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Epidemiological studies report an elevated risk of Parkinson's disease (PD) in patients with type 2 diabetes mellitus (T2DM) that is mitigated in those prescribed dipeptidyl peptidase 4 (DPP-4) inhibitors. With an objective to characterize clinically translatable doses of DPP-4 inhibitors (gliptins) in a well-characterized PD rodent model, sitagliptin, PF-00734,200 or vehicle were orally administered to rats initiated either 7-days before or 7-days after unilateral medial forebrain bundle 6-hydroxydopamine (6-OHDA) lesioning. Measures of dopaminergic cell viability, dopamine content, neuroinflammation and neurogenesis were evaluated thereafter in ipsi- and contralateral brain. Plasma and brain incretin and DPP-4 activity levels were quantified. Furthermore, brain incretin receptor levels were age-dependently evaluated in rodents, in 6-OHDA challenged animals and human subjects with/without PD. Cellular studies evaluated neurotrophic/neuroprotective actions of combined incretin administration. Pre-treatment with oral sitagliptin or PF-00734,200 reduced methamphetamine (meth)-induced rotation post-lesioning and dopaminergic degeneration in lesioned substantia nigra pars compacta (SNc) and striatum. Direct intracerebroventricular gliptin administration lacked neuroprotective actions, indicating that systemic incretin-mediated mechanisms underpin gliptin-induced favorable brain effects. Post-treatment with a threefold higher oral gliptin dose, likewise, mitigated meth-induced rotation, dopaminergic neurodegeneration and neuroinflammation, and augmented neurogenesis. These gliptin-induced actions associated with 70–80% plasma and 20–30% brain DPP-4 inhibition, and elevated plasma and brain incretin levels. Brain incretin receptor protein levels were age-dependently maintained in rodents, preserved in rats challenged with 6-OHDA, and in humans with PD. Combined GLP-1 and GIP receptor activation in neuronal cultures resulted in neurotrophic/neuroprotective actions superior to single agonists alone. In conclusion, these studies support further evaluation of the repurposing of clinically approved gliptins as a treatment strategy for PD.

The utilization of structure distortion to modulate the electronic structure and alter catalytic properties of metallic nanomaterials is a well-established practice, but accurately identifying and comprehensively understanding these distortions present significant challenges. Ligand-stabilized metal nanoclusters with well-defined structures serve as exemplary model systems to illustrate the structure chemistry of nanomaterials, among which few studies have investigated nanocluster models that incorporate structural distortions. In this work, a novel copper hydride nanocluster, Cu42(PPh3)8(RS)4(CF3COO)10(CH3O)4H10(Cu42; PPh3is triphenylphosphine and RSH is 2,4-dichlorophenylthiol), with a highly twisted structure has been synthesized in a simple way. Structural analysis reveals Cu42comprises two Cu25units that are conjoined in a nearly orthogonal manner. The dramatic distortion in the metal framework, which is driven by multiple interactions from the surface ligands, endows the cluster with a rich array of uncoordinated metal sites on the surface. The resulting cluster, as envisioned, exhibits remarkable activity in catalyzing carbonylation of anilines. The findings from this study not only provides atomically precise insights into the structural distortions that are pertinent to nanoparticle catalysts but also underscores the potential of structurally distorted NCs as a burgeoning generation of catalysts with precise structures and outstanding performances that can be tailored for specific functions.

Transbronchial needle aspiration (TBNA) is a commonly used sampling approach in the diagnosis of hilar and mediastinal lymphadenopathy as well as peripheral lesions. As a very important tool, the continued innovation of TBNA needles is a vital driving force for the development of the technique. Although TBNA plays an important role in interventional pulmonology, there are no clear standards guiding operators to choose an appropriate needle for their operation. In recent decades, with the advent of endobronchial ultrasound-guided TBNA (EBUS-TBNA), the real-time visualization of TBNA has been enabled. These modern TBNA needles, such as ViziShot2, FLEX 19G, Acquire FNB, and EchoTip ProCore, have made significant progress in specimen collection, convenience, and safety, though still remain grounded in the basic premise and initial upgrades to the original conventional TBNA (cTBNA) needles. This review introduced the developmental history of WANG cTBNA needles, and summarized the lessons of success and failure and the enlightenments for currently used EBUS- and other emerging TBNA needles, aiming to provide a significant reference for pulmonologists who lived through the cTBNA era and for junior physicians who start working in the EBUS-TBNA era. Despite its long history, TBNA is still playing significant roles in the diagnosis of pulmonary diseases. A deeper understanding from the historical perspectives would facilitate continued innovations in the field of TBNA and beyond.

The retinoic acid receptor-related orphan receptor γ (RORγ) is regarded as an attractive therapeutic target for the treatment of prostate cancer. Herein, we report the identification, optimization, and evaluation of 1,2,3,4-tetrahydroquinoline derivatives as novel RORγ inverse agonists, starting from high throughput screening using a thermal stability shift assay (TSA). The representative compounds 13e(designated as XY039) and 14a(designated as XY077) effectively inhibited the RORγ transcriptional activity and exhibited excellent selectivity against other nuclear receptor subtypes. The structural basis for their inhibitory potency was elucidated through the crystallographic study of RORγ LBD complex with 13e. Both 13eand 14ademonstrated reasonable antiproliferative activity, potently inhibited colony formation and the expression of AR, AR regulated genes, and other oncogene in AR positive prostate cancer cell lines. Moreover, 13eand 14aeffectively suppressed tumor growth in a 22Rv1 xenograft tumor model in mice. This work provides new and valuable lead compounds for further development of drugs against prostate cancer.

