Structural basis of mitochondrial protein import by the TIM23 complex.

Mitochondria import nearly all of their approximately 1,000-2,000 constituent proteins from the cytosol across their double-membrane envelope1-5. Genetic and biochemical studies have shown that the conserved protein translocase, termed the TIM23 complex, mediates import of presequence-containing proteins (preproteins) into the mitochondrial matrix and inner membrane. Among about ten different subunits of the TIM23 complex, the essential multipass membrane protein Tim23, together with the evolutionarily related protein Tim17, has long been postulated to form a protein-conducting channel6-11. However, the mechanism by which these subunits form a translocation path in the membrane and enable the import process remains unclear due to a lack of structural information. Here we determined the cryo-electron microscopy structure of the core TIM23 complex (heterotrimeric Tim17-Tim23-Tim44) from Saccharomyces cerevisiae. Contrary to the prevailing model, Tim23 and Tim17 themselves do not form a water-filled channel, but instead have separate, lipid-exposed concave cavities that face in opposite directions. Our structural and biochemical analyses show that the cavity of Tim17, but not Tim23, forms the protein translocation path, whereas Tim23 probably has a structural role. The results further suggest that, during translocation of substrate polypeptides, the nonessential subunit Mgr2 seals the lateral opening of the Tim17 cavity to facilitate the translocation process. We propose a new model for the TIM23-mediated protein import and sorting mechanism, a central pathway in mitochondrial biogenesis.

Multiomics analysis reveals the molecular mechanisms underlying virulence in Rhizoctonia and jasmonic acid-mediated resistance in Tartary buckwheat (Fagopyrum tataricum).

Rhizoctonia solani is a devastating soil-borne pathogen that seriously threatens the cultivation of economically important crops. Multiple strains with a very broad host range have been identified, but only 1 (AG1-IA, which causes rice sheath blight disease) has been examined in detail. Here, we analyzed AG4-HGI 3 originally isolated from Tartary buckwheat (Fagopyrum tataricum), but with a host range comparable to AG1-IA. Genome comparison reveals abundant pathogenicity genes in this strain. We used multiomic approaches to improve the efficiency of screening for disease resistance genes. Transcriptomes of the plant-fungi interaction identified differentially expressed genes associated with virulence in Rhizoctonia and resistance in Tartary buckwheat. Integration with jasmonate-mediated transcriptome and metabolome changes revealed a negative regulator of jasmonate signaling, cytochrome P450 (FtCYP94C1), as increasing disease resistance probably via accumulation of resistance-related flavonoids. The integration of resistance data for 320 Tartary buckwheat accessions identified a gene homolog to aspartic proteinase (FtASP), with peak expression following R. solani inoculation. FtASP exhibits no proteinase activity but functions as an antibacterial peptide that slows fungal growth. This work reveals a potential mechanism behind pathogen virulence and host resistance, which should accelerate the molecular breeding of resistant varieties in economically essential crops.

Improving the performance of single-cell RNA-seq data mining based on relative expression orderings.

The advent of single-cell RNA-sequencing (scRNA-seq) provides an unprecedented opportunity to explore gene expression profiles at the single-cell level. However, gene expression values vary over time and under different conditions even within the same cell. There is an urgent need for more stable and reliable feature variables at the single-cell level to depict cell heterogeneity. Thus, we construct a new feature matrix called the delta rank matrix (DRM) from scRNA-seq data by integrating an a priori gene interaction network, which transforms the unreliable gene expression value into a stable gene interaction/edge value on a single-cell basis. This is the first time that a gene-level feature has been transformed into an interaction/edge-level for scRNA-seq data analysis based on relative expression orderings. Experiments on various scRNA-seq datasets have demonstrated that DRM performs better than the original gene expression matrix in cell clustering, cell identification and pseudo-trajectory reconstruction. More importantly, the DRM really achieves the fusion of gene expressions and gene interactions and provides a method of measuring gene interactions at the single-cell level. Thus, the DRM can be used to find changes in gene interactions among different cell types, which may open up a new way to analyze scRNA-seq data from an interaction perspective. In addition, DRM provides a new method to construct a cell-specific network for each single cell instead of a group of cells as in traditional network construction methods. DRM's exceptional performance is due to its extraction of rich gene-association information on biological systems and stable characterization of cells.

