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Abstract Newly diagnosed patients with high-risk acute graft-versus-host disease (aGVHD) often experience poor clinical outcomes and low complete remission rates. Ruxolitinib with corticosteroids showed promising efficacy in improving response and failure free survival in our phase I study. This study (ClinicalTrials.gov: NCT04061876) sought to evaluate the safety and effectiveness of combining ruxolitinib (RUX, 5 mg/day) with corticosteroids (1 mg/kg/day methylprednisolone, RUX/steroids combined group) versus using methylprednisolone alone (2 mg/kg/day, steroids-only group). Newly diagnosed patients with intermediate- or high-risk aGVHD were included, with risk levels classified by either the Minnesota aGVHD Risk Score or biomarker assessment. Patients were randomized in a ratio of 1:1 into 2 groups: 99 patients received RUX combined with methylprednisolone, while the other 99 received methylprednisolone alone as the initial treatment. The RUX/steroids group showed a significantly higher overall response rate (ORR) on day 28 (92.9%) compared to the steroids-only group (70.7%, Odds Ratio [OR] = 5.8; 95% Confidence Interval [CI], 2.4–14.0; P

Relapsed/refractory acute myeloid leukemia (R/R-AML) has a poor prognosis. CD7 is expressed in leukemic cells in 30% of patients with AML but not in normal myeloid cells. Therefore, it can be a potential target for immunotherapy in patients with R/R-AML. Naturally selected CD7-directed chimeric antigen receptor T cells (CAR-T) have promising effects against AML based on xenotransplantation models. We report a R/R-AML case that achieved complete remission with incomplete hematologic recovery with naturally selected CD7 CAR-T therapy. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) as consolidation early after CAR T therapy, the patient experienced 12 months of disease-free survival to date. Our results confirmed that allogeneic hematopoietic stem cell transplantation after naturally selected CD7 CAR-T therapy can be a potential treatment for patients with CD7-positive R/R-AML.

Interferometry with computer-generated holograms (CGHs) is a unique solution for the highly accurate testing of large-aperture aspheric mirrors. However, no direct testing method for quantifying the measurement accuracy of CGHs has been developed. In this study, we developed a methodology for verifying CGH accuracy based on an element that is functionally equivalent to a large-aperture mirror in terms of accuracy verification. The equivalent element decreased the aperture by one or higher orders of magnitude, implying that the mirror could be replaced by a non-CGH technology in a comparison test. In this study, a 281 mm diamond-turned mirror was fabricated as the equivalent element of a 3.5 m aspheric mirror and measured using CGH and LUPHOScan profilometers. Surface error composition and root-mean-square (RMS) density analyses were performed. The methodology verification accuracy of the CGH was 4 nm (RMS) in the low- to mid-frequency bands, with a measured surface accuracy of approximately 10 nm (RMS). This methodology provides a feasible solution for CGH accuracy verification, ensuring high-accuracy and reliable testing of large-aperture aspheric mirrors.

Abstract Objectives The application of a growing rod technique can retain the growth and development potential of the spine and thorax while controlling the progression of scoliosis deformity. Theoretically, convex side short fusion combined with a concave side single growing rod technique can significantly reduce the asymmetric growth of the spine in the vertex region in most patients. However, the final clinical outcome of various techniques is yet to be clearly determined and compared between studies. Therefore, we compared the efficacy of these two growing rod techniques in treating early onset scoliosis. Methods In a retrospective study of 152 EOS patients seen between 2013.1 and 2019.12, 36 cases of EOS patients were selected for inclusion. Among the 36 cases, 11 cases were treated with convex side short fusion combined with a concave side single growing rod technique, group (A) The remaining 25 cases were treated with traditional bilateral growing rod technique, group (B) Age, gender, etiology, follow-up time, Cobb angle of main curve, T1-S1 height, coronal trunk shift, sagittal vertical axis (SVA), Cobb angle of thoracic kyphosis at last follow-up, and Cobb angle at proximal junction kyphosis of the first and last post-operation follow-up were recorded. In addition, internal fixation related complications, infection, nervous system complications were recorded as well. Results There was no statistically significant difference between group A and group B in preoperative age, Cobb angle of main curve, coronal trunk shift, T1-S1 height, SVA, Cobb angle of thoracic kyphosis (p > 0.05). However, at the last follow-up (Group A, mean 4.4 ± 1.01 years; Group B, mean 3.6 ± 0.01 years) the Cobb angle of the main curve was less and T1-S1 height greater in group A compared with group B (p 0.05). There was no statistically significant difference in the coronal imbalance ratio, thoracic kyphosis abnormality ratio, or the occurrence PJK ratio between group A and group B at the last follow-up (p > 0.05), but the sagittal imbalance ratio and internal fixation abnormality ratio were higher in group A than in the group B (p

Abstract Background Mesenchymal stem/stromal cells (MSCs) have been acknowledged as the most important stromal cells in the bone marrow (BM) microenvironment for physiologic hematopoiesis and the concomitant hematologic malignancies. However, the systematic and detailed dissection of the biological and transcriptomic signatures of BM-MSCs in multiple myeloma (MM) are largely unknown. Methods In this study, we isolated and identified BM-MSCs from 10 primary MM patients and 10 healthy donors (HD). On the one hand, we compared the multifaceted biological characteristics of the indicated two BM-MSCs, including biomarker expression pattern, multilineage differentiation potential, stemness and karyotyping, together with the cellular vitality and immunosuppressive property. On the other hand, we took advantage of RNA-SEQ and bioinformatics analysis to verify the similarities and differences at the transcriptomic level between MM-MSCs and HD-MSCs. Results As to biological phenotypes and biofunctions, MM-MSCs revealed conservation in immunophenotype, stemness and differentiation towards adipocytes and chondrocytes with HD-MSCs, whereas with impaired osteogenic differentiation potential, cellular vitality and immunosuppressive property. As to transcriptomic properties, MM-MSCs revealed multidimensional alterations in gene expression profiling and genetic variations. Conclusions Overall, our date systematic and detailed reflected the multifaceted similarities and variations between MM-MSCs and HD-MSCs both at the cellular and molecular levels, and in particular, the alterations of immunomodulation and cellular viability of MM-MSCs, which wound benefit the further exploration of the pathogenesis and new drug application (NDA) of multiple myeloma from the view of BM-MSCs.

Extraction of color and texture features of buildings from high-resolution remote sensing images often encounters the problems of interference of background information and varying target scales. In addition, most of the current attention mechanisms focus on building key feature selection for building extraction optimization, but ignore the influence of the complex background. Hence, we propose incorporating a novel reverse attention module into the network. The innovative module enables the model to selectively extract crucial building features while suppressing the impact of intricate background noise. It mitigates the influence of uniform spectral and structurally similar heterogeneous background targets on building segmentation and extraction. As a result, the overall generalizability of the model is improved. The reverse attention can also emphasize and amplify the specific details pertaining to the boundaries of the target. Furthermore, we couple a new multi-branch convolution block into the encoder, integrating dilated convolutions with multiple dilation rates. Compared to other methods that use only one multi-scale module to extract multi-scale information from high-level features, we use different receptive field convolutions to simultaneously capture multi-scale targets from multi-level features, effectively improving the ability of the model to extract multi-scale building features. The experimental findings demonstrate that our proposed multi-branch reverse attention semantic segmentation network achieves IoU of 90.59% and 81.79% on the well-known WHU building and Inria aerial image datasets, respectively.