To improve the sensing performance, the GaN-based metal oxide semiconductor (MOS)-high-electron mobility transistor (HEMT) biosensor with graded AlGaN barrier was proposed and investigated by Silvaco TCAD. The simulation results indicate that the proposed device exhibits higher sensitivity than that with the conventional AlGaN barrier. Furthermore, the impact of graded AlGaN barrier layer thickness (15–30 nm) and maximum Al mole fraction (0.1–0.25) was investigated systematically to optimize sensing sensitivity. It is demonstrated that the sensitivity of MOS-HEMT biosensors can be enhanced by decreasing the thickness or increasing the maximum Al mole fraction of graded barrier layer. This can be mainly attributed to the variation in carrier concentration and energy band structure in the MOS-HEMT heterostructure. In addition, the effect of biomolecule filling rate in the cavity on device performance was also studied. It is found that the sensitivity increases with the biomolecule filling rate. In the ideal state of 100% biomolecule filling rate, the sensing currents of MOS-HEMT biosensor reached 72.8, 154.9, 238.6, 351.8, and 399.3 mA/mm for uricase, streptavidin, biotin, ChOx, and APTES biomolecules, respectively, which are superior than previous reported MOS-HEMT biosensors. This work provides fundamental support for the development of highly sensitive GaN-based MOS-HEMT biosensors.

The coplanar symmetric small molecules-assisted CsPbI3crystallization enables the achievement of high-quality perovskite films, which can modulate energy bands and facilitate efficient carrier extraction, resulting in an impressive efficiency of 39.90% under LED@2968 K (1062 lux).

The epigenetic target CREB (cyclic-AMP responsive element binding protein) binding protein (CBP) and its homologue p300 were promising therapeutic targets for the treatment of acute myeloid leukemia (AML). Herein, we report the design, synthesis, and evaluation of a class of CBP/p300 PROTAC degraders based on our previously reported highly potent and selective CBP/p300 inhibitor 5. Among the compounds synthesized, 11c(XYD129) demonstrated high potency and formed a ternary complex between CBP/p300 and CRBN (AlphaScreen). The compound effectively degraded CBP/p300 proteins and exhibited greater inhibition of growth in acute leukemia cell lines compared to its parent compound 5. Furthermore, 11cdemonstrated significant inhibition of tumor growth in a MOLM-16 xenograft model (TGI = 60%) at tolerated dose schedules. Our findings suggest that 11cis a promising lead compound for the treatment of AML.

The origin and development of agriculture and its relationship with climate change are hotly debated topics among environmental archaeologists. In this study, we analyzed wood charcoal materials from the Neolithic Xinglong site in northern China in order to understand the woody vegetation around the site and how early millet farmers shaped local woodlands. Our results suggest that the area around the Xinglong sites during 8700–7000 yr BP was primarily woodlands, including Prunus sibiricashrubs, Ulmusand Acerforests, and Populusstands near waterways. From 8000 to 7000 yr BP, the warm and humid climate probably contributed to the expansion of Acer, Rhamnus, and Juniperus, and may have facilitated the development of early millet agriculture. Among these ancient wood fragments that we studied, the high percent of Prunuscharcoal appears to indicate an abundance of fruit trees, which might have constituted the main component of local vegetation. Meanwhile, the wood taxa illustrate the existence of a variety of ecological habitats, and it is logical to assume that people made full use of the locally available wood resources. Notably, Populusand Ulmuswere the dominant sources of fuel. The results of tree-ring curvature analyses indicate that people mainly collected trunks or large branches of Ulmus, Populus, Acer, and Juniperustimbers. We interpret the increasing use of Prunustwigs and the declining percentage of Prunuscharcoal in the period between 8000–7000 yr BP as indicating that people started to protect and manage wild fruit trees. They may have started pruning to acquire more food resources as part of the cultural responses and adaptation strategies employed by these early millet cultivators.

•Inhibition of glutamine metabolism with CB-839 normalizes hematologic and metabolic alterations in MPN.•Inhibition by CB-839 preferentially targets JAK2-V617F expressing hematopoietic stem cells.

The transcriptional coactivator cAMP response element binding protein (CREB)-binding protein (CBP) and its homologue p300 have emerged as attractive therapeutic targets for human cancers such as acute myeloid leukemia (AML). Herein, we report the design, synthesis, and biological evaluation of a series of cereblon (CRBN)-recruiting CBP/p300 proteolysis targeting chimeras (PROTACs) based on the inhibitor CCS1477. The representative compounds 14g(XYD190) and 14h(XYD198) potently inhibited the growth of AML cells with low nanomolar IC50values and effectively degraded CBP and p300 proteins in a concentration- and time-dependent manner. Mechanistic studies confirmed that 14gand 14hcan selectively bind to CBP/p300 bromodomains and induce CBP and p300 degradation in bromodomain family proteins in a CRBN- and proteasome-dependent manner. 14gand 14hdisplayed remarkable antitumor efficacy in the MV4;11 xenograft model (TGI = 88% and 93%, respectively). Our findings demonstrated that 14gand 14hare useful lead compounds and deserve further optimization and activity evaluation for the treatment of human cancers.

