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Double-layer metasurface-based edge coupler for low-loss coupling between optical fiber and thin-film lithium niobate photonic chip
Identification of an IRF–ZBP1–caspase-8–NINJ1 axis in driving PANoptosis and pathology during alcohol-associated liver disease
Innate immunity provides the critical first line of defense against infection and sterile triggers. Inflammatory cell death is a key component of the innate immune response to clear pathogens, but excessive or aberrant cell death can induce inflammation, cytokine storm, and pathology, making it a central molecular mechanism in inflammatory diseases. Alcohol-associated liver disease (ALD) is one such inflammatory disease, and the specific innate immune mechanisms driving pathology in this context remain unclear. Here, by leveraging RNA-seq and protein expression analyses in tissues from clinical samples, we identified increased expression of the innate immune sensor ZBP1 in patients with ALD. ZBP1 expression correlated with ALD progression in patients and that ethanol induced ZBP1-dependent lytic cell death, PANoptosis, in immune (macrophages, monocytes, and Kupffer cells) and nonimmune cells (hepatocytes). Mechanistically, the interferon regulatory factors (IRFs) IRF9 and IRF1 upregulated basal ZBP1 expression. Activation of ZBP1 led to PANoptosis via caspase-8 and cell membrane rupture through NINJ1, independent of gasdermin D, gasdermin E, and MLKL. In mouse models of ALD, ZBP1-deficient mice were significantly protected from disease pathology and liver damage. Furthermore, the expressions of ZBP1 and NINJ1 were upregulated in both liver and serum samples from patients with ALD, implicating these molecules as potential biomarkers. Overall, our findings establish the critical role of the IRF–ZBP1–caspase-8–NINJ1 axis in driving inflammatory cell death, PANoptosis, suggesting that targeting these molecules will have therapeutic potential in ALD and other inflammatory conditions.
Dissecting the genetic architecture of pre-harvest sprouting tolerance in Indian dwarf wheat (Triticum sphaerococcum) by multi-locus association analysis
Combination of Cas9 and adeno-associated vectors enables efficient in vivo knockdown of precise miRNAs in the rodent and primate brain
microRNAs (miRNAs) are key regulators of multiple biological functions. Although intensively studied, inactivating miRNAs in vivo is particularly challenging, especially in the brain. Here, we designed cell-specific tools aiming at downregulating defined miRNA species in vivo and investigating their function in discrete neuronal networks. Focusing on miR-124, a miRNA highly expressed in the mammalian brain and transcribed from three independent chromosomal loci, we designed and validated different guide RNAs. In vivo, our CRISPR-Cas9 designs strongly downregulate miR-124 levels without affecting the expression of other miRNAs. As a result, levels of endogenous miR-124 targets exhibit a significant increase supporting the release of its silencing activity. We provide evidence that specific deletion of miR-124 in neural stem cells of the subventricular zone altered migration of newly generated neurons into the olfactory bulb. We also showed that our vectors modified the Ca 2+ permeability of AMPA receptors, a robust functional output downstream of miR-124. We also extended our approach to other miRNAs, mammalian species, and Cas9 proteins, confirming the versatility of CRISPR-Cas9. These tool properties support their potential for elucidating miRNA functions in complex experimental in vivo settings such as brain networks.
Sensitization for proton beam therapy using 10B enriched and natural isotopic abundance of boronophenylalanine
Abstract Nuclear reactions between proton irradiation and boron via p + 11 B→3α (boron proton-capture reaction; BPCR) and n + 10 B→α+ 7 Li (boron neutron-capture reaction; BNCR) enhance the cell-killing effects of proton beam irradiation (PBI); however, which reaction exerts superior sensitization effects remains unclear. Therefore, we evaluated the efficacy of the BPCR and BNCR in enhancing the cell-killing effects of PBI. Human osteosarcoma (MG-63) and glioma (U-251 MG) cells were irradiated with PBI with and without boronophenylalanine (BPA) enriched with > 95% 10 B ( 10 B-BPA) for BNCR and BPA with natural isotopic abundance of boron (80% 11 B + 20% 10 B; N-BPA) for BPCR. Sensitizer enhancement ratios (SERs) were obtained by comparing the doses that yielded a surviving fraction of 10% (D 10 ). The D 10 values for PBI alone, PBI with 10 B-BPA, and PBI with N-BPA were 5.67, 4.85, and 5.51 and 5.21, 4.65, and 5.18 for MG-63 and U-251 MG cells, respectively. SERs of PBI with 10 B-BPA and N-BPA were 1.17 and 1.03 and 1.12 and 1.01 for MG-63 and U-251 MG cells, respectively. Our results indicate that 10 B-BPA-associated BNCR may be a better sensitizer for PBI than N-BPA-associated BPCR, which warrants further investigation into the clinical use of 10 B-enriched BPA.
