Thermochromic smart windows (TSWs) exploit temperature-driven phase transitions to autonomously regulate solar and thermal radiation, offering a promising clean technology for reducing building energy demand and enhancing indoor comfort. Despite rapid advances in thermochromic materials, large-scale deployment of TSWs remains limited by coupled challenges in performance regulation, durability, climate adaptability, and architectural integration. This review examines the scientific and technological barriers that constrain the transition of TSWs from laboratory innovation to building-scale application. We first explored the fundamental trade-offs governing solar and visible light modulation, thermal emissivity control, and switching behaviors across diverse climatic contexts, and discussed how this performance requirements interact with long-term environmental stability. We then analyzed pathways for engineering translation, including scalable fabrication, integration within building systems and the implications of window behavior for occupant experience and operational control. Looking ahead, TSWs development is shifting from isolated material optimization toward spectrally intelligent envelope systems. Future progress will depend on standardized design guidelines, clear regulatory responsibilities for long-term service, and system-level integration with adaptive building control. These advances position TSWs as a component of climate-resilient building envelopes capable of contributing to cleaning thermal infrastructure in a warming world.

Nuclear factor erythroid 2-related factor 2 (NRF2) is a master regulator of antioxidant signaling. Xirouchaki et al. show that NRF2 activation in skeletal muscle regulates metabolic homeostasis and healthy aging. Complementary evolutionary adaptations enhancing NRF2 signaling in horses underscore its role in muscle function and metabolism.

Circulating tumor cell (CTC) clusters are potent drivers of metastasis, exhibiting markedly greater metastatic capacity than single CTCs. Beyond homotypic CTC clusters, CTCs dynamically engage immune cells to form heterotypic clusters with enhanced metastatic fitness. Rather than passive assemblies, these clusters function as coordinated metastatic ecosystems, integrating adhesion, immune modulation, and metabolic adaptation to promote survival, plasticity, and immune evasion. Recent advances in CTC isolation, single-cell and spatial multiomics, and artificial intelligence-driven analyses have enabled unprecedented resolution of these dynamic interactions. Together, these findings support a conceptual shift from isolated single-cell dissemination to multicellular cooperation as an important principle of metastasis and identify CTC-immune cell clusters as actionable targets for next-generation therapies to boost immunity and prevent metastasis.

Immune checkpoint inhibitors (ICIs) elicit durable antitumor responses in immunogenic tumors but still fail in most patients. Extensive research has elucidated how ICIs trigger a wide array of antitumor responses, yet, unexpectedly, also fuel tumor immunosuppression, a major driver of therapy failure. We argue that the sheer number of variables at play will hinder upcoming research to improve ICI performance, making the classic experimental approach exceedingly time- and resource-intensive. We posit that this problem can be solved through a bidirectional feedback loop of mathematical modeling and experimental validation. This review consolidates foundational knowledge in cancer immunology and mathematical modeling and proposes strategies that enable mathematicians and immunologists to collaborate fruitfully and expedite breakthroughs in ICI therapy.

With the deep integration of renewable energy and DC loads, DC microgrids have become critical components of modern power systems. The widespread application of software-intensive controllers and power electronic devices has enhanced system flexibility but has also notably increased the risks of cyber-attacks and actuator faults. Such risks may compromise system stability and, in severe cases, cause damage to critical equipment, resulting in substantial economic losses. To address these issues, this paper proposes a distributed adaptive fault-tolerant control strategy based on fixed-time consensus and deep reinforcement learning (DRL), aiming to enhance the operational reliability of DC microgrids under actuator fault conditions. Firstly, the actuator fault effects are mapped to corruptions of control signals, which are adaptively compensated by voltage and current secondary control. Then, current sharing and voltage recovery mechanism under actuator faults is proposed based on fixed-time consensus and DRL algorithms. Besides, the fixed-time stability of the proposed control strategy is rigorously proven through the Lyapunov function. Simulation and control-hardware-in-the-loop (CHIL) experiments demonstrate that the proposed strategy exhibits excellent fault-tolerant capability and robustness under various actuator faults, load changes and communication interruptions.

Direct-to-consumer (DTC) DNA testing has led to a surge in misattributed parentage discoveries, often referred to as "not parent expected" (NPE) events. While prior research has focused primarily on the experiences of those discovering a parent was not as expected, this qualitative study explores the systemic impact of NPE events on entire families by examining how such discoveries are experienced by multiple family members. Drawing on in-depth interviews with 43 members of 11 families in the United States and Canada, we identified four interrelated processes characterizing family responses to NPE discoveries: systemic disruption, intergenerational secrecy and betrayal, ambiguous loss and identity renegotiation, and adaptive realignment over time. Guided by Family Systems Theory, Ambiguous Loss Theory, Betrayal Trauma Theory, and Communication Privacy Management Theory, we illustrate how NPE discoveries destabilize family roles, challenge kinship boundaries, and prompt complex negotiations of trust, identity, and information sharing. Our results highlight the widespread emotional impact on family members and the varied pathways they take toward adaptation, with outcomes shaped by pre-existing family dynamics, the response of the parent who had been keeping the secret, and the family's capacity for open communication and meaning making. Implications of this research include the need for family-centered therapeutic interventions, enhanced education and training for mental health professionals to address the unique challenges NPE discoveries pose, and greater public awareness of the psychosocial consequences these events have on families.

