The recent emergence of van der Waals (vdW) materials with exceptional optical nonlinearity has driven advances in next-generation nonlinear photonic devices beyond classical optics. While integrating these materials into fiber-optic platforms offers unprecedented functionalities in quantum systems, realizing telecom-band in-line photon-pair sources based on highly nonlinear vdW materials remains challenging. Here, we report photon-pair generation centered at telecom wavelength via spontaneous parametric down-conversion in a fiber-integrated device incorporating a ferroelectric vdW crystal, SnP2S6. Benefiting from its giant optical nonlinearity and relaxed phase-matching across near-visible to telecom-band wavelengths, a remarkable nonlinear conversion efficiency of 0.07% is achieved in a few-micrometer-thick SnP2S6 film. Moreover, the fiber-integrated SnP2S6 device delivers high-quality photon pairs at telecom wavelengths, achieving a detected coincidence rate of 102 counts/s. The coincidence-to-accidental ratio reached up to 55 662, which is much larger than that of previous vdW-material-based sources. Furthermore, the device generates polarization-entangled photon pairs, which are verified via quantum state tomography to exhibit fidelities of 0.97 and concurrences of 0.95. This demonstration establishes a scalable, robust fiber-integrated platform that combines the versatility of vdW materials, paving the way toward low-loss, functionalized quantum photonic systems for networking, sensing, and computing.

Dystonia is a complex movement disorder that can cause functional disability and reduce quality of life. Deep brain stimulation (DBS) provides meaningful benefits in patients with medically refractory dystonia, but clinical outcomes can vary substantially. This variability likely reflects the heterogeneity in clinical presentations, genetic background, and brain networks involved in motor control. Dystonia is a network disorder involving abnormal interactions across cortico-basal ganglia-cerebellar circuits. Therapeutic effects of DBS therefore arise from modulation of distributed motor circuits rather than a single anatomical target. Advances in non-invasive neurophysiological techniques, intraoperative recordings, and connectome-based neuroimaging have provided new insights into how DBS modulates these pathological networks. Individual response to DBS and long-term outcomes are shaped by the interaction between clinical and genetic factors, neurophysiological abnormalities, and distributed network connectivity. Combining these variables can help refine patient selection for clinical studies and support individualised neuromodulation strategies.

Diabetes has become a significant global public health challenge, and prediabetes (preD), as the earliest detectable stage of glucose metabolism disorder, constitutes a critical window for disease intervention. Currently, China has not established diagnostic criteria for HbA1c in preD, and there is limited understanding of the molecular mechanisms at the critical transition points during disease progression. This study employs a refined stratification strategy for HbA1c at intervals of 0.3%, integrating the Dynamic Network Biomarker (DNB) theory with high-throughput proteomics technology, combined with longitudinal cohort validation and machine learning methods, to systematically depict the disease progression characteristics, spanning from a healthy physiological state through the prediabetic stage and ultimately to the onset of type 2 diabetes (T2D). This cross-sectional cohort consisted of 110 subjects, divided into three groups: healthy controls (20), prediabetic (50), and type 2 diabetic (40). Of these, 28 went on to complete a 2-year longitudinal follow-up assessment. The results indicate that the HbA1c range of 6.0-6.2% (D stage) meets the three criteria of the DNB theory (high inter-molecular coherence, decoupling from external networks, and enhanced volatility), suggesting that this stage may represent a critical state for the transition from preD to T2D. A total of 37 core DNB proteins were identified through proteomics analysis, with the majority of functional annotations focused on biological processes involving extracellular matrix remodeling, inflammatory response, and insulin signaling pathways. In the longitudinal follow-up validation, the predictive efficacy of the ADAM10 protein for clinical outcomes was significant (AUC = 0.768), outperforming traditional indicators like HbA1c, demonstrating its potential value as a novel biomarker. There are several limitations in the present investigation. With the relatively small number of subjects, the short follow-up period, and the single center, single ethnic study design, the findings have limited generalizability. Additionally, the lack of functional validation of some of the important molecular targets is a methodological limitation that should be recognized. Therefore, the identified critical transition window and the clinical predictive value of DNB molecules need to be further validated through large-scale, multi-center, long-term cohort studies to obtain more reliable evidence-based medical evidence, providing a scientific basis for the precise diagnosis and early intervention of preD in the Chinese population.

