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High-throughput phenotyping (HTP) technology is now a significant bottleneck in the efficient selection and breeding of superior forage genetic resources. To better understand the status of forage phenotyping research and identify key directions for development, this review summarizes advances in HTP technology for forage phenotypic analysis over the past ten years. This paper reviews the unique aspects and research priorities in forage phenotypic monitoring, highlights key remote sensing platforms, examines the applications of advanced sensing technology for quantifying phenotypic traits, explores artificial intelligence (AI) algorithms in phenotypic data integration and analysis, and assesses recent progress in phenotypic genomics. The practical applications of HTP technology in forage remain constrained by several challenges. These include establishing uniform data collection standards, designing effective algorithms to handle complex genetic and environmental interactions, deepening the cross-exploration of phenomics-genomics, solving the problem of pathological inversion of forage phenotypic growth monitoring models, and developing low-cost forage phenotypic equipment. Resolving these challenges will unlock the full potential of HTP, enabling precise identification of superior forage traits, accelerating the breeding of superior varieties, and ultimately improving forage yield.

Abstract Triple-negative breast cancer (TNBC) is traditionally treated with systemic chemotherapy, often resulting in significant off-target toxicity. In this study, we assess the efficacy of intraductal chemotherapeutic delivery, aimed at reducing systemic side effects. Using an in situ TNBC model, created by intraductal injection of 4T1-luc cells, we identified day 3 post-tumor implantation as an optimal early intervention point. Echocardiographic analysis confirmed that intraductal administration of eribulin (ERI) or doxorubicin (DOX) did not cause cardiac dysfunction or apoptosis. Our results demonstrate that intraductal delivery of ERI and DOX significantly enhances anti-tumor and anti-metastatic effects. Mechanistically, ERI followed by DOX increased intratumoral perfusion, improved drug concentration, reversed epithelial-mesenchymal transition, and inhibited tumor cell invasion and metastasis. Additionally, this approach triggered immunogenic cell death and activated a systemic anti-tumor immune response. These findings underscore the potential of intraductal chemotherapy as a safe, highly effective approach, offering a preclinical foundation for minimally invasive TNBC therapies.

Osteoarthritis (OA) is characterized by inflammation of the synovial joints. However, the drugs used to treat OA are insufficient due to multifactorial pathogenesis of the disease. The present study determined the anti-inflammatory and antioxidant effect of Akebia quinata D. aqueous extract (AQDE) against osteoarthritis using in vitro and in vivo models of OA. Initially, the effect of AQDE was identified to determine its effect on the various biomarkers of the TNF-α mouse chondrocytes. The results suggest that AQDE causes significant ACGAN and COL2 and reduction in IL-1B, IL-6, MMP-13 and PTGS2. It also causes induction of the expression of Bcl2, CDK1, CCND, and reduction in the rate of apoptosis of mouse chondrocytes. In the in vivo rat model, AQDE improved mechanical allodynia in the Von Frey test and reduced knee joint swelling. Micro-CT scanning showed improvement in bone erosion. The level of oxidative stress (MDA, SOD, and GSH) and production of pro-inflammatory cytokines (IL-1B, and IL-6) was restored to near-normal levels in a dose-dependent manner. AQDE reduced the mRNA expression of COX-2 and NF-kb in both in vitro and in vivo study. The results demonstrated the significant pharmacological activity of AQDE against osteoarthritis in both in vitro and in vivo model.

BackgroundLife’s Crucial 9 (LC9) is an emerging cardiovascular health scoring system that incorporates Life’s Essential 8 (LE8) alongside mental health factors. However, its relationship with severe abdominal aortic calcification (SAAC) remains poorly understood.ObjectivesThe objective of this study is to investigate the relationship between LC9 scores and the incidence of SAAC in the US population.MethodsData from 2,323 participants were analyzed, originating from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) cycle. In exploring the dynamics of LC9, its constituents, and their relationship with SAAC, we employed advanced statistical methodologies, specifically multivariable logistic regression and weighted quantile sum regression. Subgroup interaction analyses were conducted to reinforce the conclusions, and mediation analysis was employed to investigate how the systemic inflammatory response index (SIRI) influences the connection between LC9 and SAAC.ResultsIn fully adjusted models, an increase of 10 points in LC9 scores was associated with a 26% reduction in the prevalence of SAAC, achieving statistical significance (P < 0.001). As LC9 scores increased, a significant decline in SAAC prevalence was noted (P < 0.05). The WQS analysis pinpointed strong links between the occurrence of SAAC and variables including exposure to tobacco, blood pressure levels, blood glucose concentrations, and mental health status, the odds ratio stood at 0.244, with the 95% CI extending from 0.119 to 0.495. SIRI was positively correlated with SAAC (P < 0.05) and decreased with rising LC9 scores (β = -0.09, P < 0.001). Mediation analysis revealed that the SIRI significantly influenced the linkage between LC9 and SAAC, accounting for 5.8% of the mediation effect, with a statistically significant p-value (P < 0.001).ConclusionThis research highlights a robust inverse relationship between elevated LC9 scores and reduced SAAC incidence, suggesting the significant role of LC9 as a key factor in diminishing the frequency of SAAC. Furthermore, SIRI mediates this relationship.

We apply the recently developed concept of the nucleon energy–energy correlator (NEEC) for the gluon sector to investigate the long-range azimuthal angular correlations in proton–proton collisions at the Large Hadron Collider. The spinning gluon in these collisions will introduce substantial nonzero [Formula: see text] asymmetries in both Higgs boson and top quark pair productions, where [Formula: see text] is the azimuthal angle between the forward and backward energy correlators in the NEEC observables. The genesis of the [Formula: see text] correlation lies in the intricate quantum entanglement. Owing to the substantial [Formula: see text] effect, the NEEC observable in Higgs boson and [Formula: see text] production emerges as a pivotal avenue for delving into quantum entanglement and scrutinizing the Bell inequality at high-energy colliders.

Abstract Background Case-based learning (CBL) utilizing three-dimensional (3D) printed hip joint models is a problem-solving teaching method that combines the tactile and visual advantages of 3D-printed models with CBL. This study aims to investigate the impact of integrating 3D printing with CBL on learning developmental dysplasia of the hip (DDH). Methods We conducted a prospective study from 2022 to 2023, including 120 fourth-year clinical medical students at Xuzhou Medical University. Students were randomly allocated into two groups of 60 participants each. The CBL group received conventional CBL teaching methods, while the 3D + CBL group utilized 3D-printed models in conjunction with CBL. Post-teaching, we analyzed and compared the theoretical and practical achievements of both groups. A questionnaire was designed to assess the impact of the educational approach on orthopedic surgery learning. Results The theory scores of the CBL group (62.88 ± 7.98) and 3D + CBL group (66.35 ± 8.85) were significantly different (t = 2.254, P = 0.026); the practical skills scores of the CBL group (57.40 ± 8.80) and 3D + CBL group (63.42 ± 11.14) were significantly different (t = 3.283, P = 0.001). The questionnaire results showed that the 3D + CBL group was greater than the CBL group in terms of hip fundamentals, ability to diagnose cases and plan treatments, interesting teaching content, willingness to communicate with the instructor and satisfaction. Conclusions The integration of 3D printing with case-based learning has yielded positive outcomes in teaching DDH, providing valuable insights into the use of 3D-printed orthopedic models in clinical education.

