Search

Over 90% of patients with pancreatic ductal adenocarcinoma (PDAC) have oncogenic KRAS mutations. Nevertheless, mutated KRAS alone is insufficient to initiate pancreatic intraepithelial neoplasia (PanIN), the precursor of PDAC. The identities of the other factors/events required to drive PanIN formation remain elusive. Here, optic-clear 3D histology is used to analyze entire pancreases of 2-week-old Pdx1-Cre; LSL-KrasG12D/+ (KC) mice to detect the earliest emergence of PanIN and observed that the occurrence is independent of physical location. Instead, it is found that the earliest PanINs overexpress Muc4 and associate with αSMA+ fibroblasts in both transgenic mice and human specimens. Mechanistically, KrasG12D/+ pancreatic cells upregulate Muc4 through genetic alterations to increase proliferation and fibroblast recruitments via Activin A secretion and consequently enhance cell transformation for PanIN formation. Inhibition of Activin A signaling using Follistatin (FST) diminishes early PanIN-associated fibroblast recruitment, effectively curtailing PanIN initiation and growth in KC mice. These findings emphasize the vital role of interactions between oncogenic KrasG12D/+ -driven genetic alterations and induced microenvironmental changes in PanIN initiation, suggesting potential avenues for early PDAC diagnostic and management approaches.

Nutritional deprivation triggers a switch from a saprotrophic to predatory lifestyle in soil-dwelling nematode-trapping fungi (NTF). In particular, the NTF Arthrobotrys oligospora secretes food and sex cues to lure nematodes to its mycelium and is triggered to develop specialized trapping devices. Captured nematodes are then invaded and digested by the fungus, thus serving as a food source. In this study, we examined the transcriptomic response of A. oligospora across the stages of sensing, trap development, and digestion upon exposure to the model nematode Caenorhabditis elegans. A. oligospora enacts a dynamic transcriptomic response, especially of protein secretion-related genes, in the presence of prey. Two-thirds of the predicted secretome of A. oligospora was up-regulated in the presence of C. elegans at all time points examined, and among these secreted proteins, 38.5% are predicted to be effector proteins. Furthermore, functional studies disrupting the t-SNARE protein Sso2 resulted in impaired ability to capture nematodes. Additionally, genes of the DUF3129 family, which are expanded in the genomes of several NTF, were highly up-regulated upon nematode exposure. We observed the accumulation of highly expressed DUF3129 proteins in trap cells, leading us to name members of this gene family as Trap Enriched Proteins (TEPs). Gene deletion of the most highly expressed TEP gene, TEP1, impairs the function of traps and prevents the fungus from capturing prey efficiently. In late stages of predation, we observed up-regulation of a variety of proteases, including metalloproteases. Following penetration of nematodes, these metalloproteases facilitate hyphal growth required for colonization of prey. These findings provide insights into the biology of the predatory lifestyle switch in a carnivorous fungus and provide frameworks for other fungal-nematode predator-prey systems.

Abstract Annotating active sites in enzymes is crucial for advancing multiple fields including drug discovery, disease research, enzyme engineering, and synthetic biology. Despite the development of numerous automated annotation algorithms, a significant trade-off between speed and accuracy limits their large-scale practical applications. We introduce EasIFA, an enzyme active site annotation algorithm that fuses latent enzyme representations from the Protein Language Model and 3D structural encoder, and then aligns protein-level information with the knowledge of enzymatic reactions using a multi-modal cross-attention framework. EasIFA outperforms BLASTp with a 10-fold speed increase and improved recall, precision, f1 score, and MCC by 7.57%, 13.08%, 9.68%, and 0.1012, respectively. It also surpasses empirical-rule-based algorithm and other state-of-the-art deep learning annotation method based on PSSM features, achieving a speed increase ranging from 650 to 1400 times while enhancing annotation quality. This makes EasIFA a suitable replacement for conventional tools in both industrial and academic settings. EasIFA can also effectively transfer knowledge gained from coarsely annotated enzyme databases to smaller, high-precision datasets, highlighting its ability to model sparse and high-quality databases. Additionally, EasIFA shows potential as a catalytic site monitoring tool for designing enzymes with desired functions beyond their natural distribution.

Current guidelines recommend limiting the rate of correction in patients with severe hyponatremia to avoid severe neurologic complications such as osmotic demyelination syndrome (ODS). However, published data have been conflicting. We aimed to evaluate the association between rapid sodium correction and ODS in patients with severe hyponatremia.

Abstract Retrosynthesis is a crucial task in drug discovery and organic synthesis, where artificial intelligence (AI) is increasingly employed to expedite the process. However, existing approaches employ token-by-token decoding methods to translate target molecule strings into corresponding precursors, exhibiting unsatisfactory performance and limited diversity. As chemical reactions typically induce local molecular changes, reactants and products often overlap significantly. Inspired by this fact, we propose reframing single-step retrosynthesis prediction as a molecular string editing task, iteratively refining target molecule strings to generate precursor compounds. Our proposed approach involves a fragment-based generative editing model that uses explicit sequence editing operations. Additionally, we design an inference module with reposition sampling and sequence augmentation to enhance both prediction accuracy and diversity. Extensive experiments demonstrate that our model generates high-quality and diverse results, achieving superior performance with a promising top-1 accuracy of 60.8% on the standard benchmark dataset USPTO-50 K.

