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Abstract With the population ages, many patients are unable to receive comprehensive care, leading to an increase in hazardous incidents, particularly falls occurring after getting out of bed. To address this issue, this paper proposes a method for recognizing bed-exit intentions using an array air spring mattress. The method integrates convolutional neural networks with feature point matching techniques to identify both global and local features of the array air spring. For global features, a one-dimensional focal loss convolutional neural network (1D-FLCNN) model is employed to classify eight internal pressure time series and determine bed-exit status based on global features. For local features, the distribution matrix and feature point matrix of the internal pressure features are extracted to represent the spatial distribution of bed-exit postures. Euclidean distance is utilized to measure the similarity between these matrices and match bed-exit postures. Finally, the recognition results from both feature types are combined using a logical OR operation to produce the final result. Experimental validation confirms that the proposed method greatly improves the anti-interference capability and effectively avoids the problem of non-recognition due to body position and external environment.

Abstract The rapid recombination of photoinduced charge carriers in semiconductors fundamentally limits their application in photocatalysis. Herein, we report that a superlattice interface and S-scheme heterojunction based on Mn0.5Cd0.5S nanorods can significantly promote ultrafast charge separation and transfer. Specifically, the axially distributed zinc blende/wurtzite superlattice interfaces in Mn0.5Cd0.5S nanorods can redistribute photoinduced charge carriers more effectively when boosted by homogeneous internal electric fields and promotes bulk separation. Accordingly, S-scheme heterojunctions between the Mn0.5Cd0.5S nanorods and MnWO4 nanoparticles can further accelerate the surface separation of charge carriers via a heterogeneous internal electric field. Subsequent capture of the photoelectrons by adsorbed H2O is as fast as several picoseconds which results in a photocatalytic H2 evolution rate of 54.4 mmol·g−1·h−1 without any cocatalyst under simulated solar irradiation. The yields are increased by a factor of ~5 times relative to control samples and an apparent quantum efficiency of 63.1% at 420 nm is measured. This work provides a protocol for designing synergistic interface structure for efficient photocatalysis.

Abstract The authors propose Point'n Move, a method that achieves interactive scene object manipulation with exposed region inpainting. Interactivity here further comes from intuitive object selection and real‐time editing. To achieve this, Gaussian Splatting Radiance Field is adopted as the scene representation and its explicit nature and speed advantage are fully leveraged. Its explicit representation formulation allows to devise a 2D prompt points to 3D masks dual‐stage self‐prompting segmentation algorithm, perform mask refinement and merging, minimize changes, and provide good initialization for scene inpainting and perform editing in real‐time without per‐editing training; all lead to superior quality and performance. The method was tested by editing both forward‐facing and 360 scenes. The method is also compared against existing methods, showing superior quality despite being more capable and having a speed advantage.

Objective: To investigate the efficacy and safety of Liqingtong (LQT) granules in patients with dampness-heat hyperuricemia. Methods: A randomized, double-blind, placebo-controlled pilot trial was conducted at the 983rd Hospital of the Joint Logistic Support Force of the People's Liberation Army from March 15, 2023, to August 10, 2023. In total, 119 participants were enrolled in this trial, and participants were given either LQT granules or placebo for 60 days based on a health education. The primary outcome was serum uric acid (SUA) level, and the secondary outcome was the traditional Chinese medicine (TCM) symptom score, measured on days 0, 30, and 60. Safety indicators, including liver function, kidney function, blood routine, glucose, blood lipid, blood pressure, and heart rate were tested on days 0 and 60 of the trial. The data were analyzed using Prism 9 software, and the significance level was set at P

Abstract The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Abstract ERBB2 (HER2) represents a newly recognized actionable oncogenic driver in non-small cell lung cancer (NSCLC), with approved targeted therapy available. Understanding the landscape of ERBB2 alterations and co-occurring mutations is essential for guiding treatment decisions. We conducted an analysis involving 3000 NSCLC patients with all types of ERBB2 alterations, drawn from two extensive retrospective cohorts: 1281 from Geneplus (Chinese) and 1719 from Guardant360 (the United States, US). The incidence of all types of ERBB2 alterations was found to be 5.6% in the Chinese group and 5.2% in the US group. In both cohorts, among oncogenic alterations of ERBB2, exon 20 insertion Y772_A775dupYVMA was the most frequent alteration (58% vs 41.6% in the Chinese vs the US), followed by G776delinsVC/LC/VV/IC (10.7% vs 9.7%), and S310X (10.5% vs 15.4%). EGFR ex20 insertions were identified in the A767-V774 region, whereas ERBB2 ex20 insertions were observed in the Y772-P780 region. Notably, EGFR ex20 insertions exhibited greater insertion diversity. Clinical characteristics of EGFR and ERBB2 ex20 NSCLC were similar, characterized by low tumor mutation burden (TMB), a predominant never-smoker population, and a majority of lung adenocarcinoma cases.

Abstract Aims The molecular signatures in epicardial adipose tissue (EAT) that contribute to the pathogenesis of heart failure with preserved ejection fraction (HFpEF) are poorly characterized. In this study, we sought to elucidate molecular signatures including genetic transcripts and long non‐coding RNAs (lncRNAs) in EAT that might modulate HFpEF development. Methods RNA sequencing (RNA‐seq) was performed to identify differentially expressed lncRNAs and mRNAs in EAT samples from patients with HFpEF (n = 5) and without HF (control, n = 5) who underwent coronary artery bypass grafting. The sequencing results were validated using quantitative real‐time PCR (qRT‐PCR). Bioinformatics analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) of differentially expressed RNAs was performed to predict enriched functions. Results HFpEF patients had higher EAT thickness and NT‐proBNP levels than the control group. A total of 64 471 transcripts were detected including 35 395 protein‐coding sequences, corresponding to 16 854 genes in EAT. RNA‐seq identified a total of 741 dysregulated mRNA transcripts (394 up‐regulated and 347 down‐regulated) and 334 differentially expressed lncRNA transcripts (222 up‐regulated and 112 down‐regulated) in the HFpEF group compared with the control group (P

Abstract Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine malignancy featured by cold tumor immune microenvironment (TIME), limited benefit from immunotherapy, and poor survival. The spatial heterogeneity of TIME significantly associated with anti-tumor immunity has not been systemically studied in SCLC. We performed ultra-high-plex Digital Spatial Profiling on 132 tissue microarray cores from 44 treatment-naive limited-stage SCLC tumors. Incorporating single-cell RNA-sequencing data from a local cohort and published SCLC data, we established a spatial proteo-transcriptomic landscape covering over 18,000 genes and 60 key immuno-oncology proteins that participate in signaling pathways affecting tumorigenesis, immune regulation, and cancer metabolism across 3 pathologically defined spatial compartments (pan-CK-positive tumor nest; CD45/CD3-positive tumor stroma; para-tumor). Our study depicted the spatial transcriptomic and proteomic TIME architecture of SCLC, indicating clear intra-tumor heterogeneity dictated via canonical neuroendocrine subtyping markers; revealed the enrichment of innate immune cells and functionally impaired B cells in tumor nest and suggested potentially important immunoregulatory roles of monocytes/macrophages. We identified RE1 silencing factor (REST) as a potential biomarker for SCLC associated with low neuroendocrine features, more active anti-tumor immunity, and prolonged survival.

