Accurate UAV Small Object Detection Based on HRFPN and EfficentVMamba.

(1) Background: Small objects in Unmanned Aerial Vehicle (UAV) images are often scattered throughout various regions of the image, such as the corners, and may be blocked by larger objects, as well as susceptible to image noise. Moreover, due to their small size, these objects occupy a limited area in the image, resulting in a scarcity of effective features for detection. (2) Methods: To address the detection of small objects in UAV imagery, we introduce a novel algorithm called High-Resolution Feature Pyramid Network Mamba-Based YOLO (HRMamba-YOLO). This algorithm leverages the strengths of a High-Resolution Network (HRNet), EfficientVMamba, and YOLOv8, integrating a Double Spatial Pyramid Pooling (Double SPP) module, an Efficient Mamba Module (EMM), and a Fusion Mamba Module (FMM) to enhance feature extraction and capture contextual information. Additionally, a new Multi-Scale Feature Fusion Network, High-Resolution Feature Pyramid Network (HRFPN), and FMM improved feature interactions and enhanced the performance of small object detection. (3) Results: For the VisDroneDET dataset, the proposed algorithm achieved a 4.4% higher Mean Average Precision (mAP) compared to YOLOv8-m. The experimental results showed that HRMamba achieved a mAP of 37.1%, surpassing YOLOv8-m by 3.8% (Dota1.5 dataset). For the UCAS_AOD dataset and the DIOR dataset, our model had a mAP 1.5% and 0.3% higher than the YOLOv8-m model, respectively. To be fair, all the models were trained without a pre-trained model. (4) Conclusions: This study not only highlights the exceptional performance and efficiency of HRMamba-YOLO in small object detection tasks but also provides innovative solutions and valuable insights for future research.

The prediction model of fall risk for the elderly based on gait analysis.

INTRODUCTION: Early screening and identification are crucial for fall prevention, and developing a new method to predict fall risk in the elderly can address the current lack of objectivity in assessment tools. METHODS: A total of 132 elderly individuals over 80 years old residing in some nursing homes in Shanghai were selected using a convenient sampling method. Fall history information was collected, and gait data during a 10-meter walk were recorded. Logistic regression was employed to establish the prediction model, and a nomogram was used to assess the importance of the indicators. The Bootstrap method was utilized for internal validation of the model, while the verification set was used for external validation. The predictive performance of the model was evaluated using the area under the ROC curve, calibration curve, and decision curve analysis (DCA) to assess clinical benefits. RESULTS: The incidence of falls in the sample population was 36.4%. The Tinetti Gait and Balance Test (TGBT) score (OR = 0.832, 95% CI: 0.734,0.944), stride length (OR = 0.007, 95% CI: 0.000,0.104), difference in standing time (OR = 0.001, 95% CI: 0.000,0.742), and mean stride time (OR = 0.992, 95% CI:0.984,1.000) were identified as significant factors. The area under the ROC curve was 0.878 (95% CI: 0.805, 0.952), with a sensitivity of 0.935 and specificity of 0.726. The Brier score was 0.135, and the Hosmer-Lemeshow test (χ2 = 10.650, P = 0.222) indicated a good fit and calibration of the model. CONCLUSION: The TGBT score, stride length, difference in standing time, and stride time are all protective factors associated with fall risk among the elderly. The developed risk prediction model demonstrates good discrimination and calibration, providing valuable insights for early screening and intervention in fall risk among older adults.

Spatial transcriptomics of gastric cancer brain metastasis reveals atypical vasculature strategies with supportive immune profiles.

