Insights into Nucleosome Organization in Mouse Embryonic Stem Cells through Chemical Mapping.

Nucleosome organization influences gene activity by controlling DNA accessibility to transcription machinery. Here, we develop a chemical biology approach to determine mammalian nucleosome positions genome-wide. We uncovered surprising features of nucleosome organization in mouse embryonic stem cells. In contrast to the prevailing model, we observe that for nearly all mouse genes, a class of fragile nucleosomes occupies previously designated nucleosome-depleted regions around transcription start sites and transcription termination sites. We show that nucleosomes occupy DNA targets for a subset of DNA-binding proteins, including CCCTC-binding factor (CTCF) and pluripotency factors. Furthermore, we provide evidence that promoter-proximal nucleosomes, with the +1 nucleosome in particular, contribute to the pausing of RNA polymerase II. Lastly, we find a characteristic preference for nucleosomes at exon-intron junctions. Taken together, we establish an accurate method for defining the nucleosome landscape and provide a valuable resource for studying nucleosome-mediated gene regulation in mammalian cells.

Modelling lung infection with Klebsiella pneumoniae after murine traumatic brain injury.

Pneumonia is a common comorbidity in patients with severe traumatic brain injury (TBI), and is associated with increased morbidity and mortality. In this study, we established a model of intratracheal Klebsiella pneumoniae administration in young adult male and female mice, at 4 days following an experimental TBI, to investigate how K. pneumoniae infection influences acute post-TBI outcomes. A dose-response curve determined the optimal dose of K. pneumoniae for inoculation (1 x 10^6 colony forming units), and administration at 4 days post-TBI resulted in transient body weight loss and sickness behaviors (hypoactivity and acute dyspnea). K. pneumoniae infection led to an increase in pro-inflammatory cytokines in serum and bronchoalveolar lavage fluid at 24 h post-infection, in both TBI and sham (uninjured) mice. By 7 days, when myeloperoxidase + neutrophil numbers had returned to baseline in all groups, lung histopathology was observed with an increase in airspace size in TBI + K. pneumoniae mice compared to TBI + vehicle mice. In the brain, increased neuroinflammatory gene expression was observed acutely in response to TBI, with an exacerbated increase in Ccl2 and Hmox1 in TBI + K. pneumoniae mice compared to either TBI or K. pneumoniae alone. However, the presence of neuroinflammatory immune cells in the injured brain, and the extent of damage to cortical and hippocampal brain tissue, was comparable between K. pneumoniae and vehicle-treated mice by 7 days. Examination of the fecal microbiome across a time course did not reveal any pronounced effects of either injury or K. pneumoniae on bacterial diversity or abundance. Together, these findings demonstrate that K. pneumoniae lung infection after TBI induces an acute and transient inflammatory response, primarily localized to the lungs with some systemic effects. However, this infection had minimal impact on secondary injury processes in the brain following TBI. Future studies are needed to evaluate the potential longer-term consequences of this dual-hit insult.

Polysaccharide-Targeting Lipid Nanoparticles to Kill Gram-Negative Bacteria.

The rapid increase and spread of Gram-negative bacteria resistant to many or all existing treatments threaten a return to the preantibiotic era. The presence of bacterial polysaccharides that impede the penetration of many antimicrobials and protect them from the innate immune system contributes to resistance and pathogenicity. No currently approved antibiotics target the polysaccharide regions of microbes. Here, describe monolaurin-based niosomes, the first lipid nanoparticles that can eliminate bacterial polysaccharides from hypervirulent Klebsiella pneumoniae, are described. Their combination with polymyxin B shows no cytotoxicity in vitro and is highly effective in combating K. pneumoniae infection in vivo. Comprehensive mechanistic studies have revealed that antimicrobial activity proceeds via a multimodal mechanism. Initially, lipid nanoparticles disrupt polysaccharides, then outer and inner membranes are destabilized and destroyed by polymyxin B, resulting in synergistic cell lysis. This novel lipidic nanoparticle system shows tremendous promise as a highly effective antimicrobial treatment targeting multidrug-resistant Gram-negative pathogens.

Replicability in cancer omics data analysis: measures and empirical explorations.