RSK1 promotes mammalian axon regeneration by inducing the synthesis of regeneration-related proteins.

In contrast to the adult mammalian central nervous system (CNS), the neurons in the peripheral nervous system (PNS) can regenerate their axons. However, the underlying mechanism dictating the regeneration program after PNS injuries remains poorly understood. Combining chemical inhibitor screening with gain- and loss-of-function analyses, we identified p90 ribosomal S6 kinase 1 (RSK1) as a crucial regulator of axon regeneration in dorsal root ganglion (DRG) neurons after sciatic nerve injury (SNI). Mechanistically, RSK1 was found to preferentially regulate the synthesis of regeneration-related proteins using ribosomal profiling. Interestingly, RSK1 expression was up-regulated in injured DRG neurons, but not retinal ganglion cells (RGCs). Additionally, RSK1 overexpression enhanced phosphatase and tensin homolog (PTEN) deletion-induced axon regeneration in RGCs in the adult CNS. Our findings reveal a critical mechanism in inducing protein synthesis that promotes axon regeneration and further suggest RSK1 as a possible therapeutic target for neuronal injury repair.

MicroRNA-99b Regulates Bacillus Calmette-Guerin-Infected Immature Dendritic Cell-Induced CD4+ T Cell Differentiation by Targeting mTOR Signaling.

This study aimed to elucidate the mechanisms by which microRNA-99b (miR-99b) regulates CD4+ T cell differentiation induced by Bacillus Calmette-Guerin (BCG)-infected immature dendritic cells (imDCs). Levels of miR-99b, interferon-gamma (IFN-γ), Foxp3, interleukin (IL)-10, IL-17, IL-23, and ROR-γt were assessed. Effects of miR-99b inhibition and mechanistic target of rapamycin (mTOR) agonist on Th17/Treg cell ratio and cytokine levels (IL-6, IL-17, IL-23) were studied. Expression of mTOR, S6K1, and 4E-BP1 related to miR-99b was analyzed. BCG-infected imDCs led to CD4+ T cell differentiation and altered levels of IFN-γ, Foxp3, IL-10, miR-99b, IL-17, IL-23, and ROR-γt. Inhibition of miR-99b increased the Th17/Treg cell ratio in CD4+ T cells co-cultured with BCG-infected imDCs, and this effect was further enhanced by the mTOR agonist. Additionally, the miR-99b inhibitor elevated the levels of IL-6, IL-17, and IL-23 when CD4+ T cells were co-cultured with BCG-infected imDCs, and the mTOR agonist further amplified this increase. Notably, miR-99b negatively regulated mTOR signaling, as the miR-99b inhibitor upregulated the expression levels of mTOR, S6K1, and 4E-BP1 while decreasing miR-99b. It was concluded that miR-99b modulates CD4+ T cell differentiation via mTOR pathway in response to BCG-infected im-DCs. Inhibiting miR-99b affects Th17/Treg ratio and pro-inflammatory cytokines, potentially impacting tuberculosis immunotherapies.

A genome-wide association study identifies a transporter for zinc uploading to maize kernels.

