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According to previous studies, D-dimer levels are associated with the prognosis of patients with pancreatic cancer (PC). However, the results of current studies are limited and controversial. Therefore, we performed this meta-analysis to assess the relationship between D-dimer levels and prognostic and pathological characteristics of PC patients. We first searched the databases of PubMed, Embase, The Cochrane Library, Web Of Science, CBM, VIP, CNKI and Wanfang to identify available studies. The relationship between pretreatment d-dimer levels and prognosis in PC patients was assessed using the combined hazard ratio (HR) and 95% confidence interval (CI). The combined odds ratio (OR) and 95% confidence interval (CI) were used in assessing the relationship between pathological characteristics and d-dimer levels in PC patients. Stata 12.0 software was used for all statistical analyses. In total, we included 13 studies involving 2777 patients. The results showed that elevated pre-treatment d -dimer levels were significantly associated with OS deterioration (HR = 1.46 95% CI: 1.34–1.59; p

Abstract Tinospora sagittata (Oliv.) Gagnep. is an important medicinal tetraploid plant in the Menispermaceae family. Its tuber, Radix Tinosporae, used in traditional Chinese medicine, is rich in diterpenoids and benzylisoquinoline alkaloids (BIAs). To enhance our understanding of medicinal compounds’ biosynthesis and Menispermaceae’s evolution, we herein report assembling a high-quality chromosome-scale genome with both PacBio HiFi and Illumina sequencing technologies. PacBio Sequel II generated 2.5 million circular consensus sequencing (CCS) reads, and a hybrid assembly strategy with Illumina sequencing resulted in 4483 contigs. The assembled genome size was 2.33 Gb, consisting of 4070 scaffolds (N50 = 42.06 Mb), of which 92.05% were assigned to 26 pseudochromosomes. T. sagittata’s chromosomal-scale genome assembly, the first species in Menispermaceae, aids Menispermaceae evolution and T. sagittata’s secondary metabolites biosynthesis understanding.

Abstract Wolfiporia cocos is a medicinal mushroom used in China. It biosynthesizes pachymic acid (PA), a main therapeutic triterpene associated with therapies. Nowadays, the unknown PA biosynthesis leads to difficulties in increasing its content in W. cocos. Herein, we report sequencing, assembling, and characterization of the genome and several transcriptomes of W. cocos. Sequence mining determined candidate genes that encode lanosterol synthase, sterol O-acyltransferase, and sterol C-24 methyltransferase likely involved in the steps from lanosterol to PA. Gene cluster analysis identified four CYP450 cDNAs likely involved in the biosynthesis of PA, namely WcCYP64-1, WcCYP64-2, WcCYP52, and WcCYP_FUM15, which were subjected to both overexpression and silencing in mycelia. The overexpression of each of WcCYP64-1, WcCYP52 and WcCYP_FUM15 increased the content of PA, 16α-hydroxytrametenolic acid, eburicoic acid, and tumulosic acid, while the silencing of each gene either significantly or slightly decreased the contents of these four compounds, indicating their involvement in the PA biosynthesis. In addition, different temperatures affected the expression of these genes and the formation of PA. By contrast, the overexpression and silencing of WcCYP64-2 did not alter the formation of these compounds. Taken together, these findings determine more potential steps in the biosynthetic pathway of PA for metabolic engineering.

Abstract Auscultation is the most effective method for diagnosing cardiovascular and respiratory diseases. However, stethoscopes typically capture mixed signals of heart and lung sounds, which can affect the auscultation effect of doctors. Therefore, the efficient separation of mixed heart and lung sound signals plays a crucial role in improving the diagnosis of cardiovascular and respiratory diseases. In this paper, we propose a blind source separation method for heart and lung sounds based on deep autoencoder (DAE), nonnegative matrix factorization (NMF) and variational mode decomposition (VMD). Firstly, DAE is employed to extract highly informative features from the heart and lung sound signals. Subsequently, NMF clustering is applied to group the heart and lung sounds based on their distinct periodicities, achieving the separation of the mixed heart and lung sounds. Finally, variational mode decomposition is used for denoising the separated signals. Experimental results demonstrate that the proposed method effectively separates heart and lung sound signals and exhibits significant advantages in terms of standardized evaluation metrics when compared to contrast methods.

With the widespread application of Synthetic Aperture Radar (SAR) images in ship detection and recognition, accurate and efficient ship classification has become an urgent issue that needs to be addressed. In few-shot learning, conventional methods often suffer from limited generalization capabilities. Herein, additional information and features are introduced to enhance the understanding and generalization capabilities of the model for targets. To address this challenge, this study proposes a few-shot ship classification method for SAR images based on scattering point topology and Dual-Branch Convolutional Neural Network (DB-CNN). First, a topology structure was constructed using scattering key points to characterize the structural and shape features of ship targets. Second, the Laplacian matrix of the topology structure was calculated to transform the topological relations between scattering points into a matrix form. Finally, the original image and Laplacian matrix were used as inputs to the DB-CNN for feature extraction. Regarding network architecture, a DB-CNN comprising two independent convolution branches was designed. These branches were tasked with processing visual and topological features, employing two cross-fusion attention modules to collaboratively merge features from both branches. This approach effectively integrates the topological relations of target scattering points into the automated learning process of the network, enhancing the generalization capabilities and enhancing the classification accuracy of the model. Experimental results demonstrated that the proposed approach obtained average accuracies of 53.80% and 73.00% in 1-shot and 5-shot tasks, respectively, on the OpenSARShip dataset. Similarly, on the FUSAR-Ship dataset, it achieved average accuracies of 54.44% and 71.36% in 1-shot and 5-shot tasks, respectively. In the case of both 1-shot and 5-shot tasks, the proposed approach outperformed the baseline by >15% in terms of accuracy, underscoring the effectiveness of incorporating scattering point topology in few-shot ship classification of SAR images.

Abstract Background Proprotein convertase subtilisin/kexin type 9 (PCSK9), the last member of the proprotein convertase family, functions as a classic regulator of low-density lipoprotein (LDL) by interacting with low-density lipoprotein receptor (LDLR). Recent studies have shown that PCSK9 can affect the occurrence and development of tumors and can be used as a novel therapeutic target. However, a comprehensive pan-cancer analysis of PCSK9 has yet to be conducted. Methods The potential oncogenic effects of PCSK9 in 33 types of tumors were explored based on the datasets of The Cancer Genome Atlas (TCGA) dataset. In addition, the immune regulatory role of PCSK9 inhibition was evaluated via in vitro cell coculture and the tumor-bearing mouse model. Finally, the antitumor efficacy of targeted PCSK9 combined with OVA-II vaccines was verified. Results Our results indicated that PCSK9 was highly expressed in most tumor types and was significantly correlated with late disease stage and poor prognosis. Additionally, PCSK9 may regulate the tumor immune matrix score, immune cell infiltration, immune checkpoint expression, and major histocompatibility complex expression. Notably, we first found that dendritic cell (DC) infiltration and major histocompatibility complex-II (MHC-II) expression could be upregulated by PCSK9 inhibition and improve CD8+ T cell activation in the tumor immune microenvironment, thereby achieving potent tumor control. Combining PCSK9 inhibitors could enhance the efficacies of OVA-II tumor vaccine monotherapy. Conclusions Conclusively, our pan-cancer analysis provided a more comprehensive understanding of the oncogenic and immunoregulatory roles of PCSK9 and demonstrated that targeting PCSK9 could increase the efficacy of long peptide vaccines by upregulating DC infiltration and MHC-II expression on the surface of tumor cells. Summary This study reveals the critical oncogenic and immunoregulatory roles of PCSK9 in various tumors and shows the promise of PCSK9 as a potent immunotherapy target.