Three-dimensional (3D)-printed biodegradable polymer scaffolds are at the forefront of personalized constructs for bone tissue engineering. However, it remains challenging to create a biological microenvironment for bone growth. Herein, we developed a novel yet feasible approach to facilitate biomimetic mineralization via self-adaptive nanotopography, which overcomes difficulties in the surface biofunctionalization of 3D-printed polycaprolactone (PCL) scaffolds. The building blocks of self-adaptive nanotopography were PCL lamellae that formed on the 3D-printed PCL scaffold via surface-directed epitaxial crystallization and acted as a linker to nucleate and generate hydroxyapatite crystals. Accordingly, a uniform and robust mineralized layer was immobilized throughout the scaffolds, which strongly bound to the strands and had no effect on the mechanical properties of the scaffolds. In vitrocell culture experiments revealed that the resulting scaffold was biocompatible and enhanced the proliferation and osteogenic differentiation of mouse embryolous osteoblast cells. Furthermore, we demonstrated that the resulting scaffold showed a strong capability to accelerate in vivobone regeneration using a rabbit bone defect model. This study provides valuable opportunities to enhance the application of 3D-printed scaffolds in bone repair, paving the way for translation to other orthopedic implants.

Several recent studies have demonstrated the great promise of ligand-protected atomically precise copper nanoclusters in driving various chemical transformation processes. The insights into key factors in controlling the catalytic performance of copper clusters at the molecular level are highly desirable but difficult to gain. Herein, we report the synthesis and comprehensive characterization of two novel Cu20nanoclusters, with the molecular formulae of Se@Cu20(PhSe)12(PPh3)2(C6H5COO)6(Cu20-1) and Se@Cu20(PhSe)12(PPh3)2(CF3COO)6(Cu20-2), which are proved to be great candidates in clarifying the structure and property relationship in catalysis. As revealed by single-crystal X-ray analysis, the two Cu20structures share an identical metal skeleton and similar ligand distributions with the only difference being in the carboxylate ligands on the surface: C6H5COO for Cu20-1 while CF3COO for Cu20-2. Surprisingly, such small distinctions in the structure cause a 16-fold catalytic activity leap in the catalytic reduction of 4-nitrophenol to 4-aminophenol. The electronic structures of the resulting clusters are distinct, which accounts for their distinct catalytic performances. This work not only provides a model system to highlight the importance of the carboxylate structures on controlling the catalysis of copper clusters but, more importantly, is also expected to simulate research attention on carboxylate engineering to modulate physicochemical properties of carboxylate-functionalized copper metal nanoclusters beyond catalysis.

Federated learning has shown its unique advantages in many different tasks, including brain image analysis. It provides a new way to train deep learning models while protecting the privacy of medical image data from multiple sites. However, previous studies suggest that domain shift across different sites may influence the performance of federated models. As a solution, we propose a gradient matching federated domain adaptation (GM-FedDA) method for brain image classification, aiming to reduce domain discrepancy with the assistance of a public image dataset and train robust local federated models for target sites. It mainly includes two stages: 1) pretraining stage; we propose a one-common-source adversarial domain adaptation (OCS-ADA) strategy, i.e., adopting ADA with gradient matching loss to pretrain encoders for reducing domain shift at each target site (private data) with the assistance of a common source domain (public data) and 2) fine-tuning stage; we develop a gradient matching federated (GM-Fed) fine-tuning method for updating local federated models pretrained with the OCS-ADA strategy, i.e., pushing the optimization direction of a local federated model toward its specific local minimum by minimizing gradient matching loss between sites. Using fully connected networks as local models, we validate our method with the diagnostic classification tasks of schizophrenia and major depressive disorder based on multisite resting-state functional MRI (fMRI), respectively. Results show that the proposed GM-FedDA method outperforms other commonly used methods, suggesting the potential of our method in brain imaging analysis and other fields, which need to utilize multisite data while preserving data privacy.

Infrared small target detection (IRSTD) has made remarkable achievements in recent years. However, the core focus of current works lies on the philosophy of “increasing network complexity,” which leaves the crucial strategies behind performance improvement unclear. To handle this, we highlight two strategies of IRSTD: 1) multireceptive field perception and 2) effective feature fusion. Focusing on these strategies, we propose a multireceptive field perception and effective feature fusion network, named MRF3Net. Specifically, for multireceptive field perception, we devise a multiple perception encoder (MPE). For effective feature fusion, we devise a feature fusion encoder (FFE) and a feature fusion decoder (FFD). The former improves the encoding efficiency by reducing the interference information and preserving target details, and the latter fuses the target information of low-level and high-level features while eliminating noise. Experiments demonstrate that MRF3Net achieves state-of-the-art performance on popular public datasets while maintaining a fast inference speed of approximately 0.011 s/frame on a single NVIDIA GeForce 3070Ti GPU and 0.049 s/frame on the NVIDIA Jetson Orin. Notably, it significantly reduces parameter costs compared with the previous state-of-the-art approaches, validating its efficiency. Moreover, our MPE, FFE, and FFD have proved to be effective in enhancing other IRSTD approaches. Our code will be made available at: https://github.com/Temperature-ai/MRF3Net.