Abstract The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

Abstract Traumatic cervical spinal cord injury (TCSCI) often causes varying degrees of motor dysfunction, common assessed by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), in association with the American Spinal Injury Association (ASIA) Impairment Scale. Accurate prediction of motor function recovery is extremely important for formulating effective diagnosis, therapeutic and rehabilitation programs. The aim of this study is to investigate the validity of a novel nested ensemble algorithm that uses the very early ASIA motor score (AMS) of ISNCSCI examination to predict motor function recovery 6 months after injury in TCSCI patients. This retrospective study included complete data of 315 TCSCI patients. The dataset consisting of the first AMS at ≤ 24 h post-injury and follow-up AMS at 6 months post-injury was divided into a training set (80%) and a test set (20%). The nested ensemble algorithm was established in a two-stage manner. Support Vector Classification (SVC), Adaboost, Weak-learner and Dummy were used in the first stage, and Adaboost was selected as second-stage model. The prediction results of the first stage models were uploaded into second-stage model to obtain the final prediction results. The model performance was evaluated using precision, recall, accuracy, F1 score, and confusion matrix. The nested ensemble algorithm was applied to predict motor function recovery of TCSCI, achieving an accuracy of 80.6%, a F1 score of 80.6%, and balancing sensitivity and specificity. The confusion matrix showed few false-negative rate, which has crucial practical implications for prognostic prediction of TCSCI. This novel nested ensemble algorithm, simply based on very early AMS, provides a useful tool for predicting motor function recovery 6 months after TCSCI, which is graded in gradients that progressively improve the accuracy and reliability of the prediction, demonstrating a strong potential of ensemble learning to personalize and optimize the rehabilitation and care of TCSCI patients.

Abstract Background Around the world, there is a high incidence of gastric ulcers. YS, an extract from the Chinese herb Albizzia chinensis (Osbeck) Merr, has potential therapeutic applications for gastrointestinal diseases. Here we elucidated the protective effect and underlying mechanism of action of YS on gastric ulcer in rats injured by ethanol. Methods The ethanol‐induced gastric ulcer rat model was used to assess the protective effect of YS. A pathological examination of gastric tissue was performed by H&E staining. GES‐1 cells damaged by hydrogen peroxide were used to simulate oxidative damage in gastric mucosal epithelial cells. Endogenous NRF2 was knocked down using small interfering RNA. Immunoprecipitation was used to detect ubiquitination of NRF2. Co‐immunoprecipitation was used to detect the NRF2–Keap1 interaction. Results YS (10 and 30 mg/kg, i.g.) significantly reduced the ulcer index, decreased MDA level, and increased SOD and GSH levels in gastric tissues damaged by ethanol. YS promoted NRF2 translocation from cytoplasm to nucleus and enhanced the NQO1 and HO‐1 expression levels in injured rat gastric tissue. In addition, YS regulated NQO1 and HO‐1 via NRF2 in H2O2‐induced oxidative injured GES‐1 cells. Further studies on the underlying mechanism indicated that YS reduced the interaction between NRF2 and Keap1 and decreased ubiquitylation of NRF2, thereby increasing its stability and expression of downstream factors. NRF2 knockdown abolished the effect of YS on MDA and SOD in GES‐1 cells treated with H2O2. Conclusion YS reduced the NRF2–Keap1 interaction, promoting NRF2 translocation into the nucleus, which increasing the transcription and translation of NQO1 and HO‐1 and improved the antioxidant capacity of rat stomach.

Abstract Constructing S-scheme heterojunctions proves proficient in achieving the spatial separation of potent photogenerated charge carriers for their participation in photoreactions. Nonetheless, the restricted contact areas between two phases within S-scheme heterostructures lead to inefficient interfacial charge transport, resulting in low photocatalytic efficiency from a kinetic perspective. Here, In2O3/Nb2O5 S-scheme heterojunctions are fabricated through a straightforward one-step electrospinning technique, enabling intimate contact between the two phases and thereby fostering ultrafast interfacial electron transfer (

ObjectiveTo explore the effectiveness of a machine learning-based multiparametric MRI radiomics nomogram for predicting the WHO/ISUP nuclear grading of clear cell renal cell carcinoma (ccRCC) before surgery.MethodsData from 86 patients who underwent preoperative renal MRI scans (both plain and enhanced) and were confirmed to have ccRCC were retrospectively collected. Based on the 2016 WHO/ISUP grading standards, patients were divided into a low-grade group (Grade I and II) and a high-grade group (Grade III and IV), and randomly split into training and testing sets at a 7:3 ratio. Radiomics features were extracted from FS-T2WI, DWI, and CE-T1WI sequences. Optimal features were selected using the Mann-Whitney U test, Spearman correlation analysis, and the least absolute shrinkage and selection operator (LASSO). Five machine learning classifiers—logistic regression (LR), naive bayes (NB), k-nearest neighbors (KNN), adaptive boosting (AdaBoost), and multilayer perceptron (MLP)—were used to build models to predict ccRCC WHO/ISUP nuclear grading. The model with the highest area under the curve (AUC) in the testing set was chosen as the best radiomics model. Independent clinical risk factors were identified using univariate and multivariate logistic regression to create a clinical model, which was combined with radiomics score (rad-score) to develop a nomogram. The model’s effectiveness was assessed using the receiver operating characteristic (ROC) curve, its calibration was evaluated using a calibration curve, and its clinical utility was analyzed using decision curve analysis.ResultsSix radiomics features were ultimately selected. The MLP classifier showed the highest diagnostic performance in the testing set (AUC=0.933). Corticomedullary enhancement level (P=0.020) and renal vein invasion (P=0.011) were identified as independent risk factors for predicting the WHO/ISUP nuclear classification and were included in the nomogram with the rad-score. The ROC curves indicated that the nomogram model had strong diagnostic performance, with AUC values of 0.964 in the training set and 0.933 in the testing set.ConclusionThe machine learning-based multiparametric MRI radiomics nomogram provides a highly predictive, non-invasive tool for preoperative prediction of WHO/ISUP nuclear grading in patients with ccRCC.

Feedback-insensitive Quantum Dot (QD) comb lasers hold significant promise for integrated dense wavelength division multiplexing photonic systems due to their ability to generate multiple wavelengths and operate without bulky isolators, facilitating the development of high-density and large-scale photonic integrated circuits. In this study, we investigated the optical feedback (OFB) influence of the InAs/GaAs QD comb laser from various perspectives. Our findings reveal that the comb laser exhibits a stable locking region with consistent optical spectra across a range of OFB strengths (−45 to −10 dB). Furthermore, under a high OFB strength of −10 dB, there is a notable 40 dB suppression of relative intensity noise in the low-frequency range (below 1 GHz). Transmission experiments demonstrate clear eye openings at 25 Gbps using a bit pattern of 231-1 pseudorandom binary sequence. Remarkably, the bit error rates decrease by five orders of magnitude under −10 dB OFB. These results indicate the ultra-robustness of 100 GHz grid QD comb laser, which exhibits great transmission enhancement under a strong OFB of −10 dB.