In biomedical research, the replicability of findings across studies is highly desired. In this study, we focus on cancer omics data, for which the examination of replicability has been mostly focused on important omics variables identified in different studies. In published literature, although there have been extensive attention and ad hoc discussions, there is insufficient quantitative research looking into replicability measures and their properties. The goal of this study is to fill this important knowledge gap. In particular, we consider three sensible replicability measures, for which we examine distributional properties and develop a way of making inference. Applying them to three The Cancer Genome Atlas (TCGA) datasets reveals in general low replicability and significant across-data variations. To further comprehend such findings, we resort to simulation, which confirms the validity of the findings with the TCGA data and further informs the dependence of replicability on signal level (or equivalently sample size). Overall, this study can advance our understanding of replicability for cancer omics and other studies that have identification as a key goal.

DNAcycP: a deep learning tool for DNA cyclizability prediction.

DNA mechanical properties play a critical role in every aspect of DNA-dependent biological processes. Recently a high throughput assay named loop-seq has been developed to quantify the intrinsic bendability of a massive number of DNA fragments simultaneously. Using the loop-seq data, we develop a software tool, DNAcycP, based on a deep-learning approach for intrinsic DNA cyclizability prediction. We demonstrate DNAcycP predicts intrinsic DNA cyclizability with high fidelity compared to the experimental data. Using an independent dataset from in vitro selection for enrichment of loopable sequences, we further verified the predicted cyclizability score, termed C-score, can well distinguish DNA fragments with different loopability. We applied DNAcycP to multiple species and compared the C-scores with available high-resolution chemical nucleosome maps. Our analyses showed that both yeast and mouse genomes share a conserved feature of high DNA bendability spanning nucleosome dyads. Additionally, we extended our analysis to transcription factor binding sites and surprisingly found that the cyclizability is substantially elevated at CTCF binding sites in the mouse genome. We further demonstrate this distinct mechanical property is conserved across mammalian species and is inherent to CTCF binding DNA motif.

PfbZIP85 Transcription Factor Mediates ω-3 Fatty Acid-Enriched Oil Biosynthesis by Down-Regulating PfLPAT1B Gene Expression in Plant Tissues.

The basic leucine zipper (bZIP) transcription factor (TF) family is one of the biggest TF families identified so far in the plant kingdom, functioning in diverse biological processes including plant growth and development, signal transduction, and stress responses. For Perilla frutescens, a novel oilseed crop abundant in polyunsaturated fatty acids (PUFAs) (especially α-linolenic acid, ALA), the identification and biological functions of bZIP members remain limited. In this study, 101 PfbZIPs were identified in the perilla genome and classified into eleven distinct groups (Groups A, B, C, D, E, F, G, H, I, S, and UC) based on their phylogenetic relationships and gene structures. These PfbZIP genes were distributed unevenly across 18 chromosomes, with 83 pairs of them being segmental duplication genes. Moreover, 78 and 148 pairs of orthologous bZIP genes were detected between perilla and Arabidopsis or sesame, respectively. PfbZIP members belonging to the same subgroup exhibited highly conserved gene structures and functional domains, although significant differences were detected between groups. RNA-seq and RT-qPCR analysis revealed differential expressions of 101 PfbZIP genes during perilla seed development, with several PfbZIPs exhibiting significant correlations with the key oil-related genes. Y1H and GUS activity assays evidenced that PfbZIP85 downregulated the expression of the PfLPAT1B gene by physical interaction with the promoter. PfLPAT1B encodes a lysophosphatidate acyltransferase (LPAT), one of the key enzymes for triacylglycerol (TAG) assembly. Heterogeneous expression of PfbZIP85 significantly reduced the levels of TAG and UFAs (mainly C18:1 and C18:2) but enhanced C18:3 accumulation in both seeds and non-seed tissues in the transgenic tobacco lines. Furthermore, these transgenic tobacco plants showed no significantly adverse phenotype for other agronomic traits such as plant growth, thousand seed weight, and seed germination rate. Collectively, these findings offer valuable perspectives for understanding the functions of PfbZIPs in perilla, particularly in lipid metabolism, showing PfbZIP85 as a suitable target in plant genetic improvement for high-value vegetable oil production.

Feature shared multi-decoder network using complementary learning for Photon counting CT ring artifact suppression.