Abstract Corn cob is a major waste mass-produced in corn agriculture. Corn cob hydrolysate containing xylose, arabinose, and glucose is the hydrolysis product of corn cob. Herein, a recombinant Escherichia coli strain BT-10 was constructed to transform corn cob hydrolysate into 1,2,4-butanetriol, a platform substance with diversified applications. To eliminate catabolite repression and enhance NADPH supply for alcohol dehydrogenase YqhD catalyzed 1,2,4-butanetriol generation, ptsG encoding glucose transporter EIICBGlc and pgi encoding phosphoglucose isomerase were deleted. With four heterologous enzymes including xylose dehydrogenase, xylonolactonase, xylonate dehydratase, α-ketoacid decarboxylase and endogenous YqhD, E. coli BT-10 can produce 36.63 g/L 1,2,4-butanetriol with a productivity of 1.14 g/[L·h] using xylose as substrate. When corn cob hydrolysate was used as the substrate, 43.4 g/L 1,2,4-butanetriol was generated with a productivity of 1.09 g/[L·h] and a yield of 0.9 mol/mol. With its desirable characteristics, E. coli BT-10 is a promising strain for commercial 1,2,4-butanetriol production.

Abstract The image‐to‐image translation (I2IT) task aims to transform images from the source domain into the specified target domain. State‐of‐the‐art CycleGAN‐based translation algorithms typically use cycle consistency loss and latent regression loss to constrain translation. In this work, it is demonstrated that the model parameters constrained by the cycle consistency loss and the latent regression loss are equivalent to optimizing the medians of the data distribution and the generative distribution. In addition, there is a style bias in the translation. This bias interacts between the generator and the style encoder and visually exhibits translation errors, e.g. the style of the generated image is not equal to the style of the reference image. To address these issues, a new I2IT model termed high‐quality‐I2IT (HQ‐I2IT) is proposed. The optimization scheme is redesigned to prevent the model from optimizing the median of the data distribution. In addition, by separating the optimization of the generator and the latent code estimator, the redesigned model avoids error interactions and gradually corrects errors during training, thereby avoiding learning the median of the generated distribution. The experimental results demonstrate that the visual quality of the images produced by HQ‐I2IT is significantly improved without changing the generator structure, especially when guided by the reference images. Specifically, the Fréchet inception distance on the AFHQ and CelebA‐HQ datasets are reduced from 19.8 to 10.2 and from 23.8 to 17.0, respectively.

To preliminarily assess the primary reasons for the reduction in polysaccharide content in Polygonatum sibiricum processed through the "Nine Steaming-Nine Processing" method and its impact on the in vitro activity of Polygonatum sibiricum polysaccharides, this study measured the levels of 5-hydroxymethylfurfural (5-HMF) and advanced glycation end-products (AGEs) in Polygonatum sibiricum processed through the "Nine Steaming-Nine Processing" method. The study also examined the structural changes of purified polysaccharides from Polygonatum sibiricum before and after the "Nine Steaming-Nine Processing" process and analyzed the influence of these changes on the in vitro activity of Polygonatum sibiricum. The results indicated that the "Nine Steaming-Nine Processing" induced the Maillard reaction in Polygonatum sibiricum, resulting in a 5-HMF content of (631.3±21.5) μg/g, and the levels of carboxymethyl lysine (CML) and carboxyethyl lysine (CEL) were (342.4±11.3) μg/g and (63.7±9.8) μg/g, respectively. This processing also had varying degrees of impact on the structure and composition of Polygonatum sibiricum polysaccharides. The glucose (Glc) content increased, while mannose (Man) and galacturonic acid (GalUA) content significantly decreased, with Man decreasing from 34.53% to 17.06%, and GalUA decreasing from 9.59% to 1.77%. The research suggests that Polygonatum sibiricum undergoes the Maillard reaction during the "Nine Steaming-Nine Processing", leading to the formation of a certain amount of AGEs. Simultaneously, the "Nine Steaming-Nine Processing" method can enhance the in vitro hypoglycemic activity of Polygonatum sibiricum polysaccharides to a certain extent.

Abstract Improving three-dimensional (3D) localization precision is of paramount importance for super-resolution imaging. By properly engineering the point spread function (PSF), such as utilizing Laguerre–Gaussian (LG) modes and their superposition, the ultimate limits of 3D localization precision can be enhanced. However, achieving these limits is challenging, as it often involves complicated detection strategies and practical limitations. In this work, we rigorously derive the ultimate 3D localization limits of LG modes and their superposition, specifically rotation modes, in the multi-parameter estimation framework. Our findings reveal that a significant portion of the information required for achieving 3D super-localization of LG modes can be obtained through feasible intensity detection. Moreover, the 3D ultimate precision can be achieved when the azimuthal index l is zero. To provide a proof-of-principle demonstration, we develop an iterative maximum likelihood estimation (MLE) algorithm that converges to the 3D position of a point source, considering the pixelation and detector noise. The experimental implementation exhibits an improvement of up to two-fold in lateral localization precision and up to twenty-fold in axial localization precision when using LG modes compared to Gaussian mode. We also showcase the superior axial localization capability of the rotation mode within the near-focus region, effectively overcoming the limitations encountered by single LG modes. Notably, in the presence of realistic aberration, the algorithm robustly achieves the Cramér-Rao lower bound. Our findings provide valuable insights for evaluating and optimizing the achievable 3D localization precision, which will facilitate the advancements in super-resolution microscopy.

To guide the more reasonable and fair allocation of medical resources, to solve the problem of fee prices negotiated by various subjects in the medical and health system and patient payment, and to solve the problem of how to ensure the privacy, accuracy, consistency and traceability of data in the process of collecting patient information in each hospital, according to the operation process of a remote consultation service, a decentralized remote intelligent consultation blockchain model is proposed. The model uses the improved ant colony algorithm under a smart contract and studies the practicality of the improved ant colony algorithm on the multi-node remote consultation service simulation platform. According to the experimental analysis results, the improved ant colony algorithm can automatically execute and effectively match the target population under the smart contract.

