Accuracy of Xpert Carba-R Assay for the Diagnosis of Carbapenemase-producing Organisms from Rectal Swabs in Asia: a Diagnostic Meta-analysis.

The Cepheid Xpert Carba-R assay has been demonstrated to be reliable for rapid detection of carbapenemase-producing orgnisms (CPO) directly from rectal swabs but the performance of which remains unclear in Asia.We searched PubMed, EMBASE and Cochrane Library databases to identify studies according to predetermined criteria. STATA 13.0 software was used to analyze the tests for sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), area under the summary receiver operating characteristic curves (AUC). QUADAS-2 was used to assess the quality of included studies with RevMan 5.2. A total of 5 unique studies involving 10807 samples met the inclusion criteria. The pooled sensitivity, specificity, PLR, NLR, and the AUC with 95% CIs of Xpert Carba-R were 0.91 (0.72-0.97), 0.99 (0.96-1.00), 71.24 (25.41-199.73), 0.09 (0.03-0.32), 0.99 (0.98-1.00), respectively. Deeks'funnel plot showed no publication bias.The present meta-analysis showed the Xpert Carba-R assay had good sensitivity and perfect specificity for detecting CPOs on rectal swabs.

SOX11 as a potential prognostic biomarker in hepatocellular carcinoma linked to immune infiltration and ferroptosis.

Objective: SOX11 is expressed in numerous malignancies, including hepatocellular carcinomas (HCC), but its oncogenic function has not been elucidated. Here, we performed a comprehensive bioinformatics analysis of the Liver Hepatocellular Carcinoma (LIHC) dataset to investigate the function of SOX11 in tumorgenesis. Methods: SOX11 expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were validated by immunohistochemistry (IHC). Co-expression, differential expression, and functional analyses utilized TCGA-LIHC, Timer 2.0, Metascape, GTEx, and LinkedOmics databases. Associations with immune infiltration, ferroptosis, and immune checkpoint genes were assessed. Genetic changes were explored via CBioPortal. Logistic regression, receiver operating characteristic curve (ROC), Kaplan-Meier analysis, and nomogram modeling evaluated associations with HCC clinicopathological features. SOX11's impact on proliferation and migration was studied in HepG2 and HuH7 cell lines. Results: SOX11 was significantly elevated in HCC tumors compared to controls. SOX11-associated genes exhibited differential expression in pathways involving extracellular membrane ion channels. Significant associations were found between SOX11 levels, immune infiltration, ferroptosis, and immune checkpoint genes in HCC tissue. SOX11 levels correlated with HCC stage, histologic grade, and tumor status, and independently predicted overall and disease-specific survival. SOX11 expression effectively distinguished between tumor and normal liver tissue. Spearman correlations highlighted a significant relationship between SOX11 and ferroptosis-associated genes. Decreased SOX11 levels in HepG2 and HuH7 cells resulted in reduced proliferation and migration. Conclusions: SOX11 was found to represent a promising biomarker within HCC diagnosis and prognosis together with being a possible drug-target.

O-PRESS: Boosting OCT axial resolution with Prior guidance, Recurrence, and Equivariant Self-Supervision.

Optical coherence tomography (OCT) is a noninvasive technology that enables real-time imaging of tissue microanatomies. The axial resolution of OCT is intrinsically constrained by the spectral bandwidth of the employed light source while maintaining a fixed center wavelength for a specific application. Physically extending this bandwidth faces strong limitations and requires a substantial cost. We present a novel computational approach, called as O-PRESS, for boosting the axial resolution of OCT with Prior guidance, a Recurrent mechanism, and Equivariant Self-Supervision. Diverging from conventional deconvolution methods that rely on physical models or data-driven techniques, our method seamlessly integrates OCT modeling and deep learning, enabling us to achieve real-time axial-resolution enhancement exclusively from measurements without a need for paired images. Our approach solves two primary tasks of resolution enhancement and noise reduction with one treatment. Both tasks are executed in a self-supervised manner, with equivariance imaging and free space priors guiding their respective processes. Experimental evaluations, encompassing both quantitative metrics and visual assessments, consistently verify the efficacy and superiority of our approach, which exhibits performance on par with fully supervised methods. Importantly, the robustness of our model is affirmed, showcasing its dual capability to enhance axial resolution while concurrently improving the signal-to-noise ratio.