BACKGROUND: Photon-counting computed tomography (Photon counting CT) utilizes photon-counting detectors to precisely count incident photons and measure their energy. These detectors, compared to traditional energy integration detectors, provide better image contrast and material differentiation. However, Photon counting CT tends to show more noticeable ring artifacts due to limited photon counts and detector response variations, unlike conventional spiral CT. OBJECTIVE: To comprehensively address this issue, we propose a novel feature shared multi-decoder network (FSMDN) that utilizes complementary learning to suppress ring artifacts in Photon counting CT images. METHODS: Specifically, we employ a feature-sharing encoder to extract context and ring artifact features, facilitating effective feature sharing. These shared features are also independently processed by separate decoders dedicated to the context and ring artifact channels, working in parallel. Through complementary learning, this approach achieves superior performance in terms of artifact suppression while preserving tissue details. RESULTS: We conducted numerous experiments on Photon counting CT images with three-intensity ring artifacts. Both qualitative and quantitative results demonstrate that our network model performs exceptionally well in correcting ring artifacts at different levels while exhibiting superior stability and robustness compared to the comparison methods. CONCLUSIONS: In this paper, we have introduced a novel deep learning network designed to mitigate ring artifacts in Photon counting CT images. The results illustrate the viability and efficacy of our proposed network model as a new deep learning-based method for suppressing ring artifacts.

Distribution and Rate of Myxoid Liposarcoma Spine Metastases: Impact on Surveillance Imaging.

BACKGROUND: Myxoid liposarcoma (LPS) has a unique tendency to spread to extrapulmonary sites, including osseous sites such as the spine, and adjacent sites such as the paraspinous tissue. No clear consensus exists to guide the approach to imaging in these patients. OBJECTIVE: The aim of this study was to investigate the rate and distribution of spine metastases in patients with myxoid LPS and detection modality. METHODS: Records of all patients with myxoid LPS evaluated at our sarcoma center were retrospectively reviewed. Disease patterns and imaging modality utilization were analyzed. RESULTS: Between 2000 and 2020, 164 patients with myxoid LPS were identified. The majority (n = 148, 90%) presented with localized disease, with half (n = 82, 50%) of all patients developing metastases or recurrence during their disease course. With a median follow-up of 69.2 months, spine/paraspinous metastases developed in 38 patients (23%), of whom 35 (92%) already had synchronous, non-spine metastases. Spine disease was only visible on magnetic resonance imaging (MRI), as opposed to other imaging modalities, for over one-quarter of patients with spine metastases (n = 10). For patients with metastatic disease, spine metastases were associated with worse median overall survival (2.1 vs. 8.7 years, p < 0.001). CONCLUSION: Spine metastases occurred in nearly one-quarter of patients with myxoid LPS and represented an advanced disease state, as they primarily presented in the setting of synchronous, non-spine metastases, and were associated with worse overall survival. Routine surveillance with spine MRI in patients with localized disease likely provides no benefit but may be considered in those with known metastatic disease.

Robotic Function-Preserving Resection of Gastric Gastrointestinal Stromal Tumor.

INTRODUCTION: Gastric gastrointestinal stromal tumors (GISTs) located at the gastroesophageal junction (GEJ), lesser curvature, posterior gastric wall, or antrum present challenges for gastric function preservation. The aim of this study was to evaluate safety and effectiveness of robot-assisted resection of gastric GIST in challenging anatomic locations. METHODS: This was a single-center case series of robotic gastric GIST resections in challenging anatomic locations performed from 2019 to 2021. GEJ GISTs are defined as tumors within 5 cm of the GEJ. Location of the tumor and distance from the GEJ were determined from the endoscopy report and/or cross-sectional imaging and operative findings. RESULTS: There were 25 consecutive patients who underwent a robot-assisted partial gastrectomy for a gastric GIST in challenging anatomic locations. Tumors were located at the GEJ (n = 12), lesser curvature (n = 7), posterior gastric wall (n = 4), fundus (n = 3), greater curvature (n = 3), and antrum (n = 2). Median distance of tumor from GEJ was 2.5 cm. Both GEJ and pylorus were successfully preserved in all patients regardless of tumor location. Median operative time was 190 min with a median estimated blood loss of 20 mL and no conversion to open approach. Median hospital stay was 3 d with solid diet intake starting 2 d after surgery. Two (8 %) patients had Grade III or higher postoperative complications. Median tumor size upon resection was 3.9 cm. Negative margins were obtained in 96.3%. There was no evidence of recurrent disease with a median follow-up of 11.3 mo. CONCLUSIONS: We demonstrate the safety and feasibility of using the robotic approach to facilitate function preservation gastrectomy in challenging anatomic locations without compromising oncologic resection.

