Capture RIC-seq reveals positional rules of PTBP1-associated RNA loops in splicing regulation.

RNA-binding proteins (RBPs) bind at different positions of the pre-mRNA molecules to promote or reduce the usage of a particular exon. Seeking to understand the working principle of these positional effects, we develop a capture RIC-seq (CRIC-seq) method to enrich specific RBP-associated in situ proximal RNA-RNA fragments for deep sequencing. We determine hnRNPA1-, SRSF1-, and PTBP1-associated proximal RNA-RNA contacts and regulatory mechanisms in HeLa cells. Unexpectedly, the 3D RNA map analysis shows that PTBP1-associated loops in individual introns preferentially promote cassette exon splicing by accelerating asymmetric intron removal, whereas the loops spanning across cassette exon primarily repress splicing. These "positional rules" can faithfully predict PTBP1-regulated splicing outcomes. We further demonstrate that cancer-related splicing quantitative trait loci can disrupt RNA loops by reducing PTBP1 binding on pre-mRNAs to cause aberrant splicing in tumors. Our study presents a powerful method for exploring the functions of RBP-associated RNA-RNA proximal contacts in gene regulation and disease.

Shape memory polymer with programmable recovery onset.

Stimulus-responsive shape-shifting polymers1-3 have shown unique promise in emerging applications, including soft robotics4-7, medical devices8, aerospace structures9 and flexible electronics10. Their externally triggered shape-shifting behaviour offers on-demand controllability essential for many device applications. Ironically, accessing external triggers (for example, heating or light) under realistic scenarios has become the greatest bottleneck in demanding applications such as implantable medical devices8. Certain shape-shifting polymers rely on naturally present stimuli (for example, human body temperature for implantable devices)8 as triggers. Although they forgo the need for external stimulation, the ability to control recovery onset is also lost. Naturally triggered, yet actively controllable, shape-shifting behaviour is highly desirable but these two attributes are conflicting. Here we achieved this goal with a four-dimensional printable shape memory hydrogel that operates via phase separation, with its shape-shifting kinetics dominated by internal mass diffusion rather than by heat transport used for common shape memory polymers8-11. This hydrogel can undergo shape transformation at natural ambient temperature, critically with a recovery onset delay. This delay is programmable by altering the degree of phase separation during device programming, which offers a unique mechanism for shape-shifting control. Our naturally triggered shape memory polymer with a tunable recovery onset markedly lowers the barrier for device implementation.

Immune regulation by fungal strain diversity in inflammatory bowel disease.

The fungal microbiota (mycobiota) is an integral part of the complex multikingdom microbial community colonizing the mammalian gastrointestinal tract and has an important role in immune regulation1-6. Although aberrant changes in the mycobiota have been linked to several diseases, including inflammatory bowel disease3-9, it is currently unknown whether fungal species captured by deep sequencing represent living organisms and whether specific fungi have functional consequences for disease development in affected individuals. Here we developed a translational platform for the functional analysis of the mycobiome at the fungal-strain- and patient-specific level. Combining high-resolution mycobiota sequencing, fungal culturomics and genomics, a CRISPR-Cas9-based fungal strain editing system, in vitro functional immunoreactivity assays and in vivo models, this platform enables the examination of host-fungal crosstalk in the human gut. We discovered a rich genetic diversity of opportunistic Candida albicans strains that dominate the colonic mucosa of patients with inflammatory bowel disease. Among these human-gut-derived isolates, strains with high immune-cell-damaging capacity (HD strains) reflect the disease features of individual patients with ulcerative colitis and aggravated intestinal inflammation in vivo through IL-1ß-dependent mechanisms. Niche-specific inflammatory immunity and interleukin-17A-producing T helper cell (TH17 cell) antifungal responses by HD strains in the gut were dependent on the C. albicans-secreted peptide toxin candidalysin during the transition from a benign commensal to a pathobiont state. These findings reveal the strain-specific nature of host-fungal interactions in the human gut and highlight new diagnostic and therapeutic targets for diseases of inflammatory origin.

