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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]