The protein composition of sperm and seminal fluid are key to male fitness. However, we currently lack an understanding of the factors that shape seminal proteome composition. The common bedbug (Cimex lectularius) mates by traumatic insemination, subjecting the ejaculate to a unique selective environment as sperm traverse the female genital and paragenital system. We provide the first high-throughput proteomic characterisation of the sperm and seminal fluid proteome in a hemimetabolous insect and the first in-depth proteomic characterisation of the male bedbug reproductive system. Our analysis revealed conserved and unique features of the bedbug sperm and seminal fluid proteome possibly linked to traumatic insemination. The sperm proteome showed elevated rates of molecular evolution, unlike most other studied insect species, yet also contained many conserved proteins. Notably, we found that bedbugs and other hemimetabolous insects share an expansion of Sperm-leucylaminopeptidases (S-Laps). Using in silico protein-ligand binding predictions, we show that S-Laps have likely retained catalytic activity in bedbugs. Our results provide a foundation for future studies of this expanding global pest.

Portopulmonary hypertension (PoPH) is a complex and underrecognized form of pulmonary arterial hypertension arising in the setting of portal hypertension, in which outcomes are driven by the interplay between pulmonary vascular disease and liver dysfunction. Despite advances in hemodynamic definitions and targeted therapies, PoPH remains associated with significant morbidity and mortality, largely due to delayed diagnosis, challenges in risk stratification, and the absence of disease-specific management strategies. Recent insights support a paradigm shift from a purely hemodynamic view toward an integrated model encompassing pulmonary vascular load, right ventricular adaptation and hepatic reserve. This multidimensional framework has important implications for screening, prognostic assessment and therapeutic decision-making, particularly in the context of liver transplantation, where treatment is increasingly aimed at achieving transplant eligibility. In this review, we provide a comprehensive and clinically oriented overview of PoPH, integrating current evidence on pathophysiology, diagnosis, risk stratification and management. We highlight key limitations of existing approaches, discuss emerging therapeutic strategies and propose a conceptual framework to guide clinical practice and future research in this challenging condition.

Hepatotoxicity remains one of the most frequent and clinically important safety concerns in adeno-associated virus (AAV) gene therapy. Yet the laboratory patterns observed after vector administration are biologically complex and often difficult to interpret. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevations are non-specific, as they may arise from AAV-induced innate and adaptive immune recognition of vector capsid, endoplasmic reticulum stress, mitochondrial strain, cholestasis, or background muscle turnover, especially in neuromuscular disorders where ALT and AST frequently exceed upper limits of normal at baseline. Traditional drug-induced liver injury frameworks, which rely on fixed multiples of population-derived reference ranges, are poorly suited to these settings and risk both overcalling benign changes and overlooking evolving toxicity. This clinical practice review outlines a mechanism-anchored strategy for interpreting hepatic biomarkers in AAV trials. We describe how vector tropism, intracellular capsid burden, and immune kinetics shape post-dose laboratory trajectories across systemic, liver-directed, and neuromuscular programs. The tissue specificity and kinetic behavior of hepatic biomarkers are examined to show why no single analyte is reliable in isolation. A personalized, baseline-anchored interpretive approach is proposed, with quantitative criteria for AAV-associated liver injury and phenotype-based classifications tailored to pediatric, neuromuscular, and liver disease populations. Finally, we translate these biological principles into a practical clinical framework emphasizing enzyme trajectory, corroboration with hepatic markers such as gamma glutamyl transferase (GGT), recognition of delayed adaptive immune responses, and early attention to bilirubin or international normalized ratio (INR) drift. Together, these concepts provide a structured and biologically grounded approach, proposed here, for interpreting liver tests after AAV gene therapy, strengthening safety monitoring while preserving transgene expression and trial integrity.

Currently, cancer treatment mainly includes surgery, radiotherapy, chemotherapy, immunotherapy, and targeted therapy, wherein radiotherapy is one of the core modalities. However, its efficacy is often limited by radiotherapy resistance in the tumour cells. In recent years, studies have found that tumour cells undergo lipid metabolic reprogramming to enhance lipid synthesis, uptake, and storage, thereby adapting to the energy and structural adjustment demands imposed by radiotherapy, gaining survival advantage and developing radiation resistance. This review mainly focused on the role of lipid metabolic changes, including fatty acids, cholesterol, and phospholipids, in radiation resistance, aiming to provide ideas for achieving individualised precision radiotherapy.