Insights into the role of glycosyltransferase in the targeted treatment of gastric cancer.

Gastric cancer is a remarkably heterogeneous tumor. Despite some advances in the diagnosis and treatment of gastric cancer in recent years, the precise treatment and curative outcomes remain unsatisfactory. Poor prognosis continues to pose a major challenge in gastric cancer. Therefore, it is imperative to identify effective targets to improve the treatment and prognosis of gastric cancer patients. It should be noted that glycosylation, a novel form of posttranslational modification, is a process capable of regulating protein function and influencing cellular activities. Currently, numerous studies have shown that glycosylation plays vital roles in the occurrence and progression of gastric cancer. As crucial enzymes that regulate glycan synthesis in glycosylation processes, glycosyltransferases are potential targets for treating GC. Hence, investigating the regulation of glycosyltransferases and the expression of associated proteins in gastric cancer cells is highly important. In this review, the related glycosyltransferases and their related signaling pathways in gastric cancer, as well as the existing inhibitors of glycosyltransferases, provide more possibilities for targeted therapies for gastric cancer.

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning.

Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities' contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77-0.91 for COD and 0.47-0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

Clinicopathological characteristics and prognosis of uterine sarcoma: a 10-year retrospective single-center study in China.

BACKGROUND: Uterine sarcoma is a rare and heterogeneous gynecological malignancy characterized by aggressive progression and poor prognosis. The current study aimed to investigate the relationship between clinicopathological characteristics and the prognosis of uterine sarcoma in Chinese patients. METHODS: In this single-center retrospective study, we reviewed the medical records of 75 patients with histologically verified uterine sarcoma treated at the First Affiliated Hospital of Xi'an Jiaotong University between 2011 and 2020. Information on clinical characteristics, treatments, pathology and survival was collected. Progression-free survival (PFS) and overall survival (OS) were visualized in Kaplan-Meier curves. Prognostic factors were identified using the log-rank test for univariate analysis and Cox-proportional hazards regression models for multivariate analysis. RESULTS: The histopathological types included 36 endometrial stromal sarcomas (ESS,48%), 33 leiomyosarcomas (LMS,44%) and 6 adenosarcomas (8%). The mean age at diagnosis was 50.2 ± 10.7 years. Stage I and low-grade accounted for the majority. There were 26 recurrences and 25 deaths at the last follow-up. The mean PFS and OS were 89.41 (95% CI: 76.07-102.75) and 94.03 (95% CI: 81.67-106.38) months, respectively. Univariate analysis showed that > 50 years, post-menopause, advanced stage, ≥ 1/2 myometrial invasion, lymphovascular space invasion and high grade were associated with shorter survival (P < 0.05). Color Doppler flow imaging positive signals were associated with shorter PFS in the LMS group (P = 0.046). The ESS group had longer PFS than that of the LMS group (99.56 vs. 76.05 months, P = 0.043). The multivariate analysis showed that post-menopause and advanced stage were independent risk factors of both PFS and OS in the total cohort and LMS group. In the ESS group, diagnosis age > 50 years and high-grade were independent risk factors of PFS, while high-grade and lymphovascular space invasion were independent risk factors of OS. CONCLUSION: In Chinese patients with uterine sarcoma, post-menopause and advanced stage were associated with a significantly poorer prognosis. The prognosis of ESS was better than that of LMS. Color Doppler flow imaging positive signals of the tumor helped to identify LMS, which needs to be further tested in a larger sample in the future.

Which riverine water quality parameters can be predicted by meteorologically-driven deep learning?

