Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes.

Most patients diagnosed with resected pancreatic adenocarcinoma (PDAC) survive less than 5 years, but a minor subset survives longer. Here, we dissect the role of the tumor microbiota and the immune system in influencing long-term survival. Using 16S rRNA gene sequencing, we analyzed the tumor microbiome composition in PDAC patients with short-term survival (STS) and long-term survival (LTS). We found higher alpha-diversity in the tumor microbiome of LTS patients and identified an intra-tumoral microbiome signature (Pseudoxanthomonas-Streptomyces-Saccharopolyspora-Bacillus clausii) highly predictive of long-term survivorship in both discovery and validation cohorts. Through human-into-mice fecal microbiota transplantation (FMT) experiments from STS, LTS, or control donors, we were able to differentially modulate the tumor microbiome and affect tumor growth as well as tumor immune infiltration. Our study demonstrates that PDAC microbiome composition, which cross-talks to the gut microbiome, influences the host immune response and natural history of the disease.

Historic dog Furs Unravel the Origin and Artificial Selection of Modern Nordic Lapphund and Elkhound dog Breeds.

The origins and extreme morphological evolution of the modern dog breeds are poorly studied because the founder populations are extinct. Here, we analyse eight 100 to 200 years old dog fur samples obtained from traditional North Swedish clothing, to explore the origin and artificial selection of the modern Nordic Lapphund and Elkhound dog breeds. Population genomic analysis confirmed the Lapphund and Elkhound breeds to originate from the local dog population, and showed a distinct decrease in genetic diversity in agreement with intense breeding. We identified eleven genes under positive selection during the breed development. In particular, the MSRB3 gene, associated with breed-related ear morphology, was selected in all Lapphund and Elkhound breeds, and functional assays showed that a SNP mutation in the 3'UTR region suppresses its expression through miRNA regulation. Our findings demonstrate analysis of near-modern dog artifacts as an effective tool for interpreting the origin and artificial selection of the modern dog breeds.

magpie: A power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing.

Recently, novel biotechnologies to quantify RNA modifications became an increasingly popular choice for researchers who study epitranscriptome. When studying RNA methylations such as N6-methyladenosine (m6A), researchers need to make several decisions in its experimental design, especially the sample size and a proper statistical power. Due to the complexity and high-throughput nature of m6A sequencing measurements, methods for power calculation and study design are still currently unavailable. In this work, we propose a statistical power assessment tool, magpie, for power calculation and experimental design for epitranscriptome studies using m6A sequencing data. Our simulation-based power assessment tool will borrow information from real pilot data, and inspect various influential factors including sample size, sequencing depth, effect size, and basal expression ranges. We integrate two modules in magpie: (i) a flexible and realistic simulator module to synthesize m6A sequencing data based on real data; and (ii) a power assessment module to examine a set of comprehensive evaluation metrics.

Crol contributes to PRE-mediated repression and Polycomb group proteins recruitment in Drosophila.

The Polycomb group (PcG) proteins are fundamental epigenetic regulators that control the repressive state of target genes in multicellular organisms. One of the open questions is defining the mechanisms of PcG recruitment to chromatin. In Drosophila, the crucial role in PcG recruitment is thought to belong to DNA-binding proteins associated with Polycomb response elements (PREs). However, current data suggests that not all PRE-binding factors have been identified. Here, we report the identification of the transcription factor Crooked legs (Crol) as a novel PcG recruiter. Crol is a C2H2-type Zinc Finger protein that directly binds to poly(G)-rich DNA sequences. Mutation of Crol binding sites as well as crol CRISPR/Cas9 knockout diminish the repressive activity of PREs in transgenes. Like other PRE-DNA binding proteins, Crol co-localizes with PcG proteins inside and outside of H3K27me3 domains. Crol knockout impairs the recruitment of the PRC1 subunit Polyhomeotic and the PRE-binding protein Combgap at a subset of sites. The decreased binding of PcG proteins is accompanied by dysregulated transcription of target genes. Overall, our study identified Crol as a new important player in PcG recruitment and epigenetic regulation.