Abstract Colon-targeted oral drug delivery systems (CDDSs) are desirable for the treatment of ulcerative colitis (UC), which is a disease with high relapse and remission rates associated with immune system inflammation and dysregulation localized within the lining of the large bowel. However, the success of current available approaches used for colon-targeted therapy is limited. Budesonide (BUD) is a corticosteroid drug, and its rectal and oral formulations are used to treat UC, but the inconvenience of rectal administration and the systemic toxicity of oral administration restrict its long-term use. In this study, we designed and prepared colon-targeted solid lipid nanoparticles (SLNs) encapsulating BUD to treat UC by oral administration. A negatively charged surfactant (NaCS-C12) was synthesized to anchor cellulase-responsive layers consisting of polyelectrolyte complexes (PECs) formed by negatively charged NaCS and cationic chitosan onto the SLNs. The release rate and colon-specific release behavior of BUD could be easily modified by regulating the number of coated layers. We found that the two-layer BUD-loaded SLNs (SLN-BUD-2L) with a nanoscale particle size and negative zeta potential showed the designed colon-specific drug release profile in response to localized high cellulase activity. In addition, SLN-BUD-2L exhibited excellent anti-inflammatory activity in a dextran sulfate sodium (DSS)-induced colitis mouse model, suggesting its potential anti-UC applications.

BackgroundLung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), remains a pervasive global public health concern. Disulfidoptosis, a nascent form of regulated cell death (RCD), presents an emerging field of inquiry. Currently, investigations into disulfidoptosis are in their initial stages. Our undertaking sought to integrate single-cell RNA sequencing (scRNA-seq) in conjunction with traditional bulk RNA sequencing (bulk RNA-seq) methodologies, with the objective of delineating genes associated with disulfidoptosis and subsequently prognosticating the clinical outcomes of LUAD patients.MethodsInitially, we conducted an in-depth examination of the cellular composition disparities existing between LUAD and normal samples using scRNA-seq data sourced from GSE149655. Simultaneously, we scrutinized the expression patterns of disulfidoptosis-associated gene sets across diverse cell types. Subsequently, leveraging the bulk RNA-seq data, we formulated disulfidoptosis-related prognostic risk signatures (DRPS) employing LASSO-Cox regression. This was accomplished by focusing on genes implicated in disulfidoptosis that exhibited differential expression within endothelial cells (ECs). Sequentially, the robustness and precision of the DRPS model were rigorously verified through both internal and external validation datasets. In parallel, we executed single-cell trajectory analysis to delve into the differentiation dynamics of ECs. Concluding our study, we undertook a comprehensive investigation encompassing various facets. These included comparative assessments of enrichment pathways, clinicopathological parameters, immune cell abundance, immune response-associated genes, impacts of immunotherapy, and drug predictions among distinct risk cohorts.ResultsThe scrutiny of scRNA-seq data underscored discernible disparities in cellular composition between LUAD and normal samples. Furthermore, disulfidoptosis-associated genes exhibited marked discrepancies within endothelial cells (ECs). Consequently, we formulated the Disulfidoptosis-Related Prognostic Signature (DRPS) to facilitate prognostic prediction. The prognostic nomogram based on the risk score effectively demonstrated DRPS’s robust capacity to prognosticate survival outcomes. This assertion was corroborated by rigorous assessments utilizing both internal and external validation sets, thus affirming the commendable predictive accuracy and enduring stability of DRPS. Functional enrichment analysis shed light on the significant correlation of DRPS with pathways intrinsic to the cell cycle. Subsequent analysis unveiled correlations between DRPS and gene mutations characteristic of LUAD, as well as indications of an immunosuppressive status. Through drug prediction, we explored potential therapeutic agents for low-risk patients. Concluding our investigation, qRT-PCR experiments confirmed the heightened expression levels of EPHX1, LDHA, SHC1, MYO6, and TLE1 in lung cancer cell lines.

Synthetic aperture radar (SAR) has emerged as a critical technology for detecting and classifying objects, such as ships, in challenging environments. However, few-shot learning remains challenging due to the limited availability of labeled SAR data, complex radar backscatter, and variations in imaging parameters. In this article, we propose a novel network, scattering-point topology for few-shot ship classification (SPT-FSC), which addresses these challenges by incorporating scattering characteristics into the network learning process through a scattering-point topology (SPT) based on scattering key points. We design a topology encoding branch through a series of operations to encode the topological information of scattering points, resulting in an SPT embedding that improves the network's adaptability to the imaging mechanism and reduces imaging variability in SAR images. To effectively fuse the SPT embedding and image features extracted from a convolutional neural network, we introduce a novel mechanism named reciprocal feature fusion attention. In addition, to address the limited diversity in the training data, we apply fine-tuning-based methodologies and construct a fine-grained ship classification dataset by combining the OpenSARShip and FUSAR-Ship datasets. Our comprehensive experiments on these datasets demonstrate the effectiveness of our proposed SPT-FSC method, achieving high accuracy and robustness in few-shot ship classification tasks for SAR images, outperforming the existing methods in this domain.

Abstract Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL.

Abstract Background Early diagnosis of prostate cancer improves its prognosis, while it is essential to upgrade screening tools. This study aimed to explore the value of a novel functional magnetic resonance imaging (MRI) technique, namely amide proton transfer (APT)-weighted MRI, combined with serum prostate-specific antigen (PSA) levels to differentiate malignant prostate lesions from benign prostate lesions. Methods Data of patients who underwent prostate examinations at Chongqing University Cancer Hospital between July 2019 and March 2022 were retrospectively analyzed. All patients underwent T2-weighted imaging (T2WI), APT, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI. Two radiologists analyzed the images independently. The ability of the quantitative parameters alone or in different combinations in differentiating malignant prostate lesions from benign prostate lesions were compared by using receiver operating characteristic (ROC) curves. According to the DeLong test, the combined parameters were significantly different from the corresponding single parameter (P 0.05). APTmax and APTmean had the high values of area under the ROC curve (AUC), which were 0.780 and 0.710, respectively. APTmax had a high sensitivity, and APTmean had a high specificity. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest AUC value (AUC: 0.880, sensitivity: 86.540, specificity: 78.260). Conclusion APTmax, APTmean, ADCmean, ADCmin, tPAD, FPSA, and PSAD showed to have a high value in differentiating malignant prostate lesions from benign prostate lesions in the separate assessment of indexes. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest diagnostic value.

The systematic identification of volatile organic compounds (VOCs) and non-VOCs will facilitate understanding the characteristic aroma and bioactive constituents of Dianhong. This article reported for the first time the volatile and non-volatile composition profiles of Dianhong from four main producing areas. A combined total of 42 VOCs were identified from four Dianhong samples by static headspace GC-MS. Thirteen VOCs were found to be important common components contributing to the characteristic aroma of Dianhong. The non-VOCs of Dianhong were evaluated by UPLC-ESI-MS, and Dianhong samples from four producing areas shared almost the same component profiles. Thirty-four components including derivatives of quinic acid, gallic acid, and catechin, flavone C-glycosides, flavonol O-glycosides, and alkaloids were characterized. Finally, catechin, gallic acid, 5-O-galloylquininc acid, and theobromine were characterized as the main non-VOCs in Dianhong. Dianhong samples from four main producing areas showed similar VOCs and non-VOCs profiles under our optimized GC-MS and LC-MS conditions.