Wheel alignment plays an important role in industrial inspection for vehicle safety. A laser-line-family-orientated method is proposed to achieve the global registration for the shoulder-to-shoulder (SS) and face-to-back (FB) camera group of the alignment measurement system and to flexibly and accurately solve the on-site convenient registration problem in the large-scale measurement. Moreover, the global and absolute references determination model is built to achieve the 1-D-target all-wheel-alignment measurement, in the light of the laser-line-family-orientated model. Furthermore, the global registration and 1-D-target all-wheel-alignment method are experimentally verified on the basis of the global and absolute and physical benchmark by the global and absolute measurement error. The measurement repeatability error of the 1-D-target all-wheel alignment of vehicle is also experimentally performed, due to the unknown real values of vehicle-wheel-alignment parameters and the virtual axes defining the parameters. The experiments indicate the accuracy, availability, and practicability of the wheel alignment method.

Early screening is essential for effective intervention and treatment of individuals with mental disorders. Functional magnetic resonance imaging (fMRI) is a noninvasive tool for depicting neural activity and has demonstrated strong potential as a technique for identifying mental disorders. Due to the difficulty in data collection and diagnosis, imaging data from patients are rare at a single site, whereas abundant healthy control data are available from public datasets. However, joint use of these data from multiple sites for classification model training is hindered by cross-domain distribution discrepancy and diverse label spaces. Herein, we propose few-shot domain-adaptive anomaly detection (FAAD) to achieve cross-site anomaly detection of brain images based on only a few labeled samples. We introduce domain adaptation to mitigate cross-domain distribution discrepancy and jointly align the general and conditional feature distributions of imaging data across multiple sites. We utilize fMRI data of healthy subjects in the Human Connectome Project (HCP) as the source domain and fMRI images from six independent sites, including patients with mental disorders and demographically matched healthy controls, as target domains. Experiments showed the superiority of the proposed method compared with binary classification, traditional anomaly detection methods, and several recognized domain adaptation methods.

This study proposes and solves a matching mechanism called Bilateral Equitable and Stable Matching (BESM) that is used to match agents on two sides and ensures not only stable matching results but also more equitable ones. Equity is measured in terms of modified egalitarian cost, side equality cost, and pair equality cost. BESM is then applied to a general two-sided crowdshipping market with a different number of agents on both sides as well as incomplete preference list by any agent. BESM is shown to generate stable and more equitable matching solutions than those in the literature. The resulting benefits are close to the solutions attained by system optimum models.

Many piezoelectric energy harvesters can harvest single direction vibration effectively. However, practical ambient vibration may be multidirectional. To capture multidirectional vibration, this paper proposes a rope-driven piezoelectric energy harvester (RPEH). The RPEH consists of two piezoelectric cantilevers, which are coupled through a non-extensible rope and a proof mass. Dynamical responses and energy harvesting performance of the RPEH under multidirectional vibrations is investigated in the experiment. It is observed that multidirectional vibrations will cause the motion of the proof mass, and then the proof mass drives the two piezoelectric cantilevers to vibrate through the rope. Compared to the linear piezoelectric cantilever, experimental results show operation bandwidth of the proposed harvester is improved by 140%, 40% and 140% in three directions (x-direction, y-direction or z-direction), respectively.

Brain biometrics, due to its unique confidentiality and concealment, has received the increasing attention of scientific researchers in recent years. It has shown that steady-state visual evoked potential (SSVEP) signals with a high signal-to-noise ratio and stable spectrum can be used as identification features. However, current studies rely on the extraction of features characterizing the activity of single brain regions, ignoring the functional coupling between different brain regions. In this study, we proposed a novel approach that considers the functional connectivity of SSVEP signals collected by different electrodes as practical biometric features. We investigated individual coherence (COH) connectivity and phase synchronization according to different visual stimulations in terms of frequency component analysis of different principal bands. Fifteen subjects were identified by the support vector machine, random forest, and $k$ -nearest neighbor algorithm. The results show that distinctive features in SSVEP functional networks among individuals can achieve high precision identification (up to 98%). The obtained identification performance shows that SSVEP spectral COH and phase synchronization have the potential for biometric applications.

Previous studies have explored the use of deep neural networks for electroencephalography (EEG)-based motor imagery (MI) recognition, but most of the models focus on the recognition performance achieved for a single subject and are challenging to transfer due to individual differences and low signal-to-noise-ratio of EEG signals. To date, few studies have paid attention to the balance between generalizability and personalization across subjects. To this end, we propose a co-teaching graph learning method for cross-subject EEG-based MI recognition. First, A novel graph learning approach is designed to improve feature extraction from a typical graph structure containing raw EEG signals. Second, two graph learning models are constructed to filter noisy data by using a co-teaching training strategy, preventing overfitting on noisy samples obtained from different subjects. The proposed model shows a 5.4% and 3.2% increase in accuracy of single- and multisubject four-class MI recognition tasks compared to the previous best method, respectively. Experimental results also demonstrate that it is easy to derive a model that can represent generic knowledge of multiple MI subjects and can be fine-tuned efficiently for new subjects.

Weakly Supervised Object Detection (WSOD) is of increasing importance in the community of computer vision as its extensive applications and low manual cost. Most of the advanced WSOD approaches build upon an indefinite and quality-agnostic framework, leading to unstable and incomplete object detectors. This paper attributes these issues to the process of inconsistent learning for object variations and the unawareness of localization quality and constructs a novel end-to-end Invariant and Equivariant Network (IENet). It is implemented with a flexible multi-branch online refinement, to be naturally more comprehensive-perceptive against various objects. Specifically, IENet first performs label propagation from the predicted instances to their transformed ones in a progressive manner, achieving affine-invariant learning. Meanwhile, IENet also naturally utilizes rotation-equivariant learning as a pretext task and derives an instance-level rotation-equivariant branch to be aware of the localization quality. With affine-invariance learning and rotation-equivariant learning, IENet urges consistent and holistic feature learning for WSOD without additional annotations. On the challenging datasets of both natural scenes and aerial scenes, we substantially boost WSOD to new state-of-the-art performance. The codes have been released at: https://github.com/XiaoxFeng/IENet.