Influence of oral microbiome on longitudinal patterns of oral mucositis severity in patients with squamous cell carcinoma of the head and neck.

BACKGROUND: This study investigated the influence of oral microbial features on the trajectory of oral mucositis (OM) in patients with squamous cell carcinoma of the head and neck. METHODS: OM severity was assessed and buccal swabs were collected at baseline, at the initiation of cancer treatment, weekly during cancer treatment, at the termination of cancer treatment, and after cancer treatment termination. The oral microbiome was characterized via the 16S ribosomal RNA V4 region with the Illumina platform. Latent class mixed-model analysis was used to group individuals with similar trajectories of OM severity. Locally estimated scatterplot smoothing was used to fit an average trend within each group and to assess the association between the longitudinal OM scores and longitudinal microbial abundances. RESULTS: Four latent groups (LGs) with differing patterns of OM severity were identified for 142 subjects. LG1 has an early onset of high OM scores. LGs 2 and 3 begin with relatively low OM scores until the eighth and 11th week, respectively. LG4 has generally flat OM scores. These LGs did not vary by treatment or clinical or demographic variables. Correlation analysis showed that the abundances of Bacteroidota, Proteobacteria, Bacteroidia, Gammaproteobacteria, Enterobacterales, Bacteroidales, Aerococcaceae, Prevotellaceae, Abiotrophia, and Prevotella_7 were positively correlated with OM severity across the four LGs. Negative correlation was observed with OM severity for a few microbial features: Abiotrophia and Aerococcaceae for LGs 2 and 3; Gammaproteobacteria and Proteobacteria for LGs 2, 3, and 4; and Enterobacterales for LGs 2 and 4. CONCLUSIONS: These findings suggest the potential to personalize treatment for OM. PLAIN LANGUAGE SUMMARY: Oral mucositis (OM) is a common and debilitating after effect for patients treated for squamous cell carcinoma of the head and neck. Trends in the abundance of specific microbial features may be associated with patterns of OM severity over time. Our findings suggest the potential to personalize treatment plans for OM via tailored microbiome interventions.

Acid-Triggered Degradation of Three-In-One Ag2S Quantum Dots for In Situ Ratiometric NIR-II Fluorescence Imaging-Guided Ion/Gas Combination Therapy.

Smart theranostic nanoprobes with the integration of multiple therapeutic modalities are preferred for precise diagnosis and efficient therapy of tumors. However, it remains a big challenge to arrange the imaging and two or more kinds of therapeutic agents without weakening the intended performances. In addition, most existing fluorescence (FL) imaging agents suffer from low spatiotemporal resolution due to the short emission wavelength (<900 nm). Here, novel three-in-one Ag2S quantum dot (QD)-based smart theranostic nanoprobes were proposed for in situ ratiometric NIR-II FL imaging-guided ion/gas combination therapy of tumors. Under the acidic tumor microenvironment, three-in-one Ag2S QDs underwent destructive degradation, generating toxic Ag+ and H2S. Meanwhile, their FL emission at 1270 nm was weakened. Upon introduction of a downconversion nanoparticle (DCNP) as the delivery carrier and NIR-II FL reference signal unit, the formed Ag2S QD-based theranostic nanoprobes could achieve precise diagnosis of tumors through ratiometric NIR-II FL signals. Also, the generated Ag+ and H2S enabled specific ion/gas combination therapy toward tumors. By combining the imaging and therapeutic functions, three-in-one Ag2S QDs may open a simple yet reliable avenue to design theranostic nanoprobes.

Proximity-Induced Bipedal DNA Walker for Accurately Visualizing microRNA in Living Cancer Cell.