Background Neoadjuvant immune checkpoint inhibitors (ICIs) have improved survival outcomes compared with chemotherapy in resectable non-small cell lung cancer (NSCLC). However, the impact of actionable genomic alterations (AGAs) on the efficacy of neoadjuvant ICIs remains unclear. We report the influence of AGAs on treatment failure (TF) in patients with resectable NSCLC treated with neoadjuvant ICIs.Methods Tumor molecular profiles were obtained from patients with stage I–IIIA resectable NSCLC (American Joint Committee on Cancer seventh edition) treated with either neoadjuvant nivolumab (N, n=23) or nivolumab+ipilimumab (NI, n=21) followed by surgery in a previously reported phase-2 randomized study (NCT03158129). TF was defined as any progression of primary lung cancer after neoadjuvant ICI therapy in patients without surgery, radiographic and/or biopsy-proven primary lung cancer recurrence after surgery, or death from possibly treatment-related complications or from primary lung cancer since randomization. Tumors with AGAs (n=12) were compared with tumors without AGAs and non-profiled squamous cell carcinomas (non-AGAs+NP SCC, n=20).Results With a median follow-up of 60.2 months, the overall TF rate was 34.1% (15/44). Tumor molecular profiling was retrospectively obtained in 47.7% (21/44) of patients and select AGAs were identified in 12 patients: 5 epidermal growth factor receptor (EGFR), 2 KRAS, 1 ERBB2, and 1 BRAF mutations, 2 anaplastic lymphoma kinase (ALK) and 1 RET fusions. The median time to TF in patients with AGAs was 24.7 months (95% CI: 12.6 to 40.4), compared with not reached (95% CI: not evaluable (NE)–NE) in the non-AGAs+NP SCC group. The TF risk was higher in AGAs (HR: 5.51, 95% CI: 1.68 to 18.1), and lower in former/current smokers (HR: 0.24, 95% CI: 0.08 to 0.75). The odds of major pathological response were 4.71 (95% CI: 0.49 to 45.2) times higher in the non-AGAs+NP SCC group, and the median percentage of residual viable tumor was 72.5% in AGAs compared with 33.0% in non-AGS+NP SCC tumors.Conclusions Patients with NSCLC harboring select AGAs, including EGFR and ALK alterations, have a higher risk for TF, shorter median time to TF, and diminished pathological regression after neoadjuvant ICIs. The suboptimal efficacy of neoadjuvant chemotherapy-sparing, ICI-based regimens in this patient subset underscores the importance of tumor molecular testing prior to initiation of neoadjuvant ICI therapy in patients with resectable NSCLC.

Introduction: Responses to first-line programmed cell death protein 1 inhibition vary among patients with metastatic NSCLC and a programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) greater than or equal to 50%. We previously reported improved clinical outcomes to first-line programmed cell death protein 1 inhibition in patients with metastatic NSCLC with a PD-L1 TPS of greater than or equal to 90% versus 50% to 89% in a pilot study. Here, we report the three-year survival with first-line pembrolizumab and cemiplimab in two large independent cohorts of patients with PD-L1 TPS greater than or equal to 90% versus 50% to 89% and characterize genomic and immunophenotypic differences between these PD-L1 expression groups, which were largely unknown. Methods: We analyzed three-year outcomes of the following two independent cohorts: (1) a multicenter cohort of patients from four academic centers in the United States treated with pembrolizumab and (2) EMPOWER-Lung 1, randomized, phase III trial comparing first-line cemiplimab with chemotherapy. Tumor genomic profiling and multiplexed immunofluorescence were performed to evaluate genomic and immunophenotypic correlates of very high PD-L1 expression. Results: At three years of follow-up, progression-free survival (hazard ratio [HR], 0.69; p < 0.001) and overall survival (HR, 0.70; p < 0.01) to first-line commercial pembrolizumab were significantly improved in patients with a PD-L1 TPS greater than or equal to 90% versus 50% to 89%. In the EMPOWER-Lung 1, patients assigned to the cemiplimab arm with a PD-L1 TPS greater than or equal to 90% also had significant improvements in progression-free survival (HR, 0.53; p < 0.0001) and overall survival (HR, 0.63; p = 0.007) compared with those with a PD-L1 of 50% to 89%. Tumor genomic profiling of 553 NSCLC samples revealed that mutations in STK11 and SMARCA4 were significantly more frequent in tumors with a PD-L1 TPS of 50% to 89% compared with those with a PD-L1 TPS greater than or equal to 90% (Q < 0.15), whereas BRCA2 was enriched in NSCLC samples with a PD-L1 TPS greater than or equal to 90% (Q < 0.15). Multiplexed immunofluorescence on 93 NSCLC samples identified higher intratumoral CD8+PD1+ T cells (p = 0.02) in tumors with PD-L1 TPS greater than or equal to 90% versus 50% to 89%. Conclusion: Pembrolizumab and cemiplimab were found to have long-term survival benefit and favorable genomic and immunophenotypic profile in patients with advanced NSCLC with PD-L1 TPS greater than or equal to 90% compared with TPS 50% to 89%.

We are concerned with the existence and concentration of multi-bump solutions for the nonlinear Kirchhoff equation $ \begin{eqnarray*} -\left ( \varepsilon ^{2}a+\varepsilon b\displaystyle {\int}_{\mathbb{R}^{3} }\left | \nabla v \right | ^{2} \mathrm {d} x \right )\Delta v+\lambda v = K(x)\left | v \right |^{2\sigma }v,\,\,\,x\in\mathbb{R}^3 \end{eqnarray*} $ with an $ L^{2} $-constraint in the $ L^{2} $-subcritical case $ \sigma\in\left(0, \, \frac{2}{3}\right) $ and the $ L^{2} $-supercritical case $ \sigma\in\left(\frac{2}{3}, \, 2 \right). $ Here $ \lambda \in \mathbb{R} $ appears as a Lagrange multiplier, $ \varepsilon $ is a small positive parameter and $ K > 0 $ possesses several local maximum points. By employing the variational gluing method and the penalization technique, we prove the existence of multi-bump solutions that are concentrated at local maximum points of $ K $ for the problem above.

Abstract While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Abstract Background Corneal neovascularization (CoNV) threatens vision by disrupting corneal avascularity, however, current treatments, including pharmacotherapy and surgery, are hindered by limitations in efficacy and adverse effects. Minocycline, known for its anti-inflammatory properties, could suppress CoNV but faces challenges in effective delivery due to the cornea's unique structure. Therefore, in this study a novel drug delivery system using minocycline-loaded nano-hydroxyapatite/poly (lactic-co-glycolic acid) (nHAP/PLGA) nanoparticles was developed to improve treatment outcomes for CoNV. Results Ultra-small nHAP was synthesized using high gravity technology, then encapsulated in PLGA by a double emulsion method to form nHAP/PLGA microspheres, attenuating the acidic by-products of PLGA degradation. The MINO@PLGA nanocomplex, featuring sustained release and permeation properties, demonstrated an efficient delivery system for minocycline that significantly inhibited the CoNV area in an alkali-burn model without exhibiting apparent cytotoxicity. On day 14, the in vivo microscope examination and ex vivo CD31 staining corroborated the inhibition of neovascularization, with the significantly smaller CoNV area (29.40% ± 6.55%) in the MINO@PLGA Tid group (three times daily) than that of the control group (86.81% ± 15.71%), the MINO group (72.42% ± 30.15%), and the PLGA group (86.87% ± 14.94%) (p

Abstract The kinematic equivalent model of an existing ankle-rehabilitation robot is inconsistent with the anatomical structure of the human ankle, which influences the rehabilitation effect. Therefore, this study equates the human ankle to the UR model and proposes a novel three degrees of freedom (3-DOF) generalized spherical parallel mechanism for ankle rehabilitation. The parallel mechanism has two spherical centers corresponding to the rotation centers of tibiotalar and subtalar joints. Using screw theory, the mobility of the parallel mechanism, which meets the requirements of the human ankle, is analyzed. The inverse kinematics are presented, and singularities are identified based on the Jacobian matrix. The workspaces of the parallel mechanism are obtained through the search method and compared with the motion range of the human ankle, which shows that the parallel mechanism can meet the motion demand of ankle rehabilitation. Additionally, based on the motion-force transmissibility, the performance atlases are plotted in the parameter optimal design space, and the optimum parameter is obtained according to the demands of practical applications. The results show that the parallel mechanism can meet the motion requirements of ankle rehabilitation and has excellent kinematic performance in its rehabilitation range, which provides a theoretical basis for the prototype design and experimental verification.