Acetylation coordinates the crosstalk between carbon metabolism and ammonium assimilation in Salmonella enterica.

Enteric bacteria use up to 15% of their cellular energy for ammonium assimilation via glutamine synthetase (GS)/glutamate synthase (GOGAT) and glutamate dehydrogenase (GDH) in response to varying ammonium availability. However, the sensory mechanisms for effective and appropriate coordination between carbon metabolism and ammonium assimilation have not been fully elucidated. Here, we report that in Salmonella enterica, carbon metabolism coordinates the activities of GS/GDH via functionally reversible protein lysine acetylation. Glucose promotes Pat acetyltransferase-mediated acetylation and activation of adenylylated GS. Simultaneously, glucose induces GDH acetylation to inactivate the enzyme by impeding its catalytic centre, which is reversed upon GDH deacetylation by deacetylase CobB. Molecular dynamics (MD) simulations indicate that adenylylation is required for acetylation-dependent activation of GS. We show that acetylation and deacetylation occur within minutes of "glucose shock" to promptly adapt to ammonium/carbon variation and finely balance glutamine/glutamate synthesis. Finally, in a mouse infection model, reduced S. enterica growth caused by the expression of adenylylation-mimetic GS is rescued by acetylation-mimicking mutations. Thus, glucose-driven acetylation integrates signals from ammonium assimilation and carbon metabolism to fine-tune bacterial growth control.

Oral Iptacopan Monotherapy in Paroxysmal Nocturnal Hemoglobinuria.

BACKGROUND: Persistent hemolytic anemia and a lack of oral treatments are challenges for patients with paroxysmal nocturnal hemoglobinuria who have received anti-C5 therapy or have not received complement inhibitors. Iptacopan, a first-in-class oral factor B inhibitor, has been shown to improve hemoglobin levels in these patients. METHODS: In two phase 3 trials, we assessed iptacopan monotherapy over a 24-week period in patients with hemoglobin levels of less than 10 g per deciliter. In the first, anti-C5-treated patients were randomly assigned to switch to iptacopan or to continue anti-C5 therapy. In the second, single-group trial, patients who had not received complement inhibitors and who had lactate dehydrogenase (LDH) levels more than 1.5 times the upper limit of the normal range received iptacopan. The two primary end points in the first trial were an increase in the hemoglobin level of at least 2 g per deciliter from baseline and a hemoglobin level of at least 12 g per deciliter, each without red-cell transfusion; the primary end point for the second trial was an increase in hemoglobin level of at least 2 g per deciliter from baseline without red-cell transfusion. RESULTS: In the first trial, 51 of the 60 patients who received iptacopan had an increase in the hemoglobin level of at least 2 g per deciliter from baseline, and 42 had a hemoglobin level of at least 12 g per deciliter, each without transfusion; none of the 35 anti-C5-treated patients attained the end-point levels. In the second trial, 31 of 33 patients had an increase in the hemoglobin level of at least 2 g per deciliter from baseline without red-cell transfusion. In the first trial, 59 of the 62 patients who received iptacopan and 14 of the 35 anti-C5-treated patients did not require or receive transfusion; in the second trial, no patients required or received transfusion. Treatment with iptacopan increased hemoglobin levels, reduced fatigue, reduced reticulocyte and bilirubin levels, and resulted in mean LDH levels that were less than 1.5 times the upper limit of the normal range. Headache was the most frequent adverse event with iptacopan. CONCLUSIONS: Iptacopan treatment improved hematologic and clinical outcomes in anti-C5-treated patients with persistent anemia - in whom iptacopan showed superiority to anti-C5 therapy - and in patients who had not received complement inhibitors. (Funded by Novartis; APPLY-PNH ClinicalTrials.gov number, NCT04558918; APPOINT-PNH ClinicalTrials.gov number, NCT04820530.).

