Geminal-atom catalysis for cross-coupling.

Single-atom catalysts (SACs) have well-defined active sites, making them of potential interest for organic synthesis1-4. However, the architecture of these mononuclear metal species stabilized on solid supports may not be optimal for catalysing complex molecular transformations owing to restricted spatial environment and electronic quantum states5,6. Here we report a class of heterogeneous geminal-atom catalysts (GACs), which pair single-atom sites in specific coordination and spatial proximity. Regularly separated nitrogen anchoring groups with delocalized π-bonding nature in a polymeric carbon nitride (PCN) host7 permit the coordination of Cu geminal sites with a ground-state separation of about 4 Å at high metal density8. The adaptable coordination of individual Cu sites in GACs enables a cooperative bridge-coupling pathway through dynamic Cu-Cu bonding for diverse C-X (X = C, N, O, S) cross-couplings with a low activation barrier. In situ characterization and quantum-theoretical studies show that such a dynamic process for cross-coupling is triggered by the adsorption of two different reactants at geminal metal sites, rendering homo-coupling unfeasible. These intrinsic advantages of GACs enable the assembly of heterocycles with several coordination sites, sterically congested scaffolds and pharmaceuticals with highly specific and stable activity. Scale-up experiments and translation to continuous flow suggest broad applicability for the manufacturing of fine chemicals.

Ordered and deterministic cancer genome evolution after p53 loss.

Although p53 inactivation promotes genomic instability1 and presents a route to malignancy for more than half of all human cancers2,3, the patterns through which heterogenous TP53 (encoding human p53) mutant genomes emerge and influence tumorigenesis remain poorly understood. Here, in a mouse model of pancreatic ductal adenocarcinoma that reports sporadic p53 loss of heterozygosity before cancer onset, we find that malignant properties enabled by p53 inactivation are acquired through a predictable pattern of genome evolution. Single-cell sequencing and in situ genotyping of cells from the point of p53 inactivation through progression to frank cancer reveal that this deterministic behaviour involves four sequential phases-Trp53 (encoding mouse p53) loss of heterozygosity, accumulation of deletions, genome doubling, and the emergence of gains and amplifications-each associated with specific histological stages across the premalignant and malignant spectrum. Despite rampant heterogeneity, the deletion events that follow p53 inactivation target functionally relevant pathways that can shape genomic evolution and remain fixed as homogenous events in diverse malignant populations. Thus, loss of p53-the 'guardian of the genome'-is not merely a gateway to genetic chaos but, rather, can enable deterministic patterns of genome evolution that may point to new strategies for the treatment of TP53-mutant tumours.

Knot data analysis using multiscale Gauss link integral.

In the past decade, topological data analysis has emerged as a powerful algebraic topology approach in data science. Although knot theory and related subjects are a focus of study in mathematics, their success in practical applications is quite limited due to the lack of localization and quantization. We address these challenges by introducing knot data analysis (KDA), a paradigm that incorporates curve segmentation and multiscale analysis into the Gauss link integral. The resulting multiscale Gauss link integral (mGLI) recovers the global topological properties of knots and links at an appropriate scale and offers a multiscale geometric topology approach to capture the local structures and connectivities in data. By integration with machine learning or deep learning, the proposed mGLI significantly outperforms other state-of-the-art methods across various benchmark problems in 13 intricately complex biological datasets, including protein flexibility analysis, protein-ligand interactions, human Ether-à-go-go-Related Gene potassium channel blockade screening, and quantitative toxicity assessment. Our KDA opens a research area-knot deep learning-in data science.

Observing heroic behavior and its influencing factors in immersive virtual environments.