Most ligand-stabilized metal nanoclusters feature a core–shell or polyhedron-derived metal framework, in which the metal active sites would be blocked by either metal–ligand interfacial shells or surface passive units. We report, in this work, a strategy of largely exposing metal sites and thus promoting catalysis via constructing metal nanoclusters with array-based geometry. Exampled here are a pair of Cu8clusters with polyhedron-derived ([Cu8(RS)6(PPh3)4(MeCN)4H]+, where RS is 3,5-bis(trifluoromethyl)benzenethiol) and array-based ([Cu8(Tf-dpf)4(NO3)2](NO3)2, Tf-dpf is N,N′-di(5-trifluoromethyl-2-pyridyl) formamidinate) structure, respectively. In sharp contrast to the cubic Cu8cluster whose metal core has been totally covered by ligands, the array-based analogue displays largely uncoordinated metal sites. As a result, the array-based Cu8cluster exhibits significantly enhanced activity in catalytic hydrogenation reactions in comparison to the cubic one. In addition, the array-based Cu8cluster shows excellent catalytic performance in the “aldehyde–acetylene–amine” A3-coupling reaction for the synthesis of propargylamines. The reaction can be converted almost perfectly with a rather low amount of cluster, which further reflects its potential catalytic application.

Copper nanostructures represent an important class of materials in CO2electrocatalytic reduction (CO2ER) reactions, but deciphering their molecular structures, especially those with multiple and irregular organic–inorganic interfaces, remains a grand challenge. Through comprehensive characterization of a 26-nuclei copper nanocluster of [Cu26(DPPE)3(CF3CO2)8(CH3O)2(tBuC≡C)4H11]+(DPPE is 1,2-bis(diphenylphosphino)ethane), which is stabilized by quintuple ligand shells of phosphine, carboxylic acid, alcohol, alkynyl, and hydride, we demonstrate in this work the efficiency of hybrid ligands in controlling geometrical arrangements, electronic structures, and catalytic performance of copper nanoclusters. The diverse ligands in the cluster endow it with a peculiar geometric structure and distinct electronic structure and, more importantly, a delicate surface structure. As a result, the cluster displays high performance in CO2ER to CO reaction.

ABSTRACTIntroductionLung cancer is one of the cancer types with the highest mortality rate, exploring a more effective treatment modality that improves therapeutic efficacy while mitigating side effects is now an urgent requirement. Designing multifunctional nanoparticles can be used to overcome the limitations of drugs and conventional drug delivery systems. Nanotechnology has been widely researched, and through different needs, suitable nanocarriers can be selected to load anti-cancer drugs to improve the therapeutic effect. It is foreseeable that with the rapid development of nanotechnology, more and more lung cancer patients will benefit from nanotechnology. This paper reviews the merits of various multifunctional nanoparticles in the treatment of lung cancer to provide novel ideas for lung cancer treatment.Areas coveredThis review focuses on summarizing various nanoparticles for targeted lung cancer therapy and their advantages and disadvantages, using nanoparticles loaded with anti-cancer drugs, delivered to lung cancer sites, enhancing drug half-life, improving anti-cancer drug efficacy and reducing side effects.Expert opinionThe delivery mode of nanoparticles with superior pharmacokinetic properties in the in vivo circulation enhances the half-life of the drug, and provides tissue-targeted selectivity and the ability to overcome biological barriers, bringing a revolution in the field of oncology.

Aneuploidies—whole-chromosome or whole-arm imbalances—are the most prevalent alteration in cancer genomes1,2. However, it is still debated whether their prevalence is due to selection or ease of generation as passenger events1,2. Here we developed a method, BISCUT, that identifies loci subject to fitness advantages or disadvantages by interrogating length distributions of telomere- or centromere-bounded copy-number events. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage specific. BISCUT identified the helicase-encoding gene WRNas a haploinsufficient tumour-suppressor gene on chromosome 8p, which is supported by several lines of evidence. We also formally quantified the role of selection and mechanical biases in driving aneuploidy, finding that rates of arm-level copy-number alterations are most highly correlated with their effects on cellular fitness1,2. These results provide insight into the driving forces behind aneuploidy and its contribution to tumorigenesis.

Nanofiltration (NF) technology has been widely used in saline wastewater treatment due to its unique separation mechanism. However, the NF membrane, as the core of the nanofiltration technology, is restricted by the trade-off between permeability and selectivity, which greatly restricts the development of NF membranes. The interlamellar arrangement of 2D boron nitride nanosheets (BNNSs) can provide additional transport channels and selectivity, as well as strong adsorption capacity due to its high specific surface area, exhibiting significant potential for advanced membranes. In this work, BNNSs prepared by tannic acid (TA)-assisted exfoliation (TA@BNNSs) were successfully adopted to fabricate thin-film nanocomposite (TFN) membranes via interfacial polymerization (IP). The resultant TFN membranes’ structure and properties were systematically characterized via various methods. The results demonstrated that the surface morphology of polyamide membranes evolved gradually from a nodular structure to a reticular topography, accompanied by the decrease of the thickness of the polyamide selective layer when incorporating TA@BNNSs into the membranes. This phenomenon can be mainly ascribed to that the uptake density and diffusion of piperazine (PIP) monomer were effectively regulated by BNNSs. This is validated by molecular dynamics and revealed by the adsorption of PIP in BN models, the diffusion coefficients, and interaction energies, respectively. In addition, the TFN membranes demonstrated improved permeance and stable solute rejection for the inorganic salts. Specifically, the water flux of PA-TA@BNNSs-10%/PMIA membrane could reach up to 109.1 ± 2.49 L·m–2·h–1while keeping a high rejection of 97.5 ± 0.38% to Na2SO4, which was superior to most of the reported membranes in the literature. Besides, the PA-TA@BNNSs-10%/PMIA membrane exhibited an excellent stability in the long-term filtration process. The finding in this work provides a potential strategy for developing the next-generation 2D material-based membranes with high-performance for separation applications.