Abstract A reliable, efficient and electrically-pumped Si-based laser is considered as the main challenge to achieve the integration of all key building blocks with silicon photonics. Despite the impressive advances that have been made in developing 1.3-μm Si-based quantum dot (QD) lasers, extending the wavelength window to the widely used 1.55-μm telecommunication region remains difficult. In this study, we develop a novel photonic integration method of epitaxial growth of III-V on a wafer-scale InP-on-Si (100) (InPOS) heterogeneous substrate fabricated by the ion-cutting technique to realize integrated lasers on Si substrate. This ion-cutting plus epitaxial growth approach decouples the correlated root causes of many detrimental dislocations during heteroepitaxial growth, namely lattice and domain mismatches. Using this approach, we achieved state-of-the-art performance of the electrically-pumped, continuous-wave (CW) 1.55-µm Si-based laser with a room-temperature threshold current density of 0.65 kA/cm−2, and output power exceeding 155 mW per facet without facet coating in CW mode. CW lasing at 120 °C and pulsed lasing at over 130 °C were achieved. This generic approach is also applied to other material systems to provide better performance and more functionalities for photonics and microelectronics.

Abstract The pressing demand for sustainable energy storage solutions has spurred the burgeoning development of aqueous zinc batteries. However, kinetics-sluggish Zn2+ as the dominant charge carriers in cathodes leads to suboptimal charge-storage capacity and durability of aqueous zinc batteries. Here, we discover that an ultrathin two-dimensional polyimine membrane, featured by dual ion-transport nanochannels and rich proton-conduction groups, facilitates rapid and selective proton passing. Subsequently, a distinctive electrochemistry transition shifting from sluggish Zn2+-dominated to fast-kinetics H+-dominated Faradic reactions is achieved for high-mass-loading cathodes by using the polyimine membrane as an interfacial coating. Notably, the NaV3O8·1.5H2O cathode (10 mg cm−2) with this interfacial coating exhibits an ultrahigh areal capacity of 4.5 mAh cm−2 and a state-of-the-art energy density of 33.8 Wh m−2, along with apparently enhanced cycling stability. Additionally, we showcase the applicability of the interfacial proton-selective coating to different cathodes and aqueous electrolytes, validating its universality for developing reliable aqueous batteries.

Surface structures and microstructures are of vital importance to the wetting behaviors and mechanical robustness of non-wetting surfaces. In this work, yttrium oxide coatings with different surface structures and microstructures were deposited via the solution precursor plasma spray (SPPS) process, powder plasma spray (PPS) process, and a newly-developed mesh shielding PPS process. The SPPS coatings showed porous microstructures and hierarchical surface structures, and thereby presented superhydrophobic behaviors. The PPS coatings showed dense lamellar microstructures and relatively flat surface topographies, resulting in mildly hydrophobic behaviors. The PPS coatings exhibited much higher mechanical robustness and more stable hydrophobicity under physical damage as compared to the SPPS coatings. The coatings deposited via the mesh shielding PPS process showed unique surface structures of conical pillars, endowing the coating with excellent hydrophobicity and high mechanical robustness. The conical-structured coatings showed quasi-superhydrophobic behaviors, and maintained relatively consistent hydrophobicity after abrasion. The effects of the microstructures and surface structures on the wetting behaviors and mechanical robustness of different coatings were comparatively investigated. The effects of the microstructures and surface structures on the wetting behaviors and mechanical robustness of different coatings were comparatively investigated. The change of wetting behaviors of coatings after different treatments was elaborated by correlating with the surface compositions. The work showed the wetting behaviors and mechanical robustness can be manipulated by tailoring the microstructures and surface structures in plasma spray processes.

IntroductionThe purpose of this study was to investigate the predictive factors of atrial fibrillation (AF) recurrence in patients after first-time radiofrequency catheter ablation (RFCA) and to develop a nomogram predictive model that can provide valuable information for determining the ablation strategy.MethodsIn total, 500 patients who had received first-time RFCA for AF were retrospectively enrolled in the study. The patients were divided into a training cohort (n = 300) and a validation cohort (n = 200) randomly at a 6:4 ratio. Lasso and multivariate logistic regression analyses were used to screen the predictors for AF recurrence during a 2-year follow-up. The C-index and a calibration plot were used to detect the discriminative ability and calibration of the nomogram. The performance of the nomogram was assessed compared with the APPLE score, CAAP-AF score, and MB-LATER score using the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), integrated discrimination index (IDI), and net reclassification index (NRI).ResultsA total of 78 patients experienced the recurrence of AF after first-time RFCA in the training cohort. The six strongest predictors for AF recurrence in the training cohort were persistent AF, duration of AF, left atrial diameter (LAD), estimated glomerular filtration rate (eGFR), N-terminal pro-brain natriuretic peptide (NT-proBNP), and autoantibody against M2-muscarinic receptor (anti-M2-R). Based on the above six variables, a nomogram prediction model was constructed with a C-index of 0.862 (95% CI, 0.815–0.909), while the C-index was 0.831 (95% CI, 0.771–0.890) in the validation cohort. DCA showed that this nomogram had greater net benefits compared with other models. Furthermore, the nomogram showed a noticeable improvement in predictive performance, sensitivity, and reclassification for AF recurrence compared with the APPLE score, CAAP-AF score, or MB-LATER score.ConclusionWe established a novel predictive tool for AF recurrence after the first-time RFCA during a 2-year follow-up period that could accurately predict individual AF recurrence.

The bilateral teleoperation system is susceptible to model parameter uncertainty and unknown disturbances in both the master and slave manipulators, resulting in instability and inaccuracies in the force and position tracking performance. To address these issues, a novel nonlinear model reference adaptive impedance controller has been designed to achieve coordinated force and position synchronization of dual manipulators. The adaptive control laws, based on sliding mode functions, have been designed to compensate for the uncertainty of the manipulator model. Furthermore, an adaptive estimation law has been employed to appraise the unknown upper bound of external disturbances. This ensures that the closed-loop model parameters of the dual manipulator converge to the reference impedance model respectively. Simultaneously, it enables the position error between the reference model response and the end-effector task space position to asymptotically converge to zero. To verify the effectiveness of the proposed controller, simulations have been conducted on the MATLAB platform and experiments on a single degree of freedom teleoperation system have been performed. The results demonstrate that the controller exhibits strong robustness and has the capability of force-position tracking ability.