DNA walker, a type of dynamic DNA device that is capable of moving progressively along prescribed walking tracks, has emerged as an ideal and powerful tool for biosensing and bioimaging. However, most of the reported three-dimensional (3D) DNA walker were merely designed for the detection of a single target, and they were not capable of achieving universal applicability. Herein, we reported for the first time the development of a proximity-induced 3D bipedal DNA walker for imaging of low abundance biomolecules. As a proof of concept, miRNA-34a, a biomarker of breast cancer, is chosen as the model system to demonstrate this approach. In our design, the 3D bipedal DNA walker can be generated only by the specific recognition of two proximity probes for miRNA-34a. Meanwhile, it stochastically and autonomously traveled on 3D tracks (gold nanoparticles) via catalytic hairpin assembly (CHA), resulting in the amplified fluorescence signal. In comparison with some conventional DNA walkers that were utilized for living cell imaging, the 3D DNA walkers induced by proximity ligation assay can greatly improve and ensure the high selectivity of bioanalysis. By taking advantage of these unique features, the proximity-induced 3D bipedal DNA walker successfully realizes accurate and effective monitoring of target miRNA-34a expression levels in living cells, affording a universal, valuable, and promising platform for low-abundance cancer biomarker detection and accurate identification of cancer.

ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization.

SUMMARY: Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, for analyzing functional profiles derived from 16S rRNA sequencing. This powerful tool enables researchers to conduct extensive differential abundance analyses and generate visually appealing visualizations that effectively highlight functional signals. With ggpicrust2, users can obtain publishable results and gain deeper insights into the functional composition of their microbial communities. AVAILABILITY AND IMPLEMENTATION: The package is open-source under the MIT and file license and is available at CRAN and https://github.com/cafferychen777/ggpicrust2. Its shiny web is available at https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/.

Lead remediation by geological fluorapatite combined with Penicillium Oxalicum and Red yeast.

Phosphate solubilizing fungi Penicillium oxalicum (POX) and Red yeast Rhodotorula mucilaginosa (Rho) have been applied in Pb remediation with the combination of fluorapatite (FAp), respectively. The secretion of oxalic acid by POX and the production of extracellular polymers (EPS) by Rho dominate the Pb remediation. In this study, the potential of Pb remediation by the fungal combined system (POX and Rho) with FAp was investigated. After six days of incubation, the combination of POX and Rho showed the highest Pb remove ratio (99.7%) and the lowest TCLP-Pb concentration (2.9 mg/L). The EPS combined with POX also enhanced Pb remediation, which has a 99.3% Pb removal ratio and 5.5 mg/L TCLP-Pb concentration. Meanwhile, Rho and EPS can also stimulate POX to secrete more oxalic acid, which reached 1510.1 and 1450.6 mg/L in six days, respectively. The secreted oxalic acid can promote FAp dissolution and the formation of lead oxalate and pyromorphite. Meanwhile, the EPS produced by Rho can combine with Pb to form EPS-Pb. In the combined system of POX + Rho and POX + EPS, all of the lead oxalate, pyromorphite, and EPS-Pb were observed. Our findings suggest that the combined application of POX and Rho with FAp is an effective approach for enhancing Pb remediation.

Spatial-temporal Bayesian accelerated failure time models for survival endpoints with applications to prostate cancer registry data.

Prostate cancer is the most common cancer after non-melanoma skin cancer and the second leading cause of cancer deaths in US men. Its incidence and mortality rates vary substantially across geographical regions and over time, with large disparities by race, geographic regions (i.e., Appalachia), among others. The widely used Cox proportional hazards model is usually not applicable in such scenarios owing to the violation of the proportional hazards assumption. In this paper, we fit Bayesian accelerated failure time models for the analysis of prostate cancer survival and take dependent spatial structures and temporal information into account by incorporating random effects with multivariate conditional autoregressive priors. In particular, we relax the proportional hazards assumption, consider flexible frailty structures in space and time, and also explore strategies for handling the temporal variable. The parameter estimation and inference are based on a Monte Carlo Markov chain technique under a Bayesian framework. The deviance information criterion is used to check goodness of fit and to select the best candidate model. Extensive simulations are performed to examine and compare the performances of models in different contexts. Finally, we illustrate our approach by using the 2004-2014 Pennsylvania Prostate Cancer Registry data to explore spatial-temporal heterogeneity in overall survival and identify significant risk factors.