Abnormal osteoclast and osteoblast differentiation is an essential pathological process in osteoporosis. As an important deubiquitinase enzyme, ubiquitin-specific peptidase 7 (USP7) participates in various disease processes through posttranslational modification. However, the mechanism by which USP7 regulates osteoporosis remains unknown. Herein, we aimed to investigate whether USP7 regulates abnormal osteoclast differentiation in osteoporosis.

ABSTRACT Self-consolidating concrete (SCC) is used nowadays in many of concrete construction projects. It has superior characteristics such as a low yield and considerable viscosity. In addition, it does not [...]

Acute hepatopancreatic necrosis disease (AHPND) is one of the most devastating diseases in aquaculture, causing significant economic losses in seafood supplies worldwide. Early detection is critical for its prevention, which requires reliable and fast-responding diagnosis tools with point-of-care testing (POCT) capacity. Recombinase polymerase amplification (RPA) has been combined with CRISPR/Cas12a for AHPND diagnosis with a two-step procedure, but the operation is inconvenient and has the risk of carryover contamination. Here, we develop an RPA-CRISPR one-pot assay that integrates RPA and CRISPR/Cas12a cleavage into simultaneous reactions. Using the special design of crRNA, which is based on suboptimal protospacer adjacent motifs (PAM), RPA and Cas12a are made compatible in one pot. The assay is highly specific with a good sensitivity of 102copies/reaction. This study provides a new choice for AHPND diagnosis with a POCT facility and sets a good example for developing RPA-CRISPR one-pot molecular diagnosis assays.

Little advance has been made toward developing alternative bottom-up synthetic strategies for N-heterocyclic carbene (NHC)-stabilized gold nanoclusters, although this unique class of nanomaterials has exhibited exciting properties. We report in this work a simple and straightforward approach toward NHC-ligated gold nanoclusters by using imidazolium salts rather than free carbenes or NHC-coordinated gold complexes (NHC–Au-X, X is counterions) as precursors. Illustrated here is a one-pot and one-step preparation of an NHC-stabilized Au13Br4cluster that features a distinct molecular formula, surface motifs, and assembling modes viachemical reduction of dpaAu, NaOMe, and FNHCBn·HBr by NaBH4(Hdpa is dipyridylamine; FNHCBn·HBr is 1,3-dibenzyl-5,6-difluoro-1H-benzo[d]imidazole-3-ium bromide). In situUV–vis and NMR studies have elucidated the base-assisted formation of NHCs from imidazolium salts for the protection of the metal core. This work not only reports a new NHC-ligated superatom that completes the Au13library, thus facilitating structure–property studies, but also opens the door to explore underlying analogues in a facile and reasonable way.

Osimertinib, the third generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), is the standard treatment for nonsmall cell lung cancer with EGFR mutation. However, osimertinib-induced interstitial lung disease (OsiILD) is considered to be a serious adverse event, so some patients will have to discontinue the use of osimertinib due to OsiILD. Almonertinib is a novel third-generation EGFR-TKI. We herein report a patient who developed OsiILD after the use of osimertinib and then switched to almonertinib for further treatment with success. This is the first report of a successfull rechallenge with low-dose almonertinib after OsiILD. We also reviewed the literature to explore the possible risk factors and the subsequent treatment of OsiILD, suggesting that low-dose almonertinib may be an option for follow-up treatment of OsiILD.

Seed plants overtook ferns to become the dominant plant group during the late Carboniferous, a period in which the climate became colder and dryer1,2. However, the specific innovations driving the success of seed plants are not clear. Here we report that the appearance of suberin lamellae (SL) contributed to the rise of seed plants. We show that the Casparian strip and SL vascular barriers evolved at different times, with the former originating in the most recent common ancestor (MRCA) of vascular plants and the latter in the MRCA of seed plants. Our results further suggest that most of the genes required for suberin formation arose through gene duplication in the MRCA of seed plants. We show that the appearance of the SL in the MRCA of seed plants enhanced drought tolerance through preventing water loss from the stele. We hypothesize that SL provide a decisive selective advantage over ferns in arid environments, resulting in the decline of ferns and the rise of gymnosperms. This study provides insights into the evolutionary success of seed plants and has implications for engineering drought-tolerant crops or fern varieties.

