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ABSTRACT: The health benefits conferred by probiotics is specific to individual probiotic strains, highlighting the importance of identifying specific strains for research and production purposes. Streptococcus thermophilus CICC 6038 and Lactobacillus delbrueckii ssp. bulgaricus CICC 6047 are exceedingly valuable for commercial use with an excellent mixed-culture fermentation. To differentiate these 2 strains from other S. thermophilus and L. delbrueckii ssp. bulgaricus, a specific, sensitive, accurate, rapid, convenient, and cost-effective method is required. In this study, we conducted a pan-genome analysis of S. thermophilus and L. delbrueckii ssp. bulgaricus to identify species-specific core genes, along with strain-specific SNPs. These genes were used to develop suitable PCR primers, and the conformity of sequence length and unique SNPs was confirmed by sequencing for qualitative identification at the strain level. The results demonstrated that SNPs analysis of PCR products derived from these primers could distinguish CICC 6038 and CICC 6047 accurately and reproducibly from the other strains of S. thermophilus and L. delbrueckii ssp. bulgaricus, respectively. The strain-specific PCR method based on SNPs herein is universally applicable for probiotics identification. It offers valuable insights into identifying probiotics at the strain level that is fit-for-purpose in quality control and compliance assessment of commercial dairy products.

The effectiveness of probiotic products hinges on the viability and precise quantification of probiotic strains. This study addresses this crucial requirement by developing and validating a precise propidium monoazide combination with quantitative polymerase chain reaction (PMA-qPCR) method for quantifying viable Lacticaseibacillus paracasei in probiotic formulations. Initially, species-specific primers were meticulously designed based on core genes from the whole-genome sequence (WGS) of L. paracasei, and they underwent rigorous validation against 462 WGSs, 25 target strains, and 37 non-target strains across various taxonomic levels, ensuring extensive inclusivity and exclusivity. Subsequently, optimal PMA treatment conditions were established using 25 different L. paracasei strains to effectively inhibit dead cell DNA amplification while preserving viable cells. The developed method exhibited a robust linear relationship (R2 = 0.994) between cycle threshold (Cq) values and viable cell numbers ranging from 103 to 108 CFU/mL, with an impressive amplification efficiency of 104.48% and a quantification limit of 7.30 × 103 CFU/mL. Accuracy assessments revealed biases within ±0.5 Log10 units, while Bland–Altman analysis demonstrated a mean bias of 0.058 Log10, with 95% confidence limits of −0.366 to 0.482 Log10. Furthermore, statistical analysis (p = 0.76) indicated no significant differences between theoretical and measured values. This validated PMA-qPCR method serves as a robust and accurate tool for quantifying viable L. paracasei in various sample matrices, including pure cultures, probiotics as food ingredients, and composite probiotic products, thereby enhancing probiotic product quality assurance and contributing to consumer safety and regulatory compliance.

Abstract. Background:. Artificial intelligence (AI) technology represented by deep learning has made remarkable achievements in digital pathology, enhancing the accuracy and reliability of diagnosis and prognosis evaluation. The spatial distribution of CD3+ and CD8+ T cells within the tumor microenvironment has been demonstrated to have a significant impact on the prognosis of colorectal cancer (CRC). This study aimed to investigate CD3CT (CD3+ T cells density in the core of the tumor [CT]) prognostic ability in patients with CRC by using AI technology. Methods:. The study involved the enrollment of 492 patients from two distinct medical centers, with 358 patients assigned to the training cohort and an additional 134 patients allocated to the validation cohort. To facilitate tissue segmentation and T-cells quantification in whole-slide images (WSIs), a fully automated workflow based on deep learning was devised. Upon the completion of tissue segmentation and subsequent cell segmentation, a comprehensive analysis was conducted. Results:. The evaluation of various positive T cell densities revealed comparable discriminatory ability between CD3CT and CD3-CD8 (the combination of CD3+ and CD8+ T cells density within the CT and invasive margin) in predicting mortality (C-index in training cohort: 0.65 vs. 0.64; validation cohort: 0.69 vs. 0.69). The CD3CT was confirmed as an independent prognostic factor, with high CD3CT density associated with increased overall survival (OS) in the training cohort (hazard ratio [HR] = 0.22, 95% confidence interval [CI]: 0.12–0.38, P