The impact of pre-processing techniques on deep learning breast image segmentation
Abstract Breast cancer is one of the most common forms of cancer worldwide, making breast imaging a critical area for developing and evaluating Deep Learning methods. In this study, we investigate how different pre-processing techniques influence model performance in breast image segmentation. Pre-processing is a crucial step in the Deep Learning pipeline that directly impacts model performance, yet studies on its role in medical imaging remain limited. We assess the influence of different pre-processing techniques on a U-Net segmentation model applied to two breast public imaging datasets: CBIS-DDSM and Duke-Breast-Cancer-MRI. We systematically explored commonly used methods, including pixel intensity normalization, spacing harmonization, resizing/padding, and orientation standardization. Two processing pipelines were developed: Domain Non-Specific, integrating standard practices from natural and medical image analysis, and Domain Specific, which preserves anatomical information through careful handling of breast imaging metadata. A detailed comparative analysis of each pre-processing technique was conducted to evaluate its impact on model performance. Despite challenges and limitations associated with dataset size and scope, our findings identify pre-processing strategies tailored for breast imaging that can improve segmentation accuracy and analysis. This study represents an initial step in evaluating pre-processing for medical image analysis, providing a foundation for future work. Our results highlight significant differences in a 3-way ANOVA F-test ( $$\alpha < 0.05$$ ) for U-Net segmentation outcomes, attributed to different pixel intensity normalization approaches, offering valuable insights for future research.
Galectin-9 binding to HLA-DR in dendritic cells controls immune synapse formation and T cell proliferation
To initiate T cell–mediated immunity, dendritic cells (DCs) present antigens to T cells through the establishment of an immune synapse (IS). While events behind IS formation in T cells are well understood, the organization of IS components at the DC membrane remains ill-defined. Galectins modulate immune responses via glycan-(in)dependent interactions but the molecular mechanisms underlying their function in DC–mediated T cell activation, are poorly described. Here, we demonstrate that intracellular galectin-9 (gal9) in DCs is required for CD4 + T cell activation through its interaction with the HLA-DR alpha- and beta- cytoplasmic domains, as supported by coimmunoprecipitation, mass spectrometry, and NMR analyses. Live-cell imaging revealed gal9-depleted DCs fail to establish stable ISs with T cells, reducing T cell activation and proliferation. Notably, HLA-DR membrane lateral mobility and recruitment to the IS was diminished in DCs lacking gal9. Conditional gal9 knockout in DCs led to enhanced tumor growth in vivo, underscoring a role for gal9 in T cell–dependent antitumor immunity. Collectively, this study reports gal9-mediated HLA-DR organization at the DC synapse, uncovering a mechanism through which intracellular galectins coordinate immune receptor positioning to enhance CD4 + T cell activation.