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Physical immune escape: Weakened mechanical communication leads to escape of metastatic colorectal carcinoma cells from macrophages.

The significance of biochemical cues in the tumor immune microenvironment in affecting cancer metastasis is well established, but the role of physical factors in the microenvironment remains largely unexplored. In this article, we investigated how the mechanical interaction between cancer cells and immune cells, mediated by extracellular matrix (ECM), influences immune escape of cancer cells. We focus on the mechanical regulation of macrophages' targeting ability on two distinct types of colorectal carcinoma (CRC) cells with different metastatic potentials. Our results show that macrophages can effectively target CRC cells with low metastatic potential, due to the strong contraction exhibited by the cancer cells on the ECM, and that cancer cells with high metastatic potential demonstrated weakened contractions on the ECM and can thus evade macrophage attack to achieve immune escape. Our findings regarding the intricate mechanical interactions between immune cells and cancer cells can serve as a crucial reference for further exploration of cancer immunotherapy strategies.

The roles of nuclear orphan receptor NR2F6 in anti-viral innate immunity.

Proper transcription regulation by key transcription factors, such as IRF3, is critical for anti-viral defense. Dynamics of enhancer activity play important roles in many biological processes, and epigenomic analysis is used to determine the involved enhancers and transcription factors. To determine new transcription factors in anti-DNA-virus response, we have performed H3K27ac ChIP-Seq and identified three transcription factors, NR2F6, MEF2D and MAFF, in promoting HSV-1 replication. NR2F6 promotes HSV-1 replication and gene expression in vitro and in vivo, but not dependent on cGAS/STING pathway. NR2F6 binds to the promoter of MAP3K5 and activates AP-1/c-Jun pathway, which is critical for DNA virus replication. On the other hand, NR2F6 is transcriptionally repressed by c-Jun and forms a negative feedback loop. Meanwhile, cGAS/STING innate immunity signaling represses NR2F6 through STAT3. Taken together, we have identified new transcription factors and revealed the underlying mechanisms involved in the network between DNA viruses and host cells.

admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties.

Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties play a crucial role in drug discovery and chemical safety assessment. Built on the achievements of admetSAR and its successor, admetSAR2.0, this paper introduced the new version of the series, admetSAR3.0, as a comprehensive platform for chemical ADMET assessment, including search, prediction and optimization modules. In the search module, admetSAR3.0 hosted over 370 000 high-quality experimental ADMET data for 104 652 unique compounds, and supplemented chemical structure similarity search function to facilitate read-across. In the prediction module, we introduced comprehensive ADMET endpoints and two new sections for environmental and cosmetic risk assessments, empowering admetSAR3.0 to provide prediction for 119 endpoints, more than double numbers compared to the previous version. Furthermore, the advanced multi-task graph neural network framework offered robust and reliable support for ADMET prediction. In particular, a module named ADMETopt was added to automatically optimize the ADMET properties of query molecules through transformation rules or scaffold hopping. Finally, admetSAR3.0 provides user-friendly interfaces for multiple types of input data, such as SMILES string, chemical structure and batch molecule file, and supports various output types, including digital, chart displays and file downloads. In summary, admetSAR3.0 is anticipated to be a valuable and powerful tool in drug discovery and chemical safety assessment at http://lmmd.ecust.edu.cn/admetsar3/.

An antioxidant feedforward cycle coordinated by linker histone variant H1.2 and NRF2 that drives nonsmall cell lung cancer progression.