Background: Gastric cancer brain metastasis (GCBM) represents a rare but highly aggressive malignancy. Metastatic cancer cells are highly heterogeneous and differentially remodels brain vasculature and immune microenvironments, which affects the treatment effectiveness and patient outcome. This study aimed to investigate the spatial interactions among different cell components, especially the vasculature system and the brain microenvironment of GCBM patients. Methods: We used digital spatial profiling to examine 140 regions composing tumor, immune, and brain tissues from three GCBM patients. Transcriptomic data with spatial information were analyzed for tissue areas related to different blood recruitment strategies. For validation, independent analysis of patient bulk transcriptomic data and in vivo single-cell transcriptomic data were performed. Results: Angiogenesis and blood vessel co-option co-existed within the same GCBM lesion. Tumors with high epithelial-mesenchymal transition and an enhanced transcriptomic gene signature composed of CTNNB1, SPARC, VIM, SMAD3, SMAD4, TGFB1, TGFB2, and TGFB3 were more prone to adopt blood vessel co-option than angiogenesis. Enriched macrophage infiltration, angiogenic chemokines, and NAMPT were found in angiogenic areas, while increased T cells, T cell activating cytokines, and reduced NAMPT were found in vessel co-option regions. Spatially, angiogenesis was enriched at the tumor edge, which showed higher DMBT1 expression than the tumor center. Conclusions: This study mapped the orchestrated spatial characteristics of tumor and immunological compositions that support the conventional and atypical vascularization strategies in GCBM. Our data provided molecular insights for more effective combinations of anti-vascular and immune therapies.

3D residual attention hierarchical fusion for real-time detection of the prostate capsule.

BACKGROUND: For prostate electrosurgery, where real-time surveillance screens are relied upon for operations, manual identification of the prostate capsule remains the primary method. With the need for rapid and accurate detection becoming increasingly urgent, we set out to develop a deep learning approach for detecting the prostate capsule using endoscopic optical images. METHODS: Our method involves utilizing the Simple, Parameter-Free Attention Module(SimAM) residual attention fusion module to enhance the extraction of texture and detail information, enabling better feature extraction capabilities. This enhanced detail information is then hierarchically transferred from lower to higher levels to aid in the extraction of semantic information. By employing a forward feature-by-feature hierarchical fusion network based on the 3D residual attention mechanism, we have proposed an improved single-shot multibox detector model. RESULTS: Our proposed model achieves a detection precision of 83.12% and a speed of 0.014 ms on NVIDIA RTX 2060, demonstrating its effectiveness in rapid detection. Furthermore, when compared to various existing methods including Faster Region-based Convolutional Neural Network (Faster R-CNN), Single Shot Multibox Detector (SSD), EfficientDet and others, our method Attention based Feature Fusion Single Shot Multibox Detector (AFFSSD) stands out with the highest mean Average Precision (mAP) and faster speed, ranking only below You Only Look Once version 7 (YOLOv7). CONCLUSIONS: This network excels in extracting regional features from images while retaining the spatial structure, facilitating the rapid detection of medical images.

Accurate Finite Element Simulations of Dynamic Behaviour: Constitutive Models and Analysis with Deep Learning.

Owing to the challenge of capturing the dynamic behaviour of metal experimentally, high-precision numerical simulations have become essential for analysing dynamic characteristics. In this study, calculation accuracy was improved by analysing the impact of constitutive models using the finite element (FE) model, and the deep learning (DL) model was employed for result analysis. The results showed that FE simulations with these models effectively capture the elastic-plastic response, and the ZA model exhibits the highest accuracy, with a 26.0% accuracy improvement compared with other models at 502 m/s for Hugoniot elastic limit (HEL) stress. The different constitutive models offer diverse descriptions of stress during the elastic-plastic response because of temperature effects. Concurrently, the parameters related to the yield strength at quasi-static influence the propagation speed of elastic waves. Calculation show that the yield strength at quasi-static of 6061 Al adheres to y = ax + b for HEL stress. The R-squared (R2) and mean absolute error (MAE) values of the DL model for HEL stress predictions are 0.998 and 0.0062, respectively. This research provides a reference for selecting constitutive models for simulation under the same conditions.

A Joint Scheduling Scheme for WiFi Access TSN.

In the context of Industry 4.0, industrial production equipment needs to communicate through the industrial internet to improve the intelligence of industrial production. This requires the current communication network to have the ability of large-scale equipment access, multiple communication protocols/heterogeneous systems interoperability, and end-to-end deterministic low-latency transmission. Time-sensitive network (TSN), as a new generation of deterministic Ethernet communication technology, is the main development direction of time-critical communication technology applied in industrial environments, and Wi-Fi technology has become the main way of wireless access for users due to its advantages of high portability and mobility. Therefore, accessing WiFi in the TSN is a major development direction of the current industrial internet. In this paper, we model the scheduling problem of TSN and WiFi converged networks and propose a scheme based on a greedy strategy distributed estimation algorithm (GE) to solve the scheduling problem. Compared with the integer linear programming (ILP) algorithm and the Tabu algorithm, the algorithm implemented in this paper outperforms the other algorithms in being able to adapt to a variety of different scenarios and in scheduling optimization efficiency, especially when the amount of traffic to be deployed is large.