Studying heroism in controlled settings presents challenges and ethical controversies due to its association with physical risk. Leveraging virtual reality (VR) technology, we conducted a three-study series with 397 participants from China to investigate heroic actions. Participants unexpectedly witnessed a criminal event in a simulated scenario, allowing observation of their tendency to physically intercept a thief. We examined situational factors (voluntariness, authority, and risk) and personal variables [gender, impulsivity, empathy, and social value orientation (SVO)] that may influence heroism. Also, the potential association between heroism and social conformity was explored. In terms of situational variables, voluntariness modulated participants' tendency to intercept the escaping thief, while perceived risk demonstrated its impact by interacting with gender. That is, in study 3 where the perceived risk was expected to be higher (as supported by an online study 5), males exhibited a greater inclination toward heroic behavior compared to females. Regarding other personal variables, the tendency to engage in heroic behavior decreased as empathy levels rose among males, whereas the opposite trend was observed for females. SVO influenced heroic behavior but without a gender interaction. Finally, an inverse relationship between heroism and social conformity was observed. The robustness of these findings was partly supported by the Chinese sample (but not the international sample) of an online study 4 that provided written descriptions of VR scenarios, indicating cultural variations. These results advance insights into motivational factors influencing heroism in the context of restoring order and highlight the power of VR technology in examining social psychological hypotheses beyond ethical constraints.

Hypernetwork modeling and topology of high-order interactions for complex systems.

Interactions among the underlying agents of a complex system are not only limited to dyads but can also occur in larger groups. Currently, no generic model has been developed to capture high-order interactions (HOI), which, along with pairwise interactions, portray a detailed landscape of complex systems. Here, we integrate evolutionary game theory and behavioral ecology into a unified statistical mechanics framework, allowing all agents (modeled as nodes) and their bidirectional, signed, and weighted interactions at various orders (modeled as links or hyperlinks) to be coded into hypernetworks. Such hypernetworks can distinguish between how pairwise interactions modulate a third agent (active HOI) and how the altered state of each agent in turn governs interactions between other agents (passive HOI). The simultaneous occurrence of active and passive HOI can drive complex systems to evolve at multiple time and space scales. We apply the model to reconstruct a hypernetwork of hexa-species microbial communities, and by dissecting the topological architecture of the hypernetwork using GLMY homology theory, we find distinct roles of pairwise interactions and HOI in shaping community behavior and dynamics. The statistical relevance of the hypernetwork model is validated using a series of in vitro mono-, co-, and tricultural experiments based on three bacterial species.

Ablation of Transcription Factor IRF4 Promotes Transplant Acceptance by Driving Allogenic CD4+ T Cell Dysfunction.

CD4+ T cells orchestrate immune responses and destruction of allogeneic organ transplants, but how this process is regulated on a transcriptional level remains unclear. Here, we demonstrated that interferon regulatory factor 4 (IRF4) was a key transcriptional determinant controlling T cell responses during transplantation. IRF4 deletion in mice resulted in progressive establishment of CD4+ T cell dysfunction and long-term allograft survival. Mechanistically, IRF4 repressed PD-1, Helios, and other molecules associated with T cell dysfunction. In the absence of IRF4, chromatin accessibility and binding of Helios at PD-1 cis-regulatory elements were increased, resulting in enhanced PD-1 expression and CD4+ T cell dysfunction. The dysfunctional state of Irf4-deficient T cells was initially reversible by PD-1 ligand blockade, but it progressively developed into an irreversible state. Hence, IRF4 controls a core regulatory circuit of CD4+ T cell dysfunction, and targeting IRF4 represents a potential therapeutic strategy for achieving transplant acceptance.

Filling metal-organic framework mesopores with TiO2 for CO2 photoreduction.

Metal-organic frameworks (MOFs)1-3 are known for their specific interactions with gas molecules4,5; this, combined with their rich and ordered porosity, makes them promising candidates for the photocatalytic conversion of gas molecules to useful products6. However, attempts to use MOFs or MOF-based composites for CO2 photoreduction6-13 usually result in far lower CO2 conversion efficiency than that obtained from state-of-the-art solid-state or molecular catalysts14-18, even when facilitated by sacrificial reagents. Here we create 'molecular compartments' inside MOF crystals by growing TiO2 inside different pores of a chromium terephthalate-based MOF (MIL-101) and its derivatives. This allows for synergy between the light-absorbing/electron-generating TiO2 units and the catalytic metal clusters in the backbones of MOFs, and therefore facilitates photocatalytic CO2 reduction, concurrent with production of O2. An apparent quantum efficiency for CO2 photoreduction of 11.3 per cent at a wavelength of 350 nanometres is observed in a composite that consists of 42 per cent TiO2 in a MIL-101 derivative, namely, 42%-TiO2-in-MIL-101-Cr-NO2. TiO2 units in one type of compartment in this composite are estimated to be 44 times more active than those in the other type, underlining the role of precise positioning of TiO2 in this system.