Abstract Sowing date and soil fertility are very important factors in the overwintering and production performance of alfalfa (Medicago sativa L.), yet there’s a knowledge gap in knowledge on how late-seeded alfalfa responds to phosphorus (P) fertilization. A field study was conducted in Inner Mongolia from 2020 to 2022 using a split-plot design. The main plots consisted of five sowing dates (31 July, 8, 16, and 24 August, and 1 September), while the subplots involved five P application rates (0, 40, 70, 100, and 130 kg P2O5 ha−1). Throughout the growing seasons, the overwintering rate, root traits, forage yield, and yield components were measured. The results revealed a consistent decrease in overwintering ability and productivity with the delayed sowing. This reduction in overwintering rate was mainly due to diminished root traits, while the decrease in forage yield was largely associated with a reduction in plants per square meter. However, P fertilizer application to late-seeded alfalfa demonstrated potential in enhancing the diameter of both the crown and taproot, thus strengthening the root system and improving the overwintering rate, the rate of increase ranges from 11.6 to 49%. This adjustment could also improve the shoots per square meter and mass per shoot, increasing by 9.4–31.3% and 15.0–27.1% respectively in 2 years, which can offset the decline in forage yield caused by late sowing and might even increase the forage yield. Regression and path analysis indicated that alfalfa forage yield is primarily affected by mass per shoot rather than shoots per square meter. This study recommended that the sowing of alfalfa in similar regions of Inner Mongolia should not be later than mid-August. Moreover, applying P fertilizer (P2O5) at 70.6–85.9 kg ha−1 can enhance the forage yield and persistence of late-seeded alfalfa. Therefore, appropriate late sowing combined with the application of P fertilizer can be used as an efficient cultivation strategy for alfalfa cultivation after a short-season crop harvest in arid and cold regions.

Abstract Objective In chronic low back pain (CLBP), the relationship between spinal pathologies and paraspinal muscles fat infiltration remains unclear. This study aims to evaluate the relationship between MRI findings and paraspinal muscles morphology and fat infiltration in CLBP patients by quantitative MRI. Methods All the CLBP patients were enrolled from July 2021 to December 2022 in four medical institutions. The cross-sectional area (CSA) and proton density fat fraction (PDFF) of the multifidus (MF) and erector spinae (ES) muscles at the central level of the L4/5 and L5/S1 intervertebral discs were measured. MRI findings included degenerative lumbar spondylolisthesis (DLS), intervertebral disc degeneration (IVDD), facet arthrosis, disc bulge or herniation, and disease duration. The relationship between MRI findings and the paraspinal muscles PDFF and CSA in CLBP patients was analyzed. Results A total of 493 CLBP patients were included in the study (198 females, 295 males), with an average age of 45.68 ± 12.91 years. Our research indicates that the number of MRI findings are correlated with the paraspinal muscles PDFF at the L4/5 level, but is not significant. Moreover, the grading of IVDD is the primary factor influencing the paraspinal muscles PDFF at the L4-S1 level (BES at L4/5=1.845, P

With the increasing social pressure and academic competition, the mental health (for convenience, abbreviated as MH) problems of college students are becoming increasingly prominent, but there are often challenges that are difficult to accurately predict and intervene in a timely manner. The aim of this article is to address the early warning needs of college students’ MH problems and construct a model that can timely identify the MH problems of college students. The experiment collected MH related data from college students in S city, and analyzed and trained these data using the Long short-term memory (LSTM) network model. By changing the number of hidden layers, learning rate, batch size, and epoch times, the most suitable training effect was achieved. By using the time-series characteristics of the LSTM model, the selected parameters from the experiment can better capture the changing trends of college students’ MH status, thereby improving prediction accuracy. Finally, three stage indicators of low, medium, and high were set up for early warning of the predicted results, in order to effectively and timely take measures. The research results indicated that the constructed model achieved a minimum regularization loss of 0.0674 after training. Finally, the adjusted model was used to predict the test set, with an average accuracy of 0.852 and an average accuracy of 0.906. The LSTM-based MH risk model performed well in predicting college students’ MH problems and could identify potential risk factors in a timely manner.

Summary: Inflammation, acinar atrophy, and ductal hyperplasia drive pancreatic remodeling in newborn cystic fibrosis (CF) ferrets lacking a functional cystic fibrosis conductance regulator (CFTR) channel. These changes are associated with a transient phase of glucose intolerance that involves islet destruction and subsequent regeneration near hyperplastic ducts. The phenotypic changes in CF ductal epithelium and their impact on islet function are unknown. Using bulk RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), and assay for transposase-accessible chromatin using sequencing (ATAC-seq) on CF ferret models, we demonstrate that ductal CFTR protein constrains PDX1 expression by maintaining PTEN and GSK3β activation. In the absence of CFTR protein, centroacinar cells adopted a bipotent progenitor-like state associated with enhanced WNT/β-Catenin, transforming growth factor β (TGF-β), and AKT signaling. We show that the level of CFTR protein, not its channel function, regulates PDX1 expression. Thus, this study has discovered a cell-autonomous CFTR-dependent mechanism by which CFTR mutations that produced little to no protein could impact pancreatic exocrine/endocrine remodeling in people with CF.

Abstract Nervous system diseases are among the most common diseases globally, posing a severe threat to patients' quality of life and placing a considerable burden on families and society. With improvements in miniaturization, intelligence, and the safety of biosensors, the combination of machinery and organisms is becoming increasingly common. In neuroscience research, biosensors of different macroscopic dimensions have been uniquely utilized to harness their relevant properties. One‐dimensional (1D) biosensors can achieve in situ real‐time monitoring of neural markers at the subcellular, single‐cell, ex vivo, and in vivo levels, with reduced impacts on organisms. Two‐dimensional (2D) biosensors can monitor the chemical behavior of cells and the neural activity of living animals. They are helpful for objectively identifying the characteristics of cells in response to external stimuli and studying the neural circuits of living animals. Three‐dimensional (3D) biosensors have shown unique advantages in point‐of‐care testing, liquid biopsy, drug screening, and mechanistic research. In clinical practice, brain‐computer interfaces (BCIs) and wearable devices have become important tools for monitoring and treatment. To date, there has been widespread adoption of BCIs in clinical practice. BCIs not only exhibit good efficacy in severe neurological and mental diseases but also provide a method for early diagnosis and treatment of these diseases. Wearable sensor devices can accurately assess the symptoms of movement disorders and play an active role in rehabilitation and treatment. In this review, we summarize the application of advanced biosensors in neuroscience research and clinical practice. The challenges and prospects of biosensors as applied to nervous system diseases under interdisciplinary promotion are also discussed in depth.

Alfalfa (Medicago sativa. L.) is a globally significant autotetraploid legume forage crop. However, despite its importance, establishing efficient gene editing systems for cultivated alfalfa remains a formidable challenge. In this study, we pioneered the development of a highly effective ultrasonic-assisted leaf disc transformation system for Gongnong 1 alfalfa, a variety widely cultivated in Northeast China. Subsequently, we created a single transcript CRISPR/Cas9 (CRISPR_2.0) toolkit, incorporating multiplex gRNAs, designed for gene editing in Gongnong 1. Both Cas9 and gRNA scaffolds were under the control of the Arabidopsis ubiquitin-10 promoter, a widely employed polymerase II constitutive promoter known for strong transgene expression in dicots. To assess the toolkit’s efficiency, we targeted PALM1, a gene associated with a recognizable multifoliate phenotype. Utilizing the CRISPR_2.0 toolkit, we directed PALM1 editing at two sites in the wild-type Gongnong 1. Results indicated a 35.1% occurrence of editing events all in target 2 alleles, while no mutations were detected at target 1 in the transgenic-positive lines. To explore more efficient sgRNAs, we developed a rapid, reliable screening system based on Agrobacterium rhizogenes-mediated hairy root transformation, incorporating the visible reporter MtLAP1. This screening system demonstrated that most purple visible hairy roots underwent gene editing. Notably, sgRNA3, with an 83.0% editing efficiency, was selected using the visible hairy root system. As anticipated, tetra-allelic homozygous palm1 mutations exhibited a clear multifoliate phenotype. These palm1 lines demonstrated an average crude protein yield increase of 21.5% compared to trifoliolate alfalfa. Our findings highlight the modified CRISPR_2.0 system as a highly efficient and robust gene editing tool for autotetraploid alfalfa.