Nanotechnology has attracted extensive attention in the diagnosis and treatment of cancer. Therefore, the research aimed at developing new nanomaterials and exploring their applications in biomedicine has attracted more attention. In this study, Bi2S3-Au nanoclusters (Bi2S3-AuNCs) as fluorescence/infrared thermal imaging-guided photothermal therapy (PTT) was prepared for the first time. It was achieved in a facile and mild way by optimizing the amount of Bi3+ and Au3+ using bovine serum albumin (BSA) as reducer and stabilizer. The as-prepared Bi2S3-AuNCs with special morphology showed high stability, excellent biocompatibility and good photostability. Apart from these, it also can accumulate at tumor sites and exhibit considerable fluorescence/infrared thermal imaging-guided PTT. Bi2S3-AuNCs nanoparticles integrate imaging and therapeutic functions into an advanced application platform, which provides the possibility to build a novel nano-cancer diagnosis and treatment platform.

Excessive nitrogen (N) fertilization and irrigation prevail in irrigated agriculture worldwide. However, little information is available that systematically evaluates grain yield, plant N uptake, residual soil NO3−-N (RSN), and N leaching under different irrigation–N regimes in an irrigated maize production system. To address such agronomic and environmental issues, a 6-year in situ lysimeter field trial was conducted in the Hetao Irrigation District of China with five treatments: 1) conventional irrigation (3,900 m3/ha) and local farmer fertilizer N rate (490 kg ha−1) (CON); 2) conventional irrigation and the recommended fertilizer N rate (420 kg ha−1) (RN); 3) deficit irrigation (2,730 m3/ha) and the recommended fertilizer N rate (SRN); 4) deficit irrigation and the recommended fertilizer N rate (with ∼ 10 % organic fertilizer N substitution) (SMN); and 5) conventional irrigation and controlled-release N fertilizer (270 kg ha−1) (CRF). Maize yield was not significantly different across treatments in 2015–2020. Averaged across years, SMN, SRN, and CRF significantly increased plant N uptake compared with that in CON by 28.84 %, 19.15 %, and 17.53 %, respectively. Residual soil NO3−-N at 0–90 cm was ranked as SRN > CON ≈ SMN > RN > CRF, whereas cumulative N in leachate from 2015–2020 (Nloss) in CON was 86.2 % to 187.1 % higher than that in other treatments. The Nloss in SRN was equivalent to that in RN and SMN, but Nloss in SMN decreased significantly compared with that in RN, indicating additive benefits of deficit irrigation and organic input on reducing N leaching. Structural equation modelling revealed that irrigation had greater effects on plant N uptake than those of fertilization, whereas N rate had a greater total effect on N leaching than that of irrigation. Overall, rampant excessive irrigation and N fertilization by farmers can be substantially reduced while maintaining grain yield and mitigating N leaching loss, with further benefits gained by applying controlled-release N fertilizer and manure in irrigated maize production.

Whether mudstone is rich in or free of organic matter has a great influence on the occurrence of water. Comparing different types of water in organic-rich and organic-free mudstones is helpful for further understanding the role of water in hydrocarbon generation. Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) combined with mass spectrometry (MS) afford the opportunity to identify the mass change, reactions and products of the sample in a real-time monitored heating process. This study compared the pyrolysis characteristics of an organic-rich mudstone (CN1) and an organic-free mudstone (CW1) by using the TGA/DTA-MS method to estimate the content of different types of H2O and CO2 in organic-rich mudstones. The results show that the mass changes in CN1 and CW1 can be divided into the three thermogravimetric (TG) stages of 0°C–200°C, 200°C–650°C, and 650°C–900°C, while the peak temperatures of H2O and CO2 obtained through MS are different for CN1 and CW1. The differences in mineral components and organic matter between CN1 and CW1 suggest that the MS peaks of H2O and CO2 in CW1 are mainly influenced by clay and carbonate minerals, and that those of CN1 are also influenced by organic matter. In addition, quantification equations for CO2 and H2O contents from both the organic and inorganic origin of the organic-rich mudstone can be established by using the MS peak area of CO2 and H2O, mass loss in TGA and the mineral composition of the organic-free mudstone. This work provides useful insights for further understanding the hydrocarbon generation mechanism, as well as quantifying different types of water in organic-rich mudstones.

Seed size (SS) constitutes a pivotal trait in watermelon breeding. In this study, we present findings from an examination of two watermelon accessions, namely, BW85 and F211. Seeds from BW85 exhibited a significant enlargement compared to those of F211 at 13 days after pollination (DAP), with the maximal disparity in seed length and width manifesting at 17 DAP. A comprehensive study involving both metabolic and transcriptomic analyses indicated a significant enrichment of the ubiquinone and other terpenoid-quinone biosynthesis KEGG pathways. To detect the genetic region governing seed size, a BSA-seq analysis was conducted utilizing the F2 (BW85 × F211) population, which resulted in the identification of two adjacent QTLs, namely, SS6.1 and SS6.2, located on chromosomes 6. SS6.1 spanned from Chr06:4847169 to Chr06:5163486, encompassing 33 genes, while SS6.2 ranged from Chr06:5379337 to Chr06:5419136, which included only one gene. Among these genes, 11 exhibited a significant differential expression between BW85 and F211 according to transcriptomic analysis. Notably, three genes (Cla97C06G113960, Cla97C06G114180, and Cla97C06G114000) presented a differential expression at both 13 and 17 DAP. Through annotation, Cla97C06G113960 was identified as a ubiquitin-conjugating enzyme E2, playing a role in the ubiquitin pathway that mediates seed size control. Taken together, our results provide a novel candidate gene influencing the seed size in watermelon, shedding light on the mechanism underlying seed development.