Microwave-assisted synthesis of highly sulfated mannuronate glycans as potential inhibitors against SARS-CoV-2.

Algae-based marine carbohydrate drugs are typically decorated with negative ion groups such as carboxylate and sulfate groups. However, the precise synthesis of highly sulfated alginates is challenging, thus impeding their structure-activity relationship studies. Herein we achieve a microwave-assisted synthesis of a range of highly sulfated mannuronate glycans with up to 17 sulfation sites by overcoming the incomplete sulfation due to the electrostatic repulsion of crowded polyanionic groups. Although the partially sulfated tetrasaccharide had the highest affinity for the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant, the fully sulfated octasaccharide showed the most potent interference with the binding of the RBD to angiotensin-converting enzyme 2 (ACE2) and Vero E6 cells, indicating that the sulfated oligosaccharides might inhibit the RBD binding to ACE2 in a length-dependent manner.

Development and validation of a clinical and laboratory-based nomogram to predict mortality in patients with severe fever with thrombocytopenia syndrome.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging global infectious disease with a high mortality rate. Clinicians lack a convenient tool for early identification of critically ill SFTS patients. The aim of this study was to construct a simple and accurate nomogarm to predict the prognosis of SFTS patients. METHODS: We retrospectively analyzed the clinical data of 372 SFTS patients collected between May 2015 and June 2023, which were divided 7:3 into a training set and an internal validation set. We used LASSO regression to select predictor variables and multivariable logistic regression to identify independent predictor variables. Prognostic nomograms for SFTS were constructed based on these factors and analysed for concordance index, calibration curves and area under the curve (AUC) to determine the predictive accuracy and consistency of the model. RESULTS: In the training set, LASSO and multivariate logistic regression analyses showed that age, SFTSV RNA, maximum body temperature, pancreatitis, gastrointestinal bleeding, pulmonary fungal infection (PFI), BUN, and PT were independent risk factors for death in SFTS patients. There was a strong correlation between neurological symptoms and mortality (P < 0.001, OR = 108.92). Excluding neurological symptoms, nomograms constructed based on the other eight variables had AUCs of 0.937 and 0.943 for the training and validation sets, respectively. Furthermore, we found that age, gastrointestinal bleeding, PFI, bacteraemia, SFTSV RNA, platelets, and PT were the independent risk factors for neurological symptoms, with SFTSV RNA having the highest diagnostic value (AUC = 0.785). CONCLUSIONS: The nomogram constructed on the basis of eight common clinical variables can easily and accurately predict the prognosis of SFTS patients. Moreover, the diagnostic value of neurological symptoms far exceeded that of other predictors, and SFTSV RNA was the strongest independent risk factor for neurological symptoms, but these need to be further verified by external data.

Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis.

BACKGROUND: Ferroptosis, is characterized by lipid peroxidation of fatty acids in the presence of iron ions, which leads to cell apoptosis. This leads to the disruption of metabolic pathways, ultimately resulting in liver dysfunction. Although ferroptosis is linked to nonalcoholic steatohepatitis (NASH), understanding the key ferroptosis-related genes (FRGs) involved in NASH remains incomplete. NASH may be targeted therapeutically by identifying the genes responsible for ferroptosis. METHODS: To identify ferroptosis-related genes and develop a ferroptosis-related signature (FeRS), 113 machine-learning algorithm combinations were used. RESULTS: The FeRS constructed using the Generalized Linear Model Boosting algorithm and Gradient Boosting Machine algorithms exhibited the best prediction performance for NASH. Eight FRGs, with ZFP36 identified by the algorithms as the most crucial, were incorporated into in FeRS. ZFP36 is significantly enriched in various immune cell types and exhibits significant positive correlations with most immune signatures. CONCLUSION: ZFP36 is a key FRG involved in NASH pathogenesis.