Nonsmall cell lung cancer (NSCLC) is highly malignant with limited treatment options, platinum-based chemotherapy is a standard treatment for NSCLC with resistance commonly seen. NSCLC cells exploit enhanced antioxidant defense system to counteract excessive reactive oxygen species (ROS), which contributes largely to tumor progression and resistance to chemotherapy, yet the mechanisms are not fully understood. Recent studies have suggested the involvement of histones in tumor progression and cellular antioxidant response; however, whether a major histone variant H1.2 (H1C) plays roles in the development of NSCLC remains unclear. Herein, we demonstrated that H1.2 was increasingly expressed in NSCLC tumors, and its expression was correlated with worse survival. When crossing the H1c knockout allele with a mouse NSCLC model (KrasLSL-G12D/+), H1.2 deletion suppressed NSCLC progression and enhanced oxidative stress and significantly decreased the levels of key antioxidant glutathione (GSH) and GCLC, the catalytic subunit of rate-limiting enzyme for GSH synthesis. Moreover, high H1.2 was correlated with the IC50 of multiple chemotherapeutic drugs and with worse prognosis in NSCLC patients receiving chemotherapy; H1.2-deficient NSCLC cells presented reduced survival and increased ROS levels upon cisplatin treatment, while ROS scavenger eliminated the survival inhibition. Mechanistically, H1.2 interacted with NRF2, a master regulator of antioxidative response; H1.2 enhanced the nuclear level and stability of NRF2 and, thus, promoted NRF2 binding to GCLC promoter and the consequent transcription; while NRF2 also transcriptionally up-regulated H1.2. Collectively, these results uncovered a tumor-driving role of H1.2 in NSCLC and indicate an "H1.2-NRF2" antioxidant feedforward cycle that promotes tumor progression and chemoresistance.

VirusRecom: an information-theory-based method for recombination detection of viral lineages and its application on SARS-CoV-2.

Genomic recombination is an important driving force for viral evolution, and recombination events have been reported for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the Coronavirus Disease 2019 pandemic, which significantly alter viral infectivity and transmissibility. However, it is difficult to identify viral recombination, especially for low-divergence viruses such as SARS-CoV-2, since it is hard to distinguish recombination from in situ mutation. Herein, we applied information theory to viral recombination analysis and developed VirusRecom, a program for efficiently screening recombination events on viral genome. In principle, we considered a recombination event as a transmission process of ``information'' and introduced weighted information content (WIC) to quantify the contribution of recombination to a certain region on viral genome; then, we identified the recombination regions by comparing WICs of different regions. In the benchmark using simulated data, VirusRecom showed a good balance between precision and recall compared to two competing tools, RDP5 and 3SEQ. In the detection of SARS-CoV-2 XE, XD and XF recombinants, VirusRecom providing more accurate positions of recombination regions than RDP5 and 3SEQ. In addition, we encapsulated the VirusRecom program into a command-line-interface software for convenient operation by users. In summary, we developed a novel approach based on information theory to identify viral recombination within highly similar sequences, providing a useful tool for monitoring viral evolution and epidemic control.

InferLoop: leveraging single-cell chromatin accessibility for the signal of chromatin loop.

Deciphering cell-type-specific 3D structures of chromatin is challenging. Here, we present InferLoop, a novel method for inferring the strength of chromatin interaction using single-cell chromatin accessibility data. The workflow of InferLoop is, first, to conduct signal enhancement by grouping nearby cells into bins, and then, for each bin, leverage accessibility signals for loop signals using a newly constructed metric that is similar to the perturbation of the Pearson correlation coefficient. In this study, we have described three application scenarios of InferLoop, including the inference of cell-type-specific loop signals, the prediction of gene expression levels and the interpretation of intergenic loci. The effectiveness and superiority of InferLoop over other methods in those three scenarios are rigorously validated by using the single-cell 3D genome structure data of human brain cortex and human blood, the single-cell multi-omics data of human blood and mouse brain cortex, and the intergenic loci in the GWAS Catalog database as well as the GTEx database, respectively. In addition, InferLoop can be applied to predict loop signals of individual spots using the spatial chromatin accessibility data of mouse embryo. InferLoop is available at https://github.com/jumphone/inferloop.

Photoacoustic: A Versatile Nongenetic Method for High-Precision Neuromodulation.