River water quality has been significantly impacted by climate change and extreme weather events worldwide. Despite increasing studies on deep learning techniques for river water quality management, understanding which riverine water quality parameters can be well predicted by meteorologically-driven deep learning still requires further investigation. Here we explored the prediction performance of a traditional Recurrent Neural Network, a Long Short-Term Memory network (LSTM), and a Gated Recurrent Unit (GRU) using meteorological conditions as inputs in the Dahei River basin. We found that deep learning models (i.e., LSTM and GRU) demonstrated remarkable effectiveness in predicting multiple water quality parameters at daily scale, including water temperature, dissolved oxygen, electrical conductivity, chemical oxygen demand, ammonia nitrogen, total phosphorous, and total nitrogen, but not turbidity. The GRU model performed best with an average determination coefficient of 0.94. Compared to the daily-average prediction, the GRU model exhibited limited error increment of 10-40 % for most water quality parameters when predicting daily extreme values (i.e., the maximum and minimum). Moreover, deep learning showed superior performance in collective prediction for multiple water quality parameters than individual ones, enabling a more comprehensive understanding of the river water quality dynamics from meteorological data. This study holds the promise of applying meteorologically-driven deep learning techniques for water quality prediction to a broader range of watersheds, particularly in chemically ungauged areas.

Insights into the history and tendency of glycosylation and digestive system tumor: A bibliometric-based visual analysis.

BACKGROUND: Glycosylation, a commonly occurring post-translational modification, is highly expressed in several tumors, specifically in those of the digestive system, and plays a role in various cellular pathophysiological mechanisms. Although the importance and detection methods of glycosylation in digestive system tumors have garnered increasing attention in recent years, bibliometric analysis of this field remains scarce. The present study aims to identify the developmental trends and research hotspots of glycosylation in digestive system tumors. AIM: To find and identify the developmental trends and research hotspots of glycosylation in digestive system tumors. METHODS: We obtained relevant literature from the Web of Science Core Collection and employed VOSviewer 1.6.19 and CiteSpace (version 6.1.R6) to perform bibliometric analysis. RESULTS: A total of 2042 documents spanning from 1978 to the present were analyzed, with the research process divided into three phases: the period of obscurity (1978-1990), continuous development period (1991-2006), and the rapid outbreak period (2007-2023). These documents were authored by researchers from 66 countries or regions, with the United States and China leading in terms of publication output. Reis Celso A had the highest number of publications, while Pinho SS was the most cited author. Co-occurrence analysis revealed the most popular keywords in this field are glycosylation, expression, cancer, colorectal cancer, and pancreatic cancer. Furthermore, the Journal of Proteome Research was the most prolific journal in terms of publications, while the Journal of Biological Chemistry had the most citations. CONCLUSION: The bibliometric analysis shows current research focus is primarily on basic research in this field. However, future research should aim to utilize glycosylation as a target for treating tumor patients.

Water quality prediction based on sparse dataset using enhanced machine learning.

Water quality in surface bodies remains a pressing issue worldwide. While some regions have rich water quality data, less attention is given to areas that lack sufficient data. Therefore, it is crucial to explore novel ways of managing source-oriented surface water pollution in scenarios with infrequent data collection such as weekly or monthly. Here we showed sparse-dataset-based prediction of water pollution using machine learning. We investigated the efficacy of a traditional Recurrent Neural Network alongside three Long Short-Term Memory (LSTM) models, integrated with the Load Estimator (LOADEST). The research was conducted at a river-lake confluence, an area with intricate hydrological patterns. We found that the Self-Attentive LSTM (SA-LSTM) model outperformed the other three machine learning models in predicting water quality, achieving Nash-Sutcliffe Efficiency (NSE) scores of 0.71 for CODMn and 0.57 for NH3N when utilizing LOADEST-augmented water quality data (referred to as the SA-LSTM-LOADEST model). The SA-LSTM-LOADEST model improved upon the standalone SA-LSTM model by reducing the Root Mean Square Error (RMSE) by 24.6% for CODMn and 21.3% for NH3N. Furthermore, the model maintained its predictive accuracy when data collection intervals were extended from weekly to monthly. Additionally, the SA-LSTM-LOADEST model demonstrated the capability to forecast pollution loads up to ten days in advance. This study shows promise for improving water quality modeling in regions with limited monitoring capabilities.

Genomic insights into the evolution and mechanisms of carbapenem-resistant hypervirulent Klebsiella pneumoniae co-harboring blaKPC and blaNDM: implications for public health threat mitigation.