The micro-mechanical properties of asphalt surfaces are significantly impacted by short-term aging during construction and long-term aging in service. This, in turn, affects macroscopic characteristics such as asphalt-aggregate adhesion and water stability of asphalt mixtures. The study investigated different aging processes had different impacts on the micromechanical properties of the asphalt on the surface. The short-term aging process had the most significant effects, while the subsequent long-term aging had similar but less important effects. The adhesion, surface energy, and Young's modulus of five different types of asphalt using atomic force microscopy (AFM) in their original state, after short-term aging through the Rolling Thin Film Oven Test (RTFOT), and after long-term aging through the RTFOT+Pressure Aging Vessel (PAV). The results showed that ZH and SK asphalts had a distinct ''bee structure'', and aging had varying effects on adhesion, surface energy, and Young's modulus in different areas (peak, valley, and other region). Before and after asphalt aging, the adhesion and surface energy approximately followed the order other region > peak > valley, while Young's modulus approximately followed the peak>valley> other region. This indicates that the bumpy ''bee structure'' does not always correspond to higher modulus or lower adhesion. It was also found that ZH asphalt and SK asphalt with a ''bee structure'' exhibited better aging resistance compared to KL asphalt without a ''bee structure''. The study also revealed that aging led to decreased adhesion and surface energy, while increasing Young's modulus. This finding indicates that as asphalt ages, adhesion decreases and asphalt elasticity increases. Additionally, it was observed that the modified asphalt showed less change in adhesion, surface energy, and Young's modulus after aging compared to the matrix asphalt, indicating that SBS modifiers contribute to improving the aging resistance of asphalt. These results will provide a good reference for understanding the microscopic changes in asphalt aging properties.

Abstract As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long‐term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi‐channel microfluidic‐based plasmonic fiber‐optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold‐coated, highly‐tilted fiber Bragg grating (TFBG) and a custom‐developed microfluidics. TFBG excites a high‐density, narrow‐cladding‐mode spectral comb that overlaps with the broad absorption of surface plasmons for high‐precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in‐parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30–170 pg mL−1, which is one order of magnitude below the clinical cut‐off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi‐channel microfluidics enables simultaneous detection of multiple biomarkers using sub‐µL sample volumes, as well as combining initial binding rate and real‐time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi‐parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large‐scale diagnosis of diseases at early stage.

Abstract. Background:. Pathological scars are a disorder that can lead to various cosmetic, psychological, and functional problems, and no effective assessment methods are currently available. Assessment and treatment of pathological scars are based on cutaneous manifestations. A two-photon microscope (TPM) with the potential for real-time non-invasive assessment may help determine the under-surface pathophysiological conditions in vivo. This study used a portable handheld TPM to image epidermal cells and dermal collagen structures in pathological scars and normal skin in vivo to evaluate the effectiveness of treatment in scar patients. Methods:. Fifteen patients with pathological scars and three healthy controls were recruited. Imaging was performed using a portable handheld TPM. Five indexes were extracted from two dimensional (2D) and three dimensional (3D) perspectives, including collagen depth, dermo-epidermal junction (DEJ) contour ratio, thickness, orientation, and occupation (proportion of collagen fibers in the field of view) of collagen. Two depth-dependent indexes were computed through the 3D second harmonic generation image and three morphology-related indexes from the 2D images. We assessed index differences between scar and normal skin and changes before and after treatment. Results:. Pathological scars and normal skin differed markedly regarding the epidermal morphological structure and the spectral characteristics of collagen fibers. Five indexes were employed to distinguish between normal skin and scar tissue. Statistically significant differences were found in average depth (t = 9.917, P

To address the limitations of deep learning models in detecting aerial insulator images from Unmanned Aerial Vehicles, we present a framework dubbed DP-FedIOD, which utilizes differential privacy and federated learning techniques for identifying the aerial insulators. It tackles the issue posed by current algorithms for inspecting insulators, which employ horizontal anchor frames and are incapable of precisely identifying both insulators and their defective parts. In addition, this study addresses the issue of insulator data being safeguarded by laws and policies that impede its wide-scale collection and dissemination among electric power companies enterprises, resulting in insufficient data volume to train deep learning models. In DP-FedIOD, we have improved the YOLOv5 algorithm by refining its head structure and loss function for directional detection of insulators and their defective parts. Additionally, an attention mechanism module has been incorporated into its backbone to enhance feature extraction capabilities. Furthermore, DP-FedIOD collaboratively trains the global model through federated learning. To prevent privacy leakage in the federated learning process, we also incorporate Laplace noise according to the differential privacy mechanism before uploading the weight information. The experimental outcomes demonstrate that the improved YOLOv5 model attains a mAP@0.5 metric of 95.00%, while DP-FedIOD achieves over 75.10% and 77.90% in precision and recall, respectively. These results indicate that DP-FedIOD has significant practical value in constructing an intelligent grid equipment detection system.

Existing studies on the vulnerability assessment of ecological drought often focus on analyzing vegetation phenotypic characteristics, overlooking the impact of drought on ecosystem services. This study proposes an ecosystem vulnerability assessment method under ecological drought stress from the perspective of ecosystem service value (ESV), considering the characteristics and interactions of hazard-causing factors and hazard-bearing bodies. The spatiotemporal evolution of ecological drought, the spatial characteristics of ecosystem vulnerability, and the vulnerability characteristics of different ecosystem types in the North China region from 1991 to 2021 were evaluated. The results showed that: (1) ecological drought exhibited a trend of intensification followed by alleviation, with the most severe droughts occurring between 2002 and 2011, affecting up to 64.3% of the region; (2) ESV was mainly influenced by vegetation cover and precipitation gradients, displaying a spatial pattern of high values in the southeast and low values in the northwest, with total ESV averaging CNY 18.23 trillion; (3) grasslands exhibited higher sensitivity to drought compared to forests, and the sensitivity was higher in summer and autumn than in winter and spring. This method assessed the vulnerability of ecological drought from the perspective of ecosystem services, providing a new approach for a more comprehensive understanding of the impact of drought on ecosystem service functions.

Abstract The magnetic hyperthermia‐based combination therapy (MHCT) is a powerful tumor treatment approach due to its unlimited tissue penetration depth and synergistic therapeutic effect. However, strong magnetic hyperthermia and facile drug loading are incompatible with current MHCT platforms. Herein, an iron foam (IF)‐drug implant is established in an ultra‐facile and universal way for ultralow‐power MHCT of tumors in vivo for the first time. The IF‐drug implant is fabricated by simply immersing IF in a drug solution at an adjustable concentration for 1 min. Continuous metal structure of IF enables ultra‐high efficient magnetic hyperthermia based on eddy current thermal effect, and its porous feature provides great space for loading various hydrophilic and hydrophobic drugs via “capillary action”. In addition, the IF has the merits of low cost, customizable size and shape, and good biocompatibility and biodegradability, benefiting reproducible and large‐scale preparation of IF‐drug implants for biological application. As a proof of concept, IF‐doxorubicin (IF‐DOX) is used for combined tumor treatment in vivo and achieves excellent therapeutic efficacy at a magnetic field intensity an order of magnitude lower than the threshold for biosafety application. The proposed IF‐drug implant provides a handy and universal method for the fabrication of MHCT platforms for ultralow‐power combination therapy.

