Search

Engineered bacteria‐mediated antitumor approaches have been proposed as promising immunotherapies for cancer. However, the off‐target bacterial toxicity narrows the therapeutic window. Living microbes will benefit from their controllable immunogenicity within tumors for safer antitumor applications. In this study, a genetically encoded microbial activation strategy is reported that uses tunable and dynamic expression of surface extracellular polysaccharides to improve bacterial biocompatibility while retaining therapeutic efficacy. Based on screening of genes associated with Salmonella survival in macrophages, a novel attenuated Salmonella chassis strain AIS (htrA gene‐deficient) highly enriched in tumors after administration and rapidly cleared from normal organs are reported. Subsequently, an engineered bacterial strain, AISI‐H, is constructed based on the AIS strain and an optimized quorum‐sensing regulatory system. The AISI‐H strain can achieve recovery of dynamic tumor‐specific bacterial virulence through a novel HTRA‐RCSA axis‐based and quorum‐sensing synthetic gene circuit‐mediated increase in extracellular polysaccharide content. These strains act "off" in normal organs to avoid unwanted immune activation and "on" in tumors for precise tumor suppression in mice. The AISI‐H strain shows significant tumor inhibition and potent activation of anticancer immunity in a melanoma mouse model. The AISI‐H strain exhibits excellent biocompatibility. This bacterial regulation strategy expands the applications of microbe‐based antitumor therapeutics. [ABSTRACT FROM AUTHOR]

Background Tumor-stroma percentage (TSP) is a prognostic risk factor in numerous solid tumors. Despite this, the prognostic significance of TSP in gastric cancer (GC) remains underexplored. Through the development of a personalized predictive model and a semi-automatic identification system, our study aimed to fully unlock the predictive potential of TSP in GC. Methods We screened GC patients from Shanghai General Hospital (SGH) between 2012 and 2019 to develop and validate a nomogram. Univariate and multivariate Cox proportional hazards regression analyses were employed to identify independent prognostic factors influencing the prognosis for GC patients. The nomogram was further validated externally by using a cohort from Bengbu Medical College (BMC). All patients underwent radical gastrectomy, with those diagnosed with locally advanced GC receiving adjuvant chemotherapy. The primary outcome measured was overall survival (OS). The semi-automatic identification of the TSP was achieved through a computer-aided detection (CAD) system, denoted as TSP-cad, while TSP identified by pathologists was labeled as TSP-visual. Results A total of 813 GC patients from SGH and 59 from BMC were enrolled in our study. TSP-visual was identified as an adverse prognostic factor for OS in GC and was found to be associated with pathological Tumor Node Metastasis staging system (pTNM) stage, T stage, N stage, perineural invasion (PNI), lymphovascular invasion (LVI), TSP-visual, tumor size, and other factors. Multivariate Cox regression using the training cohort revealed that TSP-visual (hazard ratio [HR], 2.042; 95% confidential interval [CI], 1.485–2.806; P  <   0.001), N stage (HR, 2.136; 95% CI, 1.343–3.397; P  =   0.010), PNI (HR , 1.791; 95% CI, 1.270–2.526; P  =   0.001), and LVI (HR, 1.482; 95% CI, 1.021–2.152; P  =   0.039) were independent predictors. These factors were incorporated into a novel nomogram, which exhibited strong predictive accuracy for 5-year OS in the training, internal validation, and external validation cohorts (area under the curve = 0.744, 0.759, and 0.854, respectively). The decision curve analysis of the nomogram and concordance indexes across the three cohorts outperformed the traditional pTNM (P  <   0.05). Additionally, TSP-cad assessment using a rapid multi-dynamic algorithm demonstrated good agreement with TSP-visual. Conclusions The novel nomogram based on TSP could effectively identify individuals at risk of a poor prognosis among patients with GC. TSP-cad is anticipated to enhance the evaluation process of TSP. [ABSTRACT FROM AUTHOR]