The Zn content in cereal seeds is an important trait for crop production as well as for human health. However, little is known about how Zn is loaded to plant seeds. Here, through a genome-wide association study (GWAS), we identify the Zn-NA (nicotianamine) transporter gene ZmYSL2 that is responsible for loading Zn to maize kernels. High promoter sequence variation in ZmYSL2 most likely drives the natural variation in Zn concentrations in maize kernels. ZmYSL2 is specifically localized on the plasma membrane facing the maternal tissue of the basal endosperm transfer cell layer (BETL) and functions in loading Zn-NA into the BETL. Overexpression of ZmYSL2 increases the Zn concentration in the kernels by 31.6%, which achieves the goal of Zn biofortification of maize. These findings resolve the mystery underlying the loading of Zn into plant seeds, providing an efficient strategy for breeding or engineering maize varieties with enriched Zn nutrition.

The evolutionary path of chemosensory and flagellar macromolecular machines in Campylobacterota.

The evolution of macromolecular complex is a fundamental biological question, which is related to the origin of life and also guides our practice in synthetic biology. The chemosensory system is one of the complex structures that evolved very early in bacteria and displays enormous diversity and complexity in terms of composition and array structure in modern species. However, how the diversity and complexity of the chemosensory system evolved remains unclear. Here, using the Campylobacterota phylum with a robust "eco-evo" framework, we investigated the co-evolution of the chemosensory system and one of its important signaling outputs, flagellar machinery. Our analyses show that substantial flagellar gene alterations will lead to switch of its primary chemosensory class from one to another, or result in a hybrid of two classes. Unexpectedly, we discovered that the high-torque generating flagellar motor structure of Campylobacter jejuni and Helicobacter pylori likely evolved in the last common ancestor of the Campylobacterota phylum. Later lineages that experienced significant flagellar alterations lost some key components of complex scaffolding structures, thus derived simpler structures than their ancestor. Overall, this study revealed the co-evolutionary path of the chemosensory system and flagellar system, and highlights that the evolution of flagellar structural complexity requires more investigation in the Bacteria domain based on a resolved phylogenetic framework, with no assumptions on the evolutionary direction.

Observed changes in China's methane emissions linked to policy drivers.

China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country's future progress. Here, using satellite and surface observations, we quantify China's methane emissions during 2010-2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China's methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China's energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China's methane emissions, providing input to formulating methane policy toward its climate goal.

Flavonoid extracted from Epimedium attenuate cGAS-STING-mediated diseases by targeting the formation of functional STING signalosome.

Hyperactivation of the cyclic-GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signalling pathway has been shown to be associated with the development of a variety of inflammatory diseases, and the discovery of an inhibitor of the cGAS-STING signalling pathway holds great promise in the therapeutic interventions. Epimedium flavonoid (EF), a major active ingredient isolated from the medicinal plant Epimedium, has been reported to have good anti-inflammatory activity, but its exact mechanism of action remains unclear. In the present study, we found that EF in mouse bone marrow-derived macrophages (BMDMs), THP-1 (Tohoku Hospital Pediatrics-1) as well as in human peripheral blood mononuclear cells (hPBMC) inhibited the activation of the cGAS-STING signalling pathway, which subsequently led to a decrease in the expression of type I interferon (IFN-ß, CXCL10 and ISG15) and pro-inflammatory cytokines (IL-6 and TNF-α). Mechanistically, EF does not affect STING oligomerization, but inhibits the formation of functional STING signalosome by attenuating the interaction of interferon regulatory factor 3 (IRF3) with STING and TANK-binding kinase 1 (TBK1). Importantly, in vivo experiments, EF has shown promising therapeutic effects on inflammatory diseases mediated by the cGAS-STING pathway, which include the agonist model induced by DMXAA stimulation, the autoimmune inflammatory disease model induced by three prime repair exonuclease 1 (Trex1) deficiency, and the non-alcoholic steatohepatitis (NASH) model induced by a pathogenic amino acid and choline deficiency diet (MCD). To summarize, our study suggests that EF is a potent potential inhibitor component of the cGAS-STING signalling pathway for the treatment of inflammatory diseases mediated by the cGAS-STING signalling pathway.

