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Abstract This research presents a method based on deep learning for the reverse design of sound-absorbing structures. Traditional methods require time-consuming individual numerical simulations followed by cumbersome calculations, whereas the deep learning design method significantly simplifies the design process, achieving efficient and rapid design objectives. By utilizing deep neural networks, a mapping relationship between structural parameters and the sound absorption coefficient curve is established. The forward network predicts the sound absorption coefficient curve, while the reverse network enables the on-demand design of structural parameters for broadband high sound absorption. During the design process, a mean squared error (MSE) below 0.0001 is achieved. The accuracy of the proposed design method is validated through examples. The results demonstrate that the trained deep learning neural network could effectively replace the complex physical mechanisms between structural parameters and sound absorption coefficient curves. This deep learning design method could also be extended to other types of metamaterial reverse designs, significantly enhancing the efficiency of complex metamaterial designs. Lightweight design is crucial for energy saving and emission reduction. With the total mass and average sound absorption coefficient of sound-absorbing materials as targets, the NSGA-II algorithm has been used for multi-objective optimization design. The optimized average sound absorption coefficient increased by 4.84%, and the total material mass was reduced by 18.98%.

Objective To systematically review the progress in the application of artificial intelligence in the field of pediatric otolaryngology-head and neck surgery at home and abroad， aiming to provide reference for the development and clinical practice in the future. Methods Literature related to the application of artificial intelligence in otolaryngology，head and neck surgery were searched from PubMed， Web of Science and Embase databases in June 2024， regardless of the research type， publication date and language restrictions. Subsequently， using the National Heart， Lung， and Blood Institute Study Quality Assessment Tools （NHI-SQAT） and the Oxford 2011 Levels of Evidence （LOE）， tables were designed to assess the quality of the articles and select authentic and effective literature. Literature content was extracted， and a systematic review of current status and future prospects of artificial intelligence in this field was conducted. Results After preliminary screening of abstracts and titles， full-text reading， supplementary retrieval， and exclusion of literature that did not meet quality standards， a total of 38 articles were finally included. Artificial intelligence has been widely used in the diagnosis and treatment of pediatric otolaryngological diseases in various forms. Significant clinical effects have been achieved through methods such as machine learning and big data processing， enabling surgical assistance and the establishment of diagnostic and treatment models. In recent research， the diagnosis and treatment of pediatric otitis media， assessment of pediatric hearing loss， preoperative planning and postoperative guidance， and telemedicine are becoming the main directions of exploration and application of artificial intelligence. Conclusions Application of artificial intelligence in pediatric otolaryngology head and neck surgery at home and abroad has been gradually extended in recent years. As the use of artificial intelligence in assisted diagnosis and treatment has been gradually accepted by the medical community， the application platform for artificial intelligence will become diversified in the future.

Abstract Understanding the fluorescence resonance energy transfer (FRET) of metal nanoparticles at the atomic level has long been a challenge due to the lack of accurate systems with definite distance and orientation of molecules. Here we present the realization of achieving FRET between two atomically precise copper nanoclusters through cocrystallization-induced spatial confinement. In this study, we demonstrate the establishment of FRET in a cocrystallized Cu8(p-MBT)8(PPh3)4@Cu10(p-MBT)10(PPh3)4 system by exploiting the overlapping spectra between the excitation of the Cu10(p-MBT)10(PPh3)4 cluster and the emission of the Cu8(p-MBT)8(PPh3)4 cluster, combined with accurate control over the confined space between the two nanoclusters. Density functional theory is employed to provide deeper insights into the role of the distance and dipole orientations of molecules to illustrate the FRET procedure between two cluster molecules at the electronic structure level.