In recent years, Long-Term Evolution Vehicle-to-Everything (LTE-V2X) communication technology has received extensive attention. Timing synchronization is a crucial step in the receiving process, addressing Timing Offsets (TOs) resulting from random propagation delays, sampling frequency mismatches between the transmitter and receiver or a combination of both. However, the presence of high-speed relative movement between nodes and a low antenna height leads to a significant Doppler frequency offset, resulting in a low Signal-to-Noise Ratio (SNR) for received signals in LTE-V2X communication scenarios. This paper aims to investigate LTE-V2X technology with a specific focus on time synchronization. The research centers on the time synchronization method utilizing the Primary Sidelink Synchronization Signal (PSSS) and conducts a comprehensive analysis of existing algorithms, highlighting their respective advantages and disadvantages. On this basis, a robust timing synchronization algorithm for LTE-V2X communication scenarios is proposed. The algorithm comprises three key steps: coarse synchronization, frequency offset estimation and fine synchronization. Enhanced robustness is achieved through algorithm fusion, optimal decision threshold design and predefined frequency offset values. Furthermore, a hardware-in-the-loop simulation platform is established. The simulation results demonstrate a substantial performance improvement for the proposed algorithm compared to existing methods under adverse channel conditions characterized by high frequency offsets and low SNR. [ABSTRACT FROM AUTHOR]

Autonomous driving technology heavily relies on the accurate perception of traffic environments, mainly through roadside cameras and LiDARs. Although several popular and robust 2D and 3D object detection methods exist, including R-CNN, YOLO, SSD, PointPillar, and VoxelNet, the perception range and accuracy of an individual vehicle can be limited by blocking from other vehicles or buildings. A solution is to harness roadside perception infrastructures for vehicle–infrastructure cooperative perception, using edge computing for real-time intermediate features extraction and V2X networks for transmitting these features to vehicles. This emerging migratory perception paradigm requires deploying exclusive cooperative perception services on edge servers and involves the migration of perception services to reduce response time. In such a setup, competition among multiple cooperative perception services exists due to limited edge resources. This study proposes a multi-agent reinforcement learning (MADRL)-based service scheduling method for migratory perception in vehicle–infrastructure cooperative perception, utilizing a discrete time-varying graph to model the relationship between service nodes and edge server nodes. This MADRL-based approach can efficiently address the challenges of service placement and migration in resource-limited environments, minimize latency, and maximize resource utilization for migratory perception services on edge servers. [ABSTRACT FROM AUTHOR]

Binocular stereo vision is based on the principle of parallax and uses imaging equipment to obtain two images of the measured object from different positions, and obtains the three-dimensional geometric information of the object by calculating the position deviation between the corresponding points of the image. As an important execution component of the six-degree-of-freedom platform in the flight simulator, the electric cylinder can undertake the important task of dynamic simulation, and its abnormal working state directly affects the training effect and life safety of the flight simulator users. In this paper, the electric cylinder position pose is obtained by the three-dimensional point cloud method, and the improved active learning anomaly detection algorithm is proposed to predict the electric cylinder position posture, so as to determine whether the platform electric cylinder fails. [ABSTRACT FROM AUTHOR]

Traditional mobile robots are mainly divided into wheeled robots and legged robots. They have good performance at fast-moving speeds and crossing obstacles, and weak terrain adaptability and moving speeds, respectively. Combining the advantages of these two types mentioned, a multi-functional wheel-legged hexapod robot with strong climbing capacity was designed in this paper. Each wheel-leg of the robot is driven directly by a single motor and can move smoothly and quickly in a diagonal tripod gait. Based on the obstacle-crossing way of the wheel-leg and combined with the characteristics of insects moving stably in nature, the middle part of the robot body is wider than head and tail. Tripod gait was selected to control the robot locomotion. A series of simulations and experiments were conducted to validate its excellent adaptability to various environmental conditions. The robot can traverse rugged, broken, and obstacle-ridden ground and cross rugged surfaces full of obstacles without any terrain sensing or actively controlled adaptation. It can negotiate obstacles of approximately its own height, which is much higher than its centre of gravity range. [ABSTRACT FROM AUTHOR]