Abstract Intricate assembly of multiple molecular chromophores assisted by protein scaffolds is essential in tuning the optical absorption and energy transfer in the light‐harvesting complexes of the photosynthetic systems in nature. However, it remains a challenge to achieve such structural complexity and functionality in synthetic polymer‐chromophore systems. Here, we report a series of polyester‐tethered pyrrolopyrrole cyanine derivatives and their colloidal nanoparticles dispersed in water, which show tunable J‐ or H‐aggregation excitonic coupling and near‐infrared fluorescence by precise control of the polymer chain lengths, composition, and temperature. Moreover, the optimal fluorescence or photothermal effect of the J‐aggregate nanoparticles enables broad applications in fluorescence or photoacoustic bioimaging and phototherapy.

Automatic Exploit Generation (AEG) involves automatically discovering paths in a program that trigger vulnerabilities, thereby generating exploits. While there is considerable research on heap-related vulnerability detection, such as detecting Heap Overflow and Use After Free (UAF) vulnerabilities, among contemporary heap-automated exploit techniques, only certain automated exploit techniques can hijack program control flow to the shellcode. An important limitation of this approach is that it cannot effectively bypass Linux’s protection mechanisms. To solve this problem, we introduced Automatic Advanced Heap Exploit Generation (AAHEG). It first applies symbolic execution to analyze heap-related primitives in files and then detects potential heap-related vulnerabilities without a source code. After identifying these vulnerabilities, AAHEG builds an exploit abstract syntax tree (AST) to identify one or more successful exploit strategies, such as fast bin attack and Safe-unlink. AAHEG then selects exploitable methods via an abstract syntax tree (AST) and performs final testing to produce the final exploit. AAHEG chose to generate advanced heap-related exploits because the exploits can bypass Linux protections. Basically, AAHEG can automatically detect heap-related vulnerabilities in binaries without source code, build an exploit AST, choose from a variety of advanced heap exploit methods, bypass all Linux protection mechanisms, and generate final file-form exploit based on pwntools which can pass local and remote testing. Experimental results show that AAHEG successfully completed vulnerability detection and exploit generation for 20 Capture The Flag (CTF) binary files, 11 of which have all protection mechanisms enabled.

Abstract Digital‐to‐analogue and analogue‐to‐digital in a digital array radar limits the transmission and reception of instantaneous broadband signals (IBSs), which makes it a technical bottleneck for digital array radar to obtain an instantaneous broadband high‐resolution range profile (HRRP). A frequency‐agile orthogonal frequency division multiplexing (OFDM) waveform with a high repetition frequency pulse train is proposed, which uses multiple narrowband OFDM to realise large bandwidth so that the digital array radar can easily realise the broadband working mode. This frequency hopping signal makes the digital array radar have the characteristics of broadband HRRP formation and low interception simultaneously. To solve the problem of range migration caused by high‐speed moving targets, a two‐stage sparse processing algorithm with range migration compensation capability (FS‐RMCSP) in slow time and fast time domains is proposed. By constructing a sparse processing dictionary matrix with range compensation operator according to the phase offset of the moving target echo, the proposed algorithm can complete the compensation of target range migration with high resolution, accurately recover the range‐Doppler parameters of target, and realise the coherent accumulation of target echo. The simulation results show that this waveform can obtain the range‐Doppler high‐resolution characteristics equivalent to the IBS in the radar tracking working mode. Compared with the conventional sparse signal processing algorithm, the FS‐RMCSP algorithm significantly improves the performance of target reconstruction in the scene of high‐speed moving targets.

Abstract Background To analyze the level changes of 28 cytokines in aqueous humor of patients with proliferative diabetic retinopathy (PDR) coexisting neovascular glaucoma (NVG) after intravitreal injection of conbercept (IVC), and to investigate whether these cytokines are associated with intraoperative bleeding (IOB). Methods Totally 34 eyes with NVG secondary to PDR were enrolled. Patients were randomized into two groups, and all of them underwent 25-gauge pars plana vitrectomy (PPV) combined with trabeculectomy. Group I, 18 eyes received IVC 3 days before PPV, and 100 µL aqueous humor was collected at the time of IVC pretreatment and 3 days later at the beginning of PPV respectively. Group II, 16 eyes received IVC after PPV, and 100 µL aqueous humor was collected only at the beginning of PPV. Aqueous humor from 19 eyes with age-matched cataract patients served as controls. Luminex bead-based multiplex array was used to measure the levels of 28 cytokines in aqueous humor. The baseline cytokine levels were compared among the three groups. All NVG patients were divided into IOB and non-bleeding (INB) groups. The cytokine levels of aqueous humor at the beginning of PPV were compared between group I and II, also between IOB and INB groups. IOB in NVG patients was graded according to vitreous bleeding amount. The correlation between cytokine levels and the grades of IOB were analyzed. Results Compared with controls, the baseline levels of 18 cytokines associated with inflammation and angiogenesis showed significantly increased in group I and group II (all, P 0.4, P

While understanding the long-term slip rate of active normal faults is essential for the comprehensive assessment of seismic activity, it is difficult due to the absence of age control in the erosional bedrock region. The preserved sequence of wave-cut platforms in granite allows exploration of the long-term slip rate in the footwall of some normal faults. We investigated wave-cut platforms in the southern Pearl River Delta (PRD), a coastal delta transected by the seismically active Littoral Fault Zone (LFZ) in the northern South China Sea, to derive slip rates and their impacts on the seismic hazard potential. We mapped a flight of four wave-cut platforms (T1–T4), dated the T2 and T4 platforms by 10Be cosmogenic nuclide dating, and used the absolute age to correlate the un-dated platform to global sea-level highstands. Our results allocate the ages of 128 ka, 197 ka, and 239 ka to the upper three wave-cut platforms and yield temporally various uplift rates ranging from 0.30 to 0.38 mm/a during 239–128 ka to 0.09 mm/a since 128 ka. A decrease in the uplift rate, which coincided with a decreased subsidence rate within the PRD in previous work, implied a weakened differential uplift onshore of the LFZ system. Our findings infer that the transgression event occurred as early as marine isotope stage (MIS) 7 in the PRD, consistent with the view that Pleistocene sedimentation began in MIS 5 or earlier in the PRD.

The sarpagine-ajmaline-koumine type alkaloids are among the most important groups of monoterpenoid indole alkaloids, having notable biological activity. Here the authors perform divergent syntheses of 14 natural products in this family from a common intermediate.

Maize kernel growth is sensitive to heat stress, which is predicted to result in yield loss. However, the response of maize to short-term heat stress during different kernel-growth stages is still not clear. A 3-year field experiment, included two heat-stress treatments (LSH, lag-stage heat stress; FSH, effective-filling-stage heat stress), was conducted in 2019–2021. The results showed that LSH and FSH significantly reduced the grain yield by 8.7–14.9% and 11.6–17.6%, respectively, compared with the control (CK). LSH mainly reduced the kernel number per ear, and FSH mainly reduced the kernel weight. Heat stress reduced the SPAD and chlorophyll content during the effective-filling stage, but not in the lag stage. Photosynthesis was obviously reduced under heat stress during both stages; however, the photosynthesis rate during the lag stage was higher than during the effective-filling stage. The decreased amplitude of dry matter under LSH was higher than under FSH during the heating period. However, there was no difference between the CK and LSH samples in terms of dry-matter accumulation from the end of heat stress to harvest, which was significantly reduced under FSH. Additionally, decreased starch-synthesis-related enzyme activity, i.e., adenosine diphos-phoglucose pyrophosphprylase, contributed to the kernel number and kernel weight loss in LSH and FSH, respectively. The kernel-growth rate (per ear) was lowered, but the growth duration was not shortened in this study. Consequently, LSH mainly reduced the photosynthesis rate (Pn), resulting in kernel abortion and yield penalty. FSH mainly reduced the Pn and chlorophyll content, which reduced the kernel weight, and increased yield loss.