Interventional therapy has been widely used in surgeries involving neurology, vasculature, and breasts.Image-guided, robot-assisted interventional therapy significantly enhances surgical precision and safety, emerging as a critical trend in modern interventional surgery. Among various interventional imaging methods, interventional magnetic resonance imaging (i-MRI) stands out due to its excellent soft tissue differentiation, diverse imaging contrasts, ability to yield quantitative data, and no ionizing radiation. However, the challenges facing MRI-guided therapy include the relatively low speed of imaging and the stringent compatibility demands of interventional devices. Advance in the rapid i-MRI techniques and MR-compatible equipment have propelled i-MRI to a pivotal role in clinical applications, encompassing neurological, cardiovascular, prostate, and breast interventions. This review initially provides an overview of the current i-MRI landscape. It then consolidates the application of i-MRI in multiple medical interventions, offering illustrative examples. The article further delves into the obstacles posed by i-MRI, specifically slow imaging speed and the delicate spatiotemporal resolution balance. Ultimately, it envisages the growth potential of i-MRI in multimodal imaging, real-time MRI, and i-MRI-guided interventional robotic surgery.

The spectral energy distribution (SED) of galaxies is essential for deriving fundamental properties like stellar mass and star formation history (SFH). However, conventional methods, including both parametric and nonparametric approaches, often fail to accurately recover the observed cosmic star formation rate (SFR) density due to oversimplified or unrealistic assumptions about SFH and their inability to account for the complex SFH variations across different galaxy populations. To address this issue, we introduce a novel approach that improves galaxy broadband SED analysis by incorporating physical priors derived from hydrodynamical simulations. Tests using IllustrisTNG simulations demonstrate that our method can reliably determine galaxy physical properties from broadband photometry, including stellar mass within 0.05 dex, current SFR within 0.3 dex, and fractional stellar formation time within 0.2 dex, with a negligible fraction of catastrophic failures. When applied to the Sloan Digital Sky Survey (SDSS) main photometric galaxy sample with spectroscopic redshift, our estimates of stellar mass and SFR are consistent with the widely used MPA-JHU and GSWLC catalogs. Notably, using the derived SFHs of individual SDSS galaxies, we estimate the cosmic SFR density and stellar mass density with remarkable consistency to direct observations up to z ~ 6. This demonstrates a significant advancement in deriving SFHs from SEDs that closely align with observational data. Consequently, our method can reliably recover observed spectral indices such as D _n (4000) and H δ _A by synthesizing the full spectra of galaxies using the estimated SFHs and metal enrichment histories, relying solely on broadband photometry as input. Furthermore, this method is extremely computationally efficient compared to conventional approaches.

In ΛCDM cosmology, galaxies form and evolve in their host dark matter (DM) halos. Halo mass is crucial for understanding the halo–galaxy connection. The abundance-matching (AM) technique has been widely used to derive the halo masses of galaxy groups. However, the quenching of the central galaxy can decouple the coevolution of its stellar mass and DM halo mass. Different halo assembly histories can also result in significantly different final stellar masses of the central galaxies. These processes can introduce substantial uncertainties into the halo masses derived from the AM method, particularly leading to a systematic bias between groups with star-forming centrals (blue groups) and passive centrals (red groups). To improve this, we have developed a new machine learning (ML) algorithm that accounts for these effects and is trained on simulations. Our results show that the ML method eliminates the systematic bias in the derived halo masses for blue and red groups and is, on average, ~one-third more accurate than the AM method. With careful calibrations of observable quantities from simulations and observations from the Sloan Digital Sky Survey (SDSS), we apply our ML model to the SDSS groups to derive their halo masses down to 10 ^11.5 M _⊙ or even lower. The derived SDSS group halo mass function agrees well with the theoretical predictions, and the derived stellar-to-halo mass relations for both the red and blue groups match well with those obtained from direct weak-lensing measurements. These new halo mass estimates enable more accurate investigation of the galaxy–halo connection and the role of halos in galaxy evolution.

Ischemic stroke poses a significant global health burden, with rapid revascularization treatments being crucial but often insufficient to mitigate ischemia-reperfusion (I/R) injury. Dexmedetomidine (DEX) has shown promise in reducing cerebral I/R injury, but its potential molecular mechanism, particularly its interaction with non-coding RNAs (ncRNAs), remains unclear. This study investigates DEX’s therapeutic effect and potential molecular mechanisms in reducing cerebral I/R injury. A transient middle cerebral artery obstruction (tMACO) model was established to simulate cerebral I/R injury in adult rats. DEX was administered pre-ischemia and post-reperfusion. RNA sequencing and bioinformatic analyses were performed on the ischemic cerebral cortex to identify differentially expressed non-coding RNAs (ncRNAs) and mRNAs. The sequencing results showed 6,494 differentially expressed (DE) mRNA and 2698 DE circRNA between the sham and tMCAO (I/R) groups. Additionally, 1809 DE lncRNA, 763 DE mRNA, and 2795 DE circRNA were identified between the I/R group and tMCAO + DEX (I/R + DEX) groups. Gene ontology (GO) analysis indicated significant enrichment in multicellular biogenesis, plasma membrane components, and protein binding. KEGG analysis further highlighted the potential mechanism of DEX action in reducing cerebral I/R injury, with hub genes involved in inflammatory pathways. This study demonstrates DEX’s efficacy in reducing cerebral I/R injury and offers insights into its brain-protective effects, especially in ischemic stroke. Further research is warranted to fully understand DEX’s neuroprotective mechanisms and its clinical applications.

BackgroundOsteoporosis (OP), affecting millions around the globe, is a prevalent degenerative condition of the bones characterized by a decrease in bone mineral density (BMD) and an increase in bone fragility. A novel anthropometric measure, the Body Roundness Index (BRI), provides a more accurate assessment of body fat distribution compared to traditional metrics. Using data from the National Health and Nutrition Examination Survey (NHANES), this study aims to explore the relationship between BRI and total BMD in U.S. adults aged 20 and above.MethodsData from NHANES (2011–2018) were examined, encompassing 9,295 participants following exclusions. Dual-energy X-ray absorptiometry (DXA) was employed to measure BMD. BRI was calculated using waist circumference (WC) and height. The study accounted for variables such as demographic traits, physical exam results, lab test findings, and survey responses. Weighted multivariable linear regression models and smooth curve fitting methods were utilized to assess the relationship between BRI and total BMD.ResultsThe research found a notable inverse relationship between BRI and total BMD. In the model with full adjustments, an increase of one unit in BRI was linked to a 0.0313 g/cm2 reduction in total BMD (P < 0.0001). Moreover, an inflection point was identified at BRI = 9.5229, where each one-unit rise in BRI beyond this threshold corresponded to a more substantial decrease in total BMD (0.0363 g/cm2). Analysis by subgroups revealed that this negative association was consistent across most demographic and health-related categories.ConclusionsThe results demonstrate a notable inverse relationship between BRI and total BMD, indicating that a higher BRI could be associated with lower BMD and a potentially greater risk of developing OP. This underscores the significance of accounting for body fat distribution in preventing OP and advocates for the use of BRI as a valuable marker for early intervention approaches.

We discuss the angular dependence of the recently proposed transverse momentum dependent quark and gluon diffractive parton distributions at small-x. We introduce the diffractive versions of the Sivers function and the elliptic gluon Wigner distribution and evaluate them in simple models with gluon saturation and study their geometric scaling properties. We also show that the diffractive version of the linearly polarized gluon distribution identically vanishes to leading order. These distributions enrich the physics opportunities for measuring semi-inclusive diffractive DIS processes at the future electron-ion colliders.