Abstract Background Short stature, amelogenesis imperfecta, and skeletal dysplasia with scoliosis is a rare, autosomal recessive, skeletal disorder first described in 2018. This syndrome starts with pre- and postnatal developmental delay, and gradually presents with variable facial dysmorphisms, a short stature, amelogenesis imperfecta, and progressive skeletal dysplasia affecting the limbs, joints, hands, feet, and spine. Case presentation We identified a homozygous novel nonsense mutation in exon 1 of SLC10A7 (NM_001300842.2: c.100G > T / p.Gly34*) segregating with the typical disease phenotype in a Han Chinese family. We reviewed the 12-year surgical treatment history with seven interventions on spine. Conclusion To date, only 12 cases of the SLC10A7 mutation have been reported, mainly from consanguineous families. Our patient showed a relatively severe and broad clinical phenotype compared with previously reported cases. In this patient, annual check-ups and timely surgeries led to a good outcome.

Abstract. Background:. Observational research has reported that systemic lupus erythematosus (SLE) is related to common female hormone-dependent cancers, but the underlying causal effect remains undefined. This study aimed to explore the causal association of these conditions by Mendelian randomization (MR) analysis. Methods:. We selected instrumental variables for SLE from genome-wide association studies (GWASs) conducted in European and East Asian populations. The genetic variants for female malignant neoplasms were obtained from corresponding ancestry GWASs. We utilized inverse variance weighted (IVW) as the primary analysis, followed by sensitivity analysis. Furthermore, we conducted multivariable MR (MVMR) to estimate direct effects by adjusting for the body mass index and estradiol. Finally, we implemented reverse direction MR analysis and gave a negative example to test the reliability of MR results. Results:. We found SLE was significantly negatively associated with overall endometrial cancer risk (odds ratio [OR] = 0.961, 95% confidence interval [CI] = 0.935–0.987, P = 3.57E−03) and moderately inversely related to endometrioid endometrial cancer (ENEC) (OR = 0.965, 95% CI = 0.936–0.995, P = 0.024) risk in the European population by IVW. We replicated these results using other MR models and detected a direct effect by MVMR (overall endometrial cancer, OR = 0.962, 95% CI = 0.941–0.983, P = 5.11E−04; ENEC, OR = 0.964, 95% CI = 0.940–0.989, P = 0.005). Moreover, we revealed that SLE was correlated with decreased breast cancer risk (OR = 0.951, 95% CI = 0.918–0.986, P = 0.006) in the East Asian population by IVW, and the effect was still significant in MVMR (OR = 0.934, 95% CI = 0.859–0.976, P = 0.002). The statistical powers of positive MR results were all >0.9. Conclusion:. This finding suggests a possible causal effect of SLE on the risk of overall endometrial cancer and breast cancer in European and East Asian populations, respectively, by MR analysis, which compensates for inherent limitations of observational research.

Abstract Adsorption‐based carbon capture has been recognized as an attractive method for mitigating global warming. Metal–organic frameworks (MOFs) are promising candidate adsorbents for this purpose due to their high adsorption uptake and selectivity for carbon dioxide. However, in real‐world applications, such as direct air capture, the presence of moisture in the feed gas may pose a grand challenge for CO2 adsorption in MOFs. This paper aims to address the issue of water–CO2 co‐adsorption in MOFs and present screening criteria for selecting MOFs that preferentially adsorb CO2 under humid conditions. First, we uncover a comprehensive overview of CO2–water co‐adsorption characteristics of various MOFs. Then, the high‐throughput screening methods are summarized. Both computational and experimental efforts have been dedicated to identify the promising MOFs for humid CO2 capture. According to the screening results and adsorption mechanism, the optimal preparation strategies are proposed to modulate the effect of water on CO2 uptake in MOFs. Finally, current MOF‐based CO2 capture prototypes are presented to evaluate their practical feasibility and performance. This work could offer valuable guidance for the development and application of MOFs for CO2 capture in the presence of water and inspire further research in this field.

Abstract Background Aponermin, a circularly permuted tumor necrosis factor-related apoptosis-inducing ligand, is a potential death receptor 4/5-targeted antitumour candidate. Previous phase 1/2 studies have demonstrated the efficacy of aponermin in patients with relapsed or refractory multiple myeloma (RRMM). To confirm the superiority of aponermin plus thalidomide and dexamethasone (aponermin group) over placebo plus thalidomide and dexamethasone (placebo group) in RRMM, a randomized, double-blinded, placebo controlled phase 3 trial was performed. Methods Four hundred seventeen patients with RRMM who had previously received at least two regimens were randomly assigned (2:1) to receive aponermin, thalidomide, and dexamethasone or placebo, thalidomide, and dexamethasone. The primary endpoint was progression-free survival (PFS). Key secondary endpoints included overall survival (OS) and overall response rate (ORR). Results A total of 415 patients received at least one dose of trial treatment (276 vs. 139). The median PFS was 5.5 months in the aponermin group and 3.1 months in the placebo group (hazard ratio, 0.62; 95% confidence interval [CI], 0.49–0.78; P

Given the problem that the code slice used by existing deep learning-based vulnerability sniffer methods could not comprehensively encompass the subtle characteristics between vulnerability classes, and a single deep learning sniffer model had insufficient ability to learn long context-dependent information between cross-file and cross-function code statements, a multi-type source code vulnerability sniffer method was proposed.Firstly, fine-grained two-level slices containing the types of vulnerabilities were extracted based on the control dependency and data dependency information in program dependency graph.Secondly, the two-level slices were transformed into initial feature vector.Finally, a fusion model of deep learning vulnerability sniffer suitable for two-level slices was constructed to achieve accurate vulnerability detection of multi-type source code.The experimental results on multiple synthetic datasets and two real datasets show that the proposed method outperforms the existing multi-type source code vulnerability sniffer methods.

With the rapid development of the unmanned aerial vehicles (UAVs) industry, there is increasing demand for UAV surveillance technology. Automatic Dependent Surveillance-Broadcast (ADS-B) provides accurate monitoring of UAVs. However, the system cannot encrypt messages or verify identity. To address the issue of identity spoofing, radio frequency fingerprinting identification (RFFI) is applied for ADS-B transmitters to determine the true identities of UAVs through physical layer security technology. This paper develops an ensemble learning ADS-B radio signal recognition framework. Firstly, the research analyzes the data content characteristics of the ADS-B signal and conducts segment processing to eliminate the possible effects of the signal content. To extract features from different signal segments, a method merging end-to-end and non-end-to-end data processing is approached in a convolutional neural network. Subsequently, these features are fused through EL to enhance the robustness and generalizability of the identification system. Finally, the proposed framework’s effectiveness is evaluated using collected ADS-B data. The experimental results indicate that the recognition accuracy of the proposed ELWAM-CNN method can reach up to 97.43% and have better performance at different signal-to-noise ratios compared to existing methods using machine learning.