ABSTRACT: This study aimed to investigate the symbiosis between Streptococcus thermophilus CICC 6038 and Lactobacillus delbrueckii ssp. bulgaricus CICC 6047. In addition, the effect of their different inoculum ratios was determined, and comparison experiments of fermentation characteristics and storage stability of milk fermented by their monocultures and cocultures at optimal inoculum ratio were performed. We found the time to obtain pH 4.6 and ΔpH during storage varied among 6 inoculum ratios (1:1, 2:1, 10:1, 19:1, 50:1, 100:1). By the statistical model to evaluate the optimal ratio, the ratio of 19:1 was selected, which exhibited high acidification rate and low postacidification with pH values remaining between 4.2 and 4.4 after a 50-d storage. Among the 3 groups included in our analyses (i.e., the monocultures of S. thermophilus CICC 6038 [St] and Lb. bulgaricus CICC 6047 [Lb] and their cocultures [St+Lb] at 19:1), the coculture group showed higher acidification activity, improved rheological properties, richer typical volatile compounds, more desirable sensor quality after the fermentation process than the other 2 groups. However, the continuous accumulation of acetic acid during storage showed that acetic acid was more highly correlated with postacidification than d-lactic acid for the Lb group and St+Lb group. Our study emphasized the importance of selecting an appropriate bacterial consortium at the optimal inoculum ratio to achieve favorable fermentation performance and enhanced postacidification stability during storage.

Cardiac development requires precise gene expression programs at each developmental stage guided by multiple signaling pathways and transcription factors (TFs). MESP1 is transiently expressed in mesoderm, and is essential for subsequent cardiac development, while the precise mechanism regulating its own transcription and mesoderm cell fate is not fully understood. Therefore, we developed a high content screen assay to identify regulators of MESP1 expression in mesodermal cells differentiated from human pluripotent stem cells (hPSCs). The screen identified CYT387, a JAK1/JAK2 kinase inhibitor, as a potent activator of MESP1 expression, which was also found to promote cardiomyocyte differentiation in vitro. Mechanistic studies found that JAK inhibition promotes MESP1 expression by reducing cytoplasmic calcium concentration and subsequently activating canonical WNT signaling. Our study identified a role of JAK signaling in early mesodermal cells, and sheds light on the connection between the JAK-STAT pathway and transcriptional regulation of MESP1, which expands our understanding of mesoderm and cardiac development.

The identification and quantification of viable bacteria at the species/strain level in compound probiotic products is challenging now. Molecular biology methods, e.g., propidium monoazide (PMA) combination with qPCR, have gained prominence for targeted viable cell counts. This study endeavors to establish a robust PMA-qPCR method for viable Lacticaseibacillus rhamnosus detection and systematically validated key metrics encompassing relative trueness, accuracy, limit of quantification, linear, and range. The inclusivity and exclusivity notably underscored high specificity of the primers for L. rhamnosus, which allowed accurate identification of the target bacteria. Furthermore, the conditions employed for PMA treatment were fully verified by 24 different L. rhamnosus including type strain, commercial strains, etc., confirming its effective discrimination between live and dead bacteria. A standard curve constructed by type strain could apply to commercial strains to convert qPCR Cq values to viable cell numbers. The established PMA-qPCR method was applied to 46 samples including pure cultures, probiotics as food ingredients, and compound probiotic products. Noteworthy is the congruity observed between measured and theoretical values within a 95% confidence interval of the upper and lower limits of agreement, demonstrating the relative trueness of this method. Moreover, accurate results were obtained when viable L. rhamnosus ranging from 103 to 108 CFU/mL. The comprehensive appraisal of PMA-qPCR performances provides potential industrial applications of this new technology in quality control and supervision of probiotic products.

Abstract Background and objective In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artificial intelligence (AI) and immunohistochemistry (IHC)-stained whole-slide images (WSIs) of colorectal cancer (CRC) patients to quantitatively assess the spatial associations between tumor cells and immune cells. To achieve this, we employ the Morisita-Horn ecological index (Mor-index), which allows for a comprehensive analysis of the spatial distribution patterns between tumor cells and immune cells within the TME. Materials and methods In this study, we employed a combination of deep learning technology and traditional computer segmentation methods to accurately segment the tumor nuclei, immune nuclei, and stroma nuclei within the tumor regions of IHC-stained WSIs. The Mor-index was used to assess the spatial association between tumor cells and immune cells in TME of CRC patients by obtaining the results of cell nuclei segmentation. A discovery cohort (N = 432) and validation cohort (N = 137) were used to evaluate the prognostic value of the Mor-index for overall survival (OS). Results The efficacy of our method was demonstrated through experiments conducted on two datasets comprising a total of 569 patients. Compared to other studies, our method is not only superior to the QuPath tool but also produces better segmentation results with an accuracy of 0.85. Mor-index was quantified automatically by our method. Survival analysis indicated that the higher Mor-index correlated with better OS in the discovery cohorts (HR for high vs. low 0.49, 95% CI 0.27–0.77, P = 0.0014) and validation cohort (0.21, 0.10–0.46,