Establishment of Human Pituitary Neuroendocrine Tumor Derived Organoid and Its Pilot Application for Drug Screening.

CONTEXT: Precision medicine for pituitary neuroendocrine tumors (PitNETs) is limited by the lack of reliable research models. OBJECTIVE: To generate patient-derived organoids (PDOs), which could serve as a platform for personalized drug screening for PitNET patients. DESIGN: From July 2019 to May 2022, a total of 32 human PitNET specimens were collected for the establishment of organoids with an optimized culture protocol. SETTING: This study was conducted at Sun Yat-Sen University Cancer Center. PATIENTS: PitNET patients who were pathologically confirmed were enrolled in this study. INTERVENTIONS: Histological staining and whole-exome sequencing were utilized to confirm the pathologic and genomic features of PDOs. A drug response assay on PDOs was also performed. MAIN OUTCOME MEASURES: PDOs retained key genetic and morphological features of their parental tumors. RESULTS: PDOs were successfully established from various types of PitNET samples with an overall success rate of 87.5%. Clinical nonfunctioning PitNETs-derived organoids (22/23, 95.7%) showed a higher likelihood of successful generation compared to those from functioning PitNETs (6/9, 66.7%). Preservation of cellular structure, subtype-specific neuroendocrine profiles, mutational features, and tumor microenvironment heterogeneity from parental tumors was observed. A distinctive response profile in drug tests was observed among the organoids from patients with different subtypes of PitNETs. With the validation of key characteristics from parental tumors in histological, genomic, and microenvironment heterogeneity consistency assays, we demonstrated the predictive value of the PDOs in testing individual drugs. CONCLUSION: The established PDOs, retaining typical features of parental tumors, indicate a translational significance in innovating personalized treatment for refractory PitNETs.

Dapagliflozin treatment and cardiovascular outcome in RBP4/TTRVal30Met (transthyretin cardiac amyloidosis) mice.

AIMS: Whether sodium-glucose co-transporter 2 inhibitors are effective for heart failure caused by ATTR-CA (transthyretin cardiac amyloidosis) remains uncertain. The aim of this study is to investigate the cardiovascular prognosis in ATTR-CA mice model with dapagliflozin treatment. METHODS AND RESULTS: Humanized RBP4/TTRVal50Met and RBP4/TTR mice models were constructed with clustered regularly interspaced short palindromic repeats and associated Cas9 endonuclease (CRISPR-Cas9) techniques and multiple generations breeding. A total of 6 RBP4/TTR mice received placebo treatment, when 12 RBP4/TTRVal50Met received dapagliflozin (1 mg/kg/day, 6 mice) and placebo (6 mice) treatment. Fasting glucose, intraperitoneal glucose tolerance test, and plasma brain natriuretic peptide (BNP) concentration were measured at Day 0, Week 2, and Week 4. BNP, transforming growth factor-beta (TGF-ß), collagen type I alpha 1 (COL1A1) protein levels, and Cola1, TGFß1, TNFα, IL-1ß, BNP relative quantities in cardiac, along with cardiac pathology examination including right ventricular collagen percentage, ventricular septum thickness, left ventricular wall thickness, and left ventricular internal diameter were measured at Week 4 after treatment procedure. All 18 mice completed the experiment. The baseline characteristics were balanced among three treatment groups. In placebo-treated mice, the cardiac BNP relative quantity was significantly higher in RBP4/TTRVal50Met mice than RBP4/TTR mice (RBP4[KI/KI], TTR [KI/KI]: 0.72 ± 0.46, RBP4[KI/KI], TTRVal50Met [KI/KI]: 1.44 ± 0.60, P = 0.043), indicating more significant heart failure progression in ATTR-CA mice than normal mice. In ATTR-CA mice, the cardiovascular prognosis measurements including heart failure (plasma BNP concentration and relative quantities of BNP), cardiac inflammation (relative quantities of Cola1, TGFß1, TNFα, and IL-1ß), and pathological changes (right ventricular collagen percentage, ventricular septum thickness, left ventricular wall thickness, and left ventricular internal diameter) were statistically comparable between those under dapagliflozin and placebo treatment. CONCLUSIONS: Dapagliflozin did not improve cardiovascular prognosis including the progression of heart failure, cardiac inflammation, and pathological changes in ATTR-CA mice compared with placebo. The results of this study were not in support of dapagliflozin's therapeutic effects for ATTR-CA. More pre-clinical and clinical researches to validate these findings and demonstrate the underlying mechanisms are still required.