BACKGROUND: Carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKP) co-producing blaKPC and blaNDM poses a serious threat to public health. This study aimed to investigate the mechanisms underlying the resistance and virulence of CR-hvKP isolates collected from a Chinese hospital, with a focus on blaKPC and blaNDM dual-positive hvKP strains. METHODS: Five CR-hvKP strains were isolated from a teaching hospital in China. Antimicrobial susceptibility and plasmid stability testing, plasmid conjugation, pulsed-field gel electrophoresis, and whole-genome sequencing (WGS) were performed to examine the mechanisms of resistance and virulence. The virulence of CR-hvKP was evaluated through serum-killing assay and Galleria mellonella lethality experiments. Phylogenetic analysis based on 16 highly homologous carbapenem-resistant K. pneumoniae (CRKP) producing KPC-2 isolates from the same hospital was conducted to elucidate the potential evolutionary pathway of CRKP co-producing NDM and KPC. RESULTS: WGS revealed that five isolates individually carried three unique plasmids: an IncFIB/IncHI1B-type virulence plasmid, IncFII/IncR-type plasmid harboring KPC-2 and IncC-type plasmid harboring NDM-1. The conjugation test results indicated that the transference of KPC-2 harboring IncFII/IncR-type plasmid was unsuccessful on their own, but could be transferred by forming a hybrid plasmid with the IncC plasmid harboring NDM. Further genetic analysis confirmed that the pJNKPN26-KPC plasmid was entirely integrated into the IncC-type plasmid via the copy-in route, which was mediated by TnAs1 and IS26. CONCLUSION: KPC-NDM-CR-hvKP likely evolved from a KPC-2-CRKP ancestor and later acquired a highly transferable blaNDM-1 plasmid. ST11-KL64 CRKP exhibited enhanced plasticity. The identification of KPC-2-NDM-1-CR-hvKP highlights the urgent need for effective preventive strategies against aggravated accumulation of resistance genes.

Co-transfer of IncFII/IncFIB and IncFII plasmids mediated by IS26 facilitates the transmission of mcr-8.1 and tmexCD1-toprJ1.

PURPOSE: This study aimed to characterise the whole-genome structure of two clinical Klebsiella pneumoniae strains co-harbouring mcr-8.1 and tmexCD1-toprJ1, both resistant to colistin and tigecycline. METHODS: K. pneumoniae strains TGC-02 (ST656) and TGC-05 (ST273) were isolated from urine samples of different patients hospitalised at separate times in 2021. Characterisation involved antimicrobial susceptibility testing (AST), conjugation assays, whole-genome sequencing (WGS), and bioinformatics analysis. Comparative genomic analysis was conducted on mcr-8.1-carrying and tmexCD1-toprJ1-carrying plasmids. RESULTS: Both K. pneumoniae isolates displayed a multidrug-resistant phenotype, exhibiting resistance or reduced susceptibility to ampicillin, ampicillin/sulbactam, cefazolin, aztreonam, amikacin, gentamicin, tobramycin, ciprofloxacin, levofloxacin, nitrofurantoin, trimethoprim/sulfamethoxazole, apramycin, tigecycline and colistin. WGS analysis revealed that clinical strain TGC-02 carried the TmexCD1-toprJ1 gene on a 200-Kb IncFII/IncFIB-type plasmid, while mcr-8 was situated on a 146-Kb IncFII-type plasmid. In clinical strain TGC-05, TmexCD1-toprJ1 was found on a 300-Kb IncFIB/IncHI1B/IncR-type plasmid, and mcr-8 was identified on a 137-Kb IncFII/IncFIA-type plasmid. Conjugation experiments assessed the transferability of these plasmids. While transconjugants were not obtained for TGC-05 despite multiple screening with tigecycline or colistin, pTGC-02-tmex and pTGC-02-mcr8 from clinical K. pneumoniae TGC-02 demonstrated self-transferability through conjugation. Notably, the rearrangement of pTGC-02-tmex and pTGC-02-mcr8 via IS26-based homologous recombination was observed. Moreover, the conjugative and fusion plasmids of the transconjugant co-harboured the tmexCD1-toprJ1 gene cluster and mcr-8.1, potentially resulting from IS26-based homologous recombination. CONCLUSION: The emergence of colistin- and tigecycline-resistant K. pneumoniae strains is concerning, and effective surveillance measures should be implemented to prevent further dissemination.