Background Extracting high-quality total RNA is pivotal for advanced RNA molecular studies, such as Next-generation sequencing and expression microarrays where RNA is hybridized. Despite the development of numerous extraction methods in recent decades, like the cetyl-trimethyl ammonium bromide (CTAB) and the traditional TRIzol reagent methods, their complexity and high costs often impede their application in small-scale laboratories. Therefore, a practical and economical method for RNA extraction that maintains high standards of efficiency and quality needs to be provided to optimize RNA extraction from human and mice tissues. Method This study proposes enhancements to the TRIzol method by incorporating guanidine isothiocyanate (GITC-T method) and sodium dodecyl sulfate (SDS-T method). We evaluated the effectiveness of these modified methods compared to the TRIzol method using a micro-volume UV-visible spectrophotometer, electrophoresis, q-PCR, RNA-Seq, and whole transcriptome sequencing. Result The micro-volume UV-visible spectrophotometer, electrophoresis, and RNA-Seq demonstrated that the GITC-T method yielded RNA with higher yields, integrity, and purity, while the consistency in RNA quality between the two methods was confirmed. Taking mouse cerebral cortex tissue as a sample, the yield of total RNA extracted by the GITC-T method was 1,959.06 ± 49.68 ng/mg, while the yield of total RNA extracted by the TRIzol method was 1,673.08 ± 86.39 ng/mg. At the same time, the OD260/280 of the total RNA samples extracted by the GITC-T method was 2.03 ± 0.012, and the OD260/230 was 2.17 ± 0.031, while the OD260/280 of the total RNA samples extracted by the TRIzol method was 2.013 ± 0.041 and the OD260/230 was 2.11 ± 0.062. Furthermore, q-PCR indicated that the GITC-T method achieved higher yields, purity, and greater transcript abundance of total RNA from the same types of animal samples than the TRIzol method. Conclusion The GITC-T method not only yields higher purity and quantity of RNA but also reduces reagent consumption and overall costs, thereby presenting a more feasible option for small-scale laboratory settings.

Correlation does not imply causation, but patterns of statistical association between variables can be exploited to infer a causal structure (even with purely observational data) with the burgeoning field of causal discovery. As a purely observational science, astrophysics has much to gain by exploiting these new methods. The supermassive black hole (SMBH)–galaxy interaction has long been constrained by observed scaling relations, which is low-scatter correlations between variables such as SMBH mass and the central velocity dispersion of stars in a host galaxy's bulge. This study, using advanced causal discovery techniques and an up-to-date data set, reveals a causal link between galaxy properties and dynamically measured SMBH masses. We apply a score-based Bayesian framework to compute the exact conditional probabilities of every causal structure that could possibly describe our galaxy sample. With the exact posterior distribution, we determine the most likely causal structures and notice a probable causal reversal when separating galaxies by morphology. In elliptical galaxies, bulge properties (built from major mergers) tend to influence SMBH growth, while, in spiral galaxies, SMBHs are seen to affect host galaxy properties, potentially through feedback in gas-rich environments. For spiral galaxies, SMBHs progressively quench star formation, whereas, in elliptical galaxies, quenching is complete, and the causal connection has reversed. Our findings support theoretical models of hierarchical assembly of galaxies and active galactic nuclei feedback regulating galaxy evolution. Our study suggests the potentiality for further exploration of causal links in astrophysical and cosmological scaling relations, as well as any other observational science.

We present the application of the image coaddition algorithm, upsampling and point-spread function (PSF) deconvolution coaddition (UPDC), for stacking multiple exposure images captured by the James Webb Space Telescope (JWST) Near-Infrared Camera. By addressing the PSF effect, UPDC provides visually enhanced and sharper images. Furthermore, the antialiasing and superresolution capabilities of UPDC make it easier to deblend sources overlapped on images, yielding a higher accuracy of aperture photometry. We apply this algorithm to the SMACS J0723 imaging data. Comparative analysis with the Drizzle algorithm demonstrates significant improvements in detecting faint sources, achieving accurate photometry, and effectively deblending (superresolution) closely packed sources. As a result, we have newly detected a pair of close binary stars that were previously unresolvable in the original exposures or the Drizzled image. These improvements significantly benefit various scientific projects conducted by JWST. The resulting data set, named “UPdec-Webb,” can be accessed through the official website of the Chinese Virtual Observatory.