Abstract Here, we performed N6-methyladenosine (m6A) RNA sequencing to determine the circRNA m6A methylation changes in the placentas during the pathogenesis of preeclampsia (PE). We verified the expression of the circRNA circPAPPA2 using quantitative reverse transcription-PCR. An invasion assay was carried out to identify the role of circPAPPA2 in the development of PE. Mechanistically, we investigated the cause of the altered m6A modification of circPAPPA2 through overexpression and knockdown cell experiments, RNA immunoprecipitation, fluorescence in situ hybridization and RNA stability experiments. We found that increases in m6A-modified circRNAs are prevalent in PE placentas and that the main changes in methylation occur in the 3’UTR and near the start codon, implicating the involvement of these changes in PE development. We also found that the levels of circPAPPA2 are decreased but that m6A modification is augmented. Furthermore, we discovered that methyltransferase‑like 14 (METTL14) increases the level of circPAPPA2 m6A methylation and that insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) maintains circPAPPA2 stability. Decreases in IGF2BP3 levels lead to declines in circPAPPA2 levels. In summary, we provide a new vision and strategy for the study of PE pathology and report that placental circRNA m6A modification appears to be an important regulatory mechanism.

Activated carbon has been widely used to remove hazardous Cr(VI); however, the impact of Cr2O3 precipitate on gradually declining removal ability as pH increases has received little attention. Herein, to investigate the effect of Cr2O3, SEM-EDX (scanning electron microscope-energy dispersive X-ray analysis) coupling elements mapping of chromium-loaded powdered activated carbon (PAC) revealed that a chromium layer was formed on the PAC exterior after being treated with Cr(VI) at pH 7. XPS (X-ray photoelectron spectroscopy) study confirmed that 69.93% and 39.91% Cr2O3 precipitated on the PAC surface at pH 7 and pH 3, respectively, corresponding to 17.77 mg/g and 20 mg/g removal capacity. Exhausted PAC had a removal efficiency of 92.43% after Cr2O3 being washed by H2SO4 solution, which was much higher than the removal efficiency of 51.27 % after NaOH washing. This further verified that the intrinsically developed Cr2O3 precipitate on PAC under neutral conditions limited the durability of PAC as an adsorbent. Consecutive elution assessments confirmed that adsorption and reduction ability both declined as pH increased. Raman spectroscopy and C 1s spectra of materials demonstrated two distinct Cr(VI) removal mechanisms under pH 3 and pH 7. In conclusion, the exhausted AC after Cr(VI) adsorption can be rejuvenated after the surface coated Cr2O3 is washed by the acid solution, which can expand the longevity of AC and recover Cr(III). HIGHLIGHT In this work, we scrutinized the mechanism of poor removal capacity of commercial activated carbon on toxic heavy metal Cr(VI) under neutral pH conditions. Differing from the most accepted view that electrostatic repulsion is the main consideration, our study suggested that the relatively more Cr2O3 precipitate on the surface of activated carbon under higher pH led to the low Cr(VI) sequestration capability.;

Background: Numerous studies have revealed that the long non-coding RNA LINC00662 is irregularly expressed in various cancers, as well as is correlated with cancer development and progression. Nevertheless, the clinical value of LINC00662 remains controversial. Hence, we explored the correlation of LINC00662 with cancer prognosis through meta-analysis and bioinformatics analysis.Methods: From the beginning through 12 March 2022, we searched for correlational studies on Web of Science, Embase, PubMed and The Cochrane Library. We used pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) to determine the significance of studies on survival outcomes and clinicopathological aspects in human cancers. Additionally, the Gene Expression Profiling Interactive Analysis (GEPIA) database was employed to confirm our findings.Results: Our meta-analysis of 14 studies comprising a total of 960 cancer patients revealed that LINC00662 overexpression was correlated with poor overall survival (HR = 1.91, 95% CI 1.49–2.45, p < 0.001) in cancer patients and relapse-free survival (HR = 2.12, 95% CI 1.19–3.76, p = 0.010) in hepatocellular carcinoma patients. The correlation between LINC00662 and OS was further supported by the results of subgroup analyses according to cancer type, follow-up time, HR availability, and NOS score. In addition, LINC00662 overexpression predicted advanced tumor stage (OR = 4.23, 95% CI 2.50–7.17, p < 0.001), larger tumor size (OR = 1.49, 95% CI 1.11–1.99, p = 0.008), earlier lymph node metastasis (OR = 2.40, 95% CI 1.25–4.59, p = 0.008), and earlier distant metastasis (OR = 4.78, 95% CI 2.57–8.88, p < 0.001). However, there were no statistically significant differences in age (OR = 1.16, 95% CI 0.90–1.51, p = 0.246), gender (OR = 1.10, 95% CI 0.79–1.53, p = 0.578), or differentiation grade (OR = 1.53, 95% CI 0.71–3.33, p = 0.280).Conclusion: LINC00662 expression upregulation is associated with poor prognosis and advanced clinicopathological features in patients with multiple tumors. LINC00662 may serve as a biomarker for the diagnosis and treatment of patients with tumors.

This study examines the spreading behavior of window spill fire under the action of lateral wind and its influence on the temperature distribution of polyethylene sandwich panels on the outer surface of buildings. Twelve working conditions were set up based on different opening sizes and wind speeds. Under the action of lateral wind, with a constant opening size, this study has found greater wind speed, lower average flame height, and longer horizontal flame propagation length. This study is based on the feature-length. The facade flame height model without wind was developed, and the average flame height model under extreme conditions was established based on the speculation of a lateral wind Froude number. In addition, under constant opening size, the peak surface temperature of the PE sandwich panel is the highest when the wind speed is 1 m/s. These conclusions are of great significance for fire studies.

This study investigated the impact of a multiple epoxy chain extender (ADR) on the rheological behavior, crystallization, and mechanical properties of polyglycolic acid (PGA). Tests of the torque and melt mass flow rate and dynamic rheological analysis were conducted to study the rheological behavior of PGA modified with ADR. The rheological results of the modified PGA showed a significantly increased viscosity and storage modulus with an increase in the ADR amount, which could be attributed to the chain extension/branching reactions between PGA and ADR. It was proved that ADR could be used as an efficient chain extender for tailoring the rheological performance of PGA. The Han plot of the modified PGA showed a transition of viscous behavior to elastic behavior, while the ADR content was increased from 0 to 0.9 phr. The formation of long-chain branches (LCBs) was confirmed via the Cole–Cole plot and weighted relaxation spectrum, wherein the LCBs substantially changed the rheological behavior of the modified PGA. The vGP plots predicted a star-type topological structure for the LCBs. The results of non-isothermal crystallization kinetics suggested that the crystallization of the modified PGA was predominantly homogeneous nucleation and three-dimensional growth. The crystallinity decreased slightly with the increase in the ADR amount. Compared to neat PGA, the modified PGA samples exhibited better tensile and flexural performances.