A review of solid wastes-based stabilizers for remediating heavy metals co-contaminated soil: Applications and challenges.

The remediation of heavy metals/metalloids (HMs) co-contaminated soil by solid wastes-based stabilizers (SWBS) has received major concern recently. Based on the literature reported in the latest years (2010-2023), this review systematically summarizes the different types of solid wastes (e.g., steel slag, coal fly ash, red mud, and sewage sludge, etc.) employed to stabilize HMs contaminated soil, and presents results from laboratory and field experiments. Firstly, the suitable solid wastes for soil remediation are reviewed, and the pros and cons are presented. Thereafter, the technical feasibility and economic benefit are evaluated for field application. Moreover, evaluation methods for remediation of different types of HMs-contaminated soil and the effects of SWBS on soil properties are summarized. Finally, due to the large specific surface, porous structure, and high reactivity, the SWBS can effectively stabilize HMs via adsorption, complexation, co/precipitation, ion exchange, electrostatic interaction, redox, and hydration process. Importantly, the environmental implications and long-term effectiveness associated with the utilization of solid wastes are highlighted, which are challenges for practical implementation of soil stabilization using SWBS, because the aging of soil/solid wastes has not been thoroughly investigated. Future attention should focus on modifying the SWBS and establishing an integrated long-term stability evaluation method.

ELONGATED HYPOTCOTYL5 and SPINE BASE SIZE1 together mediate light-regulated spine expansion in cucumber.

Plant trichome development is influenced by diverse developmental and environmental signals, but the molecular mechanisms involved are not well understood in most plant species. Fruit spines (trichomes) are an important trait in cucumber (Cucumis sativus L.), as they affect both fruit smoothness and commercial quality. Spine Base Size1 (CsSBS1) has been identified as essential for regulating fruit spine size in cucumber. Here, we discovered that CsSBS1 controls a season-dependent phenotype of spine base size in wild-type plants. Decreased light intensity led to reduced expression of CsSBS1 and smaller spine base size in wild-type plants, but not in the mutants with CsSBS1 deletion. Additionally, knockout of CsSBS1 resulted in smaller fruit spine base size and eliminated the light-induced expansion of spines. Overexpression of CsSBS1 increased spine base size and rescued the decrease in spine base size under low light conditions. Further analysis revealed that ELONGATED HYPOTCOTYL5 (HY5), a major transcription factor involved in light signaling pathways, directly binds to the promoter of CsSBS1 and activates its expression. Knockout of CsHY5 led to smaller fruit spine base size and abolished the light-induced expansion of spines. Taken together, our study findings have clarified a CsHY5-CsSBS1 regulatory module that mediates light-regulated spine expansion in cucumber. This finding offers a strategy for cucumber breeders to develop fruit with stable appearance quality under changing light conditions.

Antimicrobial resistance and molecular epidemiology of carbapenem-resistant Escherichia coli from urinary tract infections in Shandong, China / Resistencia a los antimicrobianos y epidemiología molecular de Escherichia coli resistente a carbapenémicos procedente de infecciones del tracto urinario en Shandong, China

Objectives: Urinary tract infection (UTI) is one of the most common extraintestinal infections, and uropathogenic Escherichia coli (UPEC) is the main cause of UTIs. However, the ability to treat UTI has been compromised by the increase in antimicrobial resistance, especially carbapenem resistance. Here, we aimed to characterize the antimicrobial resistance and molecular epidemiology of carbapenem-resistant UPEC isolated in Shandong, China. Methods: In total, 17 carbapenem-resistant UPEC (CR-UPEC) isolates were collected from July 2017 to May 2020 in the Shandong Provincial Hospital. Whole-genome sequencing and bioinformatics analyses were performed to understand the molecular epidemiology of CR-UPEC. Phylogenetic groups, drug resistance genes, biofilm formation, and virulence-related gene profiles of the isolates were analyzed. Plasmid profiling and conjugation assay were performed to evaluate the ability to transfer carbapenem resistance-related genes to other E. coli isolates. Biofilm formation was also evaluated, as it is important for the persistence of infectious diseases. Results: We observed that 15 out of 17 CR-UPEC strains were blaNDM producers, among which 4 isolates could transfer blaNDM to recipient cells. The predominant sequence type was ST167 (6/17), followed by ST410 (3/17). The most prevalent phylogenetic group was phylogenetic group A (10/17), followed by phylogenetic group C (3/17). One isolate was resistant to polymyxin, which was caused by the carriage of a transferable plasmid harboring mcr-1. Statistical analysis did not reveal any significant difference in the carriage rate of fimbriae-coding genes between strong and weak biofilm producers. Conclusions: Our observations may assist in developing new therapeutic methods for drug-resistant organisms.(AU)

Antimicrobial resistance and molecular epidemiology of carbapenem-resistant Escherichia coli from urinary tract infections in Shandong, China.