Abstract Background Tumor necrosis results from failure to meet the requirement for rapid proliferation of tumor, related to unfavorable prognosis in colorectal cancer (CRC). However, previous studies used traditional microscopes to evaluate necrosis on slides, lacking a simultaneous phase and panoramic view for assessment. Therefore, we proposed a whole-slide images (WSIs)-based method to develop a necrosis score and validated its prognostic value in multicenter cohorts. Methods Necrosis score was defined as the proportion of necrosis in the tumor area, semi-quantitatively classified into 3-level score groups by the cut-off of 10% and 30% on HE-stained WSIs. 768 patients from two centers were enrolled in this study, divided into a discovery (N = 445) and a validation (N = 323) cohort. The prognostic value of necrosis score was evaluated by Kaplan–Meier curves and the Cox model. Result Necrosis score was associated with overall survival, with hazard ratio for high vs. low in discovery and validation cohorts being 2.62 (95% confidence interval 1.59–4.32) and 2.51 (1.39–4.52), respectively. The 3-year disease free survival rates of necrosis-low, middle, and high were 83.6%, 80.2%, and 59.8% in discovery cohort, and 86.5%, 84.2%, and 66.5% in validation cohort. In necrosis middle plus high subgroup, there was a trend but no significant difference in overall survival between surgery alone and adjuvant chemotherapy group in stage II CRC (P = .075). Conclusion As a stable prognostic factor, high-level necrosis evaluated by the proposed method on WSIs was associated with unfavorable outcomes. Additionally, adjuvant chemotherapy provide survival benefits for patients with high necrosis in stage II CRC.

AbstractBackground In colorectal cancer (CRC), both tumor invasion and immunological analysis at the tumor invasive margin (IM) are significantly associated with patient prognosis, but have traditionally been reported independently. We propose a new scoring system, the TGP-I score, to assess the association and interactions between tumor growth pattern (TGP) and tumor infiltrating lymphocytes at the IM and to predict its prognostic validity for CRC patient stratification.Materials and Methods The types of TGP were assessed in hematoxylin and eosin-stained whole-slide images. The CD3+ T-cells density at the IM was automatically quantified on immunohistochemical-stained slides using a deep learning method. A discovery (N = 347) and a validation (N = 132) cohorts were used to evaluate the prognostic value of the TGP-I score for overall survival.Results The TGP-I score3 (trichotomy) was an independent prognostic factor, with higher TGP-I score3 associated with worse prognosis in the discovery (unadjusted hazard ratio [HR] for high vs. low 3.62, 95% confidence interval [CI] 2.22–5.90; p

Abstract Background With the advance in digital pathology and artificial intelligence (AI)‐powered approaches, necrosis is proposed as a marker of poor prognosis in colorectal cancer (CRC). However, most previous studies quantified necrosis merely as a tissue type and patch‐level segmentation. Thus, it was worth exploring and validating the prognostic and predictive value of necrosis proportion with a pixel‐level segmentation in large multicenter cohorts. Methods A semantic segmentation model was trained with 12 tissue types labeled by pathologists. Segmentation was performed using the U‐net model with a subsequently derived necrosis tumor ratio (NTR). We proposed the NTR score (NTR‐low or NTR‐high) to evaluate the prognostic and predictive value of necrosis for disease‐free survival (DFS) and overall survival (OS) in the development (N = 443) and validation cohorts (N = 333) using 75% as a threshold. Results The 2‐category NTR was an independent prognostic factor and NTR‐low was associated with significant prolonged DFS (unadjusted HR for high vs. low 1.72 [95% CI 1.19–2.49] and 1.98 [1.22–3.23] in the development and validation cohorts). Similar trends were observed for OS. The prognostic value of NTR was maintained in the multivariate analysis for both cohorts. Furthermore, a stratified analysis showed that NTR‐high was a high risk with adjuvant chemotherapy for OS in stage II CRC (p = 0.047). Conclusion AI‐based pixel‐level quantified NTR has a stable prognostic value in CRC associated with unfavorable survival. Additionally, adjuvant chemotherapy provided survival benefits for patients with a high NTR score in stage II CRC.

Vimentin is an intermediate filament protein responsible for maintaining cell shape. Here, the authors characterise the role of the Salmonella effector SopB on the vimentin network and its contribution to infection.

The lactic acid bacteria Streptococcus thermophilus and Lactobacillus helveticus are commonly used as starter cultures in dairy product production. This study aimed to investigate the characteristics of fermented milk using different ratios of these strains and analyze the changes in volatile compounds during fermentation and storage. A 10:1 ratio of Streptococcus thermophilus CICC 6063 to Lactobacillus helveticus CICC 6064 showed optimal fermentation time (4.2 h), viable cell count (9.64 log10 colony-forming units/mL), and sensory evaluation score (79.1 points). In total, 56 volatile compounds were identified and quantified by solid-phase microextraction and gas chromatography–mass spectrometry (SPME-GC-MS), including aldehydes, ketones, acids, alcohols, esters, and others. Among these, according to VIP analysis, 2,3-butanedione, acetoin, 2,3-pentanedione, hexanoic acid, acetic acid, acetaldehyde, and butanoic acid were identified as discriminatory volatile metabolites for distinguishing between different time points. Throughout the fermentation and storage process, the levels of 2,3-pentanedione and acetoin exhibited synergistic dynamics. These findings enhance our understanding of the chemical and molecular characteristics of milk fermented with Streptococcus thermophilus and Lactobacillus helveticus, providing a basis for improving the flavor and odor of dairy products during fermentation and storage.