In this paper, a quantitative ground risk assessment mechanism is proposed in which urban ground features are extracted based on high-resolution data in a satellite image when unmanned aerial vehicles (UAVs) operate in urban areas. Ground risk distributions are estimated and a risk map is constructed with a multi-layer method considering the comprehensive risk imposed by UAV operations. The urban ground feature extraction is first implemented by employing a K-Means clustering method to an actual satellite image. Five main categories of the ground features are classified, each of which is composed of several sub-categories. Three more layers are then obtained, which are a population density layer, a sheltering factor layer, and a ground obstacle layer. As a result, a three-dimensional (3D) risk map is formed with a high resolution of 1 m × 1 m × 5 m. For each unit in this risk map, three kinds of risk imposed by UAV operations are taken into account and calculated, which include the risk to pedestrians, risk to ground vehicles, and risk to ground properties. This paper also develops a method of the resolution conversion to accommodate different UAV operation requirements. Case study results indicate that the risk levels between the fifth and tenth layers of the generated 3D risk map are relatively low, making these altitudes quite suitable for UAV operations.

Traditional methods for testing aspheric optical lenses struggle to achieve point-by-point testing across the full aperture of the lens. To facilitate the full-aperture, high-precision, and rapid testing of aspheric optical lenses, a power testing method of lenses based on the transmission phase deflectometric technique was employed. This method determines the phase deviation of light caused by the lens, thereby fitting the transmission wavefront and quickly detecting the power distribution information of the lens. This paper constructs a power testing model based on the phase deflectometric technique, proposes a calibration method that combines DLT (direct linear transformation) and pinhole models to reduce system errors, and combines phase extraction and wavefront fitting for experimental verification. The experimental results are compared with those obtained from the commercial visual lens mapper (VM-2000). The central errors of spherical power and cylindrical power are 1% and 0.7%, respectively. This provides a reliable method for the full-aperture, high-precision, and rapid testing of aspheric optical lenses.

Heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria are the key functional microorganisms needed to achieve simultaneous nitrification and denitrification (SND). In this study, 25 strains of HN-AD bacteria were successfully isolated from a stable landfill leachate biochemical treatment system, of which 10 strains belonged to Firmicutes and 15 strains belonged to Proteobacteria. Bacillus subtilis F4 and Alcaligenes faecalis P4 displayed good tolerance at a wide range of ammonia nitrogen (NH4+-N) concentrations. When the C/N ratio was 20, the removal rates of ammonia nitrogen were 90.1% and 89.5%, and the chemical oxygen demand (COD) removal rates were 92.4% and 93.9%, respectively. The napA gene encoding periplasmic nitrate reductase (Nap) and the nirS gene encoding nitrite reductase (Nir) were detected, and nitrogen balance showed assimilation and HN-AD was the main nitrogen metabolism mode in both strains. The use of immobilization materials could increase removal rate of ammonia nitrogen by 21.1% and 29.6%, respectively. The research results of this work can provide theoretical basis and technical support for the practical application of HN-AD bacteria to enhance the treatment of high ammonia nitrogen wastewater with high efficiency and low consumption.

In view of the low degree of mechanization and poor quality of harvesting of edible sunflower after drying, an in situ bionic harvesting device was designed, which can achieve low-loss harvesting of edible sunflower without removing the edible sunflower disc. According to the physical characteristics of sunflower stalks in the field, influencing factors of in situ low-loss feeding were obtained, and the structural parameters of the in situ feeding mechanism were determined. Based on bionic technology and static analysis, the influencing factors on the performance of the bionic threshing mechanism were obtained. By analyzing the mechanical characteristics of edible sunflower seed, the operation parameters of the seed collection mechanism were determined. Based on the structural analysis results of the harvesting device, a response surface optimization test was carried out. The test results show that when the average rotation speed of the bionic loosening roller was 113.57 rpm, the average rotation speed of the simulated artificial striking roller was 230.80 rpm, the average forward speed of the harvesting device was 0.58 m/s, the working quality of the harvesting device was the best, the seed loss rate was 2.12%, and the edible sunflower disc threshing rate was 98.96%. A field verification test further confirms that under the optimal working parameters, the relative deviation between test indexes and response surface optimization test results was less than 2%. During the operation process, the movement of key components of the harvesting device was coordinated and stable. The research results can provide new ideas for the mechanized harvesting of the edible sunflower disc after drying.

The integration of biomedical imaging techniques with advanced data analytics is at the forefront of a transformative era in healthcare [...]

The journal retracts the article “Inhibition of SDF-1α/CXCR4 Signalling in Subchondral Bone Attenuates Post-Traumatic Osteoarthritis” [...]

Artificial intelligence has been applied to medical diagnosis and decision-making but it has not been used for classification of Class III malocclusions in children. Objective: This study aims to propose an innovative machine learning (ML)-based diagnostic model for automatically classifies dental, skeletal and functional Class III malocclusions. Methods: The collected data related to 46 cephalometric feature measurements from 4–14-year-old children (n = 666). The data set was divided into a training set and a test set in a 7:3 ratio. Initially, we employed the Recursive Feature Elimination (RFE) algorithm to filter the 46 input parameters, selecting 14 significant features. Subsequently, we constructed 10 ML models and trained these models using the 14 significant features from the training set through ten-fold cross-validation, and evaluated the models’ average accuracy in test set. Finally, we conducted an interpretability analysis of the optimal model using the ML model interpretability tool SHapley Additive exPlanations (SHAP). Results: The top five models ranked by their area under the curve (AUC) values were: GPR (0.879), RBF SVM (0.876), QDA (0.876), Linear SVM (0.875) and L2 logistic (0.869). The DeLong test showed no statistical difference between GPR and the other models (p > 0.05). Therefore GPR was selected as the optimal model. The SHAP feature importance plot revealed that he top five features were SN-GoMe (the ratio of the length of the anterior skull base SN to that of the mandibular base GoMe), U1-NA (maxillary incisor angulation to NA plane), Overjet (the distance between two lines perpendicular to the functional occlusal plane from U1 and L), ANB (the difference between angles SNA and SNB), and AB-NPo (the angle between the AB and N-Pog line). Conclusions: Our findings suggest that ML models based on cephalometric data could effectively assist dentists to classify dental, functional and skeletal Class III malocclusions in children. In addition, features such as SN_GoMe, U1_NA and Overjet can as important indicators for predicting the severity of Class III malocclusions.