Machine learning-based algorithm identifies key mitochondria-related genes in non-alcoholic steatohepatitis.

BACKGROUND: Evidence suggests that hepatocyte mitochondrial dysfunction leads to abnormal lipid metabolism, redox imbalance, and programmed cell death, driving the onset and progression of non-alcoholic steatohepatitis (NASH). Identifying hub mitochondrial genes linked to NASH may unveil potential therapeutic targets. METHODS: Mitochondrial hub genes implicated in NASH were identified via analysis using 134 algorithms. RESULTS: The Random Forest algorithm (RF), the most effective among the 134 algorithms, identified three genes: Aldo-keto reductase family 1 member B10 (AKR1B10), thymidylate synthase (TYMS), and triggering receptor expressed in myeloid cell 2 (TREM2). They were upregulated and positively associated with genes promoting inflammation, genes involved in lipid synthesis, fibrosis, and nonalcoholic steatohepatitis activity scores in patients with NASH. Moreover, using these three genes, patients with NASH were accurately categorized into cluster 1, exhibiting heightened disease severity, and cluster 2, distinguished by milder disease activity. CONCLUSION: These three genes are pivotal mitochondrial genes implicated in NASH progression.

Comparing the efficacy of 308-nm light-emitting diode and 308-nm excimer lamp for treating vitiligo: A randomized controlled trial.

BACKGROUND: In previous studies, the 308-nm light-emitting diode (LED) has been proven safe and effective for treating vitiligo. However, direct comparisons between the 308-nm LED and 308-nm excimer lamp (308-nm MEL) for the treatment of vitiligo are lacking. OBJECTIVE: To compare the efficacy of the 308-nm LED and 308-nm MEL for treating nonsegmental stable vitiligo. PATIENTS AND METHODS: This randomized controlled trial was conducted between January 2018 and August 2023. Enrolled patients were randomly assigned to either the 308-nm LED or the 308-nm MEL groups, both receiving 16 treatment sessions. Adverse events that occurred during the treatment were documented. RESULTS: In total, 269 stable vitiligo patches from 174 patients completed the study. A total of 131 lesions were included in the 308-nm LED group, and 138 lesions were included in the 308-nm MEL group. After 16 treatment sessions, 38.17% of the vitiligo patches in the 308-nm LED group achieved repigmentation of at least 50% versus 38.41% in the 308-nm MEL group. The two devices exhibited similar results in terms of efficacy for a repigmentation of at least 50% (p = .968). The incidence of adverse effects with the two phototherapy devices was comparable (p = .522). CONCLUSIONS: Treatment of vitiligo with the 308-nm LED had a similar efficacy rate to the 308-nm MEL, and the incidence of adverse effects was comparable between the two devices.

Improving the sensing sensitivity of silver nanoparticle-based colorimetric biosensors from the point of salt.

The sensing sensitivity was improved for silver nanoparticles (AgNPs)-based colorimetric biosensors by using the most suitable salt to induce AgNPs aggregation. As for the salt composed of low-affinity anion and monovalent cation, the cation-dependent charge screening effect was the driving force for AgNPs aggregation. Apart from the charge screening effect, both the bridging of multivalent cation to the surface ligand of AgNP and the interaction between anion and Ag contributed to inducing AgNPs aggregation. Considering the higher aggregation efficiency of AgNPs resulted in a narrower sensing range, salt composed of low-affinity anion and monovalent cation was recommended for AgNPs-based colorimetric analysis, which was confirmed by fourfold higher sensitivity of DNA-21 detection using NaF than NaCl. This work inspires further thinking on improving the sensing performance of metal nanomaterials-based sensors from the point of colloidal surface science.

Recent Advances in Carborane-Based Crystalline Porous Materials.