OBJECTIVES: Urinary tract infection (UTI) is one of the most common extraintestinal infections, and uropathogenic Escherichia coli (UPEC) is the main cause of UTIs. However, the ability to treat UTI has been compromised by the increase in antimicrobial resistance, especially carbapenem resistance. Here, we aimed to characterize the antimicrobial resistance and molecular epidemiology of carbapenem-resistant UPEC isolated in Shandong, China. METHODS: In total, 17 carbapenem-resistant UPEC (CR-UPEC) isolates were collected from July 2017 to May 2020 in the Shandong Provincial Hospital. Whole-genome sequencing and bioinformatics analyses were performed to understand the molecular epidemiology of CR-UPEC. Phylogenetic groups, drug resistance genes, biofilm formation, and virulence-related gene profiles of the isolates were analyzed. Plasmid profiling and conjugation assay were performed to evaluate the ability to transfer carbapenem resistance-related genes to other E. coli isolates. Biofilm formation was also evaluated, as it is important for the persistence of infectious diseases. RESULTS: We observed that 15 out of 17 CR-UPEC strains were blaNDM producers, among which 4 isolates could transfer blaNDM to recipient cells. The predominant sequence type was ST167 (6/17), followed by ST410 (3/17). The most prevalent phylogenetic group was phylogenetic group A (10/17), followed by phylogenetic group C (3/17). One isolate was resistant to polymyxin, which was caused by the carriage of a transferable plasmid harboring mcr-1. Statistical analysis did not reveal any significant difference in the carriage rate of fimbriae-coding genes between strong and weak biofilm producers. CONCLUSIONS: Our observations may assist in developing new therapeutic methods for drug-resistant organisms.

Mycobacterium bovis BCG Given at Birth Followed by Inactivated Respiratory Syncytial Virus Vaccine Prevents Vaccine-Enhanced Disease by Promoting Trained Macrophages and Resident Memory T Cells.

Respiratory syncytial virus (RSV) infects more than 60% of infants in their first year of life. Since an experimental formalin-inactivated (FI) RSV vaccine tested in the 1960s caused enhanced respiratory disease (ERD), few attempts have been made to vaccinate infants. ERD is characterized by Th2-biased responses, lung inflammation, and poor protective immune memory. Innate immune memory displays an increased nonspecific effector function upon restimulation, a process called trained immunity, or a repressed effector function upon restimulation, a process called tolerance, which participates in host defense and inflammatory disease. Mycobacterium bovis bacillus Calmette-Guérin (BCG) given at birth can induce trained immunity as well as heterologous Th1 responses. We speculate that BCG given at birth followed by FI-RSV may alleviate ERD and enhance protection through promoting trained immunity and balanced Th immune memory. Neonatal mice were given BCG at birth and then vaccinated with FI-RSV+Al(OH)3. BCG/FI-RSV+Al(OH)3 induced trained macrophages, tissue-resident memory T cells (TRM), and specific cytotoxic T lymphocytes (CTL) in lungs and inhibited Th2 and Th17 cell immune memory, all of which contributed to inhibition of ERD and increased protection. Notably, FI-RSV+Al(OH)3 induced tolerant macrophages, while BCG/FI-RSV+Al(OH)3 prevented the innate tolerance through promoting trained macrophages. Moreover, inhibition of ERD was attributed to trained macrophages or TRM in lungs but not memory T cells in spleens. Therefore, BCG given at birth to regulate trained immunity and TRM may be a new strategy for developing safe and effective RSV killed vaccines for young infants. IMPORTANCE RSV is the leading cause of severe lower respiratory tract infection of infants. ERD, characterized by Th2-biased responses, inflammation, and poor immune memory, has been an obstacle to the development of safe and effective killed RSV vaccines. Innate immune memory participates in host defense and inflammatory disease. BCG given at birth can induce trained immunity as well as heterologous Th1 responses. Our results showed that BCG/FI-RSV+Al(OH)3 induced trained macrophages, TRM, specific CTL, and balanced Th cell immune memory, which contributed to inhibition of ERD and increased protection. Notably, FI-RSV+Al(OH)3 induced tolerant macrophages, while BCG/FI-RSV+Al(OH)3 prevented tolerance through promoting trained macrophages. Moreover, inhibition of ERD was attributed to trained macrophages or TRM in lungs but not memory T cells in spleens. BCG at birth as an adjuvant to regulate trained immunity and TRM may be a new strategy for developing safe and effective RSV killed vaccines for young infants.