IntroductioncGMP-dependent protein kinase 1 (PRKG1) has shown to be associated with some tumorigenesis, while the role of PRKG1 in bladder cancer is unclear.MethodsTo investigate the biological and clinical significance of PRKG1 in bladder cancer, we detected the expression of PRKG1 and explored the function of PRKG1 in bladder cancer cells. The PRKG1 transcripts data was downloaded from The Cancer Genome Atlas (TCGA) database, and immunohistochemistry staining was conducted on formalin-fixed paraffin-embedded (FFPE) sample tissues. Relationship between clinical characteristics of patients and expression of PRKG1 was analyzed in FFPE samples, TCGA database, and GSE19423 dataset. PRKG1 was over-expressed, and cell proliferation, migration, invasion, apoptosis, and spheroidizing ability were then detected. Chemosensitivity to cisplatin was detected with cell viability, and half-maximal drug inhibitory concentration (IC50) was calculated. In addition, the relation between PRKG1 expression and the infiltration level of tumor immune cells in tumor microenvironment were analyzed.ResultsThe results showed expression of PRKG1 was lower in bladder cancer, compared with normal tissues both at protein and transcript levels. Lower PRKG1 expression was related to higher tumor grade, T stage, and muscle invasion, also predicted worse overall survival and recurrence free survival in patients treated with Bacillus Calmette–Guerin (BCG) intravesical immunotherapy. Analysis of tumor immune cells infiltration showed lower PRKG1 was associated with non-inflamed tumor microenvironment.ConclusionThe present study firstly identified the anti-tumor role and tumor immune regulatory role of PRKG1, also found loss of PRKG1 could be used as a prognosis factor. The present study provided a potential biomarker and therapy target to bladder cancer.

The choice of trap in entomological surveys affects the composition of captured insects, though previous comparative studies have been limited in the types of composition measured, and the effects of environmental context. We assessed the sampling bias of several traps commonly used in pollinator monitoring: blue, yellow, and white pan traps, and blue vane traps, towards different taxonomic and functional groups and their efficiency in measuring taxonomic, phylogenetic, and functional diversity. Analyses were performed in monoculture and mixed forests to understand the environmental context of trap efficiency. We found that blue pan traps generally outperformed other types in bee capture and exhibited a preference for Halictidae bees. Blue pan traps yielded the highest species richness and phylogenetic diversity, while blue vane traps captured the highest functional richness. Bias differences were frequently detected in mixed forests compared with monoculture forests. We also found the combination of blue vane and pan traps consistently correlated highest with a complete survey among two-method combinations. Based on our findings, we recommend a combination of blue vane and pan traps to obtain a more comprehensive bee collection in an efficient manner. Additionally, it is crucial to consider habitat type when designing bee trapping protocols to ensure an accurate representation of bee communities.

Abstract Liquid-liquid phase separation of proteins occurs on both surfaces of cellular membranes during diverse physiological processes. In vitro reconstitution could provide insight into the mechanisms underlying these events. However, most existing reconstitution techniques provide access to only one membrane surface, making it difficult to probe transmembrane phenomena. To study protein phase separation simultaneously on both membrane surfaces, we developed an array of freestanding planar lipid membranes. Interestingly, we observed that liquid-like protein condensates on one side of the membrane colocalized with those on the other side, resulting in transmembrane coupling. Our results, based on lipid probe partitioning and mobility of lipids, suggest that protein condensates locally reorganize membrane lipids, a process which could be explained by multiple effects. These findings suggest a mechanism by which signals originating on one side of a biological membrane, triggered by protein phase separation, can be transferred to the opposite side.

Abstract Background To investigate whether patient-specific instrumentation (PSI) improves the femoral component positioning of implants during unicompartmental knee arthroplasty (UKA) using cadaver bone models. Methods Fifty adult cadaveric femoral bone specimens collected from February 2016–2018, were randomized to receive medial UKA with a PSI guide (n = 25) or conventional instrumentation (CI) (n = 25). Standard anteroposterior and lateral view radiographs were obtained postoperatively to assess the coronal and sagittal positioning of the femoral prostheses, respectively. The osteotomy time was recorded to assess the convenience of PSI in guiding osteotomy. Results Osteotomy time significantly shortened in the PSI group (3.12 ± 0.65 versus 4.33 ± 0.73 min, p

Abstract Quantum Chromodynamics, the theory of quarks and gluons, whose interactions can be described by a local SU(3) gauge symmetry with charges called “color quantum numbers”, is reviewed; the goal of this review is to provide advanced Ph.D. students a comprehensive handbook, helpful for their research. When QCD was “discovered” 50 years ago, the idea that quarks could exist, but not be observed, left most physicists unconvinced. Then, with the discovery of charmonium in 1974 and the explanation of its excited states using the Cornell potential, consisting of the sum of a Coulomb-like attraction and a long range linear confining potential, the theory was suddenly widely accepted. This paradigm shift is now referred to as the November revolution. It had been anticipated by the observation of scaling in deep inelastic scattering, and was followed by the discovery of gluons in three-jet events. The parameters of QCD include the running coupling constant, $$\alpha _s(Q^2)$$ α s ( Q 2 ) , that varies with the energy scale $$Q^2$$ Q 2 characterising the interaction, and six quark masses. QCD cannot be solved analytically, at least not yet, and the large value of $$\alpha _s$$ α s at low momentum transfers limits perturbative calculations to the high-energy region where $$Q^2\gg \varLambda _{{\textrm{QCD}}} ^2\simeq $$ Q 2 ≫ Λ QCD 2 ≃ (250 MeV) $$^2$$ 2 . Lattice QCD (LQCD), numerical calculations on a discretized space-time lattice, is discussed in detail, the dynamics of the QCD vacuum is visualized, and the expected spectra of mesons and baryons are displayed. Progress in lattice calculations of the structure of nucleons and of quantities related to the phase diagram of dense and hot (or cold) hadronic matter are reviewed. Methods and examples of how to calculate hadronic corrections to weak matrix elements on a lattice are outlined. The wide variety of analytical approximations currently in use, and the accuracy of these approximations, are reviewed. These methods range from the Bethe–Salpeter, Dyson–Schwinger coupled relativistic equations, which are formulated in both Minkowski or Euclidean spaces, to expansions of multi-quark states in a set of basis functions using light-front coordinates, to the AdS/QCD method that imbeds 4-dimensional QCD in a 5-dimensional deSitter space, allowing confinement and spontaneous chiral symmetry breaking to be described in a novel way. Models that assume the number of colors is very large, i.e. make use of the large $$N_c$$ N c -limit, give unique insights. Many other techniques that are tailored to specific problems, such as perturbative expansions for high energy scattering or approximate calculations using the operator product expansion are discussed. The very powerful effective field theory techniques that are successful for low energy nuclear systems (chiral effective theory), or for non-relativistic systems involving heavy quarks, or the treatment of gluon exchanges between energetic, collinear partons encountered in jets, are discussed. The spectroscopy of mesons and baryons has played an important historical role in the development of QCD. The famous X,Y,Z states – and the discovery of pentaquarks – have revolutionized hadron spectroscopy; their status and interpretation are reviewed as well as recent progress in the identification of glueballs and hybrids in light-meson spectroscopy. These exotic states add to the spectrum of expected $$q{{\bar{q}}}$$ q q ¯ mesons and qqq baryons. The progress in understanding excitations of light and heavy baryons is discussed. The nucleon as the lightest baryon is discussed extensively, its form factors, its partonic structure and the status of the attempt to determine a three-dimensional picture of the parton distribution. An experimental program to study the phase diagram of QCD at high temperature and density started with fixed target experiments in various laboratories in the second half of the 1980s, and then, in this century, with colliders. QCD thermodynamics at high temperature became accessible to LQCD, and numerical results on chiral and deconfinement transitions and properties of the deconfined and chirally restored form of strongly interacting matter, called the Quark–Gluon Plasma (QGP), have become very precise by now. These results can now be confronted with experimental data that are sensitive to the nature of the phase transition. There is clear evidence that the QGP phase is created. This phase of QCD matter can already be characterized by some properties that indicate, within a temperature range of a few times the pseudocritical temperature, the medium behaves like a near ideal liquid. Experimental observables are presented that demonstrate deconfinement. High and ultrahigh density QCD matter at moderate and low temperatures shows interesting features and new phases that are of astrophysical relevance. They are reviewed here and some of the astrophysical implications are discussed. Perturbative QCD and methods to describe the different aspects of scattering processes are discussed. The primary parton–parton scattering in a collision is calculated in perturbative QCD with increasing complexity. The radiation of soft gluons can spoil the perturbative convergence, this can be cured by resummation techniques, which are also described here. Realistic descriptions of QCD scattering events need to model the cascade of quark and gluon splittings until hadron formation sets in, which is done by parton showers. The full event simulation can be performed with Monte Carlo event generators, which simulate the full chain from the hard interaction to the hadronic final states, including the modelling of non-perturbative components. The contribution of the LEP experiments (and of earlier collider experiments) to the study of jets is reviewed. Correlations between jets and the shape of jets had allowed the collaborations to determine the “color factors” – invariants of the SU(3) color group governing the strength of quark–gluon and gluon–gluon interactions. The calculated jet production rates (using perturbative QCD) are shown to agree precisely with data, for jet energies spanning more than five orders of magnitude. The production of jets recoiling against a vector boson, $$W^\pm $$ W ± or Z, is shown to be well understood. The discovery of the Higgs boson was certainly an important milestone in the development of high-energy physics. The couplings of the Higgs boson to massive vector bosons and fermions that have been measured so far support its interpretation as mass-generating boson as predicted by the Standard Model. The study of the Higgs boson recoiling against hadronic jets (without or with heavy flavors) or against vector bosons is also highlighted. Apart from the description of hard interactions taking place at high energies, the understanding of “soft QCD” is also very important. In this respect, Pomeron – and Odderon – exchange, soft and hard diffraction are discussed. Weak decays of quarks and leptons, the quark mixing matrix and the anomalous magnetic moment of the muon are processes which are governed by weak interactions. However, corrections by strong interactions are important, and these are reviewed. As the measured values are incompatible with (most of) the predictions, the question arises: are these discrepancies first hints for New Physics beyond the Standard Model? This volume concludes with a description of future facilities or important upgrades of existing facilities which improve their luminosity by orders of magnitude. The best is yet to come!