Objective·To explore the prognosis effects of tumor-stroma ratio(TSR), perineural invasion (PNI) and lymphovascular invasion (LVI) on patients with colorectal cancer (CRC). Methods·Data of 948 patients diagnosed with CRC in Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2014 to December 2018 were retrospectively analyzed, and according to pathological risk factors TSR, PNI and LVI, patients were divided into high risk group (n=81) and low risk group (n=867). After 1-1 matching with SPSS software, 67 patients of the high risk group and 67 patients of the low risk group were obtained. The overall survival (OS) time was compared between patients in the high risk group and low risk group. The results were validated by using tissue microarray (TMA) dataset of 106 CRC patients from our research group. The clinical characteristics of the high risk group and low risk group were compared. Kaplan-Meier curve was used for survival analysis, and COX regression model was used to analyze the prognosis factors. Results·Patients in the high risk group had a worse prognosis with a short median OS (27.7 months) than patients in the low risk group (31.1 months, P=0.000). The worse OS in patients with high risk group was validated in matched data and TMA dataset. Conclusion·CRC with positive perineural lymphovascular invasion combined with high TSR is a type of CRC with poor prognosis, which can effectively make up for the defect of tumor-node-metastasis (TNM) stage in prognosis and can be used to predict postoperative disease development of CRC patients and guide treatment. [ABSTRACT FROM AUTHOR]

As an electron transport component, cytochrome b5 is an essential component of the Class II cytochrome P450 monooxygenation system and widely present in animals, plants, and fungi. However, the roles of Cyt-b5 domain proteins in pathogenic oomycetes remain unknown. Peronophythora litchii is an oomycete pathogen that causes litchi downy blight, the most destructive disease of litchi. In this study, we identified a gene, designated PlCB5L1 , that encodes a Cyt-b5 domain protein in P. litchii , and characterized its function. PlCB5L1 is highly expressed in the zoospores, cysts, germinated cysts, and during early stages of infection. PlCB5L1 knockout mutants showed reduced growth rate and β-sitosterol utilization. Importantly, we also found that PlCB5L1 is required for the full pathogenicity of P. litchii. Compared with the wild-type strain, the PlCB5L1 mutants exhibited significantly higher tolerance to SDS and sorbitol, but impaired tolerance to cell wall stress, osmotic stress, and oxidative stress. Further, the expression of genes involved in oxidative stress tolerance, including peroxidase, cytochrome P450, and laccase genes, were down-regulated in PlCB5L1 mutants under oxidative stress. This is the first report that a Cyt-b5 domain protein contributes to the development, stress response, and pathogenicity in plant pathogenic oomycetes. [ABSTRACT FROM AUTHOR]

The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services. The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications. The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research. Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location. By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources. Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined. Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results. Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented. [ABSTRACT FROM AUTHOR]

In this paper, we performed a series of measurement campaigns on the wireless electromagnetic noise for two typical industrial welding scenarios. On this basis, we investigate the characterization of the impulsive noise mainly from two aspects, that is, frequency and time domains. To start with, a novel denoising method based on the dynamic threshold is proposed to identify the desirable impulse noise from the background noise. Then, in the frequency domain, we focus on the power distribution of impulsive noise at different frequency bands. Results exhibit a shadow effect with regard to different frequency bands and we characterize it by using a linear function with a Gaussian distribution. Besides, analyses on the power spectrum correlation for different polarization modes and scenarios are also provided. In the time domain, we performed a series of statistical analyses from aspects of pulse amplitude, duration, and elapse interval to characterize the impulsive noise. Furthermore, three empirical distributions are employed to depict the parameters' variation tendency, that is, Cauchy distribution for amplitude, Gamma distribution for pulse duration, and exponential distribution for pulse interval. Finally, a first‐order two‐states Markov method is proposed to model the industrial noise. Simulation results are proved to be consistent with the actual measured results in terms of the amplitude distribution. [ABSTRACT FROM AUTHOR]