Accretion of black holes at near-Eddington or super-Eddington rates represents the most powerful episode driving black hole growth, potentially occurring across various types of objects. However, the physics governing accretion and jet–disk coupling in such states remains unclear, primarily due to the difficulty in detecting associated jets, which may emit extremely weakly or exhibit episodic behavior. Only a few near/super-Eddington systems have demonstrated radio activity, and it remains uncertain whether jets exist and what their properties are in super-Eddington active galactic nuclei (AGNs) and ultraluminous X-ray sources. This uncertainty stems mainly from the complex radio emission mix, which includes contributions from jets, star formation activity, photoionized gas, accretion disk wind, and coronal activity. In this work, we conducted high-resolution, very long baseline interferometry observations to investigate jets in the highly accreting narrow-line Seyfert I system I Zw 1. Our observations successfully revealed small-scale jets (with a linear size of ∼45 pc) at both 1.5 and 5 GHz, based on the high radio brightness temperature, radio morphology, and spectral index distribution. Additionally, the parsec-scale jet observed in I Zw 1 displays a knotted morphology reminiscent of other sources accreting at similar rates. In summary, the high accretion rates and jet properties observed in the AGN I Zw 1 may support the AGN/X-ray binary analogy in this extreme state.

Abstract Rapid expansion of the probiotics industry demands fast, sensitive, comprehensive, and low‐cost strategies for quality assessment. Here, we introduce a culture‐free, one‐cell‐resolution, phenome‐genome‐combined strategy called Single‐Cell Identification, Viability and Vitality tests, and Source‐tracking (SCIVVS). For each cell directly extracted from the product, the fingerprint region of D2O‐probed single‐cell Raman spectrum (SCRS) enables species‐level identification with 93% accuracy, based on a reference SCRS database from 21 statutory probiotic species, whereas the C–D band accurately quantifies viability, metabolic vitality plus their intercellular heterogeneity. For source‐tracking, single‐cell Raman‐activated Cell Sorting and Sequencing can proceed, producing indexed, precisely one‐cell‐based genome assemblies that can reach ~99.40% genome‐wide coverage. Finally, we validated an integrated SCIVVS workflow with automated SCRS acquisition where the whole process except sequencing takes just 5 h. As it is >20‐fold faster, >10‐time cheaper, vitality‐revealing, heterogeneity‐resolving, and automation‐prone, SCIVVS is a new technological and data framework for quality assessment of live‐cell products.

Abstract Background We proposed an artificial intelligence-based immune index, Deep-immune score, quantifying the infiltration of immune cells interacting with the tumor stroma in hematoxylin and eosin-stained whole-slide images of colorectal cancer. Methods A total of 1010 colorectal cancer patients from three centers were enrolled in this retrospective study, divided into a primary (N = 544) and a validation cohort (N = 466). We proposed the Deep-immune score, which reflected both tumor stroma proportion and the infiltration of immune cells in the stroma region. We further analyzed the correlation between the score and CD3+ T cells density in the stroma region using immunohistochemistry-stained whole-slide images. Survival analysis was performed using the Cox proportional hazard model, and the endpoint of the event was the overall survival. Result Patients were classified into 4-level score groups (score 1–4). A high Deep-immune score was associated with a high level of CD3+ T cells infiltration in the stroma region. In the primary cohort, survival analysis showed a significant difference in 5-year survival rates between score 4 and score 1 groups: 87.4% vs. 58.2% (Hazard ratio for score 4 vs. score 1 0.27, 95% confidence interval 0.15–0.48, P

ABSTRACT: Lacticaseibacillus paracasei PC-01 is a probiotic candidate isolated from naturally fermented yak milk in Lhasa, Tibet, and it has been shown to possess excellent milk fermentation properties. This study used Lacticaseibacillus paracasei PC-01 as a co-fermentation strain to investigate the effect of inoculum size with a commercial starter in milk fermentation on the product flavor and profile of volatile metabolites over 28 d of cold storage. Lacticaseibacillus paracasei PC-01 was allowed to ferment in pasteurized milk with or without the commercial starter (YF-L904) at 42°C until the pH decreased to 4.5. The finished fermented milks were stored at 10°C for 28 d. Milk samples were taken at hour 0 (before fermentation) and then at d 1, 14, and 28 of cold storage. Different inoculum sizes of Lacticaseibacillus paracasei PC-01 had no significant effect on pH or titratable acidity during storage of fermented milk. Viable counts of strain PC-01 continued to increase during cold storage of the fermented milk. Generally, as storage of fermented milk proceeded, the overall sensory quality score decreased in all groups. However, the overall sensory scores of PC-01-M were generally higher than those of other groups, suggesting that a medium dose of Lacticaseibacillus paracasei PC-01 had the most obvious effect of slowing the decline in sensory quality of fermented milk during storage. Changes in sensory scores and consumer preferences were accompanied by increases in both the quantity and variety of key volatile metabolites in fermented milk during fermentation, post-ripening (d 1), and storage. Major differentially abundant metabolites, including acetaldehyde, methyl ketones, medium-chain and short-chain fatty acids, 2,3-butanedione, and acetoin, were enriched in fermented milks rated highly in the sensory evaluation. Our data confirmed that the inoculum size of co-fermentative culture affected the sensory quality and volatile metabolome of fermented milk over storage, and an optimal range of co-fermentative culture was titrated in this work.