IntroductionImproving photosynthetic use efficiency in dryland agroecosystems to sustain high agricultural yields is a key responsibility for ensuring food security.MethodsThis study was conducted in the regions on the semiarid Loess Plateau of China during 2018–2020. Dryland maize of Xianyu 335 comprised four modes: basic yield input (CK, plastic film mulching, 37500 plant.ha-1 of plant density and unfertilized), farmer input (FP, plastic film mulching, 45000 plant.ha-1 of plant density and inorganic nitrogen(N) and phosphate(P) fertilizer were 150kg.ha-1 and 90kg.ha-1), high yield and high-efficiency input (HH, full plastic-film mulching on double furrow, 67500 plant.ha-1 of plant density and N, P and organic manure(M) fertilizer were 230kg.ha-1, 140kg.ha-1 and 1500kg.ha-1), and super high yield input (SH, full plastic-film mulching on double furrow, 9000 plant.ha-1 of plant density and N, P and organic M fertilizer were 300kg.ha-1, 180kg.ha-1 and 7500kg.ha-1). The effects of different cultivation modes on yield, WUE, net photosynthetic rate(Pn), leaf area index(LAI), chlorophyll index(SPAD value) and root index were studied.ResultsThe results showed that the value average of yield and WUE for CK were 7790kg and 17480kg.ha-1 in three years. SH, HH and FP cultivation modes of yield and WUE was significant higher compared with CK cultivation mode (P

Bacterial infections and inadequate tissue regeneration capacity are prevalent issues in diabetic wounds, impeding the healing process. To solve these problems, a biomimetic hydrogel combined with bacterial cellulose (BC), recombinant human collagen type III (RHC), and ε-poly-L-Lysine (EPL) is fabricated by stepwise co-assembly technology. Owing to the RHC and EPL modifications of BC, the biomimetic hydrogel exhibited antibacterial effects and promoted fibroblast proliferation and angiogenesis, which accelerated the healing of diabetic wounds. Biomimetic hydrogels exhibit good mechanical properties and excellent water absorption, that can protect wounds and provide a moist environment. In addition, in vitro studies have shown that the hydrogels exhibit excellent antibacterial activity and biocompatibility. In vivo studies on diabetic wound healing have shown that biomimetic hydrogels can promote angiogenesis, accelerate collagen deposition, and re-epithelialize wound sites to promote wound healing. This study provides a new and promising strategy for the treatment of diabetic wounds.

ABSTRACT: As a highly infectious and contagious pathogen in chickens, infectious bronchitis virus (IBV) is currently grouped into nine genotypes (GI to GIX). However, the classification of serotypes of IBV is still not clear. In this study, 270 field strains of IBV were isolated from dead or diseased chicken flocks in eastern and southern China during January 2021 to April 2023. These isolated IBV strains could be classified into 2 genotypes, GI (including 5 lineages GI-1, GI-13, GI-19, GI-22, and GI-28) and GVI based on the complete S1 sequence. Further analysis showed that the GI-19, GI-13, GI-22, GI-28, and GVI were the dominant genotypes with the proportions of 61.48, 8.89, 8.89, 7.78, and 8.89% respectively, and the homology of S1 protein of these isolates ranged from 86.85 to 100% in GI-19, 92.22 to 100% in GI-13, 83.1 to 100% in GI-22, 94.81 to 100% in GI-28 and 90.0 to 99.8% in GVI, respectively. Moreover, cross-neutralization test with sera revealed that these isolates in GI-19 lineage could be classified into at least 3 serotypes according to the antigenic relationship. In addition, structure assay using PyMOL indicated that one mutation such as S120 in receptor binding site (RBD) of GI-19 might alter the antigenicity and conformation of S protein of IBV. Overall, our data demonstrate that not only multiple genotypes, but also multiple serotypes in a single genotype or lineage have been co-circulated in eastern and southern China, providing novel insights into the molecular evolution of the antigenicity of IBV and highlighting the significance of the selection of the dominant isolate for vaccine development in IBV endemic region.

The electromagnetic transient overvoltage in the substation is an important factor that affects the life of insulation equipment. For evaluate the economy and reliability of the insulation design of substation equipment, it is necessary to study and analyze the actual measured overvoltage waveforms in the substation. In this paper, firstly, the 3018 pieces of overvoltage data monitored in the 220 kV substation from 2018 to 2019 are preprocessed to obtain the required overvoltage waveform. Next, by analyzing and classifying the overvoltage data, four typical overvoltage waveforms suffered by the insulation equipment in the substation are extracted. Combined with the IEC60060 standard, the time parameters of the overvoltage waveform are selected and defined: wave-front time (Tf), half-value time (Thalf), main oscillation frequency (f), and attenuation constant (α). Further, statistical analysis is performed on the parameters of each waveform. The distribution law, distribution characteristics and distribution range of the parameters are obtained. Finally, the parameters of four typical overvoltage waveforms are summarized and compared, the cumulative distribution functions are obtained. This results can guide and optimize the insulation design of the insulation equipment in the substation, reduce design errors. It provide data support for the economy and reliability of insulation design.

Nasopharyngeal carcinoma with bone marrow metastasis presents a rare and challenging clinical scenario associated with exceedingly poor prognosis. While standard treatment regimens offer limited efficacy and tolerability in such cases, individualized approaches are increasingly necessary. We present the case of a 64-year-old male diagnosed with recurrent nonkeratinizing undifferentiated nasopharyngeal carcinoma with extensive bone marrow metastasis (rTxN0M1). Treatment was initiated with immunotherapy-based combination therapy, consisting of pembrolizumab and low-dose cisplatin, which resulted in an initial response. Subsequently, there was a transition to standard-dose nab-paclitaxel-cisplatin chemotherapy in combination with pembrolizumab, followed by maintenance therapy with pembrolizumab plus fruquintinib. The patient achieved a sustained response with renormalization of tumor markers, imaging findings, and bone biopsies, resulting in complete remission. This case highlights the successful management of nasopharyngeal carcinoma with extensive bone marrow metastasis through an individualized treatment approach incorporating immunotherapy.

Abstract Tumor mutational burden (TMB) and T‐cell receptor (TCR) might predict the response to immunotherapy in patients with non–small cell lung cancer (NSCLC). However, the predictive value of the combination of TMB and TCR was not clear. Targeted DNA and TCR sequencing were performed on tumor biopsy specimens. We combined TMB and TCR diversity into a TMB‐and‐TCR (TMR) score using logistic regression. In total, 38 patients with advanced NSCLC were divided into a discovery set (n = 17) and validation set (n = 21). A higher TMR score was associated with better response and longer progression‐free survival to immunotherapy in both the discovery set and validation set. The performance of TMR score was confirmed in the two external validation cohorts of 225 NSCLC patients and 306 NSCLC patients. Tumors with higher TMR scores were more likely to combine with LRP1B gene mutation (p = 0.027) and top 1% CDR3 sequences (p = 0.001). Furthermore, LRP1B allele frequency was negatively correlated with the top 1% CDR3 sequences (r = –0.55, p = 0.033) and positively correlated with tumor shrinkage (r = 0.68, p = 0.007). The TMR score could serve as a potential predictive biomarker for the response to immunotherapy in advanced NSCLC.