Ameloblastoma (AM), periapical cyst (PC), and chronic suppurative osteomyelitis (CSO) are prevalent maxillofacial diseases with similar imaging characteristics but different treatments, thus making preoperative differential diagnosis crucial. Existing deep learning methods for diagnosis often require manual delineation in tagging the regions of interest (ROIs), which triggers some challenges in practical application. We propose a new model of Wavelet Extraction and Fusion Module with Vision Transformer (WaveletFusion-ViT) for automatic diagnosis using CBCT panoramic images. In this study, 539 samples containing healthy (n = 154), AM (n = 181), PC (n = 102), and CSO (n = 102) were acquired by CBCT for classification, with an additional 2000 healthy samples for pre-training the domain-adaptive network (DAN). The WaveletFusion-ViT model was initialized with pre-trained weights obtained from the DAN and further trained using semi-supervised learning (SSL) methods. After five-fold cross-validation, the model achieved average sensitivity, specificity, accuracy, and AUC scores of 79.60%, 94.48%, 91.47%, and 0.942, respectively. Remarkably, our method achieved 91.47% accuracy using less than 20% labeled samples, surpassing the fully supervised approach’s accuracy of 89.05%. Despite these promising results, this study’s limitations include a low number of CSO cases and a relatively lower accuracy for this condition, which should be addressed in future research. This research is regarded as an innovative approach as it deviates from the fully supervised learning paradigm typically employed in previous studies. The WaveletFusion-ViT model effectively combines SSL methods to effectively diagnose three types of CBCT panoramic images using only a small portion of labeled data.

This study introduces Multi-Threshold Recurrence Rate Plots (MTRRP), a novel methodology for analyzing dynamic patterns in complex systems, such as those influenced by neurodegenerative diseases in brain activity. MTRRP characterizes how recurrence rates evolve with increasing recurrence thresholds. A key innovation of our approach, Recurrence Complexity, captures structural complexity by integrating local randomness and global structural features through the product of Recurrence Rate Gradient and Recurrence Hurst, both derived from MTRRP. We applied this technique to resting-state EEG data from patients diagnosed with Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD), and age-matched healthy controls. The results revealed significantly higher recurrence complexity in the occipital areas of AD and FTD patients, particularly pronounced in the Alpha and Beta frequency bands. Furthermore, EEG features derived from MTRRP were evaluated using a Support Vector Machine with leave-one-out cross-validation, achieving a classification accuracy of 87.7%. These findings not only underscore the utility of MTRRP in detecting distinct neurophysiological patterns associated with neurodegenerative diseases but also highlight its broader applicability in time series analysis, providing a substantial tool for advancing medical diagnostics and research.

Direct air capture (DAC) is one of the most potential technologies to mitigate CO2 emission. Adsorption technology is recognized as a promising CO2 capture method in view of its desirable characteristics including reusability of adsorbents and low capital investment. To further improve thermal performance, evaporation/condensation heat of vapor compression refrigeration (VCR) cycle in air condition system of buildings is adopted for adsorption/desorption process of DAC. Thermal performance of a 4-step temperature swing adsorption process (TSA) is analyzed at various adsorption/desorption temperatures by using different adsorbents. Analysis on Coefficient of Performance (COP) of VCR cycle is also conducted in search for a balance between adsorbent and refrigerant. Taking both real working capacity and COP into consideration, Mg-MOF-74&R134a is the best choice for more amounts of CO2. Real working capacity of Mg-MOF-74 is up to 0.38 mol•kg−1 at 70 °C, which is twice as much as that of zeolite 13X. While zeolite 13X&R134a shows the best performance of two cycles in view of exergy efficiency and COP, which could reach 81.9% and 7.21, respectively, at 35 °C. These matches will provide some guidelines for the practical application of the combination of DAC with heating, ventilation and air conditioning (HVAC).

Although the carbon pricing policy is a critical driving factor that will help China achieve economic growth, energy transition, and dual climate change mitigation goals, the kind of carbon pricing policy that will complement the country's current development situation remains controversial. We apply the World Induced Technical Change Hybrid (WITCH) model to explore the heterogeneity and synergy of different carbon pricing policies, and the results indicate that it will be challenging to achieve carbon neutrality before 2060. The study find that the combined policy —a mix of carbon tax and carbon market policies — has the optimal emission reduction effect but comes with the highest economic cost, proving to be unsuitable in the long run. The carbon tax policy is an important transitional means to assist in emission reduction, which can serve as an important supplement to carbon market policy and be phased out after the market mechanism matures.

ABSTRACT The geometric characteristics, physical parameters and contact parameters of coated cotton seeds were obtained through theoretical analysis and experimental measurements. A discrete element model reflecting the intrinsic parameters of cotton seeds was established, the contact parameters of coated cotton seeds were calibrated using Discrete Element Method (DEM), and the significant factors affecting the stacking angle were screened using the Plackett-Burman method. The optimal ranges of the parameters were determined by the steepest ascent method, and a second-order regression model of the stacking angle and significant parameters was established by a central composite design. The following optimal values were obtained for cotton seeds: collision recovery (0.38), static friction (0.57) and rolling friction (0.19) coefficients. The average value of the stacking angle obtained by simulations with the best combination of parameters was 30.52°, the result of the simulation test was 30.91°, and the relative error was 1.278%. It is shown that the discrete element particle model and calibration parameters of cotton seed are closer to the actual situation, which can provide theoretical reference for analyzing the precise seeding of cotton seed and optimizing the structural parameters of seed disperser.

Existing methods are unable to achieve high detection rates and low false alarm rates of satellite-based Automatic Dependent Surveillance-Broadcast (ADS-B) signal preambles at extremely low signal-to-noise ratios (SNRs) using limited on-star resources. In this paper, a dual-hierarchy synchronization method is proposed, including a first-level coarse synchronization and a second-level fine synchronization. The coarse synchronization process involves three steps: (1) detection of unknown signals, (2) soft decision, and (3) adaptive interval output. The first step introduces the threshold (TMSED) of the minimum signal energy to be detected to guarantee a high detection rate. In the soft decision step, a value (SV) designed to improve the robustness of the system curbs false detection caused by noise interference. In the last step, the coarse synchronization interval radius (r) is mapped out according to the SNR to reduce resource consumption. The fine synchronization process is based on the coarse synchronization output, and the correlation peak is calculated to complete the synchronization of the signal preambles. The results show that the proposed method achieves a high detection rate of 96% at an extremely low SNR using a low sampling frequency of 10 MHz. Furthermore, the adjustment of TMSED allows this method to be applied to ADS-B receivers with different sensitivities. The comprehensive performance of this method to achieve high detection rates and acceptable false alarm rates at extremely low SNRs with limited on-star resources is verified by final simulations to be superior to other methods.

To calculate the scattering impact of scratches on space-based telescope systems accurately, this study proposes fitting scratch scattering using an anisotropic scattering model based on actual test results. The stray light nonuniformity and total stray light of each mirror in a Cook-type off-axis three-mirror system was calculated. A scratch illuminated with unit radiation power can generate a maximum stray light level of 7 × 10-5 and can obscure dark targets with a brightness ratio of 1 × 10-5 to 8 × 10-5. Furthermore, as the wavelength decreases, the total stray light generated by this scratch can reach 5.7 × 10-4 when illuminated with unit radiation power in the 200 nm ultraviolet band. Such scratches on the mirrors of an off-axis three-mirror telescope cause 7–8 times higher nonuniformity of stray light than roughness scattering, decreasing signal-to-noise ratio and affecting target recognition and image processing.