Abstract Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions.

The gaming industry has been greatly impacted by virtual reality (VR), augmented reality (AR), and metaverse which provide immersive and interactive experiences. A detailed summary of the use of VR and AR in game development is given in this paper. It looks at how AR platforms are being developed for environmental simulations, assesses how presence is used in AR location-aware games, and talks about how mobile AR games that rely on image recognition are made. It also explores how VR technology affects gamer satisfaction, how AR is being used to create innovative gameplay and interactive interfaces, and how AR-based interactive training systems are being developed. We dive into the technical underpinnings, examining how VR and AR combine real-world and virtual elements to create innovative gaming experiences. This review attempts to provide insights into the current state of VR and AR in game development as well as the possible future trajectories of these technologies by looking into case studies and new developments. It becomes clear as we navigate this fusion of reality and imagination that VR and AR are more than just technological tools, rather, they are catalysts that are changing the way we interact with and experience games.

The growing interest in the fish farming industry is driven by the depletion of natural fish stocks in the market. However, intensive aquaculture systems, which involve raising fish in artificial tanks and cages, can lead to challenges such as low-quality fish and increased mortality rates, depending on the species being cultivated. To address these issues and maximize yield, this paper proposes a fish quality monitoring system with automatic correction. The system focuses on monitoring and maintaining critical water quality parameters essential for fish growth, including temperature, water level, and pH level. The system comprises an Arduino connected to sensors and a web-based application for data collection and monitoring. Correction devices such as an aquarium heater, a valve, and a water pump are integrated into the system to maintain these parameters at optimal levels for fish development. To assess the system's efficiency and reliability, two fish monitoring setups were compared: one using the proposed controlled system and the other using a traditional setup. Results indicate that the controlled system increased efficiency, reduced stress on fish farmers, decreased fish mortality rates, and improved product quality compared to the traditional setup.

Abstract Background To investigate the risk factors for new vertebral compression fractures (NVCFs) after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs) and to create a nomogram to predict the occurrence of new postoperative fractures. Methods This was a retrospective analysis of the clinical data of 529 OVCF patients who received PKP treatment in our hospital from June 2017 to June 2020. Based on whether there were new fractures within 2 years after surgery, the patients were divided into a new fracture group and a nonnew fracture group. Univariate and multivariate analyses were used to determine the risk factors for the occurrence of NVCFs after surgery. The data were randomly divided into a training set (75%) and a testing set (25%). Nomograms predicting the risk of NVCF occurrence were created based on the results of the multivariate analysis, and performance was evaluated using receiver operating characteristic curves (ROCs), calibration curves, and decision curve analyses (DCAs). A web calculator was created to give clinicians a more convenient interactive experience. Results A total of 56 patients (10.6%) had NVCFs after surgery. The univariate analysis showed significant differences in sex and the incidences of cerebrovascular disease, a positive fracture history, and bone cement intervertebral leakage between the two groups (P

Abstract Background Postoperative delayed hyponatremia (PDH) is a major cause of readmission after endoscopic transsphenoidal surgery (eTSS) for pituitary adenomas (PAs). However, the risk factors associated with PDH have not been well established, and the development of a dynamic online nomogram for predicting PDH is yet to be realized. We aimed to investigate the predictive factors for PDH and construct a dynamic online nomogram to aid in its prediction. Methods We analyzed the data of 226 consecutive patients who underwent eTSS for PAs at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020. An additional 97 external patients were included for external validation. PDH was defined as a serum sodium level below 137 mmol/L, occurring on the third postoperative day (POD) or later. Results Hyponatremia on POD 1–2 (OR = 2.64, P = 0.033), prothrombin time (PT) (OR = 1.78, P = 0.008), and percentage of monocytes (OR = 1.22, P = 0.047) were identified as predictive factors for PDH via multivariable logistic regression analysis. Based on these predictors, a nomogram was constructed with great discrimination in internal validation (adjusted AUC: 0.613–0.688) and external validation (AUC: 0.594–0.617). Furthermore, the nomogram demonstrated good performance in calibration plot, Brier Score, and decision curve analysis. Subgroup analysis revealed robust predictive performance in patients with various clinical subtypes and mild to moderate PDH. Conclusions Preoperative PT and the percentage of monocytes were, for the first time, identified as predictive factors for PDH. The dynamic nomogram proved to be a valuable tool for predicting PDH after eTSS for PAs and demonstrated good generalizability. Patients could benefit from early identification of PDH and optimized treatment decisions.