BackgroundIncreasing evidence suggests a correlation between intestinal microbiota and the gut-brain axis; however, the causal relationship between gut microbiota and postpartum depression (PPD) remains unclear.MethodsIn this study, a two-sample Mendelian randomization (MR) design was employed to analyze the GWAS data of gut microorganisms from the Mibiogen database and PPD data from the UK biobank. Various statistical methods, including inverse variance weighted, MR-Egger, weighted median, weighted model, and MR-PRESSO, were utilized to investigate the causal relationship between gut microbiota and PPD. Additionally, sensitivity analysis was conducted to assess the robustness of the findings.ResultsThrough MR analysis, it was found that phylum Actinobacteria (P=0.014, OR=0.971, 95% CI=0.948-0.994) and genus Holdemanella (P=0.023, OR=0.979, 95% CI=0.961-0.997) have protective effects on PPD, while the other two unknown genera, genus Unknown Ids 2001 (P=0.025, OR=0.972,95% CI=0.947-0.996), and genus Unknown Ids 2755 (P=0.012, OR=0.977, 95% CI=0.959-0.995) also has a protective effect on PPD. The sensitivity analysis results indicate that there is no heterogeneity or horizontal pleiotropy.ConclusionThis study has identified a causal association between Actinomycetota, Holdemanella, and PDD through MR analysis. These findings offer significant contributions to the development of personalized treatment approaches for PPD, encompassing interventions such as dietary modifications or microbiome interventions.

Abstract Livestock constitute the world’s largest anthropogenic source of methane (CH4), providing high-protein food to humans but also causing notable climate risks. With rapid urbanization and increasing income levels in China, the livestock sector will face even higher emission pressures, which could jeopardize China’s carbon neutrality target. To formulate targeted methane reduction measures, it is crucial to estimate historical and current emissions on fine geographical scales, considering the high spatial heterogeneity and temporal variability of livestock emissions. However, there is currently a lack of time-series data on city-level livestock methane emissions in China, despite the flourishing livestock industry and large amount of meat consumed. In this study, we constructed a city-level livestock methane emission inventory with dynamic spatial-temporal emission factors considering biological, management, and environmental factors from 2010 to 2020 in China. This inventory could serve as a basic database for related research and future methane mitigation policy formulation, given the population boom and dietary changes.

Abstract Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.

Dynamic simulation is widely applied in the real-time and realistic physical simulation field. How to achieve natural dynamic simulation results in real-time with small data sizes is an important and long-standing topic. In this paper, we propose a dynamic reconstruction and interpolation method grounded in physical principles for simulating dynamic deformations. This method replaces the deformation forces of the widely used eXtended Position-Based Dynamics (XPBD), which are traditionally derived from the gradient of the energy potential defined by the constraint function, with the elastic beam bending forces to more accurately represent the underlying deformation physics. By doing so, it establishes a mathematical model based on dynamic partial differential equations (PDE) for reconstruction, which are the differential equations involving both the parametric variable u and the time variable t. This model also considers the inertia forces caused by acceleration. The analytical solution to this model is then integrated with the XPBD framework, built upon Newton’s equations of motion. This integration reduces the number of design variables and data sizes, enhances simulation efficiency, achieves good reconstruction accuracy, and makes deformation simulation more capable. The experiment carried out in this paper demonstrates that deformed shapes at about half of the keyframes simulated by XPBD can be reconstructed by the proposed PDE-based dynamic reconstruction algorithm quickly and accurately with a compact and analytical representation, which outperforms static B-spline-based representation and interpolation, greatly shortens the XPBD simulation time, and represents deformed shapes with much smaller data sizes while maintaining good accuracy. Furthermore, the proposed PDE-based dynamic reconstruction algorithm can generate continuous deformation shapes, which cannot be generated by XPBD, to raise the capacity of deformation simulation.

Surface blending is an important topic in geometric modelling and is widely applied in computer-aided design and creative industries to create smooth transition surfaces. Among various surface blending methods, partial differential equation (PDE)-based surface blending has the advantages of effective shape control and exact satisfaction of blending boundary constraints. However, it is not easy to solve partial differential equations subjected to blending boundary constraints. In this paper, we investigate how to solve PDEs analytically and develop an analytical PDE-based method to achieve surface blending with C2 continuity. Taking advantage of elementary functions identified from blending boundary constraints, our proposed method first changes blending boundary constraints into a linear combination of the identified elementary functions. Accordingly, the functions for blending surfaces are constructed from these elementary functions, which transform sixth-order partial differential equations for C2 surface blending into sixth-order ordinary differential equations (ODEs). We investigate the analytical solutions of the transformed sixth-order ordinary differential equations subjected to corresponding blending boundary constraints. With the developed analytical PDE-based method, we solve C2 continuous surface blending problems. The surface blending example presented in this paper indicates that the developed method is simple and easy to use. It can be used to effectively control the shape of blending surfaces and at the same time exactly satisfy C2 continuous blending boundary constraints.

Conventional waterborne polyurethane (WPU) has poor water resistance and poor overall performance, which limits its application in outdoor coatings. A solution to this problem is urgently needed. The introduction of fluorine-containing groups can effectively improve the water resistance of WPU. In this study, a new fluorinated chain extender (HFBMA-HPA) synthesized by free radical copolymerization and epoxy resin (E-44) were used to co-modify WPU, and five waterborne fluorinated polyurethane (WFPU) emulsions with different fluorine contents were prepared by the self-emulsification method. The effects of HFBMA-HPA content on the emulsion particle properties, coating surface properties, mechanical properties, water resistance, thermal stability, and corrosion resistance were investigated. The results showed that the WFPU coating had excellent thermal stability, corrosion resistance, and mechanical properties. As the content of HFBMA-HPA increased from 0 wt% to 14 wt%, the water resistance of the WFPU coating gradually increased, the water contact angle (WCA) increased from 73° to 98°, the water absorption decreased from 7.847% to 3.062%, and the surface energy decreased from 32.8 mN/m to 22.6 mN/m. The coatings also showed impressive performances in the adhesion and flexibility tests in extreme conditions. This study provides a waterborne fluorinated polyurethane material with excellent comprehensive performance that has potential application value in the field of outdoor waterproof and anticorrosion coatings.

For advanced aircraft, the temperature environment inside the cabin is very severe due to the high flight speed and the compact concentration of the electronic equipment in the cabin. Accurately predicting the temperature environment induced inside the cabin during the flight of the aircraft can determine the temperature environment requirements of the onboard equipment inside the cabin and provide an accurate input for the thermal design optimization and test verification of the equipment. The temperature environment of the whole aircraft is divided into zones by the cluster analysis method; the heat transfer mechanism of the aircraft cabin is analyzed for the target area; and the influence of internal and external factors on the thermal environment is considered to establish the temperature environment prediction model of the target cabin. The coefficients of the equations in the model are parameterized to extract the long-term stable terms and trend change terms; with the help of the measured data of the flight state, the model coefficients are determined by a stepwise regression method; and the temperature value inside the aircraft cabin is the output by inputting parameters such as flight altitude, flight speed, and external temperature. The model validation results show that the established temperature environment prediction model can accurately predict the change curve of the cabin temperature during the flight of the aircraft, and the model has a good follow-up performance, which reduces the prediction error caused by the temperature hysteresis effect. For an aircraft, the estimated error is 2.8 °C at a confidence level of 95%. Engineering cases show that the application of this method can increase the thermal design requirements of the airborne equipment by 15 °C, increase the low-temperature test conditions by 17 °C, and avoid the problems caused by an insufficient design and over-testing. This method can accurately predict the internal temperature distribution of the cabin during the flight state of the aircraft, help designers determine the thermal design requirements of the airborne equipment, modify the thermal design and temperature test profile, and improve the environmental worth of the equipment.