The field of carborane research has witnessed continuous development, leading to the construction and development of a diverse range of crystalline porous materials for various applications. Moreover, innovative synthetic approaches are expanding in this field. Since the first report of carborane-based crystalline porous materials (CCPMs) in 2007, the synthesis of carborane ligands, particularly through innovative methods, has consistently posed a significant challenge in discovering new structures of CCPMs. This paper provides a comprehensive summary of recent advances in various synthetic approaches for CCPMs, along with their applications in different domains. The primary challenges and future opportunities are expected to stimulate further multidisciplinary development in the field of CCPMs.

Research on the Cell Wall Breaking and Subcritical Extraction of Astaxanthin from Phaffia rhodozyma.

This study focused on developing an effective cell wall-breaking method for Phaffia rhodozyma, followed by utilizing subcritical fluid extraction to isolate, extract, and concentrate astaxanthin from the complex fermentation products of P. rhodozyma. A comprehensive comparison of seven distinct methods for disrupting cell walls, including dimethyl sulfoxide treatment, lactic acid treatment, sodium hydroxide treatment, ß-glucanase enzymatic digestion, ß-mannanase enzymatic digestion, and a combined enzymatic treatment involving both ß-mannanase and ß-glucanase was conducted. The results identified the lactic acid method as the most effective in disrupting the cell walls of P. rhodozyma. The software, Design Expert, was used in the process of extracting astaxanthin from cell lysates using a subcritical extraction method. Through fitting analysis and response surface optimization analysis by Design Expert, the optimal extraction conditions were determined as follows: an extraction temperature of 41 °C, extraction frequency of two times, and extraction time of 46 min. These parameters facilitated the efficient extraction, concentration, and enrichment of astaxanthin from P. rhodozyma, resulting in an astaxanthin concentration of 540.00 mg/L. This result can establish the foundation for its high-value applications.

Synergistic interaction of Cu(II) with caffeic acid and chlorogenic acid in α-glucosidase inhibition.

BACKGROUND: Phenolic acids are widespread in foods and are beneficial to human health. However, the role of metal ions in influencing the binding of proteins with phenolic acids that contain the same parent nucleus structure remains unclear. This study investigated the inhibitory effect of caffeic acid (CA) and chlorogenic acid (CHA) on α-glucosidase and the biological effect of copper on this process. RESULTS: It was found that the esterification of CA with quinic acid could increase the fluorescence quenching, conformational change, and inhibitory effect of CHA on α-glucosidase. Copper ions reduced their fluorescence quenching and conformation-changing ability by binding to the neighboring phenolic hydroxyl group but also increased their ability to alter secondary structure and to inhibit α-glucosidase and in vitro anti-glycation. CONCLUSION: Overall, this study shows that the binding of copper ions to the phenolic hydroxyl group adjacent to CA and CHA synergistically inhibited α-glucosidase. The findings will offer a theoretical basis for investigating the properties of metal ions and phenolic acid in food chemistry and their potential applications in the prevention and treatment of diabetes mellitus. © 2023 Society of Chemical Industry.

Structurally Modulated Formation of Cyanine J-Aggregates with Sharp and Tunable Spectra for Multiplexed Optoacoustic and Fluorescence Bioimaging.

J-aggregation brings intriguing optical and electronic properties to molecular dyes and significantly expands their applicability across diverse domains, yet the challenge for rationally designing J-aggregating dyes persists. Herein, we developed a large number of J-aggregating dyes from scratch by progressively refining structure of a common heptamethine cyanine. J-aggregates with sharp spectral bands (full-width at half-maximum≤38 nm) are attained by introducing a branched structure featuring a benzyl and a trifluoroacetyl group at meso-position of dyes. Fine-tuning the benzyl group enables spectral regulation of J-aggregates. Analysis of single crystal data of nine dyes reveals a correlation between J-aggregation propensity and molecular arrangement within crystals. Some J-aggregates are successfully implemented in multiplexed optoacoustic and fluorescence imaging in animals. Notably, three-color multispectral optoacoustic tomography imaging with high spatiotemporal resolution is achieved, owing to the sharp and distinct absorption bands of the J-aggregates.