Prostate abscess, a rare condition often associated with prostate bacterial infections, often occurs in immunosuppressive individuals and manifests as fever and lower urinary tract symptoms. Clinical practice lacks standardized diagnostic and treatment protocols for prostate abscesses, resulting in predominantly empirical approaches with uncertain outcomes. This study presents a case of a giant prostate abscess, diagnosed in a patient exhibiting fever, lower urinary tract symptoms (including dysuria, urinary frequency, urgency, and weakness), and anal pain. The diagnosis was confirmed through prostate magnetic resonance imaging and transrectal color ultrasound examinations. Treatment included targeted anti-infective therapy (based on the urine culture results), urine flow diversion (suprapubic bladder puncture stomy), ultrasound-guided perineal puncture drainage of the prostatic abscess, intermittent abscess cavity irrigation, and urethral electroprostatectomy. The patient experienced a complete recovery and significantly improved quality of life. This successful case underscores several key points: (1) the importance of targeted anti-infective therapy based on etiological findings in prostate abscess treatment; (2) early urine flow diversion, precise puncture drainage, and intermittent abscess cavity irrigation may be one of crucial elements in abscess management; (3) the potential significance of transurethral prostate resection following abscess resolution in preventing recurrence. It is hoped that this case report offers new valuable insights for diagnosing and treating prostate abscesses. Slightly different from previous treatment experience, we extra used early urine diversion, intermittent abscess cavity irrigation, and etiological electroprostatectomy, which might also hold promise as potential therapies.

Objective: To compare the morphological and quantitative changes in pathological myopia (PM) and the perioperative changes in posterior scleral reinforcement (PSR) using three-dimensional magnetic resonance images (3D MRI).Methods: A total of 49 patients with high myopia (HM; 98 eyes), 15 with pathological myopia (PM; 19 eyes), and 10 without high myopia (NORM; 20 eyes) were recruited between September 2019 and July 2021. The patients underwent measurements of refractive error and axial length, as well as 3D MRI of the eyeball. Python was used to analyze the 3D MRI images, calculate the vitreous volume, establish a topography of the height of the eyeball posterior surface, and calculate the rate of change in height (H). For the PM group undergoing PSR, changes in vitreous volume and the highest point of the eyeball posterior surface in four quadrants (temporal, subtemporal, nasal, and subnasal) were compared before and after PSR.Results: The vitreous volume was smaller in the NORM group compared to the HM and PM groups (p < 0.01). The PM group had a larger volume than the HM group (p < 0.01). The H for the PM group was higher than that of the NORM and HM groups (p < 0.01). After PSR in the PM group, the total vitreous volume, as well as the volume in the subnasal and supratemporal quadrants, decreased (p < 0.05). Additionally, the highest point of the eyeball’s posterior surface was generally shifted to the upper nasal side. Finally, the shape and position of the scleral band after PSR were plotted.Conclusion: 3D MRI is capable of a quantitative description of the eyeball morphology in PM and PSR. It allows for precise calculations of changes in vitreous volume and the H of the posterior surface. It also facilitates a meticulous analysis of the specific details of the scleral band following PSR.

Since the testing of convex mirrors often requires a compensator with a larger aperture than the mirror under test, this is undoubtedly a trade-off not worth pursuing. Moreover, for surfaces with higher levels of asphericity, it further escalates the challenges in testing. In this study, high-accuracy testing of large convex aspheric surfaces with rotary symmetry was achieved via a method that combines sub-aperture stitching and Computer-Generated Holograms (CGH) compensation testing. Applying the methodology outlined in this study, practical testing was conducted on a large-aperture convex aspheric mirror with a diameter of 538 mm. The outcomes demonstrated that the center testing data and the outer ring testing data were stitched by the stitching algorithm to obtain the surface error of the full-aperture. The results were compared to those of Luphoscan and compensation testing, with a residual Root Mean Square (RMS) less than λ/20 (λ = 632.8 nm). Finally, the error analysis of the entire testing process showed that the accuracy was better than λ/50. The results demonstrate that the method can achieve highly accurate test of large convex aspheric surfaces.

One key post-transcriptional modification mechanism that dynamically controls a number of physiological processes in plants is alternative splicing (AS). However, the functional impacts of AS on fruit ripening remain unclear. In this research, we used RNA-seq data from climacteric (VED, Harukei 3) and non-climacteric (PI, PS) melon cultivars to explore alternative splicing (AS) in immature and mature fruit. The results revealed dramatic changes in differential AS genes (DAG) between the young and mature fruit stages, particularly in genes involved in fruit development/ripening, carotenoid and capsaicinoid biosynthesis, and starch and sucrose metabolism. Serine/arginine-rich (SR) family proteins are known as important splicing factors in AS events. From the melon genome, a total of 17 SR members were discovered in this study. These genes could be classified into eight distinct subfamilies based on gene structure and conserved motifs. Promoter analysis detected various cis-acting regulatory elements involved in hormone pathways and fruit development. Interestingly, these SR genes exhibited specific expression patterns in reproductive organs such as flowers and ovaries. Additionally, concurrent with the increase in AS levels in ripening fruit, the transcripts of these SR genes were activated during fruit maturation in both climacteric and non-climacteric melon varieties. We also found that most SR genes were under selection during domestication. These results represent a novel finding of increased AS levels and SR gene expression during fruit ripening, indicating that alternative splicing may play a role in fruit maturation.

Currently, staging the degree of liver fibrosis predominantly relies on liver biopsy, a method fraught with potential risks, such as bleeding and infection. With the rapid development of medical imaging devices, quantification of liver fibrosis through image processing technology has become feasible. Stacking technology is one of the effective ensemble techniques for potential usage, but precise tuning to find the optimal configuration manually is challenging. Therefore, this paper proposes a novel EVO-MS model—a multiple stacking ensemble learning model optimized by the energy valley optimization (EVO) algorithm to select most informatic features for fibrosis quantification. Liver contours are profiled from 415 biopsied proven CT cases, from which 10 shape features are calculated and inputted into a Support Vector Machine (SVM) classifier to generate the accurate predictions, then the EVO algorithm is applied to find the optimal parameter combination to fuse six base models: K-Nearest Neighbors (KNNs), Decision Tree (DT), Naive Bayes (NB), Extreme Gradient Boosting (XGB), Gradient Boosting Decision Tree (GBDT), and Random Forest (RF), to create a well-performing ensemble model. Experimental results indicate that selecting 3–5 feature parameters yields satisfactory results in classification, with features such as the contour roundness non-uniformity (Rmax), maximum peak height of contour (Rp), and maximum valley depth of contour (Rm) significantly influencing classification accuracy. The improved EVO algorithm, combined with a multiple stacking model, achieves an accuracy of 0.864, a precision of 0.813, a sensitivity of 0.912, a specificity of 0.824, and an F1-score of 0.860, which demonstrates the effectiveness of our EVO-MS model in staging the degree of liver fibrosis.