Abstract It has been shown previously that the transverse momentum dependent (TMD) factorization of heavy quarkonium production requires a TMD shape function. Its perturbative tail can be extracted by matching the cross sections valid at low and high transverse momenta. In this article we compare the order-α s TMD expressions with the order- α s 2 $$ {\alpha}_s^2 $$ collinear ones for J/ψ production in semi-inclusive deep inelastic scattering (SIDIS), employing nonrelativistic QCD in both cases. In contrast to previous studies, we find that the small transverse momentum limit of the collinear expressions contains discontinuities. We demonstrate how to properly deal with them and include their finite contributions to the TMD shape functions. Moreover, we show that soft gluon emission from the low transverse momentum Born diagrams provide the same leading order TMD shape functions as required for the matching. Their revised perturbative tails have a less divergent behavior as compared to the TMD fragmentation functions of light hadrons. Finally, we investigate the universality of TMD shape functions in heavy quarkonium production, identify the need for process dependent factorization and discuss the phenomenological implications.

BackgroundBeing complex and highly heterogeneous with regard to the etiology and clinical manifestations of depression， neuroimaging studies make a breakthrough for exploring the biological subtypes of depression， while the current data-driven approach for the identification of subtyping depression using structural magnetic resonance imaging （MRI） data is insufficient.ObjectiveTo explore the biological subtypes of depression using diffusion tensor imaging （DTI） and machine learning methods.MethodsA total of 127 patients with depression who attended Beijing Anding Hospital from September 2017 to August 2021 and met the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） diagnostic criteria were included， and another 80 healthy individuals matched for gender and age were recruited through advertisements in surrounding communities during the same period. DTI findings， demographic characteristics and clinical data were collected from all participants. Tract-based spatial statistics （TBSS） and the Johns Hopkins University （JHU） white matter probability maps were used to extract fractional anisotropy （FA） values of white matter tracts. A semi-supervised machine learning technique was used to identify the subtypes， and the FA values for whole brain white matter of patients and controls were compared.ResultsPatients with depression were classified into two biological subtypes. FA values in multiple tracts including corpus callosum and corona radiata of subtype I patients were smaller than those of healthy controls （P0.05）， while subtype I patients scored lower on HAMD-17 than subtype II patients after 12 weeks of treatment （t=2.410， P

In the field of geosciences, the integration of artificial intelligence is transitioning from perceptual intelligence to cognitive intelligence. The simultaneous utilization of knowledge and data in the geoscience domain is a universally addressed concern. In this paper, based on the interpretability of deep learning models for rock images, rock features such as structure, texture, mineral and macroscopic identification characteristics were selected to extract a rock identification subgraph from the petrographic knowledge graph and carry out rock type similarity reasoning. Comparative experiments were conducted on few-shot learning of rock images under the supervision of rock type similarity knowledge. The results of the few-shot learning comparisons demonstrate that the supervision of rock type similarity knowledge significantly enhances performance. Additionally, rock type similarity knowledge exhibits a marginal effect on improving few-shot learning performance. Given the absence of Chinese word embedding and large-scale Chinese pre-trained language models in the geological domain, graph embedding based on domain-specific knowledge graphs in geosciences can offer computable geoscience knowledge for research dually propelled by data and knowledge.

Abstract Drought stress has been a key environmental factor affecting plant growth and development. The plant genome is capable of producing long noncoding RNAs (lncRNAs). To better understand white mulberry (Morus alba L.) drought response mechanism, we conducted a comparative transcriptome study comparing two treatments: drought‐stressed (EG) and well‐watered (CK) plants. A total of 674 differentially expressed lncRNAs (DElncRNAs) were identified. In addition, 782 differentially expressed messenger RNAs (DEmRNAs) were identified. We conducted Gene Ontology (GO) and KEGG enrichment analyses focusing on the differential lncRNAs cis‐target genes. The target genes of the DElncRNAs were most significantly involved in the biosynthesis of secondary metabolites. Gene regulatory networks of the target genes involving DElncRNAs–mRNAs–DEmRNAs and DElncRNA–miRNA–DEmRNA were constructed. In the DElncRNAs–DEmRNAs network, 30 DEmRNAs involved in the biosynthesis of secondary metabolites are collocated with 46 DElncRNAs. The interaction between DElncRNAs and candidate genes was identified using LncTar. In summary, quantitative real‐time polymerase chain reaction (qRT‐PCR) validated nine candidate genes and seven target lncRNAs including those identified by LncTar. We predicted that the DElncRNAs–DEmRNAs might recruit microRNAs (miRNAs) to interact with gene regulatory networks under the drought stress response in mulberry. The findings will contribute to our understanding of the regulatory functions of lncRNAs under drought stress and will shed new light on the mulberry–drought stress interactions.

Artificial intelligence and machine learning are essential for the development of IR4.0 due to their ability to analyse vast amounts of data, automate processes, and drive innovation across various sectors. These technologies enable intelligent decision-making, predictive analytics, and automation, leading to increased efficiency, productivity, and competitiveness in the digital age. In IR4.0, AI and ML power smart systems and connected devices, transforming industries. They facilitate the integration of digital, physical, and biological systems, enabling the creation of personalized medicine and medical diagnosis smart manufacturing, self-autonomous driving vehicles, smart cities, and smart home. Hence, this review aims to address the contribution of AI and ML in the development of medical diagnosis, smart manufacturing, smart cars, smart cities, and smart homes as well as to highlight the existing challenges faced by AI and ML in these fields. This review also showcases the relevant prospects of AI and ML applications in the fields mentioned.

ObjectivesTo establish a radiomics model for distinguishing between the benign and malignant mammary gland nodules via combining the features from nodule and mammary regions on DCE-MRIMethodsIn this retrospective study, a total of 103 cases with mammary gland nodules (malignant/benign = 80/23) underwent DCE-MRI, and was confirmed by biopsy pathology. Features were extracted from both nodule region and mammary region on DCE-MRI. Three SVM classifiers were built for diagnosis of benign and malignant nodules as follows: the model with the features only from nodule region (N model), with the features only from mammary region (M model) and the model combining the features from nodule region and mammary region (NM model). The performance of models was evaluated with the area under the curve of receiver operating characteristic (AUC).ResultsOne radiomic features is selected from nodule region and 3 radiomic features is selected from mammary region. Compared with N or M model, NM model exhibited the best performance with an AUC of 0.756.ConclusionsCompared with the model only using the features from nodule or mammary region, the radiomics-based model combining the features from nodule and mammary region outperformed in the diagnosis of benign and malignant nodules.

The Event Horizon Telescope observed the horizon-scale synchrotron emission region around the Galactic center supermassive black hole, Sagittarius A* (Sgr A*), in 2017. These observations revealed a bright, thick ring morphology with a diameter of 51.8 ± 2.3 μ as and modest azimuthal brightness asymmetry, consistent with the expected appearance of a black hole with mass M ≈ 4 × 10 ^6 M _⊙ . From these observations, we present the first resolved linear and circular polarimetric images of Sgr A*. The linear polarization images demonstrate that the emission ring is highly polarized, exhibiting a prominent spiral electric vector polarization angle pattern with a peak fractional polarization of ∼40% in the western portion of the ring. The circular polarization images feature a modestly (∼5%–10%) polarized dipole structure along the emission ring, with negative circular polarization in the western region and positive circular polarization in the eastern region, although our methods exhibit stronger disagreement than for linear polarization. We analyze the data using multiple independent imaging and modeling methods, each of which is validated using a standardized suite of synthetic data sets. While the detailed spatial distribution of the linear polarization along the ring remains uncertain owing to the intrinsic variability of the source, the spiraling polarization structure is robust to methodological choices. The degree and orientation of the linear polarization provide stringent constraints for the black hole and its surrounding magnetic fields, which we discuss in an accompanying publication.