An information-motivation-behavioral skills model-based intervention for patients with epilepsy.

PURPOSE: Self-management is crucial for patients with epilepsy (PWE) as it can effectively control the condition, improve treatment outcomes, and reduce the risk of seizures. The objective of this study was to evaluate the effectiveness of health education based on the Information-Motivation-Behavioral Skills (IMB) model in improving self-management, quality of life, and medication adherence among PWE. METHOD: This study was conducted in a district in Shanghai, China, from September 2022 to March 2023. A total of 90 PWE were randomly assigned to an intervention group or a control group. Patients in the intervention group received health education based on the IMB model, whereas those in the control group received routine medical treatment only. The effectiveness of the intervention was evaluated by measuring self-management ability, quality of life, and medication adherence at three months and six months after the intervention. RESULTS: The study included a total of 90 PWE; among them, 55 patients (61.11%) were male, divided into two groups: 45 participants in the control group and 45 participants in the intervention group. After 3 and 6 months of intervention, the self-management scores of the intervention group were significantly higher than those of the control group (t = 14.274, 12.448; P < 0.05). After 6 months of the intervention, the quality-of-life scores of the intervention group were significantly higher than those of the control group (t = 2.025, P < 0.05), and the medication adherence in the intervention group was significantly higher than that in the control group (X2 = 9.003, P < 0.05). CONCLUSION: Health education based on the IMB model is a promising approach to improving self-management, quality of life, and medication adherence among PWE. It provides personalized, patient-centered interventions that consider patients' knowledge, motivation, and behavior skills, and could be a useful tool for healthcare providers in developing comprehensive care plans for individuals with epilepsy.

Inwardly rectifying potassium channels mediate polymyxin-induced nephrotoxicity.

Polymyxin antibiotics are often used as a last-line defense to treat life-threatening Gram-negative pathogens. However, polymyxin-induced kidney toxicity is a dose-limiting factor of paramount importance and can lead to suboptimal treatment. To elucidate the mechanism and develop effective strategies to overcome polymyxin toxicity, we employed a whole-genome CRISPR screen in human kidney tubular HK-2 cells and identified 86 significant genes that upon knock-out rescued polymyxin-induced toxicity. Specifically, we discovered that knockout of the inwardly rectifying potassium channels Kir4.2 and Kir5.1 (encoded by KCNJ15 and KCNJ16, respectively) rescued polymyxin-induced toxicity in HK-2 cells. Furthermore, we found that polymyxins induced cell depolarization via Kir4.2 and Kir5.1 and a significant cellular uptake of polymyxins was evident. All-atom molecular dynamics simulations revealed that polymyxin B1 spontaneously bound to Kir4.2, thereby increasing opening of the channel, resulting in a potassium influx, and changes of the membrane potential. Consistent with these findings, small molecule inhibitors (BaCl2 and VU0134992) of Kir potassium channels reduced polymyxin-induced toxicity in cell culture and mouse explant kidney tissue. Our findings provide critical mechanistic information that will help attenuate polymyxin-induced nephrotoxicity in patients and facilitate the design of novel, safer polymyxins.

Genome-Wide Analysis of Glycerol-3-Phosphate Acyltransferase (GPAT) Family in Perilla frutescens and Functional Characterization of PfGPAT9 Crucial for Biosynthesis of Storage Oils Rich in High-Value Lipids.

Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the first step in triacylglycerol (TAG) biosynthesis. However, GPAT members and their functions remain poorly understood in Perilla frutescens, a special edible-medicinal plant with its seed oil rich in polyunsaturated fatty acids (mostly α-linolenic acid, ALA). Here, 14 PfGPATs were identified from the P. frutescens genome and classified into three distinct groups according to their phylogenetic relationships. These 14 PfGPAT genes were distributed unevenly across 11 chromosomes. PfGPAT members within the same subfamily had highly conserved gene structures and four signature functional domains, despite considerable variations detected in these conserved motifs between groups. RNA-seq and RT-qPCR combined with dynamic analysis of oil and FA profiles during seed development indicated that PfGPAT9 may play a crucial role in the biosynthesis and accumulation of seed oil and PUFAs. Ex vivo enzymatic assay using the yeast expression system evidenced that PfGPAT9 had a strong GPAT enzyme activity crucial for TAG assembly and also a high substrate preference for oleic acid (OA, C18:1) and ALA (C18:3). Heterogeneous expression of PfGPAT9 significantly increased total oil and UFA (mostly C18:1 and C18:3) levels in both the seeds and leaves of the transgenic tobacco plants. Moreover, these transgenic tobacco lines exhibited no significant negative effect on other agronomic traits, including plant growth and seed germination rate, as well as other morphological and developmental properties. Collectively, our findings provide important insights into understanding PfGPAT functions, demonstrating that PfGPAT9 is the desirable target in metabolic engineering for increasing storage oil enriched with valuable FA profiles in oilseed crops.