High-precision neuromodulation plays a pivotal role in elucidating fundamental principles of neuroscience and treating specific neurological disorders. Optical neuromodulation, enabled by spatial resolution defined by the diffraction limit at the submicrometer scale, is a general strategy to achieve such precision. Optogenetics offers single-neuron spatial resolution with cellular specificity, whereas the requirement of genetic transfection hinders its clinical application. Direct photothermal modulation, an alternative nongenetic optical approach, often associates a large temperature increase with the risk of thermal damage to surrounding tissues.Photoacoustic (also called optoacoustic) neural stimulation is an emerging technology for neural stimulation with the following key features demonstrated. First, the photoacoustic approach demonstrated high efficacy without the need for genetic modification. The generated pulsed ultrasound upon ns laser pulses with energy ranging from a few µJ to tens of µJ is sufficient to activate wild-type neurons. Second, the photoacoustic approach provides sub-100-µm spatial precision. It overcomes the fundamental wave diffraction limit of ultrasound by harnessing the localized ultrasound field generated through light absorption. A spatial precision of 400 µm has been achieved in rodent brains using a fiber-based photoacoustic emitter. Single-cell stimulation in neuronal cultures in vitro and in brain slices ex vivo is achieved using tapered fiber-based photoacoustic emitters. This precision is 10 to 100 times better than that for piezo-based low-frequency ultrasound and is essential to pinpoint a specific region or cell population in a living brain. Third, compared to direct photothermal stimulation via temperature increase, photoacoustic stimulation requires 40 times less laser energy dose to evoke neuron activities and is associated with a minimal temperature increase of less than 1 °C, preventing potential thermal damage to neurons. Fourth, photoacoustics is a versatile approach and can be designed in various platforms aiming at specific applications. Our team has shown the design of fiber-based photoacoustic emitters, photoacoustic nanotransducers, soft biocompatible photoacoustic films, and soft photoacoustic lenses. Since they interact with neurons through ultrasound without the need for direct contact, photoacoustic enables noninvasive transcranial and dura-penetrating brain stimulation without compromising high precision.In this Account, we will first review the basic principles of photoacoustic and discuss the key design elements of PA transducers for neural modulation guided by the principle. We will also highlight how these design goals were achieved from a materials chemistry perspective. The design of different PA interfaces, their unique capability, and their applications in neural systems will be reviewed. In the end, we will discuss the remaining challenges and future perspectives for this technology.

Pan-cancer analysis of CDKN2A alterations identifies a subset of gastric cancer with a cold tumor immune microenvironment.

BACKGROUND: Although CDKN2A alteration has been explored as a favorable factor for tumorigenesis in pan-cancers, the association between CDKN2A point mutation (MUT) and intragenic deletion (DEL) and response to immune checkpoint inhibitors (ICIs) is still disputed. This study aims to determine the associations of CDKN2A MUT and DEL with overall survival (OS) and response to immune checkpoint inhibitors treatment (ICIs) among pan-cancers and the clinical features of CDKN2A-altered gastric cancer. METHODS: This study included 45,000 tumor patients that underwent tumor sequencing across 33 cancer types from four cohorts, the MSK-MetTropism, MSK-IMPACT, OrigiMed2020 and TCGA cohorts. Clinical outcomes and genomic factors associated with response to ICIs, including tumor mutational burden, copy number alteration, neoantigen load, microsatellite instability, tumor immune microenvironment and immune-related gene signatures, were collected in pan-cancer. Clinicopathologic features and outcomes were assessed in gastric cancer. Patients were grouped based on the presence of CDKN2A wild type (WT), CDKN2A MUT, CDKN2A DEL and CDKN2A other alteration (ALT). RESULTS: Our research showed that CDKN2A-MUT patients had shorter survival times than CDKN2A-WT patients in the MSK MetTropism and TCGA cohorts, but longer OS in the MSK-IMPACT cohort with ICIs treatment, particularly in patients having metastatic disease. Similar results were observed among pan-cancer patients with CDKN2A DEL and other ALT. Notably, CDKN2A ALT frequency was positively related to tumor-specific objective response rates to ICIs in MSK MetTropism and OrigiMed 2020. Additionally, individuals with esophageal carcinoma or stomach adenocarcinoma who had CDKN2A MUT had poorer OS than patients from the MSK-IMPACT group, but not those with adenocarcinoma. We also found reduced levels of activated NK cells, T cells CD8 and M2 macrophages in tumor tissue from CDKN2A-MUT or DEL pan-cancer patients compared to CDKN2A-WT patients in TCGA cohort. Gastric cancer scRNA-seq data also showed that CDKN2A-ALT cancer contained less CD8 T cells but more exhausted T cells than CDKN2A-WT cancer. A crucial finding of the pathway analysis was the inhibition of three immune-related pathways in the CDKN2A ALT gastric cancer patients, including the interferon alpha response, inflammatory response, and interferon gamma response. CONCLUSIONS: This study illustrates the CDKN2A MUT and DEL were associated with a poor outcome across cancers. CDKN2A ALT, on the other hand, have the potential to be used as a biomarker for choosing patients for ICI treatment, notably in esophageal carcinoma and stomach adenocarcinoma.