In a companion paper, we present the first spatially resolved polarized image of Sagittarius A* on event horizon scales, captured using the Event Horizon Telescope, a global very long baseline interferometric array operating at a wavelength of 1.3 mm. Here we interpret this image using both simple analytic models and numerical general relativistic magnetohydrodynamic (GRMHD) simulations. The large spatially resolved linear polarization fraction (24%–28%, peaking at ∼40%) is the most stringent constraint on parameter space, disfavoring models that are too Faraday depolarized. Similar to our studies of M87*, polarimetric constraints reinforce a preference for GRMHD models with dynamically important magnetic fields. Although the spiral morphology of the polarization pattern is known to constrain the spin and inclination angle, the time-variable rotation measure (RM) of Sgr A* (equivalent to ≈46° ± 12° rotation at 228 GHz) limits its present utility as a constraint. If we attribute the RM to internal Faraday rotation, then the motion of accreting material is inferred to be counterclockwise, contrary to inferences based on historical polarized flares, and no model satisfies all polarimetric and total intensity constraints. On the other hand, if we attribute the mean RM to an external Faraday screen, then the motion of accreting material is inferred to be clockwise, and one model passes all applied total intensity and polarimetric constraints: a model with strong magnetic fields, a spin parameter of 0.94, and an inclination of 150°. We discuss how future 345 GHz and dynamical imaging will mitigate our present uncertainties and provide additional constraints on the black hole and its accretion flow.

The cold interstellar medium (ISM) as the raw material for star formation is critical to understanding galaxy evolution. It is generally understood that galaxies stop making stars when, in one way or another, they run out of gas. However, here we provide evidence that central spiral galaxies remain rich in atomic gas even if their star formation rate (SFR) and molecular gas fraction have dropped significantly compared to “normal” star-forming galaxies of the same mass. Since H i is sensitive to external processes, here we investigate central spiral galaxies using a combined sample from the Sloan Digital Sky Survey, Arecibo Legacy Fast ALFA survey, and the extended GALEX Arecibo SDSS Survey. After proper incompleteness corrections, we find that the key H i scaling relations for central spirals show significant but regular systematic dependence on stellar mass. At any given stellar mass, the H i gas mass fraction is about constant with changing specific star formation rate (sSFR), which suggests that H i reservoir is ubiquitous in central spirals with any star formation status down to M _* ∼ 10 ^9 M _⊙ . Together with the tight correlation between the molecular gas mass fraction and sSFR for galaxies across a wide range of different properties, it suggests that the decline of SFR of all central spirals in the local Universe is due to the halt of H _2 supply, though there is plenty of H i gas around. These hence provide critical observations of the dramatically different behavior of the cold multiphase ISM, and a key to understand the star formation process and quenching mechanism.

The efficacy of redosing the recombinant adeno-associated virus (rAAV) vector rAAV2.5T to ferret lung is limited by AAV neutralizing antibody (NAb) responses. While immunosuppression strategies have allowed for systemic rAAV repeat dosing, their utility for rAAV lung-directed gene therapy is largely unexplored. To this end, we evaluated two immunosuppression (IS) strategies to improve repeat dosing of rAAV2.5T to ferret lungs: (1) a combination of three IS drugs (Tri-IS) with broad coverage against cellular and humoral responses (methylprednisolone [MP], azathioprine, and cyclosporine) and (2) MP alone, which is typically used in systemic rAAV applications. Repeat dosing utilized AAV2.5T-SP183-fCFTRΔR (recombinant ferret CFTR transgene), followed 28 days later by AAV2.5T-SP183-gLuc (for quantification of transgene expression). Both the Tri-IS and MP strategies significantly improved transgene expression following repeat dosing and reduced AAV2.5T NAb responses in the bronchioalveolar lavage fluid (BALF) and plasma, while AAV2.5T binding antibody subtypes and cellular immune responses by ELISpot were largely unchanged by IS. One exception was the reduction in plasma AAV2.5T binding immunoglobulin G (IgG) in both IS groups. Only the Tri-IS strategy significantly suppressed splenocyte expression of IFNA (interferon α [IFN-α]) and IL4. Our studies suggest that IS strategies may be useful in clinical application of rAAV targeting lung genetic diseases such as cystic fibrosis.

Abstract Purpose To develop a bidirectional slide guide to assist screw placement in the axial lamina and to preliminarily discuss the accuracy and feasibility of auxiliary screw placement. Methods CT data from 40 randomly selected patients were imported into the software for modelling, and cross-pinning was used to simulate pinning. According to the different crossing methods of the upper and lower laminar screws, they are divided into two groups. In the software, the position of the needlepoint of each screw is accurately measured, and the needle point is kept unchanged to simulate the movable range of the screw tail under the condition that the body does not penetrate the cortical bone. The data were compared by grouping and gender. Finally, the guide was designed by combining the screw exit point and fine adjustment angle data of all patients with the centripetal principle of the slide rail. Results The needle exit data L1/L2/L3/L4 were 6.44 ± 0.52 mm, 7.05 ± 0.48 mm, 3.55 ± 0.75 mm and 5.09 ± 0.74 mm, respectively, and the fine adjustment angle of the slide rail was 10.51° ± 0.87°. There was no significant difference between the two groups or between men and women (p > 0.05). Conclusion In this experiment, using the data obtained from the simulation of screw insertion, a two-way slide guide was designed to assist the insertion of axial laminar screws. The guide locks the screw outlet point to position and guides the screw inlet point, which improves the accuracy and safety of screw placement.

Injectable bone biomaterials like bone cement should be designed and fabricated with certain biological criteria, which include: 1) recruitment and polarization of the macrophages from M1 (pro-inflammatory) to M2 (anti-inflammatory) phenotype, 2) enhance vascularization, and 3) activate osteogenic differentiation of bone marrow-derived stem cells to promote bone healing. So far, no injectable biomaterials could spontaneously regulate the entire bone healing process that involves inflammation, angiogenesis, and osteogenesis. Therefore, in this study, we designed bone cement comprised of strontium and copper-incorporated borosilicate glass (Sr/Cu-BSG) in the liquid phase of chitosan to modulate bone healing. In vitro studies showed that the controlled release of Sr and Cu ions up-regulated anti-inflammatory genes(IL-1Ra and TGF-β1) while down-regulating pro-inflammatory genes(IL-1β and IL-6) in macrophages at 3 days. Sr and Cu ions also increased the expressions of angiogenic genes (VEGF and bFGF) in HUVECs at 5 days and osteogenic genes (Runx-2, OCN, and OPN) in hBMSCs at 7, 14, and 21 days. 5Sr3Cu-BSG bone cement exhibited the best anti-inflammatory, angiogenic, and osteogenic properties among the bone cement groups with different Sr and Cu ratios. Short-term and long-term implantation of Sr/Cu-BSGs in femoral condylar bone defects of rats and rabbits confirmed the in vitro results, where the degradation rate of Sr/Cu-BSG matched the bone healing rate. Similar to in vitro, the 5Sr3Cu-BSG group also showed the highest bone formation in vivo. Excellent physical and chemical properties, along with its bone repairing ability, make the Sr/Cu-BSG bone cement a good candidate biomaterial for treating bone defects.

Abstract Analyzing how the underlying mechanism influences land value changes is essential to understanding the land market, which contributes to sustainable urbanization. Drawing upon a land transaction dataset, we analyze the determinants of urban land prices from 2008 to 2020, considering land supply and demands, with particular attention to natural restrictions and government interventions in China. The statistical analysis suggests that the inequality in industrial and commercial land prices rose from 2008 to 2015 and decreased after 2015. The inequality in residential land prices has kept rising from 2008 to 2020 because land finance is still essential to local government. Discriminatory price strategy for industrial land prices in eastern China is getting more popular. The regression models reveal the significant negative impact of natural restrictions on land price, and such impact from natural restrictions is decreasing after 2015. The market forces represented by city-level socioeconomic factors are becoming more important after 2015, indicating a more free land market in China. We also find the gaps between cities and counties in land prices are closing, which might benefit the recent development in rural and county region of China. These findings provide important insights into the transition in the land market in China from 2008 to 2020, which also contribute to a better understanding of the spatial inequality in the land market and the heterogeneity in different land-use types.