Developing new approaches to fulfill the enantioseparation of nanocluster racemates and construct cluster-based nanomaterials with optical activity remains highly desired in cluster science, because it is an essential prerequisite for fundamental research and extensive applications of these nanomaterials. We herein propose a strategy termed “active-site exposing and partly re-protecting” to trigger the symmetry breaking of highly symmetrical nanoclusters and to render cluster crystals optically active. The vertex PPh3 of the symmetrical Ag29(SSR)12(PPh3)4 (SSR = 1, 3-benzenedithiol) nanocluster was firstly dissociated in the presence of counterions with large steric hindrance, and then the exposed Ag active sites of the obtained Ag29(SSR)12 nanocluster were partly re-protected by Ag+, yielding an Ag29(SSR)12-Ag2 nanocluster with a symmetry-breaking construction. Ag29(SSR)12-Ag2 followed a chiral crystallization mode, and its crystal displayed strong optical activity, derived from CD and CPL characterizations. Overall, this work presents a new approach (i.e., active-site exposing and partly re-protecting) for the symmetry breaking of highly symmetrical nanoclusters, the enantioseparation of nanocluster racemates, and the achievement of highly optical activity.

Background Patients with liver cirrhosis complicated by gastroesophageal variceal and rupture hemorrhage have a certain probability of rebleeding events after endoscopic treatment, and the bleeding volume of rebleeding events is greater with higher risk, which seriously affects the survival rates of patients. Objective To investigate the independent risk factors of rebleeding events within 3 years after endoscopic treatment in cirrhotic patients with gastroesophageal variceal hemorrhage, construct a nomogram risk prediction model and validate it internally. Methods Four hundred and three patients who underwent endoscopic treatment for liver cirrhosis associated gastroesophageal varices at the Tangdu Hospital and Xijing Hospital, Air Force Medical University from 2011-2022 were retrospectively collected and divided into the rebleeding group (n=252) and control group (n=151) based on the presence of rebleeding within 3 years. The general data and auxiliary examination results of the patients between both groups were compared, and the statistically significant factors were included in the multivariate Logistic regression analysis to analyze the independent risk factors. These data were then input into the R language software to construct a nomogram risk prediction model by using a specific program package. Results Multivariate Logistic regression analysis showed that smoking〔OR=2.499, 95%CI (1.232, 5.066), P=0.011〕, portal vein internal diameter〔OR=1.047, 95%CI (1.028, 1.066), P

Abstract Interstitial lung diseases (ILDs), or diffuse pulmonary lung disease, are a subset of lung diseases that primarily affect lung alveoli and the space around interstitial tissue and bronchioles. It clinically manifests as progressive dyspnea, and patients often exhibit a varied decrease in pulmonary diffusion function. Recently, variants in telomere biology-related genes have been identified as genetic lesions of ILDs. Here, we enrolled 82 patients with interstitial pneumonia from 2017 to 2021 in our hospital to explore the candidate gene mutations of these patients via whole-exome sequencing. After data filtering, a novel heterozygous mutation (NM_025099: p.Gly131Arg) of CTC1 was identified in two affected family members. As a component of CST (CTC1-STN1-TEN1) complex, CTC1 is responsible for maintaining telomeric structure integrity and has also been identified as a candidate gene for IPF, a special kind of chronic ILD with insidious onset. Simultaneously, real-time PCR revealed that two affected family members presented with short telomere lengths, which further confirmed the effect of the mutation in the CTC1 gene. Our study not only expanded the mutation spectrum of CTC1 and provided epidemiological data on ILDs caused by CTC1 mutations but also further confirmed the relationship between heterozygous mutations in CTC1 and ILDs, which may further contribute to understanding the mechanisms underlying ILDs.

Skeletal muscle regeneration is a complex process where various cell types and cytokines are involved. Single-cell RNA-sequencing (scRNA-seq) provides the opportunity to deconvolute heterogeneous tissue into individual cells based on their transcriptomic profiles. Recent scRNA-seq studies on mouse muscle regeneration have provided insights to understand the transcriptional dynamics that underpin muscle regeneration. However, a database to investigate gene expression profiling during skeletal muscle regeneration at the single-cell level is lacking. Here, we collected over 105 000 cells at 7 key regenerative time-points and non-injured muscles and developed a database, the Single-cell Skeletal Muscle Regeneration Database (SCSMRD). SCSMRD allows users to search the dynamic expression profiles of genes of interest across different cell types during the skeletal muscle regeneration process. It also provides a network to show the activity of regulons in different cell types at different time points. Pesudotime analysis showed the state changes trajectory of muscle stem cells (MuSCs) during skeletal muscle regeneration. This database is freely available at https://scsmrd.fengs-lab.com.