Causal effects of osteoporosis on structural changes in specific brain regions: a Mendelian randomization study.

Observational studies have reported that osteoporosis is associated with cortical changes in the brain. However, the inherent limitations of observational studies pose challenges in eliminating confounding factors and establishing causal relationships. And previous observational studies have not reported changes in specific brain regions. By employing Mendelian randomization, we have been able to infer a causal relationship between osteoporosis and a reduction in the surficial area (SA) of the brain cortical. This effect is partially mediated by vascular calcification. We found that osteoporosis significantly decreased the SA of global brain cortical (ß = -1587.62 mm2, 95%CI: -2645.94 mm2 to -529.32 mm2, P = 0.003) as well as the paracentral gyrus without global weighted (ß = - 19.42 mm2, 95%CI: -28.90 mm2 to -9.95 mm2, P = 5.85 × 10-5). Furthermore, we estimated that 42.25% and 47.21% of the aforementioned effects are mediated through vascular calcification, respectively. Osteoporosis leads to a reduction in the SA of the brain cortical, suggesting the presence of the bone-brain axis. Vascular calcification plays a role in mediating this process to a certain extent. These findings establish a theoretical foundation for further investigations into the intricate interplay between bone, blood vessels, and the brain.

Spatial Transcriptomics Resolve an Emphysema-Specific Lymphoid Follicle B Cell Signature in Chronic Obstructive Pulmonary Disease.

Rationale: Within chronic obstructive pulmonary disease (COPD), emphysema is characterized by a significant yet partially understood B cell immune component. Objectives: To characterize the transcriptomic signatures from lymphoid follicles (LFs) in ever-smokers without COPD and patients with COPD with varying degrees of emphysema. Methods: Lung sections from 40 patients with COPD and ever-smokers were used for LF proteomic and transcriptomic spatial profiling. Formalin- and O.C.T.-fixed lung samples obtained from biopsies or lung explants were assessed for LF presence. Emphysema measurements were obtained from clinical chest computed tomographic scans. High-confidence transcriptional target intersection analyses were conducted to resolve emphysema-induced transcriptional networks. Measurements and Main Results: Overall, 115 LFs from ever-smokers and Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-2 and GOLD 3-4 patients were analyzed. No LFs were found in never-smokers. Differential gene expression analysis revealed significantly increased expression of LF assembly and B cell marker genes in subjects with severe emphysema. High-confidence transcriptional analysis revealed activation of an abnormal B cell activity signature in LFs (q-value = 2.56E-111). LFs from patients with GOLD 1-2 COPD with emphysema showed significantly increased expression of genes associated with antigen presentation, inflammation, and B cell activation and proliferation. LFs from patients with GOLD 1-2 COPD without emphysema showed an antiinflammatory profile. The extent of centrilobular emphysema was significantly associated with genes involved in B cell maturation and antibody production. Protein-RNA network analysis showed that LFs in emphysema have a unique signature skewed toward chronic B cell activation. Conclusions: An off-targeted B cell activation within LFs is associated with autoimmune-mediated emphysema pathogenesis.