Acacia confusa is an important species in coastal shelter forests. In order to explore the effects of salt and phosphorus fertilization on leaf photosynthesis and nutrient characteristics of the seedlings. NaCl solutions were configured in the concentrations of 0% (B0), 0.2% (B1), 0.4% (B2), 0.6% (B3) and 0.8% (B4), and superphosphate solutions in the concentrations of 0 g·kg-1(P0), 0.5 g·kg-1(P1), and 1.5 g·kg-1(P2). The photosynthesis and nutrient characteristics of the seedlings were determined after being watered by the six combined solutions of salt-phosphorus coupling fertilization. The results were as follows: (1) Salt stress significantly inhibited the growth and development of the seedlings, and the higher the salt content, the greater the effect. Phosphorus application under low-salt stress was unfavorable to the growth of the seedlings, while phosphorus application under medium-high one significantly slowed down the inhibition of the seedling growth. (2) The greater the salt stress, the higher the effects on the photosynthesis of the seedlings. The stomatal closure degree of phosphorus application increased under low and medium salt stress, which aggravated the effect of salt stress on photosynthesis of the seedlings. Appropriate phosphorus application under high-salt stress could significantly improve the photosynthetic capacity of the seedlings. (3) Salt stress significantly reduced chlorophyll content and caused harm to photosystem II. Phosphorus fertilization on the seedlings under low-salt stress had adverse effects on chlorophyll synthesis. Appropriate fertilization of phosphorus in high-salt stress could increase chlorophyll synthesis, stabilize cell membrane structure, and improve the potential photosynthetic capacity of leaves. (4) Salt stress had strong interference on the contents of Fe, Mn, Na, Cu and other metal elements in leaves. Phosphorus application under salt stress could effectively promote the absorption of some elements by seedlings. In conclusion, phosphorus application after salt stress can improve the photosynthesis and nutrient absorption ability of A. confusa seedlings on the whole. The results provides a theoretical basis for improving the salt tolerance and phosphorus utilization rate of A. confusa, and have guiding significance for the sustainable management of coastal shelter forests.

Artificial coastal protection forests are difficult to manage because of nutrient stress in harsh environment. To explore the effects of salt and phosphorus stress on the seed germination and seedling growth of Casuarina equisetifolia and Acacia confusa, we respectively watered the seeds and seedlings of the two kinds of plants with the solutions of NaCl (salt) and KH2PO4 (phosphorus) in different concentrations, and then determined their growth indicators, respectively. The results were as follows: (1) High salt concentration solutions significantly inhibited seed germination and had a certain effect on the growth of seedlings, however, the effects of salt stress on seed gemination and growth were different. The salt tolerance of Acacia confusa seed germination was higher than that of Casuarina equisetifolia. The biggest relative salt damage rate of Acacia confusa was 23.03% and that of Casuarina equisetifolia was 89.15%. As the concentration of NaCl increased, the germination rate, germination potential, germination index and vitality index of Casuarina equisetifolia and Acacia confusa seeds decreased. And the maximums of the four germination indexes of Casuarina equisetifolia seed were 38.70%, 34.67%, 18.70 and 0.055, and of Acacia confusa seeds were 76.67%, 62.22%, 48.46 and 6.11, respectively. (2) The height and root length of the plants decreased with the increase of salt concentration. The plant heights of Casuarina equisetifolia and Acacia confusa were 12.29 to 6.01 mm and 48.27 to 17.33 mm, and the root lengths were 8.57 to 1.45 mm and 33.41 to 5.88 mm, respectively. The biomass of root, stem and leaf as well as root shoot ratio of Acacia confusa gradually decreased with the increase of salt concentration, but the differences between the treatments of Casuarina equisetifolia were not obvious. 0.6% and 0.4% salt stress were the thresholds for seed germination and seedling growth of the two plants, respectively. (3)The seed and seedling of Acacia confusa were more tolerant to low-phosphorus environment than Casuarina equisetifolia, and there was a difference in the optimum phosphorus concentration between the two. When the phosphorus concentration was 0.1 mmol·L-1, the seed germination rate(49.33%), germination index (23.12%) and vitality index(0.093) of Casuarina equisetifolia, as well as the biomass of root, stem and leaf, all reached the maximum. In the 5 mmol·L-1 treatment, the maximums of germination rate(81.11%), germination potential(62.22%), gemination index(38.23), vitality index(5.07), plant height (54.48 mm) and root length (37.16 mm) of Acacia confusa seeds all appeared, while their germination was inhibited in the treatment of 10 mmol·L-1. Therefore, when sowing the seed of coastal defense forest or planting its seedling, the sowing or planting mode must be selected according to the soil salt and phosphorus contents.

Abstract We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

The origins of the pair of X-ray bubbles, called eROSITA bubbles (eRBs), detected in the halo of Milky Way are debated. Here, the authors show hydrodynamical simulations suggesting circumgalactic medium wind model can explain asymmetric eRBs.

Abstract This paper uses a combination of EDXRF and LA-ICP-MS to analyse the chemical components including major elements and REE composition of the accompanying celadon from four different periods of tomb at the Yutu Hill burial complex on the Xunyang city site for sourcing their provenance. The combination of the two analytical methods not only provides additional data and information to explore the provenance of the accompanying celadon in the burials, but also validates the data’s accuracy. A comparison with the chemical composition of the products from several kiln sites producing celadon revealed that burials from the Eastern Han period (25–220 A.D) to the Tang dynasty (618–907 A.D) included celadon from the Hongzhou kiln, indicating the connection between the Xunyang city site and the Hongzhou kiln during these two periods. In addition, the REE composition of the accompanying celadon in tombs from the Six Dynasties (222–589 A.D) and the Sui dynasty (581–618 A.D) is very similar to that of Yue kiln celadon, despite their strikingly different appearance and shape. This paper deduces, based on the previous distribution of Yue kiln products in the Jiangxi region, that only the upper classes collected Yue kiln products during the initial period of their entry into Jiangxi during the Jin dynasty (266–420 A.D), but that during the later period of the Six Dynasties, the commoner classes also began to collect Yue kiln products.

Highlights 1. Machine learning significantly outperformed logistic regression models in predicting new fractures after osteoporotic vertebral compression fractures. 2. The random forest model performs best among these machine learning models.

With the development of deep learning in satellite remote sensing image segmentation, convolutional neural networks have achieved better results than traditional methods. In some full convolutional networks, the number of network layers usually increases to obtain deep features, but the gradient disappearance problem occurs when the number of network layers deepens. Many scholars have obtained multiscale features by using different convolutional calculations. We want to obtain multiscale features in the network structure while obtaining contextual information by other means. This article employs the self-attention mechanism and auxiliary loss network (SAMALNet) structure to solve the above problems. We adopt the self-attention strategy in the atrous spatial pyramid pooling module to extract multiscale features while considering the contextual information. We add auxiliary loss to overcome the gradient disappearance problem. The experimental results of extracting aquaculture areas in the Jiaozhou Bay area of Qingdao from high-resolution GF-2 satellite images show that, in general, SAMALNet achieves better experimental results compared with UPS-Net, SegNet, DeepLabv3, UNet, DeepLabv3+, and PSPNet network structures, including recall 96.34%, precision 95.91%, F1 score 96.12%, and MIoU 92.60%. SAMALNet achieved better results extracting aquaculture area boundaries than the other network structures listed above. The high accuracy of the aquaculture area can provide data support for the rational planning and environmental protection of the coastal aquaculture area and promote more rational usage of the coastal aquaculture area.