In this paper a novelty Massive Multiple Input Multiple Output (MIMO) channel model based on the birth‐and‐death process of multipath clusters is proposed. First, Massive MIMO measurements are conducted in typical outdoSor scenarios with the bandwidth of 100 MHz at frequencies of 1.4725 and 6 GHz, respectively, following with the investigation of radio propagation characteristics over antenna array. Then we research on the subchannel correlation and nonstationary based on the channel sounding experiments. Furthermore, we build up a Markov chain to characterize the birth‐and‐death process of the multipath clusters over the array, which is helpful to bring deeply insight into the cluster evolution over the antenna array axis. And the analysis results are consistent with the theory of the cluster's visible region. At last, the paper systematically demonstrates how does the spatial correlation influence the capacity of the communication system. The whole research work aims to contribute the radio channel modeling of the fifth‐generation (5G) Massive MIMO communication system. Key Points: Wideband multiantenna measurements are taken for Massive MIMO channelsCluster's birth‐and‐death process over the antenna array is studied to characterize nonstationary of Massive MIMO channelChannel capacity is studied to have an insight into the degradation caused by antenna correlation [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is a major endocrine and metabolic disorder with heterogeneous manifestations and complex etiology. As a leading cause of anovulatory infertility, the molecular diversity of the follicular microenvironment has not been fully elucidated. The aim of the present study was to investigate the follicular fluid proteomic profiles of overweight/obese and normal-weight women with PCOS, to identify novel molecular mechanisms underlying PCOS and to determine the effect of obesity on the follicular fluid protein profiles. Methods: Follicular fluid samples were collected from 3 different groups: overweight/obese PCOS patients (n = 29), normal-weight PCOS patients (n = 29), and normo-ovulatory controls (n = 29). We used a quantitative approach with tandem mass tag labeling and liquid chromatography tandem mass spectrometry to identify the differentially expressed proteins. Differential abundance of four selected proteins was confirmed by ELISA. Gene Set Enrichment Analysis was also conducted to further explore our findings. Furthermore, we compared the clinical, hormonal, and biochemical characteristics of overweight/obese and normal-weight patients with PCOS to determine the effects of obesity. Results: A total of 1,153 proteins were identified, of which 41 and 19 proteins were differentially expressed in the overweight/obese PCOS group vs. the control group, and in the normal-weight PCOS group vs. the control group, respectively. Bioinformatics analyses showed that the inflammatory, immunological, and metabolic-related biological processes were co-enriched in both subgroups of PCOS. Apolipoprotein A-II, complement C5, fetuin-B, and stromal cell-derived factor 1 were found to be involved in various processes and were validated using the ELISA analysis. From clinical features and proteomic data, obesity was found to worsen follicular development disturbances in PCOS. Conclusion: In this proteomic study, a panel of proteins were found differentially expressed in the follicular fluid of PCOS. Inflammatory, immunological, and metabolic abnormalities were identified inside the intra-follicular environment, which could be aggravated by obesity. The identified proteins were correlated with follicular growth and may be considered as candidate biomarkers as well as therapeutic targets of PCOS. [ABSTRACT FROM AUTHOR]

Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurrent neural networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a residual dilated convolutional neural network with the conditional random field (RD-CNN-CRF) for the Chinese CNER, which makes the model asynchronous in computation and thus speeding up the training period dramatically. To be more specific, Chinese characters and dictionary features are first projected into dense vector representations, then they are fed into the residual dilated convolutional neural network to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags and obtain the optimal tag sequence for the entire sequence. Computational results on the CCKS-2017 Task 2 benchmark dataset show that our proposed RD-CNN-CRF method competes favorably with state-of-the-art RNN-based methods both in terms of computational performance and training time. [ABSTRACT FROM AUTHOR]