Crohn’s-like lymphoid reaction (CLR) and tumor-infiltrating lymphocytes (TILs) are crucial for the host antitumor immune response. We proposed an artificial intelligence (AI)-based model to quantify the density of TILs and CLR in immunohistochemical (IHC)-stained whole-slide images (WSIs) and further constructed the CLR-I (immune) score, a tissue level- and cell level-based immune factor, to predict the overall survival (OS) of patients with colorectal cancer (CRC). The TILs score and CLR score were obtained according to the related density. And the CLR-I score was calculated by summing two scores. The development (Hospital 1, N = 370) and validation (Hospital 2 & 3, N = 144) cohorts were used to evaluate the prognostic value of the CLR-I score. The C-index and integrated area under the curve were used to assess the discrimination ability. A higher CLR-I score was associated with a better prognosis, which was identified by multivariable analysis in the development (hazard ratio for score 3 vs score 0 = 0.22, 95% confidence interval 0.12–0.40, P

Abstract Background Profound heterogeneity in prognosis has been observed in colorectal cancer (CRC) patients with intermediate levels of disease (stage II–III), advocating the identification of valuable biomarkers that could improve the prognostic stratification. This study aims to develop a deep learning-based pipeline for fully automatic quantification of immune infiltration within the stroma region on immunohistochemical (IHC) whole-slide images (WSIs) and further analyze its prognostic value in CRC. Methods Patients from two independent cohorts were divided into three groups: the development group (N = 200), the internal (N = 134), and the external validation group (N = 90). We trained a convolutional neural network for tissue classification of CD3 and CD8 stained WSIs. A scoring system, named stroma-immune score, was established by quantifying the density of CD3+ and CD8+ T-cells infiltration in the stroma region. Results Patients with higher stroma-immune scores had much longer survival. In the development group, 5-year survival rates of the low and high scores were 55.7% and 80.8% (hazard ratio [HR] for high vs. low 0.39, 95% confidence interval [CI] 0.24–0.63, P

Background & Aims: The circadian clock is crucial for physiological homeostasis including gut homeostasis. Disorder of the circadian clock may contribute to many diseases including inflammatory bowel disease (IBD). However, the role and the mechanisms of circadian clock involvement in IBD still are unclear. Methods: Disorder of the circadian clock including chronic social jet lag and circadian clock gene deficiency mice (Bmal1-/-, and Per1-/-Per2-/-) were established. Dextran sulfate sodium (DSS) and/or azoxymethane were used to induce mouse models of colitis and its associated colorectal cancer. Flow cytometry, immunohistochemistry, immunofluorescence, Western blot, and reverse-transcription quantitative polymerase chain reaction were used to analyze the characteristics of immune cells and their related molecules. Results: Mice with disorders of the circadian clock including chronic social jet lag and circadian clock gene deficiency were susceptible to colitis. Functionally, regulatory B (Breg) cells highly expressing Programmed cell death 1 ligand 1 (PDL1) in intestinal intraepithelial lymphocytes (IELs) helped to alleviate the severity of colitis after DSS treatment and was dysregulated in DSS-treated Bmal1-/- mice. Notably, interleukin 33 in the intestinal microenvironment was key for Bmal1-regulated PDL1+ Breg cells and interleukin 33 was a target of Bmal1 transcriptionally. Dysregulated PDL1+ B cells induced cell death of activated CD4+ T cells in DSS-treated Bmal1-/- mice. Consequently, circadian clock disorder was characterized as decreased numbers of Breg+ PDL1+ cells in IELs and dysfunction of CD4+ T cells promoted colitis-associated colorectal cancer (CRC) in mice. In clinical samples from CRC patients, low expression of Bmal1 gene in paracancerous tissues and center area of tumor was associated closely with a poorer prognosis of CRC patients. Conclusions: Our study uncovers the importance of the circadian clock regulating PDL1+ Breg+ cells of IELs in IBD and IBD-associated CRC.