Comparative genomics on chloroplasts of Rubus (Rosaceae).

Rubus, the largest genus in Rosaceae, contains over 1400 species that distributed in multiple habitats across the world, with high species diversity in the temperate regions of Northern Hemisphere. Multiple Rubus species are cultivated for their valuable fruits. However, the intrageneric classification and phylogenetic relationships are still poorly understood. In this study, we sequenced, assembled, and characterized 17 plastomes of Rubus, and conducted comparative genomics integrating with 47 previously issued plastomes of this genus. The 64 plastomes of Rubus exhibited typical quadripartite structure with sizes ranging from 155,144 to 156,700 bp, and contained 132 genes including 87 protein-coding genes, 37 tRNA genes and eight rRNA genes. All plastomes are conservative in the gene order, the frequency of different types of long repeats and simple sequence repeats (SSRs), the codon usage, and the selection pressure of protein-coding genes. However, there are also some differences in the Rubus plastomes, including slight contraction and expansion of the IRs, a variation in the numbers of SSRs and long repeats, and some genes in certain clades undergoing intensified or relaxed purifying selection. Phylogenetic analysis based on whole plastomes showed that the monophyly of Rubus was strongly supported and resolved it into six clades corresponding to six subgenera. Moreover, we identified 12 highly variable regions that could be potential molecular markers for phylogenetic, population genetic, and barcoding studies. Overall, our study provided insight into plastomic structure and sequence diversification of Rubus, which could be beneficial for future studies on identification, evolution, and phylogeny in this genus.

MHESMMR: a multilevel model for predicting the regulation of miRNAs expression by small molecules.

According to the expression of miRNA in pathological processes, miRNAs can be divided into oncogenes or tumor suppressors. Prediction of the regulation relations between miRNAs and small molecules (SMs) becomes a vital goal for miRNA-target therapy. But traditional biological approaches are laborious and expensive. Thus, there is an urgent need to develop a computational model. In this study, we proposed a computational model to predict whether the regulatory relationship between miRNAs and SMs is up-regulated or down-regulated. Specifically, we first use the Large-scale Information Network Embedding (LINE) algorithm to construct the node features from the self-similarity networks, then use the General Attributed Multiplex Heterogeneous Network Embedding (GATNE) algorithm to extract the topological information from the attribute network, and finally utilize the Light Gradient Boosting Machine (LightGBM) algorithm to predict the regulatory relationship between miRNAs and SMs. In the fivefold cross-validation experiment, the average accuracies of the proposed model on the SM2miR dataset reached 79.59% and 80.37% for up-regulation pairs and down-regulation pairs, respectively. In addition, we compared our model with another published model. Moreover, in the case study for 5-FU, 7 of 10 candidate miRNAs are confirmed by related literature. Therefore, we believe that our model can promote the research of miRNA-targeted therapy.

Revisiting airway epithelial dysfunction and mechanisms in chronic obstructive pulmonary disease: the role of mitochondrial damage.