A novel lactate dehydrogenase-based risk score model to predict the prognosis of primary central nervous system germ cell tumor treated with chemoradiotherapy.

BACKGROUND: The prognostic role of lactate dehydrogenase (LDH) has been confirmed in many malignant tumors, but the role of serum LDH in primary central nervous system germ cell tumor (GCT) remains unknown. This study aimed to assess the prognostic value of LDH in GCT patients and develop a nomogram to predict prognosis in patients undergoing chemoradiotherapy. METHODS: A total of 161 patients with GCT were included in this study. Using a restricted cubic spline (RCS) model, the optimal cutoff point for LDH was determined to be 217 U/L. The survival of GCT patients was evaluated using the Kaplan-Meier method and log-rank test to analyze the effects of LDH levels. Univariate Cox regression, multivariate Cox regression, and LASSO Cox regression were conducted to identify prognostic factors, which were incorporated into a nomogram for predicting overall survival (OS). The predictive accuracy of the nomogram was assessed using the C-index, calibration curve, area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and risk group stratification. The net benefits of the nomogram at different threshold probabilities were quantified using decision curve analysis (DCA). RESULTS: The high-LDH group had significantly shorter OS compared to the low-LDH group (P = 0.016). Based on the SYSUCC cohort, three variables were shown to be significant factors for OS and were incorporated in the nomogram: LDH, histopathology, and dissemination. It showed good discrimination ability, with C-index of 0.789 (95% CI, 0.671-0.907). Additionally, the clinical usefulness of the nomogram was confirmed by calibration curves and time-dependent AUC. DCA further highlighted the potential of the nomogram to guide clinical treatment strategies for patients. Moreover, there was a significant difference in OS among patients categorized into different risk groups (P < 0.001). CONCLUSION: LDH levels may serve as a reliable predictor for assessing the therapeutic effect of chemoradiotherapy in GCT. The developed nomogram exhibits high accuracy in predicting survival outcomes, aiding in the classification of prognostic groups, and supporting informed clinical decision-making.

Proteomic Identification and Characterization of Collagen from Bactrian Camel (Camelus bactrianus) Hoof.

With the development of camel-derived food and pharmaceutical cosmetics, camel hoof, as a unique by-product of the camel industry, has gradually attracted the attention of scientific researchers in the fields of nutrition, health care, and biomaterial development. In this study, the protein composition and collagen type of Bactrian camel hoof collagen extract (CHC) were analyzed by LC-MS/MS, and the functional properties of CHC were further investigated, including its rheological characteristics, emulsification and emulsion stability, and hygroscopicity and humectancy. Proteomic identification confirmed that CHC had 13 collagen subunits, dominated by type I collagen (α1, α2), with molecular weights mainly in the 100-200 KDa range and a pI of 7.48. An amino acid study of CHC revealed that it carried the standard amino acid profile of type I collagen and was abundant in Gly, Pro, Glu, Ala, and Arg. Additionally, studies using circular dichroism spectroscopy and Fourier transform infrared spectroscopy revealed that CHC contains a collagen-like triple helix structure that is stable and intact. Different concentrations of CHC solutions showed shear-thinning flow behavior. Its tan δ did not differ much with increasing concentration. The CHC has good emulsifying ability and stability, humectancy, and hygroscopicity. This study provides a basis for utilizing and developing Bactrian camel hoof collagen as a functional ingredient.

Differential effects of PGAM5 knockout on high fat high fructose diet and methionine choline-deficient diet induced non-alcoholic steatohepatitis (NASH) in mice.