Plants have long served as natural indicators of environmental conditions, and recent advances in synthetic biology are enabling the design of engineered sentinels - living sensors that can report on abiotic and biotic stressors. This review summarizes recent advances in designing sensor plants, also called phytosensors or sentinel plants, highlighting three major strategies: (1) exploiting native promoter systems responsive to environmental cues, (2) engineering protein-based genetically encoded biosensors that detect specific molecules of interest, and (3) constructing interkingdom signaling networks between plants and microbes to extend sensing capabilities to the rhizosphere. These sense-response modules can be coupled to optical reporters (e.g., fluorescence, bioluminescence, and pigment-based) that enable remote detection via drones and satellite imaging. Continued improvements in promoter design, receptor modularity, and signal visualization technologies are driving the development of robust, field-deployable plant biosensors. Together, these innovations position engineered sensor plants as scalable, self-sustaining sentinels for real-time environmental monitoring and land management.

Traditional 3D bioprinting of corneal constructs relies on planar slicing, which often results in a significant stairstep effect and the loss of anatomical curvature. Curvilinear layering has emerged as a promising alternative to address these limitations. The presented methodology, based on non-planar layer integration, ensures a smoother surface finish. The model's surface is identified via vertex normals and reconstructed using the Poisson method. Finally, surface parametrization is applied to generate spatially curved trajectories. To validate the algorithm, corneal constructs were printed using a planar and the proposed non-planar approach. Quantitative evaluation of micro-Computed Tomography data revealed that the non-planar approach achieved significantly higher morphological fidelity, successfully replicating the intended parabolic profile of the human cornea. Furthermore, the non-planar constructs demonstrated adequate functional performance, characterized by high optical transparency. Thereby, the feasibility of printing non-planar layers using the proposed novel approach is successfully demonstrated. Furthermore, the comparative analysis confirms the method's potential for corneal biofabrication when compared to traditional planar methods.

The Tau Global Conference 2025, hosted by the Alzheimer's Association, CurePSP, and the Rainwater Charitable Foundation, convened international experts from academia, industry, government, and philanthropy to explore advances and challenges in tauopathy research. The meeting highlighted progress across tau biology, including emerging models of tau regulation, degradation, and propagation; advances in biomarker development for the diagnosis and staging of tauopathies; and evolving therapeutic strategies targeting diverse aspects of tau pathophysiology. Discussions also emphasized the importance of cross-sector collaboration, and global initiatives to address disparities in tau research. This report synthesizes key insights from the conference and underscores the critical role of interdisciplinary, biomarker-driven, and globally inclusive approaches in accelerating the translation of tau research into effective clinical applications.

Thymidine kinase 2 deficiency (TK2d) (MIM 609560) is an ultra-rare, autosomal recessive mitochondrial myopathy caused by TK2 variants, leading to mitochondrial DNA depletion and/or multiple deletions. People with thymidine kinase 2 deficiency experience progressive myopathy, bulbar weakness and respiratory insufficiency, often losing the ability to walk, eat and breathe independently. Doxecitine and doxribtimine represents the first approved treatment for patients with thymidine kinase 2 deficiency with age of symptom onset ≤12 years by the US Food and Drug Administration and the European Medicines Agency; previously, disease management was limited to supportive care. We investigated the efficacy and safety of pyrimidine nucleos(t)ide therapy in thymidine kinase 2 deficiency. Patients treated with pyrimidine nucleos(t)ides were pooled from retrospective (NCT03701568, NCT05017818) and prospective (NCT03845712) studies and company-supported Expanded Access Programs. Untreated patients were pooled from literature reviews and a retrospective chart review study (NCT05017818). Patient subgroups were stratified by age of thymidine kinase 2 deficiency symptom onset (≤12 years and >12 years). The primary outcome was survival in 50th-percentile matched pairs of treated and untreated patients. Other outcomes included status of developmental motor milestones, ventilatory and feeding tube support, and safety. In total, 218 patients were included (treated: 104; untreated: 114). Baseline demographics and characteristics were comparable between subgroups. Most patients had an age of symptom onset ≤12 years [treated: 82/104 (78.8%); untreated: 93/114 (81.6%)]. In the age-of-symptom-onset-≤12-years subgroup, restricted mean survival time (95% confidence interval) was 29.2 (28.2, 30.3) years over the 30 years after symptom onset for treated patients and 14.4 (11.1, 17.6) years for untreated patients. Loss of ≥1 acquired motor milestone was more frequent before treatment start than after. Substantially more patients regained ≥1 lost motor milestone after treatment start than before. Ventilatory and feeding support were used across all age-of-symptom-onset subgroups, but some patients reduced or discontinued support after starting treatment and fewer patients initiated support after treatment start than before. Most treatment-emergent adverse events (TEAEs) did not lead to discontinuation. The most frequent TEAE was diarrhoea [43/50 patients (86.0%)], which was generally mild or moderate and resolved with dose reduction. Serious TEAEs occurred in 28/50 patients (56.0%); few were considered to be drug related [4/50 (8.0%)]. In total, 3/67 patients (4.5%) experienced a fatal serious TEAE, which were not considered to be drug related. These findings indicate that pyrimidine nucleos(t)ide therapy improves survival and functional outcomes in people with thymidine kinase 2 deficiency, especially those with age of symptom onset ≤12 years, and has an acceptable safety profile.