Efficient removal of thiamethoxam by freshwater microalgae Scenedesmus sp. TXH: Removal mechanism, metabolic degradation and application.

Neonicotinoids, as the most widely used pesticides in the world, help improve the production of crops. Meanwhile, it also brings potential threats to surrounding environments and other organisms because of its wide use and even abuse. In this study, Scenedesmus sp. TXH isolated from a wastewater treatment plant was used to remove the neonicotinoid pesticide thiamethoxam (THIA). The removal efficiency, degradation pathway, metabolite fate of THIA and physicochemical effects on microalgae cells were studied. Meanwhile, the feasibility of using microalgal technology to remove THIA from municipal wastewater was also explored. The results showed that 5-40 mg/L of THIA slightly promoted the growth of microalgae, while 60 mg/L THIA severely inhibited microalgal growth. It was observed that malondialdehyde content and superoxide dismutase activity in 60 mg/L THIA group increased significantly (p < 0.05) in the early stage of the experiment, indicating that THIA caused oxidative damage to microalgae. Scenedesmus sp. TXH showed high-efficient degradation ability and high resistance to THIA, with 100% removal of THIA at 5, 20 and 40 mg/L groups and 97.5% removal of THIA at 60 mg/L group on day 12. THIA was mainly removed by biodegradation, accounting for 78.18%, 93.50%, 96.81% and 91.35% under 5, 20, 40 and 60 mg/L on day 12, respectively. Six degradation products were identified, and four potential degradation pathways were proposed. In practical wastewater, the removal efficiency of total dissolved nitrogen, total dissolved phosphorus, ammonia nitrogen and THIA reached 85.68%, 90.00%, 98.43% and 100%, respectively, indicating that Scenedesmus sp. TXH was well adapted to the wastewater and effectively removed THIA and conventional pollutants.

Changes of bacterial community structure,monosaccharide composition and CO2 exchange along the successional stages of biological soil crusts.

Biological soil crusts (BSCs) are a dominant ecological landscape of drylands, which have a significant impact on global biogeochemical flux. However, it is unclear how bacterial community and physiological characteristics vary along the BSCs successional stages. In this study, bacterial community composition, physiological characteristics, and monosaccharide composition of extracellular polysaccharides (EPSs) were compared among different successional stages. Our findings demonstrated that besides the dominant bacterial species, the bacterial communities also showed considerable differences between these two stages. Cyanobacteria were keystone taxa in the early stage, while heterotrophic bacteria (Proteobacteria, Actinobacteria and Acidobacteria) were keystone taxa in the later stages. According to the results of CO2 exchange, cyanobacterial crusts accumulated net carbon faster than moss crusts, while moss crusts had a significantly higher respiration rate. The monosaccharide analysis indicated that the EPSs components also varied depending on BSCs' successional stages. Specifically, the contents of rhamnose and arabinose were higher in the cyanobacterial crusts than other types of crusts, while the contents of fucose, xylose, mannose and glucose were the highest in cyanobacterial-lichen crusts, and galactose content was highest in the moss crusts. Altogether, our results stress the heterogeneous variation of BSCs along with succession, and this work offered a fresh viewpoint for a deeper comprehension of the interactions between the monosaccharide components of EPS and the networks of bacterial communities in BSCs.