Monolayer-protected nanoclusters are ideal models for understanding the correlations between structures and properties of inorganic nanoparticles, especially for those molecules with identical sizes but comparable structures. Here, we controllably prepared and structurally determined a valence-neutral Au24+xAg20‑x(SPhtBu)26 (0 < x < 4) nanocluster with comparable structure features to a well-known Au12Ag32(SPhF2)30 cluster. The Au24+xAg20‑x(SPhtBu)26 cluster contained a hollow Au12@M20 metallic kernel (M = Au/Ag), 12 Au1(SR)2 staples, and two bridging SR molecules, and its average molecular formula was determined to be Au26.3Ag17.7(SPhtBu)26, as evidenced by X-ray crystallography and electrospray ionization mass spectrometry. Because of the ligand effect and the asymmetrical arrangement of the Au dopants in the dodecahedral cage, the Au24+xAg20‑x(SPhtBu)26 nanocluster exhibited lower molecular symmetry relative to Au12Ag32(SPhF2)30 in terms of the dodecahedral kernel and motif shell structures. Besides, the strong π–π interaction in Au24+xAg20‑x(SPhtBu)26 contributed to its enhanced photoluminescence intensity compared with Au12Ag32(SPhF2)30. The study, herein, extends the 44-metal-atom cluster family, thereby enabling us to better understand the correlations between their structures and properties at the atomic level.

Tertiary lymphoid structures (TLSs), referred to as tertiary lymphoid organs and lymphoid tissue neogenesis, are aggregates of immune cells that occur in nonlymphoid tissues. In recent years, it has been found that TLSs within the tumor microenvironment have been associated with local adaptive immune immunity against cancer and favorable prognosis in several human solid tumors, including gynecological cancers. The issue of the prognosis of gynecological cancers, including endometrial, cervical, and ovarian cancer, is an enormous challenge that many clinical doctors and researchers are now facing. Concerning the predictive prognostic role of TLSs, effective evaluation, and quantification of TLSs in human tissues may be used to assist gynecologists in assessing the clinical outcome of gynecological cancer patients. This review summarizes the current knowledge of TLSs in gynecological cancers, mainly focusing on the potential mechanism of TLS neogenesis, methods for evaluating TLSs, their prognostic value, and their role in antitumor immune immunity. This review also discusses the new therapeutic methods currently being explored in gynecological cancers to induce the formation of TLSs.

An accurate intrinsic structural model is essential to describing the high-temperature deformation behavior of metal materials. Support Vector Regression (SVR) has strong regression analysis capabilities, but its application research in constructing constitutive models of 25CrMo4 steel still needs to be improved. In this study, we use grid search, particle swarm optimization, improved genetic algorithm, and improved gray wolf optimization to optimize SVR parameters. A constitutive relationship model for 25CrMo4 steel under high-temperature compression based on SVR was established through training using experimental data models. The predicted data of SVR constitutive models with different optimization algorithms were compared with experimental data. Statistical values, such as average absolute percentage error (AAPE), mean absolute percentage error (MAPE), and correlation coefficient (R2), were introduced to evaluate the accuracy of each model. The particle swarm optimization-SVR model achieved the best performance, with an AAPE of 0.455 38, MAPE of 0.489 09%, and R2 of 0.999 74. Furthermore, compared to other models, it requires the least time. This model has a higher accuracy than other commonly used instantaneous models. These findings can provide a basis for selecting appropriate deformation parameters and preventing hot working defects of 25CrMo4 steel, thus helping to improve the manufacturing process and material properties.