The metabolomic physics of complex diseases.

Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of high-risk individuals and disease prevention. However, current approaches can only characterize individual key metabolites, without taking into account the reality that complex diseases are multifactorial, dynamic, heterogeneous, and interdependent. Here, we leverage a statistical physics model to combine all metabolites into bidirectional, signed, and weighted interaction networks and trace how the flow of information from one metabolite to the next causes changes in health state. Viewing a disease outcome as the consequence of complex interactions among its interconnected components (metabolites), we integrate concepts from ecosystem theory and evolutionary game theory to model how the health state-dependent alteration of a metabolite is shaped by its intrinsic properties and through extrinsic influences from its conspecifics. We code intrinsic contributions as nodes and extrinsic contributions as edges into quantitative networks and implement GLMY homology theory to analyze and interpret the topological change of health state from symbiosis to dysbiosis and vice versa. The application of this model to real data allows us to identify several hub metabolites and their interaction webs, which play a part in the formation of inflammatory bowel diseases. The findings by our model could provide important information on drug design to treat these diseases and beyond.

Spatio-temporal transcriptome dynamics coordinate rapid transition of core crop functions in 'lactating' pigeon.

Pigeons (Columba livia) are among a select few avian species that have developed a specialized reproductive mode wherein the parents produce a 'milk' in their crop to feed newborn squabs. Nonetheless, the transcriptomic dynamics and role in the rapid transition of core crop functions during 'lactation' remain largely unexplored. Here, we generated a de novo pigeon genome assembly to construct a high resolution spatio-temporal transcriptomic landscape of the crop epithelium across the entire breeding stage. This multi-omics analysis identified a set of 'lactation'-related genes involved in lipid and protein metabolism, which contribute to the rapid functional transitions in the crop. Analysis of in situ high-throughput chromatin conformation capture (Hi-C) sequencing revealed extensive reorganization of promoter-enhancer interactions linked to the dynamic expression of these 'lactation'-related genes between stages. Moreover, their expression is spatially localized in specific epithelial layers, and can be correlated with phenotypic changes in the crop. These results illustrate the preferential de novo synthesis of 'milk' lipids and proteins in the crop, and provides candidate enhancer loci for further investigation of the regulatory elements controlling pigeon 'lactation'.

AVCAPIR: A Novel Procalcific PIWI-Interacting RNA in Calcific Aortic Valve Disease.