Stevens-Johnson syndrome (SJS) is a rare and severe mucocutaneous disorder often triggered by medications or infections. Our previous research identified that four key genes, Ikzf1, Ptger3, Mavs, and Tlr3 are involved in SJS susceptibility and the conjunctival epithelial innate immune response, demonstrating their role in regulating interferon-stimulated genes. However, the interplay among these regulatory factors remains unclear. This study aimed to elucidate the crosstalk mechanisms between the pathways regulated by these four genes in conjunctival epithelial cells. We constructed a comprehensive gene regulatory network using transcriptomic data from murine conjunctival epithelial cells under 16 distinct conditions, including polyI:C stimulation across wild-type, knockout, and transgenic backgrounds for the key genes. A targeted network analysis systematically identified numerous candidate genes mediating the crosstalk between the regulatory pathways initiated by Ikzf1, Ptger3, Mavs, and Tlr3. The identified candidates suggest the involvement of diverse signaling pathways previously unlinked to SJS pathology. Our findings suggest that the pathogenesis of SJS may arise not from the dysfunction of isolated genes but from the disruption of a balance maintained by intricate pathway crosstalk.

Frailty is a heterogeneous aging phenotype that represents accumulated biological vulnerability among very old adults. How frailty relates to key late-life transitions at advanced ages remains incompletely understood. We examined the longitudinal association between frailty status and a composite endpoint of incident long-term care insurance certification (level ≥ 2) or death, and assessed whether circulating biomarkers (growth differentiation factor-15 [GDF-15] and N-terminal pro-B-type natriuretic peptide [NT-proBNP]) provided information beyond frailty. In this cohort study, 992 community-dwelling adults aged 85-89 years in Japan, classified using physical frailty criteria at baseline as either robust, prefrail, or frail, were followed up to 7.5 years. Risk over time was compared using Kaplan-Meier methods, and Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs). Kaplan-Meier curves showed clear separation across the frailty groups. In multivariable models, prefrail and frail status were associated with a higher risk of the composite endpoint (aHRs 1.62 and 2.13 vs. robust, respectively). After adjusting for frailty status and covariates, higher GDF-15 and NT-proBNP levels were independently associated with greater risk. The GDF-15 association was adequately described by a linear term, whereas NT-proBNP showed evidence of nonlinearity with a steeper gradient toward the upper range. As a supportive summary of risk stratification, 5-year discrimination changed only modestly after adding biomarkers. Frailty strongly stratified the risk of major late-life transitions, and baseline GDF-15 and NT-proBNP may help characterize residual biological heterogeneity beyond frailty, with contrasting dose-response patterns.

Subjective color (SC) refers to chromatic perception induced by achromatic stimuli, as classically demonstrated using Benham's top. Despite nearly two centuries of investigation, the underlying neural mechanisms remain unclear. We developed artificial neural network models trained on natural videos using predictive learning to investigate SC generation. These models successfully reproduced artificial subjective color (ASC) from achromatic testing stimuli that contained no explicit chromatic information. Critically, ASC characteristics were systematically influenced by the colors of moving objects in the training videos. Using progressively simplified stimuli, ranging from natural scenes to 3D computer graphics and 2D animations, we demonstrated that the colors of moving objects primarily determine ASC properties. We propose that predictive learning establishes color associations with motion patterns, causing the arcs on Benham's top to be perceived as moving objects with corresponding colors. These findings suggest that cortical predictive mechanisms may complement retinal processes in generating subjective color phenomena.

Understanding and controlling cell-state and phenotype transitions is central to biological discovery and therapeutic development, yet identifying true causal regulators from observational transcriptomic data remains challenging because of confounding and correlated signals. CauFinder is a framework that integrates causal disentanglement modeling with network control to prioritize causal regulators of state and phenotype transitions from observed data. By leveraging causal reasoning based on do-calculus and optimizing information-flow metrics, CauFinder separates putative causal factors from spurious associations, quantifies transition-relevant states, and nominates master regulators. Across simulations and multiple real-world datasets, CauFinder identifies regulators associated with diverse transitions, including differentiation, adenocarcinoma-to-squamous transdifferentiation, and shifts between drug-sensitive and drug-resistant states. In epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) resistance, CauFinder prioritizes DAAM1 as a previously unrecognized driver. Small interfering RNA (siRNA)-mediated knockdown of DAAM1 enhances sensitivity to osimertinib, providing functional support for this causal prediction. Overall, CauFinder enables actionable target nomination and testable hypotheses for intervening in disease-relevant state transitions using observational transcriptomic data.