Chronic exposure to environmental hazards causes airway epithelial dysfunction, primarily impaired physical barriers, immune dysfunction, and repair or regeneration. Impairment of airway epithelial function subsequently leads to exaggerated airway inflammation and remodeling, the main features of chronic obstructive pulmonary disease (COPD). Mitochondrial damage has been identified as one of the mechanisms of airway abnormalities in COPD, which is closely related to airway inflammation and airflow limitation. In this review, we evaluate updated evidence for airway epithelial mitochondrial damage in COPD and focus on the role of mitochondrial damage in airway epithelial dysfunction. In addition, the possible mechanism of airway epithelial dysfunction mediated by mitochondrial damage is discussed in detail, and recent strategies related to airway epithelial-targeted mitochondrial therapy are summarized. Results have shown that dysregulation of mitochondrial quality and oxidative stress may lead to airway epithelial dysfunction in COPD. This may result from mitochondrial damage as a central organelle mediating abnormalities in cellular metabolism. Mitochondrial damage mediates procellular senescence effects due to mitochondrial reactive oxygen species, which effectively exacerbate different types of programmed cell death, participate in lipid metabolism abnormalities, and ultimately promote airway epithelial dysfunction and trigger COPD airway abnormalities. These can be prevented by targeting mitochondrial damage factors and mitochondrial transfer. Thus, because mitochondrial damage is involved in COPD progression as a central factor of homeostatic imbalance in airway epithelial cells, it may be a novel target for therapeutic intervention to restore airway epithelial integrity and function in COPD.

Development and evaluation of a risk assessment tool for the personalized screening of breast cancer in Chinese populations: A prospective cohort study.

INTRODUCTION: Breast cancer is a significant contributor to female mortality, exerting a public health burden worldwide, especially in China, where risk-prediction models with good discriminating accuracy for breast cancer are still scarce. METHODS: A multicenter screening cohort study was conducted as part of the Cancer Screening Program in Urban China. Dwellers aged 40-74 years were recruited between 2014 and 2019 and prospectively followed up until June 30, 2021. The entire data set was divided by year of enrollment to develop a prediction model and validate it internally. Multivariate Cox regression was used to ascertain predictors and develop a risk-prediction model. Model performance at 1, 3, and 5 years was evaluated using the area under the curve, nomogram, and calibration curves and subsequently validated internally. The prediction model incorporates selected factors that are assigned appropriate weights to establish a risk-scoring algorithm. Guided by the risk score, participants were categorized into low-, medium-, and high-risk groups for breast cancer. The cutoff values were chosen using X-tile plots. Sensitivity analysis was conducted by categorizing breast cancer risk into the low- and high-risk groups. A decision curve analysis was used to assess the clinical utility of the model. RESULTS: Of the 70,520 women enrolled, 447 were diagnosed with breast cancer (median follow-up, 6.43 [interquartile range, 3.99-7.12] years). The final prediction model included age and education level (high, hazard ratio [HR], 2.01 [95% CI, 1.31-3.09]), menopausal age (≥50 years, 1.34 [1.03-1.75]), previous benign breast disease (1.42 [1.09-1.83]), and reproductive surgery (1.28 [0.97-1.69]). The 1-year area under the curve was 0.607 in the development set and 0.643 in the validation set. Moderate predictive discrimination and satisfactory calibration were observed for the validation set. The risk predictions demonstrated statistically significant differences between the low-, medium-, and high-risk groups (p < .001). Compared with the low-risk group, women in the high- and medium-risk groups posed a 2.17-fold and 1.62-fold elevated risk of breast cancer, respectively. Similar results were obtained in the sensitivity analyses. A web-based calculator was developed to estimate risk stratification for women. CONCLUSIONS: This study developed and internally validated a risk-adapted and user-friendly risk-prediction model by incorporating easily accessible variables and female factors. The personalized model demonstrated reliable calibration and moderate discriminative ability. Risk-stratified screening strategies contribute to precisely distinguishing high-risk individuals from asymptomatic individuals and prioritizing breast cancer screening. PLAIN LANGUAGE SUMMARY: Breast cancer remains a burden in China. To enhance breast cancer screening, we need to incorporate population stratification in screening. Accurate risk-prediction models for breast cancer remain scarce in China. We established and validated a risk-adapted and user-friendly risk-prediction model by incorporating routinely available variables along with female factors. Using this risk-stratified model helps accurately identify high-risk individuals, which is of significant importance when considering integrating individual risk assessments into mass screening programs for breast cancer. Current clinical breast cancer screening lacks a constructive clinical pathway and guiding recommendations. Our findings can better guide clinicians and health care providers.