BACKGROUND: Calcification of the aortic valve leads to increased leaflet stiffness and consequently results in the development of calcific aortic valve disease (CAVD). However, the underlying molecular and cellular mechanisms of calcification remain unclear. Here, we identified a novel aortic valve calcification-associated PIWI-interacting RNA (piRNA; AVCAPIR) that increases valvular calcification and promotes CAVD progression. METHODS: Using piRNA sequencing, we identified piRNAs contributing to the pathogenesis of CAVD that we termed AVCAPIRs. High-cholesterol diet-fed ApoE-/- mice with AVCAPIR knockout were used to examine the role of AVCAPIR in aortic valve calcification (AVC). Gain- and loss-of-function assays were conducted to determine the role of AVCAPIR in the induced osteogenic differentiation of human valvular interstitial cells. To dissect the mechanisms underlying AVCAPIR-elicited procalcific effects, we performed various analyses, including an RNA pulldown assay followed by liquid chromatography-tandem mass spectrometry, methylated RNA immunoprecipitation sequencing, and RNA sequencing. RNA pulldown and RNA immunoprecipitation assays were used to study piRNA interactions with proteins. RESULTS: We found that AVCAPIR was significantly upregulated during AVC and exhibited potential diagnostic value for CAVD. AVCAPIR deletion markedly ameliorated AVC in high-cholesterol diet-fed ApoE-/- mice, as shown by reduced thickness and calcium deposition in the aortic valve leaflets, improved echocardiographic parameters (decreased peak transvalvular jet velocity and mean transvalvular pressure gradient, as well as increased aortic valve area), and diminished levels of osteogenic markers (Runx2 and Osterix) in aortic valves. These results were confirmed in osteogenic medium-induced human valvular interstitial cells. Using unbiased protein-RNA screening and molecular validation, we found that AVCAPIR directly interacts with FTO (fat mass and obesity-associated protein), subsequently blocking its N6-methyladenosine demethylase activity. Further transcriptomic and N6-methyladenosine modification epitranscriptomic screening followed by molecular validation confirmed that AVCAPIR hindered FTO-mediated demethylation of CD36 mRNA transcripts, thus enhancing CD36 mRNA stability through the N6-methyladenosine reader IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1). In turn, the AVCAPIR-dependent increase in CD36 stabilizes its binding partner PCSK9 (proprotein convertase subtilisin/kexin type 9), a procalcific gene, at the protein level, which accelerates the progression of AVC. CONCLUSIONS: We identified a novel piRNA that induced AVC through an RNA epigenetic mechanism and provide novel insights into piRNA-directed theranostics in CAVD.

An altered extracellular matrix-integrin interface contributes to Huntington's disease-associated CNS dysfunction in glial and vascular cells.

Astrocytes and brain endothelial cells are components of the neurovascular unit that comprises the blood-brain barrier (BBB) and their dysfunction contributes to pathogenesis in Huntington's disease (HD). Defining the contribution of these cells to disease can inform cell-type-specific effects and uncover new disease-modifying therapeutic targets. These cells express integrin (ITG) adhesion receptors that anchor the cells to the extracellular matrix (ECM) to maintain the integrity of the BBB. We used HD patient-derived induced pluripotent stem cell (iPSC) modeling to study the ECM-ITG interface in astrocytes and brain microvascular endothelial cells and found ECM-ITG dysregulation in human iPSC-derived cells that may contribute to the dysfunction of the BBB in HD. This disruption has functional consequences since reducing ITG expression in glia in an HD Drosophila model suppressed disease-associated CNS dysfunction. Since ITGs can be targeted therapeutically and manipulating ITG signaling prevents neurodegeneration in other diseases, defining the role of ITGs in HD may provide a novel strategy of intervention to slow CNS pathophysiology to treat HD.

The GWAS SNP rs80207740 modulates erythrocyte traits via allele-specific binding of IKZF1 and targeting XPO7 gene.

Genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with erythrocyte traits. However, the functional variants and their working mechanisms remain largely unknown. Here, we reported that the SNP of rs80207740, which was associated with red blood cell (RBC) volume and hemoglobin content across populations, conferred enhancer activity to XPO7 gene via allele-differentially binding to Ikaros family zinc finger 1 (IKZF1). We showed that the region around rs80207740 was an erythroid-specific enhancer using reporter assays, and that the G-allele further enhanced activity. 3D genome evidence showed that the enhancer interacted with the XPO7 promoter, and eQTL analysis suggested that the G-allele upregulated expression of XPO7. We further showed that the rs80207740-G allele facilitated the binding of transcription factor IKZF1 in EMSA and ChIP analyses. Knockdown of IKZF1 and GATA1 resulted in decreased expression of Xpo7 in both human and mouse erythroid cells. Finally, we constructed Xpo7 knockout mouse by CRISPR/Cas9 and observed anemic phenotype with reduced volume and hemoglobin content of RBC, consistent to the effect of rs80207740 on erythrocyte traits. Overall, our study demonstrated that rs80207740 modulated erythroid indices by regulating IKZF1 binding and Xpo7 expression.