Introduction: Percutaneous microwave ablation (MWA) is clinically accepted for the treatment of lung tumors and oligometastatic disease. Bronchoscopic MWA is under development and evaluation in the clinical setting. We previously reported on the development of a bronchoscopy-guided MWA system integrated with clinical virtual bronchoscopy and navigation and demonstrated the feasibility of transbronchial MWA, using a maximum power of 60 W at the catheter input. Here, we assessed the performance of bronchoscopy-guided MWA with an improved catheter (maximum power handling of up to 120 W) in normal porcine lung in vivo (as in the previous study). Methods: A total of 8 bronchoscopy-guided MWA were performed (n = 2 pigs; 4 ablations per pig) with power levels of 90 W and 120 W applied for 5 and 10 min, respectively. Virtual bronchoscopy planning and navigation guided transbronchial or endobronchial positioning of the MWA applicator for ablation of lung parenchyma. Following completion of ablations and post-procedure CT imaging, the lungs were harvested and sectioned for gross and histopathologic ablation analysis. Results: Bronchoscopy-guided MWA with applied energy levels of 90 W/5 min and 120 W/10 min yielded ablation zones with short-axis diameters in the range of 20–28 mm (56–116% increase) as compared to ∼13 mm from our previous study (60 W/10 min). Histology of higher-power and previous lower-power ablations was consistent, including a central necrotic zone, a thermal fixation zone with intact tissue architecture, and a hemorrhagic periphery. Catheter positioning and its confirmation via intra-procedural 3D imaging (e.g., cone-beam CT) proved to be critical for ablation consistency. Conclusion: Bronchoscopy-guided MWA with an improved catheter designed for maximum power 120 W yields large ablations in normal porcine lung in vivo.

Abstract Bcr-Abl transformation leads to chronic myeloid leukemia (CML). The acquirement of T315I mutation causes tyrosine kinase inhibitors (TKI) resistance. This study develops a compound, JMF4073, inhibiting thymidylate (TMP) and cytidylate (CMP) kinases, aiming for a new therapy against TKI-resistant CML. In vitro and in vivo treatment of JMF4073 eliminates WT-Bcr-Abl-32D CML cells. However, T315I-Bcr-Abl-32D cells are less vulnerable to JMF4073. Evidence is presented that ATF4-mediated upregulation of GSH causes T315I-Bcr-Abl-32D cells to be less sensitive to JMF4073. Reducing GSH biosynthesis generates replication stress in T315I-Bcr-Abl-32D cells that require dTTP/dCTP synthesis for survival, thus enabling JMF4073 susceptibility. It further shows that the levels of ATF4 and GSH in several human CML blast-crisis cell lines are inversely correlated with JMF4073 sensitivity, and the combinatory treatment of JMF4073 with GSH reducing agent leads to synthetic lethality in these CML blast-crisis lines. Altogether, the investigation indicates an alternative option in CML therapy.

Abstract In the context of China's resolute advancement of dual carbon goals (carbon peaking and carbon neutrality), urban agglomerations emerge as pivotal areas for carbon emission mitigation due to their dense economic activities and rapid urbanization. Previous studies overlook regional disparities in carbon emission prediction, disregarding the variations and policy directives across different provinces or cities. Therefore, this study addresses the research gap by investigating synergistic strategies to foster regional carbon peaking within the Beijing-Tianjin-Hebei region. Employing a novel approach tailored to regional segmentation policies, we provide more accurate predictions reflecting real-world conditions and distinct policy landscapes. Meanwhile, we integrate carbon emission efficiency into our analysis, emphasizing the dual goals of emission reduction and quality economic growth. Our empirical investigation in the Beijing-Tianjin-Hebei region, utilizing the Super-SBM and extended STIRPAT models, reveals upward trends in carbon emission efficiency, with varying trajectories across cities. Scenario simulations informed by the "14th Five-Year Plan" demonstrate that under the green development scenario, carbon peaking accelerates, alongside enhanced efficiency, supporting long-term emission reduction. Moreover, we design seven regional synergy carbon peak strategies for scenario simulations to facilitate the rational layout of dual carbon policies for collaborative development. We find that synergistic strategies have proven more effective in reducing regional carbon emission and increasing efficiency than strategies focusing solely on economic development or energy conservation. This innovative finding emphasizes the necessity of comprehensive green development in the Beijing-Tianjin-Hebei region and provides strong evidence for policymakers. Our research contributes to targeted strategies for improving carbon emission efficiency and reducing emissions, emphasizing the importance of synergistic approaches for regional carbon reduction.