Abstract Overflow metabolism-caused acetate accumulation is a major problem that restricts industrial applications of various bacteria. 2,3-Butanediol (2,3-BD) synthesis in microorganisms is an ancient metabolic process with unidentified functions. We demonstrate here that acetate increases and then decreases during the growth of a bacterium Enterobacter cloacae subsp. dissolvens SDM. Both bifunctional acetaldehyde/ethanol dehydrogenase AdhE-catalyzed ethanol production and acetate-induced 2,3-BD biosynthesis are indispensable for the elimination of acetate generated during overflow metabolism. 2,3-BD biosynthesis from glucose supplies NADH required for acetate elimination via AdhE-catalyzed ethanol production. The coupling strategy involving 2,3-BD biosynthesis and ethanol production is widely distributed in bacteria and is important for toxic acetate elimination. Finally, we realized the co-production of ethanol and acetoin from chitin, the second most abundant natural biopolymer whose catabolism involves inevitable acetate production through the coupling acetate elimination strategy. The synthesis of a non-toxic chemical such as 2,3-BD may be viewed as a unique overflow metabolism with desirable metabolic functions.

The arc-shaped tectonic belt, located in the northeastern margin of the Tibetan Plateau, is one of the leading edges of the plateau’s outward growth and uplift expansion, with a large number of active faults and frequent seismic activity. Researchers have carried out numerous studies on active faults in this region, and a wealth of reliable basic data has been accumulated. However, integrating multidisciplinary data to establish a 3D geometrical structure model that is concerned about seismogenic tectonics and can be tested, has become the key to restricting the regional seismic hazard evaluation. Based on a series of published active tectonic research, we analyze in detail the surface and deep coupling relationships of the major active faults in this region and establish three sets of 3D fault structure models, which are built respectively by active fault mapping and dip angles (the V1 model), 7 magnetotelluric profiles and 7 auxiliary profiles (the V2 model), and multi-source data (the V3 model) and continuously close to the real geological facts. From the model perspective, it is suggested that the controversial Haiyuan fault is a crustal-scale left-slip fault and the shape of the Liupanshan fault reflects the absorption of the left-slip component of the Haiyuan fault. Comparing the same fault plane of these three models, we find that the V3 model is more consistent with geological facts, showing that by assisting the multi-source data 3D geological modeling technique we can establish a 3D geological model closest to the real regional structure. Finally, combining the V3 model, the fault segmentation, and the empirical formulas of the moment magnitude-rupture parameters, we segment the faults and calculate the potential moment magnitudes of the major active faults in the study region. The faults with relatively higher seismic hazards are the Liupanshan fault, the southeastern segment of the Xiangshan-Tianjingshan fault, the westernmost segment of the Haiyuan fault, and the West Qinling fault, of which the estimated potential moment magnitudes are generally more than 7.0. Our study provides a referenced 3D geological model for exploring the deep structures of the region, regional geological research, and earthquake disaster prevention.

The wide use of browser extensions brings the privacy leakage problem. The previous works detected private data transmission to find privacy leakage in Chrome or Firefox, but the real challenge is to determine whether the transmission is reasonable because the privacy data that existed in transmission does not absolutely mean leaking. To this end, we establish a privacy model for each extension, which contains the sensitive information permitted to be used and servers authorized to communicate with. In order to evaluate the effectiveness of the proposed method, we develop a dynamic browser extension privacy detection framework. It first builds privacy models for extensions and records all network traffic when accessing test pages. Then, the leakage results are presented according to the strict privacy leakage judgment rules. In this paper, the experiments are conducted in a real environment, and our work is verified by 34,095 extensions which are collected from 3 mainstream browsers in China from November 2019 to August 2020. There is a total of 2,983 extensions that exist privacy leakage. We further conduct a comprehensive analysis of the results including calculating the precision, recall, accuracy, and F1 score for each type of leakage, and show the information leaked by different extension categories and the malicious domain name that collecting the users’ privacy, as well as the results changing of detection over time.

Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention due to its significance and challenges. In recent years, numerous detectors based on deep learning have achieved good performance in the field of SAR ship detection. However, ship targets of the same type always have various representations in SAR images under different imaging conditions, while different types of ships may have a high degree of similarity, which considerably complicates SAR target recognition. Meanwhile, the ship target in the SAR image is also obscured by background and noise. To address these issues, this paper proposes a novel oriented ship detection method in SAR images named SPG-OSD. First, we propose an oriented two-stage detection module based on the scattering characteristics. Second, to reduce false alarms and missing ships, we improve the performance of the network by incorporating SAR scattering characteristics in the first stage of the detector. A scattering-point-guided region proposal network (RPN) is designed to predict possible key scattering points and make the regression and classification stages of RPN increase attention to the vicinity of key scattering points and reduce attention to background and noise. Third, supervised contrastive learning is introduced to alleviate the problem of minute discrepancies among SAR object classes. Region-of-Interest (RoI) contrastive loss is proposed to enhance inter-class distinction and diminish intra-class variance. Extensive experiments are conducted on the SAR ship detection dataset from the Gaofen-3 satellite, and the experimental results demonstrate the effectiveness of SPG-OSD and show that our method achieves state-of-the-art performance.

The Programmable Logic Controller (PLC) is located at the junction of the virtual network and physical reality in the Industrial Control System (ICS), which is vulnerable to attacks due to its weak security. Specifically, firmware tampering attacks take the firmware under the PLC operating system as the primary attack target. The firmware provides the bridge between PLC’s hardware and software, which means tampering against the firmware can be more destructive and harmful than other attacks. However, existing defense and forensics methods against firmware tampering attacks are asymmetrical, which directly leads to the proliferation of such attacks and the difficulty of forensic tracing. How to accurately, quickly, and efficiently conduct forensics for such attacks is an urgent problem. In this paper, we designed and implemented a reliable detection method based on Joint Test Action Group (JTAG) and memory comparison—Aye, which can detect mainstream firmware tampering attacks reliably. To determine the effectiveness and reliability of Aye, we selected a widely used PLC to observe Aye’s performance in defense and forensics by simulating the two latest PLC firmware tampering attack methods. The experimental results show that Aye can effectively defend against firmware tampering attacks, helping improve the efficiency and accuracy of such attack detection and forensics.