ß-Caryophyllene mitigates ischemic stroke-induced white matter lesions by inhibiting pyroptosis.

ß-Caryophyllene (BCP), a selective agonist for cannabinoid receptor 2 (CB2R), has demonstrated promising protective effects in various pathological conditions. However, the neuroprotective effects of BCP on white matter damage induced by ischemic stroke have not been elucidated previously. In this study, we find that BCP not only improves sensorimotor and cognitive function via CB2R but also mitigates white matter lesions in mice following ischemic stroke. Furthermore, BCP enhances the viability of MO3.13 oligodendrocytes after oxygen-glucose deprivation and reoxygenation (OGD/R), attenuating OGD/R-induced cellular damage and pyroptosis. Notably, these protective effects of BCP are partially enhanced by the NLRP3 inhibitor MCC950 and counteracted by the NLRP3 activator nigericin. In addition, nigericin significantly exacerbates neurological outcomes and increases white matter lesions following BCP treatment in middle cerebral artery occlusion (MCAO) mice. These results suggest that BCP may ameliorate neurological deficits and white matter damage induced by cerebral ischemia through inhibiting NLRP3-mediated pyroptosis.

A rapid protocol for ribosome profiling of low input samples.

Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments that are protected by ribosomes from nucleolytic digestion. While the overall principle is simple, the workflow of ribosome profiling experiments is complex and challenging, and typically requires large amounts of sample, limiting its broad applicability. Here, we present a new protocol for ultra-rapid ribosome profiling from low-input samples. It features a robust strategy for sequencing library preparation within one day that employs solid phase purification of reaction intermediates, allowing to reduce the input to as little as 0.1 pmol of ∼30 nt RNA fragments. Hence, it is particularly suited for the analyses of small samples or targeted ribosome profiling. Its high sensitivity and its ease of implementation will foster the generation of higher quality data from small samples, which opens new opportunities in applying ribosome profiling.

Immune Regulation of the Liver Through the PCSK9/CD36 Pathway During Heart Transplant Rejection.

BACKGROUND: PCSK9 (proprotein convertase subtilisin/kexin 9), which is mainly secreted by the liver, is not only a therapeutic target for hyperlipidemia and cardiovascular disease, but also has been implicated in the immune regulation of infections and tumors. However, the role of PCSK9 and the liver in heart transplant rejection (HTR) and the underlying mechanisms remain unclear. METHODS: We assessed serum PCSK9 expression in both murine and human recipients during HTR and investigated the effect of PCSK9 ablation on HTR by using global knockout mice and a neutralizing antibody. Moreover, we performed multiorgan histological and transcriptome analyses, and multiomics and single-cell RNA-sequencing studies of the liver during HTR, as well. We further used hepatocyte-specific Pcsk9 knockout mice to investigate whether the liver regulated HTR through PCSK9. Last, we explored the regulatory effect of the PCSK9/CD36 pathway on the phenotype and function of macrophages in vitro and in vivo. RESULTS: Here, we report that murine and human recipients have high serum PCSK9 levels during HTR. PCSK9 ablation prolonged cardiac allograft survival and attenuated the infiltration of inflammatory cells in the graft and the expansion of alloreactive T cells in the spleen. Next, we demonstrated that PCSK9 was mainly produced and significantly upregulated in the recipient liver, which also showed a series of signaling changes, including changes in the TNF-α (tumor necrosis factor α) and IFN-γ (interferon γ) signaling pathways and the bile acid and fatty acid metabolism pathways. We found mechanistically that TNF-α and IFN-γ synergistically promoted PCSK9 expression in hepatocytes through the transcription factor SREBP2 (sterol regulatory element binding protein 2). Moreover, in vitro and in vivo studies indicated that PCSK9 inhibited CD36 expression and fatty acid uptake by macrophages and strengthened the proinflammatory phenotype, which facilitated their ability to promote proliferation and IFN-γ production by donor-reactive T cells. Last, we found that the protective effect of PCSK9 ablation against HTR is dependent on the CD36 pathway in the recipient. CONCLUSIONS: This study reveals a novel mechanism for immune regulation by the liver through the PCSK9/CD36 pathway during HTR, which influences the phenotype and function of macrophages and suggests that the modulation of this pathway may be a potential therapeutic target to prevent HTR.