We utilize the publicly available code GIZMO to re-simulate 12 galaxies selected from the Numerical Investigation of a Hundred Astronomical Object (NIHAO) simulation suite, which were run with the GASOLINE code, then compare their properties. We find that while both codes with the same initial conditions and large-scale environments can successfully produce similar galactic disks in Milky Way-mass systems, yet significant differences are still seen in many aspects, particularly the circumgalactic medium (CGM) environment they reside in. Specifically, the thermal feedback recipe used in GASOLINE results in ubiquitous, long-term, large-scale outflows, primarily driven by high-density hot interstellar medium from the galaxy center, preventing the intergalactic medium from falling efficiently. Recycled gas and inflows in the CGM appear at 10 ^4∼5 K, playing a crucial role in the formation of cold disks in the NIHAO simulations. In contrast, disk galaxies simulated by GIZMO do not exhibit prominent outflows at low redshifts, but instead display quasi-virialized hot gas halos that arise from the interaction between inflows and feedback-driven outflows. Therefore, the origins of mass and angular momentum of the cold disk in the two simulations are quite different, even though the final morphologies of the corresponding galaxies are both disky. The differences in the distribution of CGM gas are mainly due to different feedback models implemented in the two codes. Future observations of CGM could provide valuable insight into the physics governing the baryon cycle in galaxies.

Understanding the assembly pattern of metal nanoclusters in crystalline units at the atomic level is crucial for an in-depth understanding of their supramolecular interactions and structure–property correlations. In this study, two Au9Ag6 nanoclusters bearing a similar framework were controllably synthesized and structurally determined. By tailoring the peripheral thiol ligands from SPhpOMe to SPhoMe (HSPhpOMe = 4-methoxythiophenol, HSPhoMe = 2-methylbenzenethiol), the hierarchical assembly of cluster molecules in their superlattice varied from “ABAB” to “ABCDABCD”. Based on the atomically precise structures of the two nanoclusters, we proposed that such differences in crystalline packing modes resulted from a combination of their structural differences, including intramolecular coordination preferences (Au–P vs. Ag–Cl), steric hindrance effects of thiol ligands (SPhpOMe vs. SPhoMe), and intra-/inter-cluster interactions (C–H···π, π···π, and H···H). We also investigated the structure/assembly-dependent optical properties of the two clusters at different states and rationalized the obtained structure–property correlations at the atomic level. Moreover, this study presented an interesting case for analyzing the hierarchical assembly of metal nanoclusters, allowing an in-depth understanding of the ligand effect on the crystalline assemblies of metal nanoclusters with atomic precision.

Abstract Developing new templates to evaluate the ligand engineering effect in manipulating nanoclusters from both molecular and supramolecular aspects remains highly desired in cluster science because it allows for an in‐depth understanding of structure‐property correlations. We herein presented the secondary ligand (i.e., the phosphine ligand) engineering based on an Ag29 nanocluster template and its dual effects on intracluster structures and intercluster aggregates. The “dissociation‐combination equilibrium” of phosphine ligands on the nanocluster surface was controlled by tailoring the C–H⋯π interactions within the ligand shell, which led to the fabrication of a family of [Ag29(BDT)12(PR3)x]3– nanoclusters. On the molecular level, the dissociation of phosphine ligands contracted the nanocluster framework, while the overall configuration of [Ag29(BDT)12]3– was retained. On the supramolecular level, the complete dissociation of phosphine ligands yielded a bare nanocluster, which followed a chiral crystallization mode, and its crystals displayed high optical activity, derived from circular dichroism and circularly polarized luminescence characterizations. Overall, this work presents the peripheral ligand effects in directionally controlling intracluster configurations and intercluster aggregations, which hopefully benefit future design and preparation of new nanoclusters or cluster‐based nanomaterials with customized structures and performances.

The aim of the present investigation is to study the effect of track support structures on the metro 5th to 8th-order out-of-round (OOR) wheel caused by friction-induced vibrations. Three finite element models of metro-leading wheelset-track systems with three types of track support structures were established. The motion stabilities of these systems were studied using the complex feature value method. Three unstable vibrations that may cause the formation of the 5th to 8th order wheel OOR profiles were predicted. The simulation results show that the saturated creep forces can lead to unstable vibrations of wheelset-track systems, which are capable of inducing the 5th to 8th-order OOR wheel shapes. Choosing the appropriate value of the fastener damping and using the rail dampers are helpful to reduce or even eliminate wheel polygonal wear caused by these vibrations.