The extended duration of mulching in Xinjiang cotton fields leads to a significant decline in the tensile strength of plastic film. When recycling is in operation, the soil and the spring teeth of the machinery used can easily cause secondary damage and fracture the residual film. Establishing appropriate working parameters for recycling is essential to enhance the overall quality of collection efforts. By analyzing the motion process of a chain-tooth residual film pickup device, we identified key working parameters that significantly impact the efficiency of recycling. Employing the finite element method (FEM) and a coupled algorithm incorporating smooth particle hydrodynamics (SPH), we developed a coupled finite element model representing the interaction among spring teeth, soil, and residual film. Through simulation and analysis of the process of inserting the spring teeth into the soil to collect film, we derived the governing rules for residual film stress and deformation changes. Utilizing forward speed, rotational angular velocity, and angle of entry into the soil of the spring teeth as test factors and selecting the residual film stress and the residual film deformation as test indices, we conducted a multi-factor simulation test. We established a mathematical model correlating test factors with test indices, and the influence of each factor on the test index was analyzed. Subsequently, we optimized the working parameters of the spring teeth. The results indicated that the optimal working parameters are forward speed of 1111.11 mm/s, rotational angular velocity of 25 rad/s, and angle of entry into the soil of 30°. At these values, the average peak stress of residual film was 4.51 MPa and the height of residual film pickup was 84.48 mm. To validate the optimized the spring teeth impact on performance, field experiments were conducted with recovery rate and winding rate as test indices. The results demonstrated a 92.1% recovery rate and a 1.1% winding rate under the optimal combination of working parameters. The finite element model presented in this paper serves as a reference for designing and analyzing key components of residual film recycling machines.

BackgroundSmall cell carcinoma of the bladder is rare and has a poor prognosis. This study aimed to investigate whether radiotherapy after bladder-sparing surgery could improve the survival benefits of patients.MethodsThis population-based retrospective cohort study used data from the Surveillance, Epidemiology, and End Results cohort in the United States to investigate small cell carcinoma of the bladder. Univariate and multivariate Cox regression analyses were used to identify significant risk factors influencing the clinical prognosis. A propensity score matching (PSM) algorithm was used to reduce the interference of confounding factors in each study group. The matched groups underwent Kaplan–Meier survival analysis to assess the potential survival benefits.ResultsUnivariate regression analysis demonstrated that age (P

The main purpose of this manuscript is to investigate the Sturm-Liouville BVP for non-autonomous Lagrangian systems. Under the suitable assumptions, we establish an existence theorem for three nonnegative solutions via Bonanno-Candito's three critical point theory. As an application in the complete Sturm-Liouville equations with Sturm-Liouville BVC, we get an existence theorem of three nonnegative solutions. Meanwhile, we give three examples to show the correctness of our results.

Diagnosis of bile duct cancer often occur in advanced stages, leading to poor survival. Here, the authors combine light scattering and diffuse reflectance spectroscopies in a minimally invasive endoscopic technique for directly assessing the malignant potential of the bile duct lining, and demonstrate 97% detection accuracy.

Abstract Background The survival rate for patients with relapsed and refractory acute myeloid leukaemia (R/R-AML) remains poor, and treatment is challenging. Chimeric antigen receptor T cells (CAR-T cells) have been widely used for haematologic malignancies. Current CAR-T therapies for acute myeloid leukaemia mostly target myeloid-lineage antigens, such as CD123 and CD33, which may be associated with potential haematopoietic toxicity. As a lineage-specific receptor, CD7 is expressed in acute myeloid leukaemia cells and T cells but is not expressed in myeloid cells. Therefore, the use of CD7 CAR-T cells for R/R-AML needs to be further explored. Methods In this report, immunohistochemistry and flow cytometry were used to analyse CD7 expression in clinical samples from R/R-AML patients and healthy donors (HDs). We designed naturally selected CD7 CAR-T cells to analyse various functions and in vitro antileukaemic efficacy based on flow cytometry, and xenograft models were used to validate in vivo tumour dynamics. Results We calculated the percentage of cells with CD7 expression in R/R-AML patients with minimal residual disease (MRD) (5/16, 31.25%) from our institution and assessed CD7 expression in myeloid and lymphoid lineage cells of R/R-AML patients, concluding that CD7 is expressed in T cells but not in myeloid cells. Subsequently, we designed and constructed naturally selected CD7 CAR-T cells (CD7 CAR). We did not perform CD7 antigen knockdown on CD7 CAR-T cells because CD7 molecule expression is naturally eliminated at Day 12 post transduction. We then evaluated the ability to target and kill CD7+ acute myeloid leukaemia cells in vitro and in vivo. Naturally selected CD7 CAR-T cells efficiently killed CD7+ acute myeloid leukaemia cells and CD7+ primary blasts of R/R-AML patients in vitro and significantly inhibited leukaemia cell growth in a xenograft mouse model. Conclusion Naturally selected CD7 CAR-T cells represent an effective treatment strategy for relapsed and refractory acute myeloid leukaemia patients in preclinical studies.

Abstract An extreme drought occurred in the Yangtze River Basin in 2022, inflicting huge impacts nationwide. To provide a reference for drought prevention and mitigation, this paper presents a comprehensive analysis of the drought in the Yangtze River Basin in terms of its characteristics, causes, impacts, and response strategies. It concludes that this extreme drought stood out by its long duration, wide impact range, and severe intensity, as a combined result of abnormal high‐temperature weather and massive social water consumption. Serious impacts are observed in various fields of the economy, including agricultural irrigation, urban and rural water supply, power generation, and navigation. Finally, drought mitigation measures and effects are examined, and future drought response and mitigation strategies are proposed.

CIOMP report their progress in high-accuracy manufacturing of the world’s largest SiC aspheric mirror. The final surface figure error is 15.2 nm RMS and aerial density is less than 120 kg/m2.

Downy mildew (DM) is a major foliar disease globally causing great economic loss in melon production. Utilizing disease-resistant cultivars is the most efficient approach for disease control, while discovery of disease-resistant genes is crucial for the success of DM-resistant breeding. To address this problem, two F2 populations were constructed using the DM-resistant accession PI 442177 in this study, and QTLs conferring DM resistance were mapped using linkage map and QTL-seq analysis, respectively. A high-density genetic map with the length of 1096.7 cM and density of 0.7 cM was generated by using the genotyping-by-sequencing data of a F2 population. A major QTL DM9.1 with the phenotypic variance explained proportion of 24.3-37.7% was consistently detected at the early, middle, and late growth stages using the genetic map. QTL-seq analyses on the two F2 populations also validated the presence of DM9.1. Kompetitive Allele-Specific PCR (KASP) assay was further carried out to fine map DM9.1 into 1.0 Mb interval. A KASP marker co-segregating with DM9.1 was successfully developed. These results not only provided valuable information for DM-resistant gene cloning, but also offered useful markers for melon DM-resistant breeding programs.