BACKGROUND: Phosphoglycerate mutase 5 (PGAM5), a phosphatase involved in mitochondrial homeostasis, is reported to be closely related to the metabolic stress induced by high-fat diet (HFD) or cold. In this study, we aimed to investigate the effects of PGAM5 on hepatic steatosis, inflammation and fibrosis in nonalcoholic steatohepatitis (NASH). METHODS AND RESULTS: We generated PGAM5 global knockout (GKO) mice and their wildtype (WT) littermates using CRISPR/CAS9. The mice were fed with a high fat high fructose (HFHF) diet for 12 weeks or a methionine choline-deficient (MCD) diet (methionine choline supplemented (MCS) as control) for 6 weeks. Hepatic PGAM5 expression was up-regulated in humans with NASH and WT mice fed with HFHF and MCS, and reduced in WT mice fed with MCD diet. In HFHF-fed mice, GKO had reduced body weight, hepatic triglyceride (TG) content and serum transaminase along with decreased hepatic pro-inflammatory and pro-fibrotic responses compared with their WT control. GKO had increased expression of antioxidative gene glutathione peroxidase-6 (GPX6) and activation of mammalian target of rapamycin (mTOR). In mice fed with MCS diet, GKO significantly increased serum TNF-α and IL-6 and decreased hepatic GPX6 mRNA expression. There was no difference in hepatic steatosis, inflammation or fibrosis between GKO and WT mice fed with MCD diet. We investigated the role of PGAM5 deficiency in a variety of cell types. In differentiated THP-1 cells, PGAM5 silencing significantly increased pro-inflammatory cytokine secretion and decreased antioxidative proteins, including nuclear factor erythroid 2- related factors (NRF2), heme oxygenase-1 (HO-1) and GPX6 without affecting mTOR activity. In HepG2 cells with steatosis, PGAM5 knockdown reduced insulin sensitivity, increased mTOR phosphorylation and reduced the expression of NRF2, catalase (CAT), HO-1 and GPX6. Conversely, PGAM5 knockdown reduced TG accumulation, increased insulin sensitivity, and increased antioxidative genes in 3T3-L1 cells, despite the up-regulation in mTOR phosphorylation. CONCLUSIONS: PGAM5-KO relieved hepatic steatosis and inflammation in HFHF model, promoted inflammation in MCS-fed mice and had no effects on the MCD-fed model. The distinct effects may be owing to the different effects of PGAM5-KO on anti-oxidative pathways in energy-dependent, possible involves mTOR, and/or cell type-dependent manner. Our findings suggest that PGAM5 can be a potential therapeutic target for NASH.

The effect of physical exercise on disordered social communication in individuals with autism Spectrum disorder: a systematic review and meta-analysis of randomized controlled trials.

Objective: The aim of this systematic review and meta-analysis was to systematically investigate the intervention effect of physical exercise on disordered social communication in patients with autism spectrum disorders. Methods: This systematic review and meta-analysis used the PubMed, Web of Science, the Cochrane Library, and Embase electronic databases to conduct a systematic search of literature describing randomized controlled trials (RCTs) on the effect of physical exercise on disordered social communication in autistic patients from the first year of inclusion to 21 January 2023. Results: A total of 14 RCTs including 460 autistic patients were analyzed. A meta-analysis showed that physical exercise had a positive effect on social communication disorder (SMD = 0.45, 95% CI: 0.15, 0.74, p < 0.05) in autistic patients. Subgroup analysis showed that exercise programs with multiple components (SMD = 0.73, 95% CI: 0.39, 1.06, P < 0.001), a moderate duration (SMD = 0.73, 95% CI: 0.38, 1.08, P < 0.001), a moderate-high frequency (SMD = 0.84, 95% CI: 0.53, 1.14, P < 0.001), and a long duration (SMD = 0.77, 95% CI: 0.36, 1.18, P < 0.001) led to significant improvement. Conclusion: Physical exercise can improve disordered social communication in patients with autism spectrum disorders. Specifically, early intervention, multi-component exercise, a moderate period, moderate and high frequency, long duration, and multi-participant programs were most effective. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/ RecordID= CRD42023422482.