Metformin ameliorates mitochondrial damage induced by C9orf72 poly(GR) via upregulating AKT phosphorylation.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are devastating neurodegenerative diseases with no effective cure. GGGGCC repeat expansion in C9orf72 is the most common genetic cause of both ALS and FTD. A key pathological feature of C9orf72 related ALS/FTD is the presence of abnormal dipeptide repeat proteins translated from GGGGCC repeat expansion, including poly Glycine-Arginine (GR). In this study, we observed that (GR)50 conferred significant mitochondria damage and cytotoxicity. Metformin, the most widely used clinical drug, successfully relieved (GR)50 induced mitochondrial damage and inhibited (GR)50 related cytotoxicity. Further research revealed metformin effectively restored mitochondrial function by upregulating AKT phosphorylation in (GR)50 expressed cells. Taken together, our results indicated restoring mitochondrial function with metformin may be a rational therapeutic strategy to reduce poly(GR) toxicity in C9orf72 ALS/FTD patients.

In Situ Optical Detection of Amines at a Parts-per-Quadrillion Level by Severing the Through-Space Conjugated Supramolecular Domino.

Conventional fluorophores suffer from low sensitivity and selectivity in amine detection due to the inherent limitations in their "one-to-one" stoichiometric sensing mechanism. Herein, we propose a "one-to-many" chain reaction-like sensing mechanism by creating a domino chain consisting of one fluorescent molecule (e.g., PTF1) and up to 40 nonemissive polymer chains (pPFPA) comprising over thousand repeating units (PFPA). PTF1 (the domino trigger) interacts with adjacent PFPA units (the following blocks) through polar-π interactions and initiates the domino effect, creating effective through-space conjugation along pPFPA chains and generating amplified yellow fluorescent signals through charge transfer between PTF1 and pPFPA. Amine exposure causes rapid dismantling of the fluorophore-pPFPA-based domino chain and significantly reduces the amplified emissions, thus providing an ultrasensitive method for detecting amines. Relying on the above merits, we achieve a limit of detection of 177 ppq (or 1.67 × 10-12 M) for triethylamine, which is nearly 4 orders lower than that of previous methods. Additionally, the distinct reactivity of pPFPA toward different amines allows for the discrimination of primary, secondary, and tertiary amines. This study presents a "domino effect" sensing mechanism that has not yet been reported and provides a general approach for chemical detection that is beyond the reach of conventional methods.

Concurrent nimotuzumab and intensity-modulated radiotherapy for elderly patients with locally advanced nasopharyngeal carcinoma.

Because of the common physical condition, reduced organ function, and comorbidities, elderly patients with nasopharyngeal carcinoma (NPC) are often underrepresented in clinical trials. The optimal treatment of elderly patients with locally advanced NPC remains unclear. The purpose of this study was to evaluate the efficacy of concurrent nimotuzumab combined with intensity-modulated radiotherapy (IMRT) in elderly patients with locally advanced NPC. We conducted a single-arm, phase II trial for elderly patients with stage III-IVA NPC (according to UICC-American Joint Committee on Cancer TNM classification, 8th edition). All patients received concurrent nimotuzumab (200 mg/week, 1 week prior to IMRT) combined with IMRT. The primary end-point was complete response (CR) rate. The secondary end-points were survival, safety, and geriatric assessment. Between March 13, 2017 and November 12, 2018, 30 patients were enrolled. In total, 20 (66.7%) patients achieved CR, and objective response was observed in 30 (100.0%) patients 1 month after radiotherapy. The median follow-up time was 56.05 months (25th-75th percentile, 53.45-64.56 months). The 5-year locoregional relapse-free survival, distant metastasis-free survival, cancer-specific survival, disease-free survival, and overall survival were 89.4%, 86.4%, 85.9%, 76.5%, and 78.8%, respectively. Grade 3 mucositis occurred in 10 (33%) patients and grade 3 pneumonia in 3 (10%) patients. Concurrent nimotuzumab combined with IMRT is effective and well-tolerated for elderly patients with locally advanced NPC.