Abstract Background Preeclampsia is a severe disease in pregnant women, which is primarily managed by early screening and prevention. Circular RNAs (circRNAs) have increasingly been shown to be important biological regulators involved in numerous diseases. Further, increasing evidence has demonstrated that circRNAs can be used as diagnostic biomarkers. This study was conducted to evaluate the potential of circCRAMP1L, previously identified to be downregulated in preeclampsia, as a novel biomarker for predicting the development of preeclampsia. Methods We measured the expression of circCRAMP1L, which is reportedly relevant to trophoblast physiology, in plasma samples from 64 patients with preeclampsia and 64 age-, gestational age-, and body mass index-matched healthy pregnant women by qRT-PCR. MTT proliferation and transwell invasion assays revealed the biological role of circCRAMP1L in preeclampsia pathogenesis. RNA immunoprecipitation and dual-luciferase reporter assays clarified the mechanism underlying the biological function of circCRAMP1L in TEV-1 cells. Results circCRAMP1L circulating levels were significantly lower in patients with preeclampsia (2.66 ± 0.82, △Ct value) than in healthy pregnant women (3.95 ± 0.67, △Ct value, p

The Qilian Shan, located in the northeastern Tibetan Plateau, is an intraplate orogenic belt that underwent several episodes of fold and thrust deformation, particularly during the Mesozoic and Cenozoic. However, the deformation styles and relationships between the basin and mountains remain controversial. Therefore, in the current study, we conducted detailed field mapping of the sedimentary basins in Sunan and Huangcheng, and observed three episodes of compressive tectonic activity. We also restored a deformed section to determine the shortening rate of the Cretaceous sedimentary Sunan Basin. The first thrust episode, during the Paleogene, involved a southwestward thrust motion, comprising the Yumu Shan and Gaizhangdaban thrust systems. The second Neogene episode involved the northeastern thrust belt in the northern Qilian Shan, which comprises the Northern Qilian thrust system. The third episode produced NW-trending strike-slip activity that became the major tectonic deformation style; thus, the entire block rotated clockwise. Additionally, the restored section revealed that the Cretaceous strata have been shortened by ∼3.56%. Collectively, these results indicate that the Sunan and Huangcheng area on the northeastern Tibetan Plateau is influenced by the far-field effects of the collision between the Indian and Asian continents, as well as the effects of intraplate orogenic processes related to the collision of the Alashan Block and the Qilian Shan. Therefore, the current study has defined the deformation style in the northeastern Qilian Shan region, so we wish to give a clarification of the tectonic evolution and forecast the tectonic propagation in the Qilian Shan region.

Purpose. To investigate the aqueous levels of angiogenic factors in nonproliferative diabetic retinopathy (NPDR) patients with diabetic macular edema (DME) and to ascertain their association with optical coherence tomography angiography (OCTA) metrics. Methods. This study enrolled 21 NPDR eyes with DME (NPDR/DME+), 17 NPDR eyes without DME (NPDR/DME-), and 16 diabetic eyes without retinopathy (DWR). Luminex bead-based multiplex array was used to measure the levels of 25 cytokines. OCTA system with a scan area of 3×3 mm was used to measure retinal thickness (RT), retinal volume (RV), superficial vessel density (SVD), deep vessel density (DVD), foveal avascular zone (FAZ) area, perimeter and acircularity index. Results. The levels of ANGPTL4 were significantly different among the three groups (P

This paper proposes a method for optimizing unbalanced force and unbalanced moment of the multistage disk based on sequence quadratic program algorithm to solve the vibration problem of gas turbine tie rod rotor. This method guides the assembly phase of the multistage disks. The influence of unbalanced force and unbalanced moment on the vibration of the tie rod rotor are analyzed based on the characteristics of rotor structure and assembly process. A dynamic model of the unbalanced force and unbalanced moment of the tie rod rotor is established. The sequence quadratic program algorithm is used to optimize multi-dimension of unbalanced force and moment, so the global optimal solution can be obtained. In order to verify the effectiveness of the optimization method proposed in this paper, vibration control experiments are carried out for traditional tie rod rotor and gas turbine tie rod rotor structure. The results show that both unbalanced force optimization and unbalanced moment optimization can control the tie rod rotor vibration effectively, and unbalanced moment optimization is better. Unbalanced moment optimization is used to perform constant speed and speed-up experiment on the gas turbine tie rod rotor structure. At 1200r/min, the maximum vibration reduction of the system is 76.68%. And the vibration has a decrease of 43.3% at the first-order critical speed. The proposed method in this paper can be used not only for the guidance of tie rod rotor assembly of gas turbine, but also for the vibration control during operation.

Medicinal plants produce important substrates for their adaptation and defenses against environmental factors and, at the same time, are used for traditional medicine and industrial additives. Plants have relatively little in the way of secondary metabolites via biosynthesis. Recently, the whole-genome sequencing of medicinal plants and the identification of secondary metabolite production were revolutionized by the rapid development and cheap cost of sequencing technology. Advances in functional genomics, such as transcriptomics, proteomics, and metabolomics, pave the way for discoveries in secondary metabolites and related key genes. The multi-omics approaches can offer tremendous insight into the variety, distribution, and development of biosynthetic gene clusters (BGCs). Although many reviews have reported on the plant and medicinal plant genome, chemistry, and pharmacology, there is no review giving a comprehensive report about the medicinal plant genome and multi-omics approaches to study the biosynthesis pathway of secondary metabolites. Here, we introduce the medicinal plant genome and the application of multi-omics tools for identifying genes related to the biosynthesis pathway of secondary metabolites. Moreover, we explore comparative genomics and polyploidy for gene family analysis in medicinal plants. This study promotes medicinal plant genomics, which contributes to the biosynthesis and screening of plant substrates and plant-based drugs and prompts the research efficiency of traditional medicine.

BackgroundThe COVID-19 pandemic has affected people’s daily lives and has caused economic loss worldwide. Anecdotal evidence suggests that the pandemic has increased depression levels among the population. However, systematic studies of depression detection and monitoring during the pandemic are lacking. ObjectiveThis study aims to develop a method to create a large-scale depression user data set in an automatic fashion so that the method is scalable and can be adapted to future events; verify the effectiveness of transformer-based deep learning language models in identifying depression users from their everyday language; examine psychological text features’ importance when used in depression classification; and, finally, use the model for monitoring the fluctuation of depression levels of different groups as the disease propagates. MethodsTo study this subject, we designed an effective regular expression-based search method and created the largest English Twitter depression data set containing 2575 distinct identified users with depression and their past tweets. To examine the effect of depression on people’s Twitter language, we trained three transformer-based depression classification models on the data set, evaluated their performance with progressively increased training sizes, and compared the model’s tweet chunk-level and user-level performances. Furthermore, inspired by psychological studies, we created a fusion classifier that combines deep learning model scores with psychological text features and users’ demographic information, and investigated these features’ relations to depression signals. Finally, we demonstrated our model’s capability of monitoring both group-level and population-level depression trends by presenting two of its applications during the COVID-19 pandemic. ResultsOur fusion model demonstrated an accuracy of 78.9% on a test set containing 446 people, half of which were identified as having depression. Conscientiousness, neuroticism, appearance of first person pronouns, talking about biological processes such as eat and sleep, talking about power, and exhibiting sadness were shown to be important features in depression classification. Further, when used for monitoring the depression trend, our model showed that depressive users, in general, responded to the pandemic later than the control group based on their tweets (n=500). It was also shown that three US states—New York, California, and Florida—shared a similar depression trend as the whole US population (n=9050). When compared to New York and California, people in Florida demonstrated a substantially lower level of depression. ConclusionsThis study proposes an efficient method that can be used to analyze the depression level of different groups of people on Twitter. We hope this study can raise awareness among researchers and the public of COVID-19’s impact on people’s mental health. The noninvasive monitoring system can also be readily adapted to other big events besides COVID-19 and can be useful during future outbreaks.