Genome-wide identification of SWEET genes reveals their roles during seed development in peanuts.

Sugar Will Eventually be Exported Transporter (SWEET) proteins are highly conserved in various organisms and play crucial roles in sugar transport processes. However, SWEET proteins in peanuts, an essential leguminous crop worldwide, remain lacking in systematic characterization. Here, we identified 94 SWEET genes encoding the conservative MtN3/saliva domains in three peanut species, including 47 in Arachis hypogea, 23 in Arachis duranensis, and 24 in Arachis ipaensis. We observed significant variations in the exon-intron structure of these genes, while the motifs and domain structures remained highly conserved. Phylogenetic analysis enabled us to categorize the predicted 286 SWEET proteins from eleven species into seven distinct groups. Whole genome duplication/segment duplication and tandem duplication were the primary mechanisms contributing to the expansion of the total number of SWEET genes. In addition, an investigation of cis-elements in the potential promoter regions and expression profiles across 22 samples uncovered the diverse expression patterns of AhSWEET genes in peanuts. AhSWEET24, with the highest expression level in seeds from A. hypogaea Tifrunner, was observed to be localized on both the plasma membrane and endoplasmic reticulum membrane. Moreover, qRT-PCR results suggested that twelve seed-expressed AhSWEET genes were important in the regulation of seed development across four different peanut varieties. Together, our results provide a foundational basis for future investigations into the functions of SWEET genes in peanuts, especially in the process of seed development.

Immobilizing Ordered Oxophilic Indium Sites on Platinum Enabling Efficient Hydrogen Oxidation in Alkaline Electrolyte.

Addressing the sluggish kinetics in the alkaline hydrogen oxidation reaction (HOR) is a pivotal yet challenging step toward the commercialization of anion-exchange membrane fuel cells (AEMFCs). Here, we have successfully immobilized indium (In) atoms in an orderly fashion into platinum (Pt) nanoparticles supported by reduced graphene oxide (denoted as O-Pt3In/rGO), significantly enhancing alkaline HOR kinetics. We have revealed that the ordered atomic matrix enables uniform and optimized hydrogen binding energy (HBE), hydroxyl binding energy (OHBE), and carbon monoxide binding energy (COBE) across the catalyst. With a mass activity of 2.3066 A mg-1 at an overpotential of 50 mV, over 10 times greater than that of Pt/C, the catalyst also demonstrates admirable CO resistance and stability. Importantly, the AEMFC implementing this catalyst as the anode catalyst has achieved an impressive power output compared to Pt/C. This work not only highlights the significance of constructing ordered oxophilic sites for alkaline HOR but also sheds light on the design of well-structured catalysts for energy conversion.

Button-Push On-Demand Synthesis for Rapid Optimization of Antiviral Peptidomimetics.

The optimization of hit compounds into drug candidates is a pivotal phase in drug discovery but often hampered by cumbersome manual synthesis of derivatives. While automated organic molecule synthesis has enhanced efficiency, safety, and cost-effectiveness, achieving fully automated multistep synthesis remains a formidable challenge due to issues such as solvent and reagent incompatibilities and the accumulation of side-products. We herein demonstrate an automated solid-phase flow platform for synthesizing α-keto-amides and nitrile peptidomimetics, guided by docking simulations, to identify potent broad-spectrum antiviral leads. A compact parallel synthesizer was built in-house, capable of producing 5 distinct molecules per cycle; 525 reactions could be finished within three months to generate 42 derivatives for a structure-activity relationship (SAR) investigation. Among these, ten derivatives exhibited promising target inhibitory activity (IC50 < 100 nM) including two with antiviral activity (EC50 < 250 nM). The platform, coupled with digital chemical recipe files, offers rapid access to a wide range of peptidomimetics, serving as a valuable reservoir for broad-spectrum antiviral candidates. This automated solid-phase flow synthesis approach expedites the generation of previously difficult complex molecular scaffolds. By integration of SPS-flow synthesis with medicinal chemistry campaign, >10-fold target inhibitory activity was achieved from a small set of derivatives, which indicates the potential to shift the paradigm of drug discovery.