Gender-specific data-driven adiposity subtypes using deep-learning-based abdominal CT segmentation.

OBJECTIVE: The aim of this study was to quantify abdominal adiposity and generate data-driven adiposity subtypes with different diabetes risks. METHODS: A total of 3817 participants from the Pinggu Metabolic Disease Study were recruited. A deep-learning-based recognition model on abdominal computed tomography (CT) images (A-CT model) was developed and validated in 100 randomly selected cases. The volumes and proportions of subcutaneous fat, visceral fat, liver fat, and muscle fat were automatically recognized in all cases. K-means clustering was used to identify subgroups using the proportions of the four fat components. RESULTS: The Dice indices among the measurements assessed by the A-CT model and manual evaluation to detect liver fat, muscle fat, and subcutaneous fat areas were 0.96, 0.95, and 0.92, respectively. Three subtypes were generated separately in men and women: visceral fat dominant type (VFD); subcutaneous fat dominant type (SFD); and intermuscular fat dominant type (MFD). Compared with the SFD group, the MFD group had similar diabetes risk, and the VFD group had a 60% higher diabetes risk when age and BMI were adjusted for in men. The adjusted odds ratio for diabetes was 1.92 (95% CI: 1.32-2.78) in the MFD group and 6.14 (95% CI: 4.18-9.03) in the VFD group in women. CONCLUSIONS: This study identified gender-specific abdominal adiposity subgroups, which may help clinicians to distinguish diabetes risk quickly and automatically.

Salt-and-pepper Noise Reduction for Medical Images Based on Image Fusion.

BACKGROUND: During the collection process, the prostate capsule is prone to introduce salt and pepper noise due to gastrointestinal peristalsis, which will affect the precision of subsequent object detection. OBJECTIVE: A cascade optimization scheme for image denoising based on image fusion was proposed to improve the peak signal-to-noise ratio(PSNR) and contour protection performance of heterogeneous medical images after image denoising. METHOD: Anisotropic diffusion fusion (ADF) was used to decompose the images denoised by adaptive median filter, non-local adaptive median filter and artificial neural network to generate the base layer and detail layer, which were fused by weighted average and Karhunen-Loeve Transform respectively. Finally, the image was reconstructed by linear superposition. RESULTS: Compared with the traditional denoising method, the image denoised by this method has a higher PSNR while maintaining the image edge contour. CONCLUSION: Using the denoised dataset for object detection, the detection precision of the obtained model is higher.

High-intensity interval training improves cognitive impairment of vascular dementia rats by up-regulating expression of brain-derived neurotrophic factor in the hippocampus.

The present study aims to investigate the effect and its potential mechanism of high-intensity intermittent training (HIIT) on cognitive function in vascular dementia (VD) rats. The VD rats with the cognitive impairment were induced by bilateral common carotid artery occlusion (BCCAO), and the ones in the moderate-intensity continuous training (MICT) group and HIIT group received MICT or HIIT for 5 consecutive weeks, respectively. The swimming speed, endurance, and grip strength of rats were all measured after training. The effect and mechanisms of HIIT on ameliorating the cognitive dysfunction were further evaluated by the Morris water maze test, histomorphological analysis, and Western blot analysis. As a result, no significant difference in motor function between VD rats and sham rats was observed. After 5-week HIIT, the motor function of VD rats was significantly enhanced. The results of the Morris water maze test revealed that HIIT significantly reduced escape latency as well as distance to find the platform compared with the sedentary control group (SED group), indicating the improvement in cognitive function. In addition, the hippocampal tissue damage of VD rats measured by H&E staining was markedly ameliorated after 5-week HIIT. Moreover, brain-derived neurotrophic factor (BDNF) expression level in the cerebral cortex and hippocampus tissue detected by Western blot were significantly up-regulated in HIIT group compared to SED group and MICT group. In conclusion, HIIT can improve BCCAO-induced cognitive impairment via up-regulating BDNF expression in VD rats.

Hydrodynamic simulation of hypervelocity generation by multidimensional graded impactors: Planarity enhancement study.