Optimizing nitrogen (N) management based on the critical N dilution curve (NCDC) has been proven a precision fertilization strategy to diagnose crop N nutrition status. However, few explorations have been done to establish a NCDC for dryland maize under double ridge-furrow mulching, a planting system that has been widely adopted in semi-arid areas. Moreover, the influences of various rainfall conditions on NCDC remain unclear. Therefore, a 9-yr field nitrogen fertilization experiment from 2013 to 2021 (five nitrogen rates: 0, 75, 150, 225, and 300 kg N ha–1, respectively, represented by N0, N0.25, N0.50, N0.75, and N1) was applied to established the NCDC under two planting systems (Flatting without mulching, CK; Double ridge-furrow with mulching, DRFM) and two rainfall types (rainfall season and drought season). Compared with CK, DRFM significantly increased plant dry matter (PDM, 5.5–12.8%) and N concentration (4.2–6.9%), ultimately improved grain yield (+16.9%), cumulative nitrogen recovery efficiency (CNRE, +9.8%) and crop water productivity (WPc, +26.3%). Rainfall from jointing to silking stage was an important contributor to grain yield. Compared with rainy season, drought season triggered a 51.7% yield loss and 17.1% reduction in NRE, respectively. The NCDC of the CK and DRFM were Nc=36.6×PDM−0.37 and Nc=38.4×PDM−0.36 in rainy season, respectively; the NCDC of the CK and DRFM were Nc =34.5×PDM−0.27 and Nc=37.3×PDM−0.30 in drought season, respectively. The nitrogen nutrition index (NNI) and plant nitrogen requirement (PNR) based on the NCDC intuitively recorded the N nutritional status. The improved soil micro-environment, PDM and N uptake was recorded in N0.75 (225 kg N ha–1 yr–1) under wet season and in N0.50 (150 kg N ha–1 yr–1) under drought season, respectively, which brought an increase in crop productivity with a suitable N nutrition status. The findings highlight an accurate and effective method for assessing the N nutrition status of rainfed maize, and optimize fertilization strategy for sustainable production in semi-arid regions.

IntroductionMild traumatic brain injury (mTBI) is a prevalent health issue with significant effects on patients' lives. Understanding and attitudes toward mTBI among patients and their families can influence management and outcomes. This study aimed to assess knowledge and attitudes toward mTBI in these groups.MethodsA cross-sectional study was conducted at Zhejiang Hospital from July 1, 2023, to September 30, 2023. Patients with mTBI and their family members participated. Data were collected via an online questionnaire covering demographic information and mTBI knowledge and attitudes. Knowledge scores ranged from 0 to 20 and attitude scores from 8 to 40. Multivariate logistic regression identified factors influencing these scores.ResultsA total of 573 valid questionnaires were analyzed (289 males, 50.44%; 284 females, 49.56%). Among respondents, 258 (45.03%) had experienced a concussion. Mean knowledge and attitude scores were 11.00 ± 2.75 and 27.78 ± 4.07, respectively. Monthly per capita income of 5,000–10,000 RMB was negatively associated with knowledge and attitude scores (β = 0.160, 95% CI: [3.245 to 0.210], P = 0.026). Middle school education decreased the likelihood of positive attitudes toward mTBI (OR = 0.378, 95% CI: [0.1630.874], P = 0.023). mTBI due to falls was associated with increased likelihood of positive attitudes (OR = 3.588, 95% CI: [1.274–10.111], P = 0.016).DiscussionSignificant gaps in knowledge and attitudes toward mTBI exist among patients and their families, influenced by income and education levels. Personal experience with mTBI from falls correlates with more positive attitudes. These findings highlight the need for targeted educational interventions to improve understanding and attitudes, ultimately enhancing patient care and management. Comprehensive, accessible mTBI education is crucial for fostering positive attitudes and better knowledge among patients and their families.

IntroductionIn light of the public health burden of the COVID-19 pandemic, boosting the safety and immunogenicity of COVID-19 vaccines is of great concern. Numerous Traditional Chinese medicine (TCM) preparations have shown to beneficially modulate immunity. Based on pilot experiments in mice that showed that supplementation with Huoxiang Suling Shuanghua Decoction (HSSD) significantly enhances serum anti-RBD IgG titers after inoculation with recombinant SARS-CoV-2 S-RBD protein, we conducted this randomized, double-blind, placebo-controlled clinical trial aimed to evaluate the potential immunogenicity boosting effect of oral HSSD after a third homologous immunization with Sinovac’s CoronaVac SARS-CoV-2 (CVS) inactivated vaccine.MethodsA total of 70 participants were randomly assigned (1:1 ratio) to receive a third dose of CVS vaccination and either oral placebo or oral HSSD for 7 days. Safety aspects were assessed by recording local and systemic adverse events, and by blood and urine biochemistry and liver and kidney function tests. Main outcomes evaluated included serum anti-RBD IgG titer, T lymphocyte subsets, serum IgG and IgM levels, complement components (C3 and C4), and serum cytokines (IL-6 and IFN-γ). In addition, metabolomics technology was used to analyze differential metabolite expression after supplementation with HSSD.ResultsFollowing a third CVS vaccination, significantly increased serum anti-RBD IgG titer, reduced serum IL-6 levels, increased serum IgG, IgM, and C3 and C4 levels, and improved cellular immunity, evidenced by reduce balance deviations in the distribution of lymphocyte subsets, was observed in the HSSD group compared with the placebo group. No serious adverse events were recorded in either group. Serum metabolomics results suggested that the mechanisms by which HSSD boosted the immunogenicity of the CVS vaccine are related to differential regulation of purine metabolism, vitamin B6 metabolism, folate biosynthesis, arginine and proline metabolism, and steroid hormone biosynthesis.ConclusionOral HSSD boosts the immunogenicity of the CVS vaccine in young and adult individuals. This trial provides clinical reference for evaluation of TCM immunomodulators to improve the immune response to COVID-19 vaccines.

Accurate diagnoses are crucial in determining the most effective treatment across different cancers. In challenging cases, morphology-based traditional pathology methods have important limitations, while molecular profiling can provide valuable information to guide clinical decisions. We present a 35-year female with lung cancer with choriocarcinoma features. Her disease involved the right lower lung, brain, and thoracic lymph nodes. The pathology from brain metastasis was reported as “metastatic choriocarcinoma” (a germ cell tumor) by local pathologists. She initiated carboplatin and etoposide, a regimen for choriocarcinoma. Subsequently, her case was assessed by pathologists from an academic cancer center, who gave the diagnosis of “adenocarcinoma with aberrant expression of β-hCG” and finally pathologists at our hospital, who gave the diagnosis of “poorly differentiated carcinoma with choriocarcinoma features”. Genomic profiling detected a KRAS G13R mutation and transcriptomics profiling was suggestive of lung origin. The patient was treated with carboplatin/paclitaxel/ipilimumab/nivolumab followed by consolidation radiation therapy. She had no evidence of progression to date, 16 months after the initial presentation. The molecular profiling could facilitate diagnosing of challenging cancer cases. In addition, chemoimmunotherapy and local consolidation radiation therapy may provide promising therapeutic options for patients with lung cancer exhibiting choriocarcinoma features.