Modern embedded systems have achieved relatively high processing power. They can be used for edge computing and computer vision, where data are collected and processed locally, without the need for network communication for decision-making and data analysis purposes. Face detection, face recognition, and pose detection algorithms can be executed with acceptable performance on embedded systems and are used for home security and monitoring. However, popular machine learning frameworks, such as MediaPipe, require relatively high usage of CPU while running, even when idle with no subject in the scene. Combined with the still present false detections, this wastes CPU time, elevates the power consumption and overall system temperature, and generates unnecessary data. In this study, a low-cost low-resolution infrared thermal sensor array was used to control the execution of MediaPipe’s pose detection algorithm using single-board computers, which only runs when the thermal camera detects a possible subject in its field of view. A lightweight algorithm with several filtering layers was developed, which allowed the effective detection and isolation of a person in the thermal image. The resulting hybrid computer vision proved effective in reducing the average CPU workload, especially in environments with low activity, almost eliminating MediaPipe’s false detections, and reaching up to 30% power saving in the best-case scenario.

The origin of the hollow icosahedral M12 kernel in metal nanoclusters is under debate. Here the authors demonstrate the Au alloying-induced kernel collapse from small-sized nano-building blocks as a viable approach for the generation of hollow icosahedral M12 kernel in metal nanoclusters.

Apiaceae is a major family from Apiales and includes many important vegetable and medicinal crops. Heat shock transcription factors (Hsf) play important roles in heat tolerance during plant development. Here, we conducted systematic analyses of the Hsf gene family in three Apiaceae species, including 17 Apium graveolens (celery), 32 Coriandrum sativum (coriander), and 14 Daucus carota (carrot). A total of 73 Hsf genes were identified in three representative species, including Arabidopsis thaliana, Vitis vinifera, and Lactuca sativa. Whole-genome duplication played important roles in the Hsf gene family's expansion within Apiaceae. Interestingly, we found that coriander had more Hsf genes than celery and carrot due to greater expansion and fewer losses. Twenty-seven branches of the phylogenetic tree underwent considerable positive selection in these Apiaceae species. We also explored the expression patterns of Hsf genes in three plant organs. Collectively, this study will serve as a rich gene resource for exploring the molecular mechanisms of heat tolerance. Additionally, this is the first study to report on the Hsf gene family in Apiaceae; thus, our research will provide guidance for future comparative and functional genomic studies on the Hsf gene family and others in Apiaceae.

In the process of ultrasonic vibration cutting (UVC), the acoustic performance parameters of ultrasonic machining system change because of systems heating up and cutting loads. The changes of acoustic performance parameters will affect resonant frequency, impedance, and power match of the ultrasonic machining system, and stability of the amplitude of UVC system. It is hard to monitor the acoustic performance parameters online. Based on the analysis of the correlation mechanism between transducer temperature and acoustic performance parameters, the correlation models between transducer temperature and resonance frequency, static capacitance, and dynamic resistance of ultrasonic vibration machining system are established by curve regression analysis modeling method. The acoustic performance parameters of an ultrasonic vibration machining system are determined by transducer temperature using the correlation models. The effectiveness of the model is verified by experiments. It gives the information for the stability evaluation of the ultrasonic vibration machining process, the dynamic impedance matching of the ultrasonic machining system, and the power matching adjustment of the ultrasonic power supply.

Abstract Syndecan-4 (SDC4) functions as a major endogenous membrane-associated receptor and widely regulates cytoskeleton, cell adhesion, and cell migration in human tumorigenesis and development, which represents a charming anti-cancer therapeutic target. Here, SDC4 was identified as a direct cellular target of small-molecule bufalin with anti-hepatocellular carcinoma (HCC) activity. Mechanism studies revealed that bufalin directly bond to SDC4 and selectively increased SDC4 interaction with substrate protein DEAD-box helicase 23 (DDX23) to induce HCC genomic instability. Meanwhile, pharmacological promotion of SDC4/DDX23 complex formation also inactivated matrix metalloproteinases (MMPs) and augmented p38/JNK MAPKs phosphorylation, which are highly associated with HCC proliferation and migration. Notably, specific knockdown of SDC4 or DDX23 markedly abolished bufalin-dependent inhibition of HCC proliferation and migration, indicating SDC4/DDX23 signaling axis is highly involved in the HCC process. Our results indicate that membrane-spanning proteoglycan SDC4 is a promising druggable target for HCC, and pharmacological regulation of SDC4/DDX23 signaling axis with small-molecule holds great potential to benefit HCC patients.