The γ -ray narrow-line Seyfert 1 (NLS1) galaxies can be considered to be the third class of γ -ray active galactic nuclei possessing relativistic jets. In this paper, we present multi-band high-resolution Very Long Baseline Array (VLBA) images of the γ -ray NLS1, SDSS J211852.96-073227.5 (J2118-0732, z = 0.26). We find a core-jet radio morphology and significant flux density variations in the radio core. The high brightness temperature estimated from VLBA images and core variability demonstrate that it exhibits substantial relativistic beaming effects. By considering radio emission in several bands, we find that the source has an inverted spectrum above 1 GHz but a steep spectrum at low frequencies ranging from 74 MHz–1 GHz; these may arise from the present activity and the old diffuse/extended emission, respectively. The core-jet morphology, significant flux density variations, and beaming effect make J2118-0732 resemble a blazar. Considering the low mass of its central black hole and the ongoing merger environment, J2118-0732 may represent a low-mass, low-power counterpart of blazars, and may finally evolve into a blazar.

We report the fourth installment in the series of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) quasar survey, which includes quasars observed between 2017 September and 2021 June. There are in total 13,066 quasars reliably identified, of which 6685 are newly discovered that are not reported in the Sloan Digital Sky Survey (SDSS) DR14 quasar catalog or Million Quasars catalog. Because LAMOST does not provide accurate absolute flux calibration, we recalibrate the spectra with the SDSS/Pan-STARRS1 multiband photometric data. The emission-line properties of H α , H β , Mg ii , and C iv and the continuum luminosities are measured by fitting the recalibrated spectra. We also estimate the single-epoch virial black hole masses ( M _BH ) using the derived emission-line and continuum parameters. This is the first time that the emission-line and continuum fluxes were estimated based on LAMOST recalibrated quasar spectra. The catalog and spectra for these quasars are available online. After the 9 yr LAMOST quasar survey, there are in total 56,175 identified quasars, of which 24,127 are newly discovered. The LAMOST quasar survey not only discovers a great number of new quasars but also provides a database for investigating the spectral variability of the quasars observed by both LAMOST and SDSS and finding rare quasars, including changing-look quasars and broad absorption line quasars.

BackgroundF-box and WD repeat domain-containing 7 (Fbw7) is well known as a tumor suppressor and ubiquitin ligase which targets a variety of oncogenic proteins for proteolysis. We previously reported that Fbw7 promotes apoptosis in diffuse large B-cell lymphoma (DLBCL) through Fbw7-mediated ubiquitination of Stat3. This study aimed to identify the mechanism of Fbw7-mediated aerobic glycolysis reprogramming in DLBCL.MethodsExpression levels of Fbw7 and Lactate Dehydrogenase A (LDHA) in human DLBCL samples were evaluated by immunohistochemistry. Crosstalk between Fbw7 and LDHA signaling was analyzed by co-immunoprecipitation, ubiquitination assay, western blotting and mRNA quanlitative analyses. In vitro and in vivo experiments were used to assess the effect of the Fbw7-mediated LDHA/lactate/miR-223 axis on DLBCL cells growth.ResultsFbw7 could interact with LDHA to trigger its ubiquitination and degradation. Inversely, lactate negatively regulated Fbw7 via trigging the expression of miR-223, which targeted Fbw7 3’-UTR to inhibit its expression. In vivo and in vitro experiments revealed that miR-223 promoted tumor growth and that the effects of miR-223 on tumor growth were primarily related to the inhibition of Fbw7-mediated LDHA’s ubiquitination.ConclusionsWe demonstrated that the ubiquitin-ligase Fbw7 played a key role in LDHA-related aerobic glycolysis reprogramming in DLBCL. Our study uncovers a negative functional loop consisting of a Fbw7-mediated LDHA/lactate/miR-223 axis, which may support the future ABC-DLBCL therapy by targeting LDHA-related inhibition.

Abstract Background YAP activation is crucial for cancer development including colorectal cancer (CRC). Nevertheless, it remains unclear whether N6-Methyladenosine (m6A) modified transcripts of long noncoding RNAs (lncRNAs) can regulate YAP activation in cancer progression. We investigated the functional link between lncRNAs and the m6A modification in YAP signaling and CRC progression. Methods YAP interacting lncRNAs were screened by RIP-sequencing, RNA FISH and immunofluorescence co-staining assays. Interaction between YAP and lncRNA GAS5 was studied by biochemical methods. MeRIP-sequencing combined with lncRNA-sequencing were used to identify the m6A modified targets of YTHDF3 in CRC. Gain-of-function and Loss-of-function analysis were performed to measure the function of GAS5-YAP-YTHDF3 axis in CRC progression in vitro and in vivo. Results GAS5 directly interacts with WW domain of YAP to facilitate translocation of endogenous YAP from the nucleus to the cytoplasm and promotes phosphorylation and subsequently ubiquitin-mediated degradation of YAP to inhibit CRC progression in vitro and in vivo. Notably, we demonstrate the m6A reader YTHDF3 not only a novel target of YAP but also a key player in YAP signaling by facilitating m6A-modified lncRNA GAS5 degradation, which profile a new insight into CRC progression. Clinically, lncRNA GAS5 expressions is negatively correlated with YAP and YTHDF3 protein levels in tumors from CRC patients. Conclusions Our study uncovers a negative functional loop of lncRNA GAS5-YAP-YTHDF3 axis, and identifies a new mechanism for m6A-induced decay of GAS5 on YAP signaling in progression of CRC which may offer a promising approach for CRC treatment.