Circulating microRNAs in association with pancreatic cancer risk within 5 years.

Early detection is critical for improving pancreatic cancer prognosis. Our study aims to identify circulating microRNAs (miRNAs) associated with pancreatic cancer risk. The two-stage study used plasma samples collected ≤5 years prior to cancer diagnosis, from case-control studies nested in five prospective cohort studies. The discovery stage included 185 case-control pairs from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Replication stage samples comprised 277 pairs from Shanghai Women's Health Study/Shanghai Men's Health Study, Southern Community Cohort Study, and Multiethnic Cohort Study. Seven hundred and ninety-eight miRNAs were measured using the NanoString nCounter Analysis System. Odds ratios (OR) and 95% confidence intervals (CI) for per 10% change in miRNAs in association with pancreatic cancer risk were derived from conditional logistic regression analysis in discovery and replication studies, separately, and then meta-analyzed. Stratified analysis was conducted by age at diagnosis (<65/≥65 years) and time interval between sample collection and diagnosis (≤2/>2 years). In the discovery stage, 120 risk associated miRNAs were identified at p < .05. Three were validated in the replication stage: hsa-miR-199a-3p/hsa-miR-199b-3p, hsa-miR-767-5p, and hsa-miR-191-5p, with respective ORs (95% CI) being 0.89 (0.84-0.95), 1.08 (1.02-1.13), and 0.90 (0.85-0.95). Five additional miRNAs, hsa-miR-640, hsa-miR-874-5p, hsa-miR-1299, hsa-miR-22-3p, and hsa-miR-449b-5p, were validated among patients diagnosed at ≥65 years, with OR (95% CI) of 1.23 (1.09-1.39), 1.33 (1.16-1.52), 1.25 (1.09-1.43), 1.28 (1.12-1.46), 0.76 (0.65-0.89), and 1.22 (1.07-1.39), respectively. The miRNA targets were enriched in pancreatic carcinogenesis/progression-related pathways. Our study suggests that circulating miRNAs may identify individuals at high risk for pancreatic cancer ≤5 years prior to diagnosis, indicating its potential utility in cancer screening and surveillance.

Increased mutations in lipopolysaccharide biosynthetic genes cause time-dependent development of phage resistance in Salmonella.

Understanding how bacteria evolve resistance to phages has implications for phage-based therapies and microbial evolution. In this study, the susceptibility of 335 Salmonella isolates to the wide host range Salmonella phage BPSELC-1 was tested. Potentially significant gene sets that could confer resistance were identified using bioinformatics approaches based on phage susceptibility phenotypes; more than 90 potential antiphage defense gene sets, including those involved in lipopolysaccharide (LPS) biosynthesis, DNA replication, secretion systems, and respiratory chain, were found. The evolutionary dynamics of Salmonella resistance to phage were assessed through laboratory evolution experiments, which showed that phage-resistant mutants rapidly developed and exhibited genetic heterogeneity. Most representative Salmonella hosts (58.1% of 62) rapidly developed phage resistance within 24 h. All phage-resistant mutant clones exhibited genetic heterogeneity and observed mutations in LPS-related genes (rfaJ and rfaK) as well as other genes such as cellular respiration, transport, and cell replication-related genes. The study also identified potential trade-offs, indicating that bacteria tend to escape fitness trade-offs through multi-site mutations, all tested mutants increased sensitivity to polymyxin B, but this does not always affect their relative fitness or biofilm-forming capacity. Furthermore, complementing the rfaJ mutant gene could partially restore the phage sensitivity of phage-resistant mutants. These results provide insight into the phage resistance mechanisms of Salmonella and the complexity of bacterial evolution resulting from phage predation, which can inform future strategies for phage-based therapies and microbial evolution.