Los inhibidores de puntos de control inmunitarios mejoran enormemente el pronóstico del cáncer; sin embargo, los eventos adversos graves relacionados con el sistema inmunitario pueden causar la muerte de manera prematura. Las recomendaciones actuales para el tratamiento de neumonitis inducida por inhibidores de puntos de control (CIP) se basan principalmente en terapias inmunosupresoras, y también se requieren agentes antifibróticos, especialmente en pacientes con mala respuesta a los corticosteroides y curso más prolongado de neumonitis. Esto se debe a que los cambios fibróticos tienen un papel importante en la evolución patológica de la CIP. Presentamos un caso que demuestra que el nintedanib es un candidato prometedor para tratar o prevenir la CIP, por su potente efecto antifibrótico y su perfil de seguridad. Por otra parte, el nintedanib podría inhibir parcialmente el crecimiento tumoral en pacientes con cáncer de pulmón no-microcítico, y su eficacia puede mejorar aún más si se le combina con otras terapias antitumorales.

Training neural network classifiers (NNCs) usually requires all instances to be correctly labeled, which is difficult and/or expensive to satisfy in some practical applications. When label noise is present, mislabeled data will severely mislead the training of NNCs, resulting in poor generalization performance. In this work, we address the label noise issue by removing mislabeled instances from the training data. A COnsistence-based Mislabeled Instances REmoval (COMIRE) method is proposed. The main idea is based on the observation that during the training of the NNC, the training loss and the model’s prediction uncertainty of correctly labeled instances show similar trends, while those of mislabeled instances have quite different trends. Thus, the consistency between the two trends can be used to distinguish correctly labeled instances from mislabeled ones. On this basis, an iteration scheme is introduced to further increase the separability between the two types of data. Experimental results show that COMIRE can effectively identify the mislabeled instances. Moreover, the classification performance is significantly improved after removing the identified instances from the noisy training data.

In this study, Gonskikh et al. demonstrate how a noncatalytic cleft and rRNA binding-dependent phase separation are essential for the proper localization and function of DIMT1, an 18SrRNA methyltransferase involved in ribosome biogenesis. They further discuss the relevance of this finding to cell proliferation in AML.

Silver paste accounts for a substantial portion of the nonsilicon cost of tunnel oxide polysilicon contact solar cells. Silver consumption is as well a major concern for material sustainability of global PV manufacturing. It is necessary to propose innovative grid line designs to reduce the amount of silver paste. Partially interrupting the metal fingers (also known as “Finger Break”) between the bus bars in areas where the fingers carry a relatively small current is a good method for reducing silver consumption in industrial production. Under the assumption of uniform generated current density (ISO-current), this article discusses the impact of the width of finger interruption on the cell efficiency under two different scenarios. Through simulations, experiments, and outdoor testing, it was found that one of the considered novel grid designs can save silver paste to a great extent, but suffers a rapid decline in power conversion efficiency, and also poses potential stability risks, while the other grid design not only saves silver, it does not severely affect the efficiency, and can be used outdoors while maintaining stability. Based on the different light intensities, the finger interruption width can be as high as 5 mm, resulting in a saving of 9.32 mg (∼1.61 mg/W) of silver paste on the front surface of 158.75 cm×158.75 cm solar cell, for a reduction of 12.97% of the original front silver consumption.

In this article, we study how to resist malware attacks in cyber-physical power systems (CPPSs) through cyber protection. A model that incorporates the power flow analysis, the cyber monitoring and control, and the factor of cyber protection is proposed to simulate malware attacks in CPPSs. Meanwhile, an evaluation method is also developed to estimate the effectiveness of different cyber protection strategies. Through simulations, we conduct case studies in a test CPPS generated by coupling the IEEE 118 Bus System with a scale-free communication network. The protection effects of three heuristic cyber protection strategies, namely, target protection, random protection, and acquaintance protection are compared and analyzed. Simulation results reveal that compared with the other two strategies, target protection can suppress malware propagation and resist malware attacks more effectively. Moreover, we also investigate the optimal cyber protection problem in CPPSs and formulate it as a zero-one integer programming problem. We solve the problem by genetic algorithm and find that some low-degree cyber nodes also play a significant role in resisting malware attacks in CPPSs, especially when the protection budget is tight.

Nitrification, the stepwise oxidation of ammonia to nitrate via nitrite, is a key process in the marine nitrogen cycle. Reported nitrite oxidation rates frequently exceed ammonia oxidation rates below the euphotic zone, raising the fundamental question of whether the two steps are balanced and if alternative sources contribute to nitrite production in the dark ocean. Here we present vertically resolved profiles of ammonia, urea, and nitrite oxidation rates and their kinetic traits in the oligotrophic Subtropical North Pacific. Our results show active urea‐derived nitrogen oxidation (urea‐N oxidation) in the presence of experimental ammonium amendment, suggesting direct urea utilization. The depth‐integrated rates of urea‐N oxidation and ammonia oxidation are comparable, demonstrating that urea‐N oxidation is a significant source of nitrite. The additional nitrite from urea‐N oxidation helps to balance the two steps of nitrification in our study region. Nitrifiers exhibit high affinity for their substrates, and the apparent half‐saturation constants for ammonia and nitrite oxidation decrease with depth. The apparent half‐saturation constant for urea‐N oxidation is higher than that for ammonia oxidation and shows no clear vertical trend. Such kinetic traits may account for the relatively higher urea concentration than ammonium concentration in the ocean's interior. Moreover, a compilation of our results and reported data shows a trend of increased urea‐N oxidation relative to ammonia oxidation from the eutrophic coastal zone to the oligotrophic open ocean. This trend reveals a substrate‐dependent biogeographic distribution of urea‐N oxidation across marine environments and provides new information on the balance and flux of the marine nitrification process. Active urea‐derived nitrogen oxidation in the presence of added ammonium suggests direct urea utilization by marine ammonia oxidizersSubstrate affinity regulates the vertical distribution of ammonia, urea, and nitrite in the ocean's interiorNitrite production from urea is comparable to that from ammonia oxidation in the energy‐starved mesopelagic ocean Active urea‐derived nitrogen oxidation in the presence of added ammonium suggests direct urea utilization by marine ammonia oxidizers Substrate affinity regulates the vertical distribution of ammonia, urea, and nitrite in the ocean's interior Nitrite production from urea is comparable to that from ammonia oxidation in the energy‐starved mesopelagic ocean