A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study.

BACKGROUND: Uterine sarcoma (US) is a rare malignant uterine tumor with aggressive behavior and rapid progression. The purpose of this study was to constructa comprehensive nomogram to predict cancer-specific survival (CSS) of patients with US-based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: A retrospective population-based study was conducted using data from patients with US between 2010 and 2015 from the SEER database. They were randomly divided into a training cohort and a validation cohort ata 7-to-3 ratio. Multivariate Cox analysis was performed to identify independent prognostic factors. Subsequently, a nomogram was established to predict patient CSS. The discrimination and calibration of the nomogram were evaluated by the concordance index (C-index) and the area under the curve (AUC). Finally, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the benefits of the new prediction model. RESULTS: A total of 3861 patients with US were included in our study. As revealed in multivariate Cox analysis, age at diagnosis, race, marital status, insurance record, tumor size, pathology grade, histological type, SEER stage, AJCC stage, surgery status, radiotherapy status, and chemotherapy status were found to be independent prognostic factors. In our nomogram, pathology grade had strongest correlation with CSS, followed by age at diagnosis and surgery status. Compared to the AJCC staging system, the new nomogram showed better predictive discrimination with a higher C-index in the training and validation cohorts (0.796 and 0.767 vs. 0.706 and 0.713, respectively). Furthermore, the AUC value, calibration plotting, NRI, IDI, and DCA also demonstrated better performance than the traditional system. CONCLUSION: Our study validated the first comprehensive nomogram for US, which could provide more accurate and individualized survival predictions for US patients in clinical practice.

Olaparib maintenance monotherapy in Chinese patients with platinum-sensitive relapsed ovarian cancer: China cohort from the phase III SOLO2 trial.

AIM: The phase III SOLO2 global study demonstrated the efficacy and safety of maintenance olaparib, a poly(adenosine diphosphate-ribose) polymerase inhibitor, in platinum-sensitive relapsed ovarian cancer patients with a BRCA mutation. This separate China cohort of SOLO2 investigated the efficacy and safety of maintenance olaparib in Chinese patients. METHODS: Patients received olaparib (300 mg twice daily, oral, tablets) or matched placebo. Primary endpoint was investigator-assessed progression-free survival (Response Evaluation Criteria in Solid Tumors version 1.1). Safety and tolerability were also assessed. RESULTS: Thirty-two patients were treated. Olaparib treatment led to an improvement in progression-free survival compared with placebo (hazard ratio = 0.44, 95% confidence interval: 0.17-1.19; median = 13.8 vs. 5.5 months). Results of secondary efficacy endpoints of time to first subsequent treatment/death and time to treatment discontinuation/death were consistent with progression-free survival results. Time to second progression/death and time to second subsequent treatment/death data were immature at data cutoff. The most common adverse events in the olaparib arm were nausea (81.8%), anemia (45.5%), and decreased appetite (36.4%). Grade ≥3 adverse events were experienced by 36.4% of olaparib and 10.0% of placebo patients. No adverse events led to discontinuation of treatment. There were six deaths (olaparib, five; placebo, one); one death in the olaparib arm was due to an unknown cause, all others were related to disease progression. CONCLUSIONS: Efficacy and safety findings in the China SOLO2 cohort support the use of olaparib (300 mg twice daily) as maintenance treatment for Chinese patients with platinum-sensitive relapsed ovarian cancer and a BRCA mutation.

