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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]

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]