Despite recent progress in individual nanocluster synthesis, understanding the competing or coexisting effects between particles in solution remains challenging. Here, the authors present the synthesis of a bi-nanocluster system comprising two atomically precise nanoclusters, and map out the interdependent relationship between them.

Abstract. Background. Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Genome-wide association studies in non-Asian population revealed a link between COPD and mutations in the PTCH1 gene encoding Patched1, a receptor in the Hedgehog signaling pathway important for lung morphogenesis and pulmonary function. The aim of this study was to investigate the association between PTCH1 polymorphisms and the COPD risk in the Chinese Han population. Methods. We performed a case-control study including 296 patients with COPD and 300 healthy individuals. Single-nucleotide polymorphisms in the PTCH1 gene were identified and genotyped based on the linkage disequilibrium analysis in all participants. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using logistic regression analysis after adjustment for age, gender, and smoking. Results. In total, 28 single-nucleotide polymorphisms were identified in patients with COPD. Among them, “A” allele of rs28491365 (OR: 1.388, 95% CI: 1.055–1.827, P = 0.018), and “G” alleles of rs10512248 (OR: 1.299, 95% CI: 1.021–1.653, P = 0.033) and rs28705285 (OR: 1.359, 95% CI: 1.024–1.803, P = 0.033; respectively) were significantly associated with an increased COPD risk. Genetic model analysis revealed that the “T/T” genotype of rs34695652 was associated with a decreased COPD risk under the recessive model (OR: 0.490, 95% CI: 0.270–0.880, P = 0.010), whereas rs28504650/rs10512248 haplotype CG was significantly associated with an increased COPD risk after adjustment for age, gender, and smoking status (OR: 6.364, 95% CI: 1.220–33.292, P = 0.028). Conclusions. The study provides a new insight into the role of PTCH1 polymorphisms in the susceptibility to COPD in the Chinese Han population.

Oncolytic viruses can activate tumor neoantigen-specific T cell responses. However, PD-L1 upregulation on tumor cells and immune cells leads to tumor resistance to this immunotherapy approach. Here, the authors develop an oncolytic virus which expresses both a PD-L1 inhibitor and GM-CSF which allows an improved tumor neoantigen-specific T cell response in preclinical models.

Antibiotic-resistant Pseudomonas aeruginosa is insensitive to antibiotics and difficult to deal with. An understanding of the resistance mechanisms is required for the control of the pathogen. In this study, gas chromatography–mass spectrometer (GC-MS)-based metabolomics was performed to identify differential metabolomes in ciprofloxacin (CIP)-resistant P. aeruginosa strains that originated from P. aeruginosa ATCC 27853 and had minimum inhibitory concentrations (MICs) that were 16-, 64-, and 128-fold (PA-R16CIP, PA-R64CIP, and PA-R128CIP, respectively) higher than the original value, compared to CIP-sensitive P. aeruginosa (PA-S). Upregulation of fatty acid biosynthesis forms a characteristic feature of the CIP-resistant metabolomes and fatty acid metabolome, which was supported by elevated gene expression and enzymatic activity in the metabolic pathway. The fatty acid synthase inhibitor triclosan potentiates CIP to kill PA-R128CIP and clinically multidrug-resistant P. aeruginosa strains. The potentiated killing was companied with reduced gene expression and enzymatic activity and the returned abundance of fatty acids in the metabolic pathway. Consistently, membrane permeability was reduced in the PA-R and clinically multidrug-resistant P. aeruginosa strains, which were reverted by triclosan. Triclosan also stimulated the uptake of CIP. These findings highlight the importance of the elevated biosynthesis of fatty acids in the CIP resistance of P. aeruginosa and provide a target pathway for combating CIP-resistant P. aeruginosa.