High-quality chromosome-level genome assembly and multi-omics analysis of rosemary (Salvia rosmarinus) reveals new insights into the environmental and genome adaptation.

High-quality genome of rosemary (Salvia rosmarinus) represents a valuable resource and tool for understanding genome evolution and environmental adaptation as well as its genetic improvement. However, the existing rosemary genome did not provide insights into the relationship between antioxidant components and environmental adaptability. In this study, by employing Nanopore sequencing and Hi-C technologies, a total of 1.17 Gb (97.96%) genome sequences were mapped to 12 chromosomes with 46 121 protein-coding genes and 1265 non-coding RNA genes. Comparative genome analysis reveals that rosemary had a closely genetic relationship with Salvia splendens and Salvia miltiorrhiza, and it diverged from them approximately 33.7 million years ago (MYA), and one whole-genome duplication occurred around 28.3 MYA in rosemary genome. Among all identified rosemary genes, 1918 gene families were expanded, 35 of which are involved in the biosynthesis of antioxidant components. These expanded gene families enhance the ability of rosemary adaptation to adverse environments. Multi-omics (integrated transcriptome and metabolome) analysis showed the tissue-specific distribution of antioxidant components related to environmental adaptation. During the drought, heat and salt stress treatments, 36 genes in the biosynthesis pathways of carnosic acid, rosmarinic acid and flavonoids were up-regulated, illustrating the important role of these antioxidant components in responding to abiotic stresses by adjusting ROS homeostasis. Moreover, cooperating with the photosynthesis, substance and energy metabolism, protein and ion balance, the collaborative system maintained cell stability and improved the ability of rosemary against harsh environment. This study provides a genomic data platform for gene discovery and precision breeding in rosemary. Our results also provide new insights into the adaptive evolution of rosemary and the contribution of antioxidant components in resistance to harsh environments.

MiRLoc: predicting miRNA subcellular localization by incorporating miRNA-mRNA interactions and mRNA subcellular localization.

Subcellular localization of microRNAs (miRNAs) is an important reflection of their biological functions. Considering the spatio-temporal specificity of miRNA subcellular localization, experimental detection techniques are expensive and time-consuming, which strongly motivates an efficient and economical computational method to predict miRNA subcellular localization. In this paper, we describe a computational framework, MiRLoc, to predict the subcellular localization of miRNAs. In contrast to existing methods, MiRLoc uses the functional similarity between miRNAs instead of sequence features and incorporates information about the subcellular localization of the corresponding target mRNAs. The results show that miRNA functional similarity data can be effectively used to predict miRNA subcellular localization, and that inclusion of subcellular localization information of target mRNAs greatly improves prediction performance.

Adapt-Kcr: a novel deep learning framework for accurate prediction of lysine crotonylation sites based on learning embedding features and attention architecture.

Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes. The identification of Kcr sites is critical to better understanding their functional mechanisms. However, the existing experimental techniques for detecting Kcr sites are cost-ineffective, to a great need for new computational methods to address this problem. We here describe Adapt-Kcr, an advanced deep learning model that utilizes adaptive embedding and is based on a convolutional neural network together with a bidirectional long short-term memory network and attention architecture. On the independent testing set, Adapt-Kcr outperformed the current state-of-the-art Kcr prediction model, with an improvement of 3.2% in accuracy and 1.9% in the area under the receiver operating characteristic curve. Compared to other Kcr models, Adapt-Kcr additionally had a more robust ability to distinguish between crotonylation and other lysine modifications. Another model (Adapt-ST) was trained to predict phosphorylation sites in SARS-CoV-2, and outperformed the equivalent state-of-the-art phosphorylation site prediction model. These results indicate that self-adaptive embedding features perform better than handcrafted features in capturing discriminative information; when used in attention architecture, this could be an effective way of identifying protein Kcr sites. Together, our Adapt framework (including learning embedding features and attention architecture) has a strong potential for prediction of other protein posttranslational modification sites.