Reduced IGF-1 signaling fails to limit Alzheimer’s disease progression in a novel rat model of IGF-1R haploinsufficiency
Abstract The growth hormone/insulin-like growth factor-1 (GH/IGF-1) signaling pathway has been strongly implicated in the aging process. Lifespan is profoundly increased in both male and female dwarf mice, while low IGF-1 signaling per se leads to more modest improvements in female lifespan. However, as opposed to the consistency offered by studies in dwarf mice, nuances in the relationship of this axis with health and disease have also been observed, including in rat models of low GH/IGF-1 signaling. This complexity further extends to cognitive decline and Alzheimer’s disease (AD), where this relationship has proven to be nuanced. To help address these gap, we have generated a new rat model of Igf1r + /− haploinsufficiency, to assess effects on metabolic health and AD. Similar to mice, we find that constitutively reduced IGF-1R levels leads to ~ 15% reduced adult body size in male and female rats, while not impairing insulin sensitivity. However, when crossed with TgF344-AD rats, lowering IGF-1 signaling per se failed to confer protection against AD-related pathology, including amyloid burden, phosphorylated tau or neuroinflammation in male and female TgF344-AD rats, and even appeared to exacerbate facets of disease in females, including an increase in cortical small amyloid plaques. Moreover, a unique hippocampal proteomic signature emerges in female Het/AD rats, including lower levels of proteins involved in redox balance. Overall, these data suggest a nuanced relationship of IGF-1R tone and AD exists and that better defining a more precise role of growth factor signaling in CNS health and disease throughout the life course is warranted.
Mutations and mitotic recombination events in nondividing cells
Demonstration of particulate matter characterization from HVO-blended diesel using an integrated multi-instrument approach
Genetics of prelingual isolated deafness and Usher syndrome in the Maghreb and Jordan: Harnessing the potential of homozygosity
The molecular genetic diagnosis of prelingual sensorineural hearing impairment (HI) is essential for genetic counseling and patient management. Effective diagnosis requires a knowledge of the genetic architecture of HI, which is often lacking. We established a cohort of 450 unrelated patients with familial (at least two affected relatives) severe-to-profound bilateral prelingual HI in five countries with high consanguinity rates: Tunisia, Jordan, Algeria, Morocco, and Mauritania (the TJAMM cohort). Recessive and dominant inheritance were observed in 92% and 8% of cases, respectively; 14% were syndromic. Genome analysis detected 211 different mutations (36% not reported before) in 49 deafness genes, and fully resolved 90% of cases of autosomal recessive isolated deafness (DFNB forms), 89% of the mutations being homozygous. The deafness genes involved were similar in different countries, but their mutations, except a few in GJB2 and LRTOMT , differed considerably, suggesting an overrepresentation of private mutations. Biallelic missense mutations in MYO7A , CDH23 , PCDH15 , USH1C cause either DFNB forms or Usher syndrome type 1 (USH1) ( USH1/DFNB genes). Such mutations were overrepresented (13% of patients), highlighting the importance of distinguishing between these two mutation classes. We hypothesized that current difficulties might stem from the misclassification of certain mutations. By studying the 65 USH1/DFNB missense mutations reported to cause DFNB in the homozygous state, we identified some that, when associated with a loss-of-function mutation, resulted in USH1, a characteristic pattern of some recessive hypomorphic mutations. This reappraised classification of USH1/DFNB mutations has the potential to improve molecular diagnosis and patient management significantly.
Development of an automated transformer-based text analysis framework for monitoring fire door defects in buildings
Abstract Fire door defects in residential buildings negatively impact construction management by reducing fire safety effectiveness, increasing the likelihood of smoke and fire spreading, and consequently putting occupant safety at greater risk. To address this critical safety issue, this study proposes and evaluates five transformer-based text classification methods—BERT, RoBERTa, ALBERT, DistilBERT, and XLNet—for automated defect detection. These methods are optimized using both common and method-specific hyperparameters, resulting in 1,458 model variants evaluated through multiple metrics. Among these, the optimized RoBERTa achieves the highest performance, demonstrating F1 scores of 92.13% (frame gap), 87.29% (door closer adjustment), 78.17% (contamination), 82.89% (dent), 80.17% (scratch), 96.66% (sealing components), 98.43% (mechanical components), and 67.81% (others), yielding an average F1 score of 85.44%. Furthermore, RoBERTa significantly outperforms the other optimized 535 text classification models (ANN, SVM, DT, LR, 1D CNN, and LSTM). These results underscore the potential and effectiveness of transformer-based methods for safety management in real-world construction scenarios.