Abstract Background Personal history of cancer is an independent risk factor for lung cancer but is omitted from existing lung cancer screening eligibility criteria. In this study, we assess the lung cancer risk among cancer survivors and discuss potential implications for screening. Methods This was a retrospective, secondary analysis of data from the Surveillance, Epidemiology and End Results (SEER) registry and the MD Anderson Cancer Center (MDACC). We estimated the standardized incidence ratios (SIRs) for lung cancer by site of first primary cancer using data from SEER. We assessed the lung cancer risk among head and neck cancer survivors from MDACC using cumulative incidence and compared the risk ratios (RR) by individuals' screening eligibility status. Results Other than first primary lung cancer (SIR: 5.10, 95% CI: 5.01–5.18), cancer survivors in SEER with personal history of head and neck cancer (SIR: 3.71, 95% CI: 3.63–3.80) had the highest risk of developing second primary lung cancer, followed by bladder (SIR: 1.86, 95% CI: 1.81–1.90) and esophageal cancers (SIR: 1.78, 95% CI: 1.61–1.96). Head and neck cancer survivors had higher risk to develop lung cancer compared to the National Lung Screening Trial's subjects, (781 vs. 572 per 100,000 person‐years, respectively). Head and neck cancer survivors ineligible for lung cancer screening seen at MDACC had significantly higher lung cancer risk than head and neck cancer survivors from SEER (RR: 1.9, p

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

In response to the international appeal of developing low-carbon economy and realizing carbon peaking and neutrality goals, China has been exploring the construction of the carbon emissions trading market for years. Without the guidance of advanced technology, there would not be a low-carbon economy in the first place. Based on panel data of 30 provinces and cities in China from 2005 to 2020, this paper takes Beijing—which is the first pilot city in China—as the only treated group and uses the Synthetic Control Method to study the impact of the pilot policy on low-carbon technology innovation. The results show that, firstly, the number of low-carbon technology patents in Beijing increases significantly after the implementation of the pilot policy, proving a positive influence on technology innovation. Secondly, the policy effect has a certain time lag and is sensitive to the shock from both domestic and foreign carbon market, but this effect is gradually stable over time. This paper confirms that technological innovation is the key means of promoting the development of the low-carbon economy and calls on various carbon trading markets to pay attention to the internal mechanism of promoting low-carbon technology innovation to stimulate the vitality of market entities.

In bone-milling surgical procedures, the intense friction between the tool and bone material often results in high cutting temperatures, leading to the thermal necrosis of bone cells. This paper aims to investigate the effect of micro-texture on the tribological properties of YG8 cemented carbide in contact with bone. The main objective is to guide the design of tool surface microstructures to reduce frictional heat generation. To minimize experimental consumables and save time, numerical simulations are first conducted to determine the optimal machining depth for the texture. Subsequently, micro-textures with different shapes and pitches are prepared on the surface of YG8 cemented carbide. These textured samples are paired with bovine cortical bone pins featuring various bone unit arrangements, and friction and wear tests are conducted under physiological saline lubrication. The experimental results indicate that the appropriate shape and pitch of the micro-texture can minimize the coefficient of friction. The parallel arrangement of bone units exhibits a lower coefficient of friction compared to the vertical arrangement. This study holds significant implications for the design and fabrication of future micro-texture milling cutters.

Forests make an important contribution to the global carbon cycle and climate regulation. Caijiachuan watershed false acacia (Robinia pseudoacacia Linn.) plantation forests have been created for 30 years, but a series of problems have arisen due to the irrationality of the density involved at that time. To precisely assess the contribution of R. pseudoacacia plantations with different densities to this cycle, we measured the diameter at breast height (DBH), tree height (H), biomass, and carbon stocks in trees, shrubs, herbs, litter, and soil across different density ranges, denoted as D1 = 900–1400, D2 = 1401–1900, D3 = 1901–2400, D4 = 2401–2900, and D5 = 2901–3400 trees ha−1. In order to achieve the purpose of accurately estimating the biomass, carbon stocks and the contribution rate of each part in different densities of R. pseudoacacia plantations were measured. The results are as follows: (1) Both DBH and H decreased with increasing density, and field surveys were much more difficult and less accurate for H than DBH. Based on the two allometric growth models, it was found that the determination coefficient of the biomass model that incorporated both H and DBH (0.90) closely resembled that of the model using only DBH (0.89), with an error margin of only 0.04%. (2) At the sample scale, stand density significantly affected R. pseudoacacia stem biomass and total biomass. At the individual plant scale, stand density significantly affected R. pseudoacacia organ biomass. Increasing stand densities promoted the accumulation of vegetation biomass within the sample plot but did not improve the growth of individual R. pseudoacacia trees. The stem biomass constituted the majority of the total R. pseudoacacia biomass (58.25%–60.62%); the total R. pseudoacacia biomass represented a significant portion of the vegetation biomass (93.02%–97.37%). (3) The total carbon stock in the sample plots tended to increase with increasing stand density, indicating a positive correlation between density and the carbon stock of the whole plantation forest ecosystem. Hence, in future R. pseudoacacia plantations, appropriate densities should be selected based on specific objectives. For wood utilization, a planting density of 900–1400 trees ha−1 should be controlled. For carbon fixation, an initial planting density of 2900–3400 trees ha−1 should be selected for R. pseudoacacia. This study provides theoretical support for local forest management and how to better sequester carbon.

The Chinese government has implemented numerous ecological policies in Qinghai Province aimed at protecting and restoring the natural ecosystem. Yet, amid global climate change, the precise effects of these policies on ecological improvement remain ambiguous. There is an urgent need for a comprehensive evaluation of the effects of these policies at a regional scale and an analysis of the changes in policy implementation stages to optimize the strategic direction of regional ecological policies. In this study, using mathematical statistics and spatial analysis, we analysed the spatial and temporal characteristics of the Normalized Difference Vegetation Index (NDVI) in Qinghai Province from 2000 to 2023. Further, by systematically reviewing ten major ecological policies currently or previously implemented in the region, we explored the response of vegetation restoration to these policies through both horizontal and vertical evaluations by reasonably delineating the policy study sub-zones. The study identified distinct stages of policy implementation—regreening, stabilizing, and natural recovery—and correlated these stages with the efficacy of policy impacts. Our findings indicate significant vegetation coverage improvements across Qinghai Province over the past two decades, with all ecological policies positively influencing the environment. The main contribution of this study is that it comprehensively evaluates the impact of multiple ecological policies on vegetation restoration at the regional scale, providing a reference for the formulation and adjustment of subsequent ecological policies.

China is currently experiencing rapid expansion in its transportation land. To promote sustainable land use, accurately estimating transportation land demand is crucial. This study aims to develop a comprehensive framework for urban transportation land forecasting within the Yangtze River Economic Belt (YREB), providing support for optimizing regional land allocation. Employing methods such as meta-analysis, statistical analysis, and BP neural network analysis, this study forecasts the transportation land demand of 127 cities in the YREB. The study findings indicate that cities with high transportation land demand are mainly distributed in the middle and upper reaches of the Yangtze River. Moreover, the growth rate of transportation land in the upper reaches significantly outstrips that in the middle and lower reaches, suggesting a focus shift in transportation infrastructure construction toward the upper regions. Additionally, some cities within the YREB face a mismatch between the supply and demand of transportation land, necessitating proactive adjustments to their land supply plans to achieve a balance between supply and demand. The main contribution of this study is the development of a comprehensive and adaptable framework that guides the development of future strategies for optimal land allocation by forecasting transportation land demand at a regional level.