Predicting the structure of unexplored novel fentanyl analogues by deep learning model.

Fentanyl and its analogues are psychoactive substances and the concern of fentanyl abuse has been existed in decades. Because the structure of fentanyl is easy to be modified, criminals may synthesize new fentanyl analogues to avoid supervision. The drug supervision is based on the structure matching to the database and too few kinds of fentanyl analogues are included in the database, so it is necessary to find out more potential fentanyl analogues and expand the sample space of fentanyl analogues. In this study, we introduced two deep generative models (SeqGAN and MolGPT) to generate potential fentanyl analogues, and a total of 11 041 valid molecules were obtained. The results showed that not only can we generate molecules with similar property distribution of original data, but the generated molecules also contain potential fentanyl analogues that are not pretty similar to any of original data. Ten molecules based on the rules of fentanyl analogues were selected for NMR, MS and IR validation. The results indicated that these molecules are all unreported fentanyl analogues. Furthermore, this study is the first to apply the deep learning to the generation of fentanyl analogues, greatly expands the exploring space of fentanyl analogues and provides help for the supervision of fentanyl.

NcPath: a novel platform for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways.

SUMMARY: Non-coding RNAs play important roles in transcriptional processes and participate in the regulation of various biological functions, in particular miRNAs and lncRNAs. Despite their importance for several biological functions, the existing signaling pathway databases do not include information on miRNA and lncRNA. Here, we redesigned a novel pathway database named NcPath by integrating and visualizing a total of 178 308 human experimentally validated miRNA-target interactions (MTIs), 32 282 experimentally verified lncRNA-target interactions (LTIs) and 4837 experimentally validated human ceRNA networks across 222 KEGG pathways (including 27 sub-categories). To expand the application potential of the redesigned NcPath database, we identified 556 798 reliable lncRNA-protein-coding genes (PCG) interaction pairs by integrating co-expression relations, ceRNA relations, co-TF-binding interactions, co-histone-modification interactions, cis-regulation relations and lncPro Tool predictions between lncRNAs and PCG. In addition, to determine the pathways in which miRNA/lncRNA targets are involved, we performed a KEGG enrichment analysis using a hypergeometric test. The NcPath database also provides information on MTIs/LTIs/ceRNA networks, PubMed IDs, gene annotations and the experimental verification method used. In summary, the NcPath database will serve as an important and continually updated platform that provides annotation and visualization of the pathways on which non-coding RNAs (miRNA and lncRNA) are involved, and provide support to multimodal non-coding RNAs enrichment analysis. The NcPath database is freely accessible at http://ncpath.pianlab.cn/. AVAILABILITY AND IMPLEMENTATION: NcPath database is freely available at http://ncpath.pianlab.cn/. The code and manual to use NcPath can be found at https://github.com/Marscolono/NcPath/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Inverse relationship between HBV DNA levels and liver histopathological changes in immune-tolerant CHB patients.

Limited data exist regarding the association between hepatitis B virus (HBV) DNA levels and liver histopathological changes in patients with chronic hepatitis B (CHB) during the immune tolerant (IT) phase. In this study, we retrospectively analysed liver biopsy results from 150 adult IT-CHB patients. The liver tissue necroinflammation and fibrosis were evaluated by the Scheuer scoring system. Multivariate logistic regression, smooth curve fitting, and segmented regression models were used to examine the association between HBV DNA levels and liver histopathological changes. A total of 26%, 30.67% and 42% of IT patients had significant necroinflammation (≥G2), significant fibrosis (≥S2) and significant histopathological changes (≥G2 and/or ≥S2), respectively. HBV DNA levels were independently and non-linear inversely associated with significant necroinflammation and histopathological changes in IT-CHB patients. Patients with HBV DNA levels <107 IU/mL had a higher risk of significant histopathological changes compared to those with levels >107 IU/mL. The findings were further confirmed by smooth curve fitting analyses, subgroup and sensitivity analyses. In segmented regression model analyses, the optimal DNA value for the lowest odds ratio of significant histopathological changes was 7.26 log10 IU/mL. A non-linear inverse association between HBV DNA levels and significant histopathological changes in IT-CHB patients. DNA 7.26 log10 IU/mL may serve as a potential cut-off point to define a 'true immune tolerant phase' with minimal liver histopathological changes.