Background: Infertility has become a global health issue with the number of couples seeking in vitro fertilization (IVF) worldwide continuing to rise. Some couples remain childless after several IVF cycles. Women undergoing IVF face greater risks and financial burden. A prediction model to predict the live birth chance prior to the first IVF treatment is needed in clinical practice for patients counselling and shaping expectations.Methods: Clinical data of 7188 women who underwent their first IVF treatment at the Reproductive Medical Center of Shengjing Hospital of China Medical University during 2014-2018 were retrospectively collected. Machine-learning based models were developed on 70% of the dataset using pre-treatment variables, and prediction performances were evaluated on the remaining 30% using receiver operating characteristic (ROC) analysis and calibration plot. Nested cross-validation was used to make an unbiased estimate of the generalization performance of the machine learning algorithms.Results: The XGBoost model achieved an area under the ROC curve of 0.73 on the validation dataset and showed the best calibration compared with other machine learning algorithms. Nested cross-validation resulted in an average accuracy score of 0.70 ± 0.003 for the XGBoost model.Conclusions: A prediction model based on XGBoost was developed using age, AMH, BMI, duration of infertility, previous live birth, previous miscarriage, previous abortion and type of infertility as predictors. This study might be a promising step to provide personalized estimates of the cumulative live birth chance of the first complete IVF cycle before treatment. [ABSTRACT FROM AUTHOR]

This paper presents a novel and practical study on the position-based radio propagation channel for High-Speed Railway by performing extensive measurements at 2.35 GHz in China. The specification on the path loss model is developed. In particular, small scale fading properties such as K-factor, Doppler frequency feature and time delay spread are parameterized, which show dynamic variances depending on the train location and the transceiver separation. Finally, the statistical position-based channel models are firstly established to characterize the High-Speed Railway channel, which significantly promotes the evaluation and verification of wireless communications in relative scenarios. [ABSTRACT FROM PUBLISHER]

The majority of sprawling-posture quadrupedal vertebrates, such as geckos and lizards, adopt a cyclical lateral swing pattern of their trunk that is coordinated with limb movements to provide extraordinary flexibility and mobility. Inspired by the gecko's locomotory gait and posture, a gecko-like robot with a flexible spine driven by shape memory alloy (SMA) springs was proposed in this work. The static parameters of the SMA spring were experimentally measured, and the flexible spine driven by SMA springs can be deflected bidirectionally. A kinematic model of the spine mechanism was established, and the mathematical relationship between the thermodynamic behavior of the SMA springs and spinal deflection was systematically analyzed. When a gecko trots with a lateral swing pattern of its trunk, the body and the spine show a standing wave shape and a single-peak C-type curve, respectively. The lateral spine deflection and trotting gait were combined in a collaborative model of a flexible spine and limbs to describe in detail the specific relationships between leg joint variables and spine deflection angle. Planar motion tests of a prototype robot were also conducted by using four high-speed cameras to record the trajectory of each point of the body, which verified the proposed model. From the acquired results, it was demonstrated that, compared with a rigid body, a robot with a flexible spine has a longer stride length, higher speed, and a greatly reduced turning radius.