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

Objectives: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The objective is to showcase a big data approach that takes advantage of large electronic medical record (EMR) data to emulate clinical trials. To overcome the limitations of regression analysis, a deep learning-based analysis pipeline was developed. Study Design and Setting: Lumpectomy (breast-conserving surgery) and mastectomy are the two most commonly used surgical procedures for early-stage female breast cancer patients. An emulation trial was designed using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data to evaluate their relative effectiveness in overall survival. The analysis pipeline consisted of a propensity score step, a weighted survival analysis step, and a bootstrap inference step. Results: A total of 65,997 subjects were enrolled in the emulated trial, with 50,704 and 15,293 in the lumpectomy and mastectomy arms, respectively. The two surgery procedures had comparable effects in terms of overall survival (survival year change = 0.08, 95% confidence interval (CI): -0.08, 0.25) for the elderly SEER-Medicare early-stage female breast cancer patients. Conclusion: This study demonstrated the power of "mining large EMR data + deep learning-based analysis," and the proposed analysis strategy and technique can be potentially broadly applicable. It provided convincing evidence of the comparative effectiveness of lumpectomy and mastectomy.

BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models.

BACKGROUND: In the CRISPR-Cas9 system, the efficiency of genetic modifications has been found to vary depending on the single guide RNA (sgRNA) used. A variety of sgRNA properties have been found to be predictive of CRISPR cleavage efficiency, including the position-specific sequence composition of sgRNAs, global sgRNA sequence properties, and thermodynamic features. While prevalent existing deep learning-based approaches provide competitive prediction accuracy, a more interpretable model is desirable to help understand how different features may contribute to CRISPR-Cas9 cleavage efficiency. RESULTS: We propose a gradient boosting approach, utilizing LightGBM to develop an integrated tool, BoostMEC (Boosting Model for Efficient CRISPR), for the prediction of wild-type CRISPR-Cas9 editing efficiency. We benchmark BoostMEC against 10 popular models on 13 external datasets and show its competitive performance. CONCLUSIONS: BoostMEC can provide state-of-the-art predictions of CRISPR-Cas9 cleavage efficiency for sgRNA design and selection. Relying on direct and derived sequence features of sgRNA sequences and based on conventional machine learning, BoostMEC maintains an advantage over other state-of-the-art CRISPR efficiency prediction models that are based on deep learning through its ability to produce more interpretable feature insights and predictions.

Genome-wide identification and functional analysis of Dof transcription factor family in Camelina sativa.

BACKGROUND: Dof transcription factors (TFs) containing C2-C2 zinc finger domains are plant-specific regulatory proteins, playing crucial roles in a variety of biological processes. However, little is known about Dof in Camelina sativa, an important oil crop worldwide, with high stress tolerance. In this study, a genome-wide characterization of Dof proteins is performed to examine their basic structural characteristics, phylogenetics, expression patterns, and functions to identify the regulatory mechanism underlying lipid/oil accumulation and the candidate Dofs mediating stress resistance regulation in C. sativa. RESULTS: Total of 103 CsDof genes unevenly distributed on 20 chromosomes were identified from the C. sativa genome, and they were classified into four groups (A, B, C and D) based on the classification of Arabidopsis Dof gene family. All of the CsDof proteins contained the highly-conserved typic CX2C-X21-CX2C structure. Segmental duplication and purifying selection were detected for CsDof genes. 61 CsDof genes were expressed in multiple tissues, and 20 of them showed tissue-specific expression patterns, suggesting that CsDof genes functioned differentially in different tissues of C. sativa. Remarkably, a set of CsDof members were detected to be possible involved in regulation of oil/lipid biosynthesis in C. sativa. Six CsDof genes exhibited significant expression changes in seedlings under salt stress treatment. CONCLUSIONS: The present data reveals that segmental duplication is the key force responsible for the expansion of CsDof gene family, and a strong purifying pressure plays a crucial role in CsDofs' evolution. Several CsDof TFs may mediate lipid metabolism and stress responses in C. sativa. Several CsDof TFs may mediate lipid metabolism and stress responses in C. sativa. Collectively, our findings provide a foundation for deep understanding the roles of CsDofs and genetic improvements of oil yield and salt stress tolerance in this species and the related crops.

Selection and validation of appropriate reference genes for RT-qPCR analysis of Nitraria sibirica under various abiotic stresses.