Detunable wireless Litzcage coil for human head MRI at 1.5 T.

Inductively coupled radiofrequency (RF) coils are an inexpensive and simple method to realize wireless RF coils in magnetic resonance imaging (MRI), which can significantly ease the MRI scan setup and improve patient comfort because they do not require bulky components such as cables, baluns, preamplifiers, and connectors. However, volume-type wireless coils are typically operated in transmit/receive mode because detuning such coils is much more challenging due to their complex structure and multiple resonant modes. Meanwhile, adding too many detuning circuits to a wireless coil would decrease the coil's quality factor, impair the signal-to-noise ratio, and increase the cost. In this work, we proposed, constructed, and tested a novel wireless volume coil based on the Litzcage design for 1.5-T head imaging. Being an inductively coupled coil, it has a much simpler structure, resulting in a lighter weight and less bulky design. Despite its simpler structure, it exhibits comparable imaging performance with a commercial receive array, providing an alternative to conventional wired coils with a high cost and complex structure. The unique figure-of-8 conductor pattern within the rungs ensures that the proposed wireless Litzcage can be efficiently detuned with minimal detuning circuits.

Antibiotic use during radical surgery in stage I-III colorectal cancer: correlation with outcomes?

AIMS: Accumulating evidence indicates that the use of antibiotics (ATBs) in cancer patients is potentially correlated with patient prognosis. Interestingly, the use of these agents is not uncommon in colorectal cancer (CRC) patients during surgery; however, their prognostic value in the clinic has never been addressed. MATERIALS AND METHODS: Data on ATB use during surgery, including the cumulative defined daily dose (cDDD) and the number of categories, were collected. Differences in the clinical data between the low and high cDDD subgroups and between subgroups with ≤ 4 and >4 categories. Additionally, the disease-free survival (DFS) and overall survival (OS) among these subgroups and the specific categories were compared. Finally, a Cox proportional hazard model was used to validate the risk factors for the outcome. RESULTS: The number of categories, rather than the cDDD, was a significant predictor of both DFS (P = 0.043) and OS (P = 0.039). Patients with obstruction are more likely to have a high cDDD, whereas older patients are more likely to have multiple categories. There were no significant differences in the DFS (log rank = 1.36, P = 0.244) or OS (log rank = 0.40, P = 0.528) between patients in the low- and high-cDDD subgroups, whereas patients with ≤ 4 categories had superior DFS (log rank = 9.92, P = 0.002) and OS (log rank = 8.30, P = 0.004) compared with those with >4 categories. Specifically, the use of quinolones was harmful to survival (DFS: log rank = 3.67, P = 0.055; OS: log rank = 5.10, P = 0.024), whereas the use of macrolides was beneficial to survival (DFS: log rank = 12.26, P < 0.001; OS: log rank = 9.77, P = 0.002). Finally, the number of categories was identified as an independent risk factor for both DFS (HR = 2.05, 95% CI: 1.35-3.11, P = 0.001) and OS (HR = 1.82, 95% CI: 1.14-2.90, P = 0.012). CONCLUSIONS: The cDDD of ATBs during surgery in stage I-III CRC patients did not correlate with outcome; however, patients in multiple categories or a specific category are likely to have inferior survival. These results suggest that particular caution should be taken when selecting ATBs for these patients in the clinic.