Background: Infertility has been confirmed as a significant medical and social problem. Heavy metal exposure refers to a risk factor for infertility, which is capable of damaging the reproductive system of males and females. However, heavy metal exposure and female infertility have rarely been investigated. The aim of this study was to analyze the association between heavy metal exposure and female infertility., Methods: A cross-sectional study using data from three cycles of the National Health and Nutrition Examination Survey (NHANES, 2013-2018) was performed. Female infertility was evaluated by positive responses to question rhq074 in the questionnaire. Cadmium (Cd), lead (Pb), mercury (Hg), and arsenic (As) levels in blood or urine were examined by inductively coupled plasma mass spectrometry. The correlation between heavy metal and female infertility was analyzed through weighted logistic regression., Results: A total of 838 American women aged 20-44 years were covered in the study. Among all participants, 112 (13.37%) women were subjected to infertility. Urinary Cd and urinary As levels were significantly higher in infertile women than in control women ( P < 0.05, P < 0.05). Urinary As showed a positive correlation with the prevalence of female infertility, and the risk of infertility rose with the increase of urinary As levels ( P for trend = 0.045). Urinary Cd was associated with female infertility in some weighted logistic regression (Crude, Q2: OR = 3.99, 95% CI 1.82, 8.74, Q3: OR = 2.90, 95% CI 1.42, 5.92. Model 1, Q2: OR = 3.68, 95% CI 1.64, 8.27, Q3: OR = 2.33, 95% CI 1.13, 4.48. Model 2, Q2: OR = 4.11, 95% CI 1.63, 10.07, Q3: OR = 2.44, 95% CI 1.07, 5.53. Model 3, Q2: OR = 3.77, 95% CI 1.52, 9.35). Moreover, blood Pb (OR = 1.52, 95% CI 1.07, 2.16), urinary Pb (OR = 1.68, 95% CI 1.11, 2.55), and urinary As (OR = 1.02, 95% CI 1.00, 1.03) were positively correlated with the risk of infertility in women aged 35-44 years. The blood Pb (OR = 1.67, 95% CI 1.16, 2.40, 2.49) and urinary Pb (OR = 1.54, 95% CI 1.00, 2.38) in women with BMI ≥25 were positively correlated with the risk of infertility., Conclusions: Urinary As was significantly associated with female infertility, and the risk of infertility increased with higher urinary As levels. To some extent, urinary Cd was correlated with infertility. Blood/urine Pb was related to infertility in advanced age and overweight/obese women. The results of this study need to be further validated in future prospective studies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lin, Lin, Qiu, You and Xu.)

Students frequently generate mnemonic cues to help them remember difficult or abstract information (Tullis & Maddox, Metacognition and Learning , 2020, 15, 129). Self-generated mnemonics have the potential to be particularly effective means of remembering target information because they can transform abstract information into meaningful units, connect information to existing schema, and create distinct retrieval routes to the targets. Across five experiments, we compared the effectiveness of self-generated mnemonics to mnemonics generated by others for remembering chemistry information. Generating one's own mnemonics consistently boosted recall for both the chemistry content and the mnemonic itself. However, experimentally boosting recall of mnemonics through retrieval practice did not affect recall of associated chemistry content. These results indicate that improved recall of chemistry content is not caused by better recall of the mnemonic itself; rather, generating a mnemonic involves deep and effortful processing of chemistry content that boosts recall more than reading someone else's mnemonic. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

As an electron transport component, cytochrome b 5 is an essential component of the Class II cytochrome P450 monooxygenation system and widely present in animals, plants, and fungi. However, the roles of Cyt-b 5 domain proteins in pathogenic oomycetes remain unknown. Peronophythora litchii is an oomycete pathogen that causes litchi downy blight, the most destructive disease of litchi. In this study, we identified a gene, designated PlCB5L1 , that encodes a Cyt-b 5 domain protein in P . litchii , and characterized its function. PlCB5L1 is highly expressed in the zoospores, cysts, germinated cysts, and during early stages of infection. PlCB5L1 knockout mutants showed reduced growth rate and β-sitosterol utilization. Importantly, we also found that PlCB5L1 is required for the full pathogenicity of P . litchii . Compared with the wild-type strain, the PlCB5L1 mutants exhibited significantly higher tolerance to SDS and sorbitol, but impaired tolerance to cell wall stress, osmotic stress, and oxidative stress. Further, the expression of genes involved in oxidative stress tolerance, including peroxidase, cytochrome P450, and laccase genes, were down-regulated in PlCB5L1 mutants under oxidative stress. This is the first report that a Cyt-b 5 domain protein contributes to the development, stress response, and pathogenicity in plant pathogenic oomycetes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Li, Li, Zhou, Situ, Lin, Qiu, Yuan, Xi, Jiang and Kong.)