BACKGROUND: Nitraria sibirica Pall. is a halophytic shrub with strong environmental adaptability that can survive in extremely saline-alkali and drought-impacted environments. Gene expression analysis aids in the exploration of the molecular mechanisms of plant responses to abiotic stresses. RT-qPCR is the most common technique for studying gene expression. Stable reference genes are a prerequisite for obtaining accurate target gene expression results in RT-qPCR analysis. RESULTS: In this study, a total of 10 candidate reference genes were selected from the transcriptome of N. sibirica, and their expression stability in leaves and roots under different treatment conditions (salt, alkali, drought, cold, heat and ABA) was evaluated with the geNorm, NormFinder, BestKeeper, comparative ΔCt and RefFinder programs. The results showed that the expression stability of the candidate reference genes was dependent on the tissue and experimental conditions tested. ACT7 combined with R3H, GAPDH, TUB or His were the most stable reference genes in the salt- or alkali-treated leaves, salt-treated roots and drought-treated roots, respectively; R3H and GAPDH were the most suitable combination for drought-treated leaves, heat-treated root samples and ABA-treated leaves; DIM1 and His maintained stable expression in roots under alkali stress; and TUB combined with R3H was stable in ABA-treated roots. TBCB and GAPDH exhibited stable expression in heat-treated leaves; TBCB, R3H, and ERF3A were stable in cold-treated leaves; and the three most stable reference genes for cold-treated roots were TBCB, ACT11 and DIM1. The reliability of the selected reference genes was further confirmed by evaluating the expression patterns of the NsP5CS gene under the six treatment conditions. CONCLUSION: This study provides a theoretical reference for N. sibirica gene expression standardization and quantification under various abiotic stress conditions and will help to reveal the molecular mechanisms that confer stress tolerance to N. sibirica.

Mobilizable antibiotic resistance genes are present in dust microbial communities.

The decades-long global trend of urbanization has led to a population that spends increasing amounts of time indoors. Exposure to microbes in buildings, and specifically in dust, is thus also increasing, and has been linked to various health outcomes and to antibiotic resistance genes (ARGs). These are most efficiently screened using DNA sequencing, but this method does not determine which microbes are viable, nor does it reveal whether their ARGs can actually disseminate to other microbes. We have thus performed the first study to: 1) examine the potential for ARG dissemination in indoor dust microbial communities, and 2) validate the presence of detected mobile ARGs in viable dust bacteria. Specifically, we integrated 166 dust metagenomes from 43 different buildings. Sequences were assembled, annotated, and screened for potential integrons, transposons, plasmids, and associated ARGs. The same dust samples were further investigated using cultivation and isolate genome and plasmid sequencing. Potential ARGs were detected in dust isolate genomes, and we confirmed their placement on mobile genetic elements using long-read sequencing. We found 183 ARGs, of which 52 were potentially mobile (associated with a putative plasmid, transposon or integron). One dust isolate related to Staphylococcus equorum proved to contain a plasmid carrying an ARG that was detected metagenomically and confirmed through whole genome and plasmid sequencing. This study thus highlights the power of combining cultivation with metagenomics to assess the risk of potentially mobile ARGs for public health.

Use of Neoadjuvant Imatinib to Facilitate Minimally Invasive Resection of Gastric Gastrointestinal Stromal Tumors.

BACKGROUND: Neoadjuvant imatinib is used to downstage surgery for large and/or unfavorably located gastric gastrointestinal stromal tumors (GISTs), but data regarding minimally invasive surgery (MIS) after neoadjuvant imatinib are limited. PATIENTS AND METHODS: We analyzed patients undergoing resection of nonmetastatic primary gastric GISTs larger than or equal to 4.5 cm in diameter at our institution between 2009 and 2020, as no tumors below this size received neoadjuvant imatinib. RESULTS: We identified 71 patients, 43 of whom (61%) received neoadjuvant imatinib. Patients receiving neoadjuvant imatinib had larger tumors at diagnosis [median diameter 8.6 cm (range 4.5-25 cm) versus 5.9 cm (range 4.5-11 cm), p < 0.01]. After a median 7.2 months of imatinib, tumors shrank by a median 34% in diameter, such that there was no longer a significant size difference at time of surgery between groups (median 6.3 cm versus 5.9 cm, p = 0.69). Of 29 patients for whom neoadjuvant imatinib was used to facilitate MIS, 21 (72%) underwent successful MIS, which accounted for 49% of the entire neoadjuvant cohort. In a multivariable regression model, smaller tumor size at time of surgery was predictive of successful MIS, but tumor location was not. CONCLUSIONS: Neoadjuvant imatinib caused significant tumor shrinkage, and MIS was successful in 72% of cases for which neoadjuvant imatinib was intended to facilitate it. Smaller tumor size at time of surgery, but not tumor location, was associated with successful MIS, which may help inform patient selection for neoadjuvant imatinib.