Functional recovery induced by KCC2-enabled relay pathways in completely injured spinal cords in adult rats
Despite tremendous progress in promoting endogenous axon regeneration and engineering relay pathways by cell transplantation, the obtained functional recovery is still limited. We reason that these regenerated connections might not be able to integrate into the functional circuits in injured spinal cord. In this study, we tested whether modulating the neuronal excitability by pharmacological potassium–chloride cotransporter (KCC2) activation could enhance the functional outcomes of these regenerative treatments in a complete spinal cord injury (SCI) in adult rats. We found that while osteopontin/insulin-like growth factor 1 overexpression (to enhance axon regeneration) or neural stem cell (NSC) transplantation (to build a relay) alone failed to restore the interrupted spinal circuitry, the double treatment facilitated the integration of NSCs into the host spinal network, significantly promoting axonal regeneration and synapse formation. Behavioral assessments demonstrated that the addition of CLP290, a KCC2 agonist, to the combined treatment markedly improved hindlimb locomotion, as evidenced by higher Basso, Beattie and Bresnahan (BBB) scores and enhanced joint oscillation in fine locomotion analysis. Consistently, electrophysiological evaluations indicated partial restoration of electrical transmission through the reconstructed spinal network. Our findings highlight the synergistic effects of KCC2-mediated neuronal modulation on promoting functional recovery after complete SCI.
Dislocation analysis and structural characteristics of feal alloys under different heating rates using molecular dynamics simulation
Abstract In this study, molecular dynamics simulations are performed to investigate the dislocation behavior and structural characteristics of ferroaluminum (FeAl) alloys under different heating rates. This alloy has a remarkably low cost, is easy to fabricate, and exhibits good corrosion, sulfidation, and oxidation resistance, making it suitable for applications such as furnace fittings, heating elements, and heat exchange pipes. Molecular dynamics simulations are frequently used to analyze the behavior of atoms and molecules based on physical laws, such as classical Newtonian mechanics. During the heating process, the temperature increases from 300 K to 2500 K, exceeding the material’s melting point. The effect of the heating rate varies at 44, 27, 20, and 16 K ps −1 . The results indicate that higher heating rates cause dislocations to occur at higher temperatures in the bcc crystal structure, whereas lower heating rates result in dislocations at lower temperatures. Additionally, faster heating rates cause phase transitions to take place at higher temperatures compared to slower heating rates, influencing the distribution of local structures during the transition phase. This study primarily aims to enhance the understanding of structural changes in the FeAl alloy at the atomic scale.
Can speed cameras make streets safer? Quasi-experimental evidence from New York City
Each year, approximately 40,000 people die in vehicle collisions in the United States, generating $340 billion in economic costs. To make roads safer without expanding police contact, many cities have turned to automated traffic enforcement, cameras that detect and fine speeding motorists. Does automated enforcement reduce vehicle collisions and injuries? Many previous studies are limited to correlational evidence. By contrast, this study estimates the causal effect of automated enforcement on road safety in a difference-in-differences design. We exploit the staggered rollout of 2,000 speed cameras across New York City between 2014 and 2023, combining data on 700,000 collisions and 200,000 injuries with data on 18 million tickets issued. We find that cameras reduce collisions and injuries by 5 and 2.5% per month on average, respectively. Cumulatively, over the seven months following their introduction, collisions declined by 30% and injuries by 16%.
Event-related potential responses of ex-combatants and war victims differ for bias stimuli
Abstract Antagonistic social identities are reflected in neurophysiological responses to implicit bias, yet empirical validation in real-life post-conflict contexts remains scarce. This cross-sectional study assessed neurocognitive responses to bias-related stimuli among 76 Colombian participants, including both victims and ex-combatants of the armed conflict. Using an Implicit Association Test combined with EEG recording and cluster-based permutation analysis, we examined group differences in event-related potentials. Results revealed differential activation patterns: a language-related N400 and an emotion-related Late Positive Potential (LPP), both showing distinct latencies and amplitudes between groups. Particularly, victims exhibited stronger LPP modulation and delayed mid-to-late components, suggesting heightened emotional processing and increased cognitive load in evaluating bias-laden content. These findings highlight how lived experiences of victimization—not merely exposure to violence—shape neurophysiological processing of intergroup bias. Our results underscore the relevance of implicit cognitive markers for informing psychosocial interventions in transitional justice and reconciliation settings.