A novel HD-Zip I/C2H2-ZFP/WD-repeat complex regulates the size of spine base in cucumber.

Fruit spine is an important trait in cucumber, affecting not only commercial quality, but also fruit smoothness, transportation and storage. Spine size is determined by a multi-cellular base. However, the molecular mechanism underlying the regulation of cucumber spine base remains largely unknown. Here, we report map-based cloning and characterization of a spine base size 1 (SBS1) gene, encoding a C2H2 zinc-finger transcription factor. Near-isogenic lines of cucumber were used to map, identify and quantify cucumber spine base size 1 (CsSBS1). Yeast-hybrid, bimolecular fluorescence complementation (BiFC), co-immunoprecipitation (Co-IP) and RNA-sequencing assays were used to explore the molecular mechanism of CsSBS1 in regulating spine base size development. CsSBS1 was specifically expressed in cucumber ovaries with particularly high expression in fruit spines. Overexpression of CsSBS1 resulted in large fruit spine base, while RNA-interference silencing of CsSBS1 inhibited the expansion of fruit spine base. Sequence analysis of natural cucumber accessions revealed that CsSBS1 was lost in small spine base accessions, resulting from a 4895 bp fragment deletion in CsSBS1 locus. CsSBS1 can form a trimeric complex with two positive regulators CsTTG1 and CsGL1 to regulate spine base development through ethylene signaling. A novel regulator network is proposed that the CsGL1/CsSBS1/CsTTG1 complex plays a significant role in regulating spine base formation and size, which offers a strategy for cucumber breeders to develop smooth fruit.

Conjugation of plasmid harboring bla NDM-1 in a clinical Providencia rettgeri strain through the formation of a fusion plasmid.

Providencia rettgeri has recently gained increased importance owing to the New Delhi metallo-ß-lactamase (NDM) and other ß-lactamases produced by its clinical isolates. These enzymes reduce the efficiency of antimicrobial therapy. Herein, we reported the findings of whole-genome sequence analysis and a comprehensive pan-genome analysis performed on a multidrug-resistant P. rettgeri 18004577 clinical strain recovered from the urine of a hospitalized patient in Shandong, China, in 2018. Providencia rettgeri 18004577 was found to have a genome assembly size of 4.6 Mb with a G + C content of 41%; a circular plasmid p18004577_NDM of 273.3 Kb, harboring an accessory multidrug-resistant region; and a circular, stable IncT plasmid p18004577_Rts of 146.2 Kb. Additionally, various resistance genes were identified in its genome, including bla NDM-1, bla OXA-10, bla PER-4, aph(3')-VI, ant(2'')-Ia, ant(3')-Ia, sul1, catB8, catA1, mph(E), and tet. Conjugation experiments and whole-genome sequencing revealed that the bla NDM-1 gene could be transferred to the transconjugant via the formation of pJ18004577_NDM, a novel hybrid plasmid. Based on the genetic comparison, the main possible formation process for pJ18004577_NDM was the insertion of the [ΔISKox2-IS26-ΔISKox2]-aph(3')-VI-bla NDM-1 translocatable unit module from p18004577_NDM into plasmid p18004577_Rts in the Russian doll insertion structure (ΔISKox2-IS26-ΔISKox2), which played a role similar to that of IS26 using the "copy-in" route in the mobilization of [aph(3')-VI]-bla NDM-1. The array, multiplicity, and diversity of the resistance and virulence genes in this strain necessitate stringent infection control, antibiotic stewardship, and periodic resistance surveillance/monitoring policies to preempt further horizontal and vertical spread of the resistance genes. Roary analysis based on 30 P. rettgeri strains pan genome identified 415 core, 756 soft core, 5,744 shell, and 12,967 cloud genes, highlighting the "close" nature of P. rettgeri pan-genome. After a comprehensive pan-genome analysis, representative biological information was revealed that included phylogenetic distances, presence or absence of genes across the P. rettgeri bacteria clade, and functional distribution of proteins. Moreover, pan-genome analysis has been shown to be an effective approach to better understand P. rettgeri bacteria because it helps develop various tailored therapeutic strategies based on their biological similarities and differences.