Hypervelocity impact in the universe can be generated by a three-stage gas gun. Achieving the desirable planarity of the flyer enlarges the experimentally effective area of the flyer under the hypervelocity condition. The multidimensional graded density impactor (MDGDI) enhances the planarity of the flyer. In this investigation, a one-dimensional Lagrange elastoplastic hydrodynamic method and a Euler grid finite difference method were used to examine the relationship between the structure of graded density impactors (GDIs) and the planarity of flyers. MDGDIs lead to a deviation of the stress wave produced by the one-dimensional graded density impactor (1DGDI), which offsets the stress disturbance effect, changes the velocity at each particle, and enhances the planarity of flyers. The proportion of flat areas of the flyer increases from 52.70% to 95.71% by adopting MDGDIs. The proportion of flat areas is linear with the wave impedance of the high-impedance layer for 1DGDIs and the wave impedance near the barrel of the high-impedance layer for MDGDIs. This investigation guides the design of GDIs and expands the application of gas gun technology in the field of hypervelocity impact.

Selective Electroreductive Hydroboration of Olefins with B2pin2.

Organoboron showed great potential in the synthesis of various high-value chemical compounds. Direct hydroboration of olefins has been witnessed over time as a mainstream method for the synthesis of organoboron compounds. In this work, an electroreductive anti-Markovnikov hydroboration approach of olefins with readily available B2pin2 to synthesize valuable organoboron compounds with high chemo- and regioselectivities under metal catalyst-free conditions was reported. This protocol exhibited broad substrate scope and good functional-group tolerance on styrenes and heteroaromatic olefins, providing synthetically useful alkylborons with high efficiency and even various deuterium borylation products with good D-incorporation when CD3CN was employed as solvent. Furthermore, gram-scale reactions and extensive functional derivatization further highlighted the potential of this method.

Single-cell RNA sequencing reveals tumor heterogeneity, microenvironment, and drug-resistance mechanisms of recurrent glioblastoma.

Glioblastomas are highly heterogeneous brain tumors. Despite the availability of standard treatment for glioblastoma multiforme (GBM), i.e., Stupp protocol, which involves surgical resection followed by radiotherapy and chemotherapy, glioblastoma remains refractory to treatment and recurrence is inevitable. Moreover, the biology of recurrent glioblastoma remains unclear. Increasing evidence has shown that intratumoral heterogeneity and the tumor microenvironment contribute to therapeutic resistance. However, the interaction between intracellular heterogeneity and drug resistance in recurrent GBMs remains controversial. The aim of this study was to map the transcriptome landscape of cancer cells and the tumor heterogeneity and tumor microenvironment in recurrent and drug-resistant GBMs at a single-cell resolution and further explore the mechanism of drug resistance of GBMs. We analyzed six tumor tissue samples from three patients with primary GBM and three patients with recurrent GBM in which recurrence and drug resistance developed after treatment with the standard Stupp protocol using single-cell RNA sequencing. Using unbiased clustering, nine major cell clusters were identified. Upregulation of the expression of stemness-related and cell-cycle-related genes was observed in recurrent GBM cells. Compared with the initial GBM tissues, recurrent GBM tissues showed a decreased proportion of microglia, consistent with previous reports. Finally, vascular endothelial growth factor A expression and the blood-brain barrier permeability were high, and the O6 -methylguanine DNA methyltransferase-related signaling pathway was activated in recurrent GBM. Our results delineate the single-cell map of recurrent glioblastoma, tumor heterogeneity, tumor microenvironment, and drug-resistance mechanisms, providing new insights into treatment strategies for recurrent glioblastomas.

Proposed prognostic subgroups and facilitated clinical decision-making for additional locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma: a retrospective study based on recursive partitioning analysis.