Identifier network is one of promising network architectures to solve IP dual-property issues by separating network into access network and core network. The key design is the identifier/location separation mechanism which introduces user accessing address space and network routing address space to represent the identifier and location of terminal, respectively. The core network can prevent the cyber attacks by controlling the mapping relationship between Accessing IDentifier (AID) and Routing IDentifier (RID) via the mapping system. While the access network is facing serious security problems which makes it easily to be attacked. Therefore, this work focuses on access network security and studies AID shuffling mechanism by randomizing identifier through virtual AID. However, how the mapping servers allocate virtual AID to terminals in a reasonable way is quite difficult. To solve this problem, we propose an AID shuffling mechanism based on Group-buying Auction for Identifier Network (GAIN) among mapping servers, accessing switching routers and terminals. First, GAIN decides a group bid for each group leader and the winning virtual AID range for each group. Second, the mapping servers allocate the identifier for each terminal. Third, GAIN determines how much each winning group leaders should pay for virtual AID range to each mapping server in the winning group. We evaluate the identifier assignment of GAIN in terms of rationality, budget balance, computational tractability and truthfulness. The large-scale simulations are performed to evaluate GAIN, and the results are presented to verify the effectiveness and efficiency by comparing with other state-of-the-art approaches.

Myosin is a diverse superfamily of motor proteins responsible for actin-based motility and contractility in eukaryotic cells. Myosin-18 family, including myosin-18A and myosin-18B, belongs to an unconventional class of myosin, which lacks ATPase motor activity, and the investigations on their functions and molecular mechanisms in vertebrate development and diseases have just been initiated in recent years. Myosin-18A is ubiquitously expressed in mammalian cells, whereas myosin-18B shows strong enrichment in striated muscles. Myosin-18 family is important for cell motility, sarcomere formation, and mechanosensing, mostly by interacting with other cytoskeletal proteins and cellular apparatus. Myosin-18A participates in several intracellular transport processes, such as Golgi trafficking, and has multiple roles in focal adhesions, stress fibers, and lamellipodia formation. Myosin-18B, on the other hand, participates in actomyosin alignment and sarcomere assembly, thus relating to cell migration and muscle contractility. Mutations of either Myo18a or Myo18b cause cardiac developmental defects in mouse, emphasizing their crucial role in muscle development and cardiac diseases. In this review, we revisit the discovery history of myosin-18s and summarize the evolving understanding of the molecular functions of myosin-18A and myosin-18B, with an emphasis on their separate yet closely related functions in cell motility and contraction. Moreover, we discuss the diseases tightly associated with myosin-18s, especially cardiovascular defects and cancer, as well as highlight the unanswered questions and potential future research perspectives on myosin-18s.

Background: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated TSR quantification on routine haematoxylin and eosin (HE) stained whole-slide images (WSI) and further investigated its prognostic validity for patient stratification. Methods: We trained a convolutional neural network (CNN) model using transfer learning, with its nine-class tissue classification performance evaluated in two independent test sets. Patch-level segmentation on WSI HE slides was performed using the model, with TSR subsequently derived. A discovery (N=499) and validation cohort (N=315) were used to evaluate the prognostic value of TSR for overall survival (OS). Findings: The CNN-quantified TSR was a prognostic factor, independently of other clinicopathologic characteristics, with stroma-high associated with reduced OS in the discovery (HR 1.72, 95% CI 1.24-2.37, P=0.001) and validation cohort (2.08, 1.26-3.42, 0.004). Integrating TSR into a Cox model with other risk factors showed improved prognostic capability. Interpretation: We developed a deep learning model to quantify TSR based on histologic WSI of CRC and demonstrated its prognostic validity for patient stratification for OS in two independent CRC patient cohorts. This fully automatic approach allows for the objective and standardised application while reducing pathologists' workload. Thus, it can potentially be of significant aid in clinical prognosis prediction and decision-making. Funding: National Key Research and Development Program of China, National Science Fund for Distinguished Young Scholar, and National Science Foundation for Young Scientists of China.

