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Abstract 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.

The charging modules of Electric vehicles (EVs) always run in a complex and variable state. As the weakness in the reliable operation of charging modules, the accurate lifetime prediction of aluminum electrolytic capacitors (Al-caps) is important for the later maintenance and reliability design. The hotspot temperature calculation method and lifetime model limit the accuracy of aluminum electrolytic capacitors lifetime prediction methods, which cannot meet the increasing requirements for reliability. In order to solve the problems above, this paper has proposed a hotspot temperature calculation method based on the ripple current with frequency characteristics and the cooling conditions on the heat generation and thermal conductivity of the capacitors. Furthermore, the lifetime model under reference voltage has been constructed with 3D surface fitting toolbox, which describes the trends of capacitor lifetime with ambient temperature and hotspot temperature under the constant voltage condition. Considering the variation of voltage, the multiple lifetime model of capacitor is established with a voltage correction coefficient. With the proposed method, it can be realized about the real-time lifetime prediction of capacitors under multiple operating profiles such as ripple current, thermal dissipation conditions, ambient temperature and operating voltage. Finally, the effectiveness of the proposed method is verified with the annual profiles of a 30 kW EV charging module.

BackgroundInfertility 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.MethodsA 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.ResultsA 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.ConclusionsUrinary 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.

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.

Background: To evaluate whether the addition of human menopausal gonadotropin (HMG) during the early follicular phase of controlled ovarian stimulation improves clinical outcomes in patients classified as group 4 on the Patient-Oriented Strategy Encompassing IndividualizeD Oocyte Number (POSEIDON) classification. Methods: A prospective, randomized, and non-blind controlled trial was conducted, involving 172 patients seeking infertility treatment with an indication for in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI). Among them, 78 patients were randomly assigned to the HMG/follicle stimulating hormone (FSH) group, receiving 75 IU of HMG for FSH on either day 2 or day 3 of menstruation, while 94 patients were assigned to the FSH monotherapy group. Results: The total dose of gonadotropin used in the HMG/FSH group (2510.77 ± 368.11) was higher than that in the FSH alone group (2310.98 ± 641.33), indicating greater medication usage (p < 0.001). In terms of the mean number of retrieved oocytes and good quality embryos, the HMG supplementation group demonstrated a slight increasing trend (3.79 and 1.43, respectively) compared to the FSH alone group (3.44 and 1.16, respectively), though these differences did not show statistical significance. There is no significant difference in the outcomes of ongoing pregnancy rates, biochemical pregnancy rates, or clinical pregnancy rates per end-cycle or embryo transfer cycle between the two groups. Conclusion: The addition of HMG to FSH during the early follicular phase for IVF/ICSI did not provide any benefits for patients classified as group 4 on the POSEIDON classification. Clinical Trial Registration: The study was registered at Chinese Clinical Trial Registry (https://www.chictr.org.cn), registration number: ChiCTR2100043040.

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.

The conducted measurement campaigns at home and abroad were presented.Meanwhile, proposals and standard channel models from the international standardization organization were reviewed.The propagation characteristics of massive MIMO wireless channels were investigated based on the indoor and outdoor measurements.Moreover, the traditional and novel methods of channel modeling were analyzed.Finally, open research issues were presented.

The large-scale construction of 5G wireless communication network enhances the development of C-V2X (cellular-vehicle to everything) towards diversified directions.Large bandwidth services,such as high-definition video and AR/VR,bring great transmission and processing pressure to the classical network architecture.Meanwhile,traffic safety services characterized by ultra-high reliability and low delay put stringent requirements on network performance.The network architecture of providing services and computing localization through setting user panel down to close to the terminals and MEC (multiple access edge computing) can meet the requirements of data short loop transmission and ultra-low delay in the internet of vehicles scenario.The combination of MEC and V2X was explored in depth,the MEC networking scenario,MEC network architecture and the key technologies and challenges of MEC were analyzed.The combination scheme of MEC and C-V2X integration of network planning was provided.The application of MEC in C-V2X was presented in several specific scenarios.

Background: Extranodal extension (ENE) and log odds of positive lymph nodes (LODDS) are associated with the aggressiveness of both colon and rectal cancers. The current study evaluated the clinicopathological significance and the prognostic impact of ENE and LODDS in the colon and rectal patients independently. Methods: The clinical and histological records of 389 colorectal cancer (CRC) patients who underwent curative surgery were reviewed. Results: For the ENE system, 244 patients were in the ENE1 group and 145 in the ENE2 system. Compared with the ENE1 system, the patients included in the ENE2 system were prone to nerve invasion (P

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 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.

Background: Exposure to ambient air pollution has been reported to be inversely correlated with human reproductive health. However, the results of previous studies exploring the association between air pollution and in vitro fertilization (IVF) outcomes are conflicting, and further research is needed to clarify this association. Objectives: This study aimed to investigate the associations between exposure to air pollutants and IVF outcomes. Methods: We conducted a multicenter retrospective cohort study involving 20,835 patients from four cities in Northern China, contributing to 11,787 fresh embryo transfer cycles, 9050 freeze-all cycles, and 17,676 frozen-thawed embryo transfer (FET) cycles during 2014–2018. We calculated the daily average concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, CO, and SO2) during different exposure windows in IVF treatment timeline using data from the air monitoring station nearest to the residential site as approximate individual exposure. Generalized estimation equation models were used to assess the association between air pollution exposure and IVF outcomes. Results: Exposure to O3, NO2, and CO during most exposure windows in fresh embryo transfer cycles were correlated with lower possibilities of biochemical pregnancy, clinical pregnancy, and live birth. An inverse association of exposure to O3 and SO2 with pregnancy outcomes was observed in FET cycles. In addition, we found a significant association of exposure to air pollutants with a higher risk of ectopic pregnancy and lower oocyte yield. Conclusions: Our study provided large-scale human evidence of the association between air pollution and adverse human reproductive outcomes in the population opting for IVF. Thus, exposure to air pollutants in the population opting for IVF should be limited to improve treatment outcomes.

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.

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.

The wireless channel of High-Speed Railway communication system is rapidly time-varying. The orthogonal frequency division multiplexing transmitting over this channel will be exposed to the intercarrier interference caused by large Doppler spread. The sectorised antenna can be employed for Doppler mitigation and obtaining Doppler diversity gain. In this paper the performance of this directional antenna is analyzed. The preferable partition scheme for the omnidirectional antenna and the optimal Doppler compensation frequency are addressed firstly. And the uncorrelated property of the signal received from the different sectorised antennas is demonstrated originally which can be utilized for Doppler diversity gain. Finally, it is proved by the simulation results that this architecture will allows us to achieve remarkable performance under high mobility conditions.

The various problems of medical data governance and data availability in the context of real-world research on a specific disease type were analyzed. The definitions and concepts of the data governance were provided, such as hospital data governance, regional data governance, data governance of disease-specific alliances, governance of medical annotation data and knowledge-based data. Here, the common methodologies and personality methodologies of data governance were summarized. Furthermore, the technologies of master data management, metadata management and data quality control in data governance were further discussed. Finally, the basic framework of medical big data standards was given, and the medical data quality was simply evaluated which based on the existing data governance evaluation standards.