The COVID-19 pandemic poses a threat to global health. Due to its high sensitivity, specificity, and stability, real-time fluorescence quantitative (real-time PCR) detection has become the most extensively used approach for diagnosing SARS-CoV-2 pneumonia. According to a report from the World Health Organization, emerging and underdeveloped nations lack nucleic acid detection kits and polymerase chain reaction (PCR) instruments for molecular biological detection. In addition, sending samples to a laboratory for testing may result in considerable delays between sampling and diagnosis, which is not favorable to the timely prevention and control of new crown outbreaks. Concurrently, there is an urgent demand for accurate PCR devices that do not require a laboratory setting, are more portable, and are capable of completing testing on-site. Hence, we report on HDLRT-qPCR, a new, low-cost, multiplexed real-time fluorescence detection apparatus that we have developed for on-site testing investigations of diverse diseases in developing nations. This apparatus can complete on-site testing rapidly and sensitively. The entire cost of this instrument does not exceed USD 760. In order to demonstrate the applicability of our PCR instrument, we conducted testing that revealed that we achieved gradient amplification and melting curves comparable to those of commercially available equipment. Good consistency characterized the testing outcomes. The successful detection of target genes demonstrates the reliability of our inexpensive PCR diagnostic technique. With this apparatus, there is no need to transport samples to a central laboratory; instead, we conduct testing at the sampling site. This saves time on transportation, substantially accelerates overall testing speed, and provides results within 40 min.

The Industrial Control System (ICS) is a public facility that provides services to lots of users; thus, its security has always been a critical factor in measuring its availability. Recently, a new type of attack on ICS has occurred frequently, which realizes the extortion of users by invading the information domain and destroying the physical domain. However, due to the diversity and unavailability of an ICS control logic, the targets of such attacks are usually limited to PCs and servers, leaving more disruptive attack methods unexplored. To contribute more possible attack methods to strengthen the immunity of ICS, in this paper, we propose a novel ransomware attack method named Industrial Control System Automatic Ransomware Constructor (ICS-ARC). Compared to existing ICS ransomware, ICS-ARC can automatically generate an International Electrotechnical Commission (IEC) compliant payload to compromise the Programmable Logic Controller (PLC) without a pre-known control logic, dramatically reducing adversary requirements and leaving room for error. To evaluate the attack capability of ICS-ARC, we built a tap water treatment system as the simulation experiment target for verification. The experimental results determine that ICS-ARC can automatically generate malicious code without the control logic and complete the attack against target PLCs. In addition, to assist the related research on future attacks and defenses, we present the statistical results and corresponding analysis of PLC based on Shodan.

The COVID-19 outbreak has affected the lives of people across the globe. To investigate the mental impact of COVID-19 and to respond to the call of researchers for the use of unobtrusive and intensive measurement in capturing time-sensitive psychological concepts (e.g., affect), we used big data methods to investigate the impact of COVID-19 by analyzing 348,933 tweets that people posted from April 1, 2020 to April 24, 2020. The dataset covers 2,231 working adults, who are from 454 counties across 48 states in the United States. In this study, we theorize the similarity and dissimilarity between COVID-19 and other common stressors. Similar to other stressors, pandemic severity negatively influenced the well-being of people by increasing negative affect. However, we did not find an influence of pandemic severity on the positive affect of the people. Dissimilar to other stressors, the protective factors for people during COVID-19 are not common factors that make people resilient to stress and they echo the unique experience during COVID-19. Moreover, we analyzed the text content of 348,933 tweets through Linguistic Inquiry Word Count (LIWC) and word cloud analysis to further reveal the psychological impact of COVID-19 and why the protective factors make people resilient to the mental impact of COVID-19. These exploratory analyses revealed the specific emotions that people experienced and the topics that people are concerned about during the pandemic. The theoretical and practical implications are discussed.

Background: Although mainstream guidelines recommend dual antiplatelet therapy (DAPT) with aspirin and clopidogrel in patients following transcatheter aortic valve replacement (TAVR), it is not evidence-based. We aim to investigate the safety and efficacy of DAPT vs. single antiplatelet therapy (SAPT) after TAVR, and review updated evidence.Methods: We systematically searched PubMed, Embase, and Cochrane for studies comparing DAPT to SAPT after TAVR from inception to November 30, 2020. The primary outcome was major adverse cardiac and cerebrovascular events, including all-cause mortality, cardiovascular death, myocardial infarction (MI), stroke, and major or life-threatening bleeding (LTB). Subgroup analysis was performed according to study type (randomized control trials vs. observational studies) using a fixed-effects model. The quality of evidence was assessed by two scoring systems and GRADE (Grading of Recommendations Assessment, Development, and Evaluation).Results: Twelve studies of 20,766 patients were included in our meta-analysis. Compared with SAPT, DAPT was associated with an increased risk for combined life threatening and major bleeding [OR 1.73 (1.19–2.51), p = 0.004] after TAVR. Such a difference was largely driven by major bleeding [OR 2.29 (1.68–3.11), p < 0.001]. There were no significant differences on major adverse cardiovascular events (MACE) [OR 1.19 (0.99–1.44), p = 0.07], cardiovascular mortality [OR 1.46 (0.93–2.30), p = 0.10], and stroke [OR 0.97 (0.80–1.16), p = 0.71].Conclusions: Compared with SAPT, post-TAVR DAPT was associated with increased risks of major or life-threatening bleeding without additional benefits of reducing thrombotic events. Future guidelines for post-TAVR antiplatelet strategy are expected to be updated as new high-quality evidence emerges.Systematic Review Registration: PROSPERO, Identifier: CRD42021230075.

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is a rare autosomal dominant hereditary cancer syndrome characterized by a predisposition to cutaneous leiomyomas, uterine leiomyomas, and renal cell carcinoma (RCC). It is known to be caused by germline mutations of the fumarate hydratase (FH) gene, which encodes an enzyme component of the citric acid cycle and catalyzes the conversion of fumarate to L-malate. Currently, there is no standardized treatment for HLRCC, which may be due in part to a lack of understanding of the underlying mechanisms. Here, the underlying molecular mechanisms by which the inactivation of FH causes HLRCC are discussed. Additionally, potential therapeutic pharmacological strategies are also summarized to provide new perspectives for the prevention and treatment of HLRCC.

Aiming at the problem of vibration reduction and noise reduction of bevel gear transmission system，a method for solving the vibration of bevel gear by using an integral squeeze film damper（ISFD） is proposed. An experiment bench of bevel gear transmission system is built，and a comparative study is conducted on the vibration characteristics of the bevel gear transmission system with rigid support and ISFD elastic damping support. The experimental results show that the ISFD elastic damping support can reduce vibration significantly in a wide frequency range with excellent damping performance，and the reduction of vibration acceleration of the bearing block is up to 40%. Comparing the vibrations of bevel gear transmission system at different speeds，it is verified that the ISFD elastic damping support has a great effect on vibration reduction over a wide speed range.