indices. Our study provides a quantitative framework for evaluating metric robustness and reveals that widely used indices differ fundamentally in their response to dimensionality—a mathematical behaviour that must be understood before ecological interpretation. We recommend reporting trait number alongside functional diversity values and exercising caution when comparing communities assessed with different trait sets, particularly for richness and evenness metrics.

What Should Ecology Study for Watershed?

Microalgae as a Sustainable Bioresource for Bioplastic Production

Bioplastics are biomaterial-derived plastics and are superior to petrochemical-based plastics in terms of resource renewability, planetary sustainability, and environmental biodegradability. Extensive research has been carried out over the last decades to identify and characterize desirable biomaterials for bioplastic manufacturing, and among those explored, microalgal biomass has received special attention due to its numerous advantages over other bioresources, including high areal productivity, the potential to use non-arable land, and the ability to reduce waste. Nonetheless, the cultivation and biorefinery processes for microalgae still need innovative development to make microalgal bioplastics economically viable. The primary focus of this review is to examine the established and emerging technologies for manufacturing bioplastics from microalgal biomass, starting from the exploration of bioresource availability and outlining technical routes of production. In particular, both upstream and downstream processes of microalgal cultivation pertinent to bioplastic production are reviewed in detail, analyzed in depth, and evaluated from the perspective of economic viability. The technical challenges and research opportunities, as well as prospects of current approaches and future methodologies for microalgal production of bioplastics, are also discussed, mostly based upon our research experiences in microalgal bioengineering, and it is our opinion that, despite these existing challenges, microalgal biomass could still be one of the most promising feedstocks for sustainable manufacturing of bioplastics.

Electromagnetic Tracking for Rehabilitation Applications—A Survey

Motion tracking plays a crucial role in the quantitative assessment and clinical rehabilitation of motor symptoms. While optical tracking and inertial sensing are mainstream, they are frequently limited by line-of-sight occlusions or data drift. Electromagnetic tracking (EMT) technology offers a powerful complementary solution due to its unique capabilities in full-pose tracking and occlusion-free measurements. To facilitate the integration of this technology into medical settings, this paper presents a structured overview of EMT approaches within rehabilitation applications. We systematically review the field from foundational physics and hardware architectures to advanced algorithmic frameworks. Particular emphasis is placed on recent breakthroughs in interference compensation and data-driven methods that enhance tracking robustness. Furthermore, we categorize representative clinical applications by scenario and target population, ultimately outlining key research trends and open opportunities to guide future development in this expanding domain.

An Overview for Optimal Planning and Reliable Operations of Multi Vector Energy Systems for On-Grid and Standalone Applications

The increasing global demand for electricity has accelerated the integration of renewable energy sources, including solar photovoltaic (PV) systems, wind energy conversion systems (WECS), and battery energy storage systems (BESS), into modern power networks. Although these resources improve sustainability and reduce dependence on fossil fuels, their intermittent and variable nature introduces significant challenges related to system reliability, power quality, operational costs, and energy management, particularly in standalone and off-grid applications. This study presents a comprehensive review and analysis of both standalone and grid-connected renewable energy systems employed in distributed generation. Special emphasis is placed on evaluating the impact of renewable energy variability on system performance and reliability. Furthermore, the study investigates the role of green hydrogen technologies, including electrolyzes and fuel cells, as long-term energy storage solutions in hybrid renewable energy systems. The findings indicate that integrating green hydrogen with solar and wind resources can significantly enhance energy reliability, improve system flexibility, and ensure a continuous power supply in off-grid environments. The study highlights hybrid green hydrogen-based renewable energy systems as a promising pathway toward sustainable, reliable, and resilient future energy infrastructures.