The early-life microbiota triggers life-long effects on physiological functions and health disorders. Previous studies in adult twins or animal models have revealed associations between host genetics and the harmonious microbiota. However, such associations may be obscured by the fact that each intra-pair of twins will continually encounter various environmental factors as they grow up. Here, we collected the meconium samples from nineteen dizygotic pairs (DZ, n = 38) and nine monozygotic pairs (MZ, n = 18) with cesarean delivery, and 16S rRNA gene sequencing was performed to profile the microbiome at birth. Diversity analysis showed that alpha diversity was not significantly different between two groups, whereas beta diversity of MZ twins was significantly lower than that of either DZ twins or unrelated individuals (i.e., randomly selected individual pairs of non-twinship) (p < 0.05). Two groups had very similar microbial classifications but different relative abundances of certain taxa including more Firmicutes (p = 0.05, Wilcoxon test) at the phylum level and lower abundances of five genera (p < 0.05) in DZ group compared to MZ group, including Rheinheimera, Proteus, SMB53, Sphingobium, and Megamonas. Co-occurrence analysis in each group showed slightly more complicated microbial interactions in DZ than MZ twins, although 22 shared bacterial genera co-existed in two groups, with both Rheinheimera and Megamonas having different centralities in their respective co-occurrence networks. Mean intra-class correlation coefficient (ICC) were also significantly higher for MZ (0.312) compared to DZ twins (0.138) (p < 0.05). The predicted microbial gene functions related to carbohydrate were higher in DZ group, whereas folding, sorting, degradation, cell motility pathways and energy metabolism were markedly over-represented in the microbiota of MZ group. In summary, our study uncovered that microbial diversity and components of the meconium microbiome between DZ and MZ twins were partially consistent with that in singleton neonates by cesarean delivery, but several distinctions related to the heritability supported genetic contributions to intestinal microbiome in early life.

Computerized image analysis for whole-slide images has been shown to improve efficiency, accuracy, and consistency in histopathology evaluations. We aimed to assess whether immunohistochemistry (IHC) image quantitative features can reflect the immune status and provide prognostic information for colorectal cancer patients. A fully automated pipeline was designed to extract histogram features from IHC digital images in a training set (N = 243). A Hist-Immune signature was generated with selected features using the LASSO Cox model. The results were validated using internal (N = 147) and external (N = 76) validation sets. The five-feature-based Hist-Immune signature was significantly associated with overall survival in training (HR 2.72, 95% CI 1.68–4.41, P

The domain name system is a critical component of the Internet infrastructure,which maps host names to IP ad-dresses and is involved in most Internet transactions.DNS security has a profound effect on the overall security of Internet and it is also a vital research content of Internet security.In order to improve the security capability of DNS,many enhanced protocols,monitoring mechanisms and best practices were proposed.But recent DNS attack events indicate there are still many recent major research challenges of DNS security problems.The existing achievements and challenges were summarized and discussed,which included security enhanced,behavior monitoring and privacy protection.

Mobile agent is a kind of program which can transfer via asynchronous mode independently in the sensor network with outstanding prospects in application. However, due to the openness of the sensor network, mobile agents are facing the threat of security, such as being stolen and modified. How to protect sensors from attacks of malicious mobile agents becomes an important issue in the field. Traditional access control strategies such as hybrid encryption mechanism, partial results of the package, and other methods have some defects in the application. We design a multisensor interaction trust model with complete β distribution and introduce incomplete β distribution to optimize the trust model according to the actual situation of detection data loss for mobile agent system in the wireless sensor networks. In addition, the introduction of the malicious behavior feedback mechanism ensures the security of sensors in the mobile agent system. The experimental results show that the reputation model of incomplete β distribution can simulate the actual situation well, resist the attacks of malicious agents, and ensure the security of sensors in the system.

A hybrid nanocomposite consisting of hydroxylated multi-walled carbon nanotubes (MWCNTs−OH) and cube mesoporous carbon (CMK−8) was applied in this study to construct an MWCNT−OH/CMK−8/gold electrode (GE) electrochemical sensor and simultaneously perform the electro-reduction of olaquindox (OLA) and carbadox (CBX). The respective peak currents of CBX and OLA on the modified electrode increased by 720- and 595-fold relative to the peak current of GE. The performances of the modified electrode were investigated with electrochemical impedance spectroscopy, cyclic voltammetry, and differential pulse voltammetry. Then, the modified electrodes were used for the individual and simultaneous determination of OLA and CBX. The fabricated sensor demonstrated a linear response at 0.2−500 nmol/L in optimum experimental conditions, and the detection limits were 104.1 and 62.9 pmol/L for the simultaneous determination of OLA and CBX, respectively. As for individual determination, wide linear relationships were obtained for the detected OLA with levels of 0.05−500 nmol/L with LOD of 20.7 pmol/L and the detected CBX with levels of 0.10−500 nmol/L with LOD of 50.2 pmol/L. The fabricated sensor was successfully used in the independent and simultaneous determination of OLA and CBX in spiked pork samples.