BACKGROUND: The high heterogeneity of de novo metastatic nasopharyngeal carcinoma (dmNPC) makes its prognosis and treatment challenging. We aimed to accurately stage dmNPC and assess the patterns of treatment strategies for different risk groups. METHODS: The study enrolled a total of 562 patients, 264 from 2007 to 2013 in the training cohort and 298 from 2014 to 2017 in the validation cohort. Univariate and multivariate Cox regression analyses were conducted to determine the independent variables for overall survival (OS). Recursive partitioning analysis (RPA) was applied to establish a novel risk-stratifying model based on these variables. RESULTS: After pairwise comparisons of OS, three risk groups were generated: low-risk (involved lesions ≤ 4 without liver involvement), intermediate-risk (involved lesions ≤ 4 with liver involvement or involved lesions > 4 with Epstein-Barr virus (EBV)-DNA < 62,000 copies/ml), and high-risk (involved lesions > 4 with EBV-DNA > 62,000 copies/ml). The 3-year OS rate differed significantly between groups (80.4%, 42.0%, and 20.4%, respectively, all P < 0.05). Adding locoregional intensity-modulated radiotherapy (LRRT) followed by palliative chemotherapy (PCT) resulted in a significant OS benefit over PCT alone for the low- and intermediate-risk groups (P = 0.0032 and P = 0.0014, respectively). However, it provided no survival benefits for the high-risk group (P = 0.6). Patients did not benefit from concurrent chemotherapy during LRRT among the three subgroups (P = 0.12, P = 0.13, and P = 0.3, respectively). These results were confirmed with the validation cohort. CONCLUSIONS: The novel RPA model revealed superior survival performance in subgroup stratification and could facilitate more effective treatment strategies for dmNPC.

Adjuvant Temozolomide Chemotherapy With or Without Interferon Alfa Among Patients With Newly Diagnosed High-grade Gliomas: A Randomized Clinical Trial.

Importance: High-grade gliomas (HGGs) constitute the most common and aggressive primary brain tumor, with 5-year survival rates of 30.9% for grade 3 gliomas and 6.6% for grade 4 gliomas. The add-on efficacy of interferon alfa is unclear for the treatment of HGG. Objectives: To compare the therapeutic efficacy and toxic effects of the combination of temozolomide and interferon alfa and temozolomide alone in patients with newly diagnosed HGG. Design, Setting, and Participants: This multicenter, randomized, phase 3 clinical trial enrolled 199 patients with newly diagnosed HGG from May 1, 2012, to March 30, 2016, at 15 Chinese medical centers. Follow-up was completed July 31, 2021, and data were analyzed from September 13 to November 24, 2021. Eligible patients were aged 18 to 75 years with newly diagnosed and histologically confirmed HGG and had received no prior chemotherapy, radiotherapy, or immunotherapy for their HGG. Interventions: All patients received standard radiotherapy concurrent with temozolomide. After a 4-week break, patients in the temozolomide with interferon alfa group received standard temozolomide combined with interferon alfa every 28 days. Patients in the temozolomide group received standard temozolomide. Main Outcomes and Measures: The primary end point was 2-year overall survival (OS). Secondary end points were 2-year progression-free survival (PFS) and treatment tolerability. Results: A total of 199 patients with HGG were enrolled, with a median follow-up time of 66.0 (95% CI, 59.1-72.9) months. Seventy-nine patients (39.7%) were women and 120 (60.3%) were men, with ages ranging from 18 to 75 years and a median age of 46.9 (95% CI, 45.3-48.7) years. The median OS of patients in the temozolomide plus interferon alfa group (26.7 [95% CI, 21.6-31.7] months) was significantly longer than that in the standard group (18.8 [95% CI, 16.9-20.7] months; hazard ratio [HR], 0.64 [95% CI, 0.47-0.88]; P = .005). Temozolomide plus interferon alfa also significantly improved median OS in patients with O6-methylguanine-DNA methyltransferase (MGMT) unmethylation (24.7 [95% CI, 20.5-28.8] months) compared with temozolomide (17.4 [95% CI, 14.1-20.7] months; HR, 0.57 [95% CI, 0.37-0.87]; P = .008). Seizure and influenzalike symptoms were more common in the temozolomide plus interferon alfa group, with 2 of 100 (2.0%) and 5 of 100 (5.0%) patients with grades 1 and 2 toxic effects, respectively (P = .02). Finally, results suggested that methylation level at the IFNAR1/2 promoter was a marker of sensitivity to temozolomide plus interferon alfa. Conclusions and Relevance: Compared with the standard regimen, temozolomide plus interferon alfa treatment could prolong the survival time of patients with HGG, especially the MGMT promoter unmethylation variant, and the toxic effects remained tolerable. Trial Registration: ClinicalTrials.gov Identifier: NCT01765088.