This study aimed to assess the function of γ-aminobutyric acid (GABA) on growth performance, food intake and glucose homeostasis of Micropterus salmoidesfed carbohydrate (CHO)-enriched diets. The intracerebroventricular glucose + GABA co-injected fish had higher cumulative food intake, and expression of orexigenic genes (ghrelinand neuropeptide y (npy)) in the brain than those of the single glucose-injected group. In the feeding trial, M. salmoides(10.35 ± 0.05 g) were fed four feeds containing a control feed (10 % CHO, C) and three GABA contents [0 (HC), 50 (HC-G1), and 100 (HC-G2) mg kg−1, respectively] of high-CHO feed (20 % CHO) for 12 weeks. High CHO prominently (P< 0.05) decreased WGR, SGR, FI, p-Ampk protein content, and expression of ghrelin, npy, fbpase, pparα, cpt1αand aco1compared with the control group, but the opposite was true for plasma glucose and triglyceride levels, tissue glycogen and lipid contents, and expression of proopiomelanocortin, leptin a, gk, pk, gs, chrebp, srebp1, fasand acc1. HC-G2 diets prominently (P< 0.05) up-regulated WGR, SGR, FI, p-Ampk protein content, and expression of ghrelin, npy, gk, pk, chrebp, srebp1, fasand acc1compared with the HC group. Also, HC-G2 diets increased glucose tolerance of M. salmoidesfed high-CHO diets after glucose loading. Overall, GABA improved the growth performance, food intake and glucose homeostasis of high-CHO-fed fish by the increase of appetite, glycolysis, glycogenesis and lipolysis, as well as the inhibition of gluconeogenesis and lipid synthesis.

This paper is based on the first principles of density functional theory and uses the virtual crystal approximation method to calculate and analyze the optical properties of differently proportioned Eu3+-doped Bismuth silicate (Bi4Si3O12, or BSO). The results show that minor Eu3+doping (1/12–1/3) improves the polarization ability of BSO and reduces energy loss. Additionally, doping an appropriate amount of Eu3+(1/12–1/3) can improve light absorption and transmission of BSO to some extent. That is to say, Eu3+doping improves the response of BSO to infrared light, and the absorption capacity in the ultraviolet and visible light regions is also enhanced. The theoretical research in this paper elucidates the changes in the optical properties of BSO after doping with Eu3+, providing a theoretical basis for expanding its application as a scintillation crystal in high-energy physics experiments, nuclear medicine, and other fields.

Coordination of cellular metabolism is essential for optimal T cell responses. Here, we identify cytosolic acetyl-CoA production as an essential metabolic node for CD8 T cell function in vivo. We show that CD8 T cell responses to infection depend on acetyl-CoA derived from citrate via the enzyme ATP citrate lyase (ACLY). However, ablation of ACLY triggers an alternative, acetate-dependent pathway for acetyl-CoA production mediated by acyl-CoA synthetase short-chain family member 2 (ACSS2). Mechanistically, acetate fuels both the TCA cycle and cytosolic acetyl-CoA production, impacting T cell effector responses, acetate-dependent histone acetylation, and chromatin accessibility at effector gene loci. When ACLY is functional, ACSS2 is not required, suggesting acetate is not an obligate metabolic substrate for CD8 T cell function. However, loss of ACLY renders CD8 T cells dependent on acetate (via ACSS2) to maintain acetyl-CoA production and effector function. Together, ACLY and ACSS2 coordinate cytosolic acetyl-CoA production in CD8 T cells to maintain chromatin accessibility and T cell effector function.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors.

A serous effusion is a buildup of extra fluid in the serous cavities including pleural, peritoneal, and pericardial cavities. It is important to distinguish benign reactive effusions from effusions caused by malignant proliferation in cytopathology since different diagnoses can lead to completely different disease staging and therapeutic choices. The conventional cytopathology procedure has the disadvantages of low throughput and low objectivity. To enhance the efficiency and accuracy of malignant serous effusion diagnosis, in this paper, an imaging flow cytometry, called optofluidic time‐stretch microscopy is first employed, to image the cells in the serous effusion at an event rate of 100 000 events per second and with a spatial resolution better than 1 µm. The acquired cellular images are then analyzed using a convolutional neural network, by which the malignant cells are accurately detected. The performance of the method is validated with 18 clinical samples, including 14 malignant and 4 benign ones. The results show that the method can detect malignant cells at an accuracy of 90.53%. The high throughput, high accuracy, and high convenience of the method make it a potential solution for malignant serous effusion diagnosis in various scenarios. Intelligent imaging flow cytometry to image the cells in the serous effusion at an event rate of 100 000 events per second and with a spatial resolution better than 1 µm. High accuracy and high throughput convolutional neural network in clinical settings to distinguish benign reactive effusions from effusions caused by malignant proliferation.