A virus-borne DNA damage signaling pathway controls the lysogeny-induction switch in a group of temperate pleolipoviruses.

Many prokaryotic viruses are temperate and their reactivation is tightly regulated. However, except for a few bacterial model systems, the regulatory circuits underlying the exit from lysogeny are poorly understood, especially in archaea. Here, we report a three-gene module which regulates the switch between lysogeny and replicative cycle in a haloarchaeal virus SNJ2 (family Pleolipoviridae). The SNJ2 orf4 encodes a winged helix-turn-helix DNA binding protein which maintains lysogeny through repressing the expression of the viral integrase gene intSNJ2. To switch to the induced state, two other SNJ2-encoded proteins, Orf7 and Orf8, are required. Orf8 is a homolog of cellular AAA+ ATPase Orc1/Cdc6, which is activated upon mitomycin C-induced DNA damage, possibly through posttranslational modification. Activated Orf8 initiates the expression of Orf7 which, in turn, antagonizes the function of Orf4, leading to the transcription of intSNJ2, thereby switching SNJ2 to the induced state. Comparative genomics analysis revealed that the SNJ2-like Orc1/Cdc6-centered three-gene module is common in haloarchaeal genomes, always present in the context of integrated proviruses. Collectively, our results uncover the first DNA damage signaling pathway encoded by a temperate archaeal virus and reveal an unexpected role of the widely distributed virus-encoded Orc1/Cdc6 homologs.

Cervicovaginal microbiota long-term dynamics and prediction of different outcomes in persistent human papillomavirus infection.

Persistent human papillomavirus (HPV) infection can lead to cervical intraepithelial neoplasia (CIN) and cervical cancer, posing serious threats to the health of women. Although the cervicovaginal microbiota is strongly associated with CIN, the dynamics of the microbiota during CIN development are unknown. In this retrospective cohort study, we analyzed 3-year longitudinal data from 72 patients diagnosed with a persistent HPV infection almost all caused by high-risk HPV types. Patients were categorized into groups with HPV persistent infection (n = 37), progression to CIN (n = 16), and CIN regression (n = 19) based on infection outcome during the follow-up period. Furthermore, 16S rRNA gene sequencing was performed on consecutively collected cervical samples to explore the composition and dynamics of the cervicovaginal microbiota during the development and regression of CIN. Our results showed that the composition of the cervicovaginal microbiota varied among women with different HPV infection outcomes and remained relatively stable during the follow-up period. Notably, the serial follow-up data showed that these microbial alterations were present for at least 1-2 years and occurred before pathologic changes. In addition, microbial markers that were highly discriminatory for CIN progression or regression were identified. This study provides evidence for a temporal relationship between changes in the cervicovaginal microbiota and the development of CIN, and our findings provide support for future microbial intervention strategies for CIN.

Synthesis, preclinical evaluation and pilot clinical translation of [68Ga]Ga-PMD22, a novel nanobody PET probe targeting CLDN18.2 of gastrointestinal cancer.

PURPOSE: Claudin18.2 (CLDN18.2) is a novel target for diagnosis and therapy of gastrointestinal cancer. This study aimed to evaluate the safety and feasibility of a novel CLDN18.2-targeted nanobody, PMD22, labeled with gallium-68 ([68Ga]Ga), for detecting CLDN18.2 expression in patients with gastrointestinal cancer using PET/CT imaging. METHODS: [68Ga]Ga-PMD22 was synthesized based on the nanobody, and its cell binding properties were assayed. Preclinical pharmacokinetics were determined in CLDN18.2-positive xenografts using microPET/CT. Effective dosimetry of [68Ga]Ga-PMD22 was evaluated in 5 gastrointestinal cancer patients, and PET/CT imaging of [68Ga]Ga-PMD22 and [18F]FDG were performed head-to-head in 16 gastrointestinal cancer patients. Pathological tissues were obtained for CLDN18.2 immunohistochemical (IHC) staining and comparative analysis with PET/CT findings. RESULTS: Cell binding assay showed that [68Ga]Ga-PMD22 had a higher binding ability to AGSCLDN18.2 and BGC823CLDN18.2 cells than to AGS and BGC823 cells (p < 0.001). MicroPET/CT images showed that [68Ga]Ga-PMD22 rapidly accumulated in AGSCLDN18.2 and BGC823CLDN18.2 tumors, and high contrast tumor to background imaging was clearly observed. In the pilot study, the effective dose of [68Ga]Ga-PMD22 was 1.68E-02 ± 1.45E-02 mSv/MBq, and the CLDN18.2 IHC staining result was highly correlated with the SUVmax/BKGstomach of [68Ga]Ga-PMD22 (rs = 0.848, p < 0.01). CONCLUSION: A novel [68Ga]Ga-labeled nanobody probe targeting CLDN18.2, [68Ga]Ga-PMD22, was established and preliminarily proved to be safe and effective in revealing CLDN18.2-positive gastrointestinal cancer, providing a basis for the clinical translation of the agent. CLINICAL TRIAL REGISTRATION: This study was registered on the ClinicalTrials.gov (NCT05937919).

Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to predict the human epidermal growth factor receptor 2 (HER2)-low-positive status and further verified the difference in prognosis by the DLR model. METHODS: A total of 481 patients with breast cancer who underwent preoperative MRI were retrospectively recruited from two institutions. Traditional radiomics features and deep semantic segmentation feature-based radiomics (DSFR) features were extracted from segmented tumors to construct models separately. Then, the DLR model was constructed to assess the HER2 status by averaging the output probabilities of the two models. Finally, a Kaplan‒Meier survival analysis was conducted to explore the disease-free survival (DFS) in patients with HER2-low-positive status. The multivariate Cox proportional hazard model was constructed to further determine the factors associated with DFS. RESULTS: First, the DLR model distinguished between HER2-negative and HER2-overexpressing patients with AUCs of 0.868 and 0.763 in the training and validation cohorts, respectively. Furthermore, the DLR model distinguished between HER2-low-positive and HER2-zero patients with AUCs of 0.855 and 0.750, respectively. Cox regression analysis showed that the prediction score obtained using the DLR model (HR, 0.175; p = 0.024) and lesion size (HR, 1.043; p = 0.009) were significant, independent predictors of DFS. CONCLUSIONS: We successfully constructed a DLR model based on MRI to noninvasively evaluate the HER2 status and further revealed prospects for predicting the DFS of patients with HER2-low-positive status. CLINICAL RELEVANCE STATEMENT: The MRI-based DLR model could noninvasively identify HER2-low-positive status, which is considered a novel prognostic predictor and therapeutic target. KEY POINTS: • The DLR model effectively distinguished the HER2 status of breast cancer patients, especially the HER2-low-positive status. • The DLR model was better than the traditional radiomics model or DSFR model in distinguishing HER2 expression. • The prediction score obtained using the model and lesion size were significant independent predictors of DFS.

Comparative analysis of the main haematological indexes and RNA detection for the diagnosis of SARS-CoV-2 infection.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become a public health emergency of international concern. SARS-CoV-2 RNA detection is the diagnostic criterion for coronavirus disease 2019 (COVID-19). Nevertheless, RNA detection has many limitations, such as being time-consuming and cost-prohibitive, and it must be performed in specialized laboratories. Virus antibody detection is a routine method for screening for multiple viruses, but data about SARS-CoV-2 antibody detection are limited. METHOD: Throat swabs and blood were collected from 67 suspected SARS-CoV-2 infection patients at the Affiliated Hospital of Zunyi Medical University and Zunyi Fourth People's Hospital isolated observation departments. Throat swab samples were subjected to SARS-CoV-2 RNA detection by real-time PCR. Blood was used subjected to SARS-CoV-2 IgG/IgM detection by an enzyme-linked immunosorbent assay (ELISA) and gold immunochromatography assay (GICA). Blood underwent C-reactive protein detection by immunoturbidimetry, and white blood cells, neutrophil percentages and lymphocyte percentages were counted and calculated, respectively. Clinical symptoms, age and lifestyle habits (smoking and drinking) in all patients were recorded. Data were analysed using SPSS version 19. The results were confirmed by T and χ2 tests; correlations with detection results were analysed by kappa coefficients. Odds ratio (OR) and corrected OR values were analysed by logistic regression. P < 0.05 was considered statistically significant. RESULTS: Of the 67 patients included in this study, 26 were SARS-CoV-2 RNA-positive. GICA IgM sensitivity was 50.9% (13/26), and specificity was 90.2% (37/41). ELISA IgM sensitivity was 76.9% (20/26), and specificity was 90.2% (37/41). ELISA IgG sensitivity was 76.9% (20/26), and specificity was 95.1% (39/41). The kappa coefficients between RNA detection and ELISA IgG, ELISA IgM, and GICA IgM results were 0.741 (P < 0.01), 0.681 (P < 0.01) and 0.430 (P < 0.01), respectively. CONCLUSION: Among the candidate blood indicators, serum IgG and IgM detected by ELISA had the best consistency and validity when compared with standard RNA detection; these indicators can be used as potential preliminary screening tools to identify those who should undergo nucleic acid detection in laboratories without RNA detection abilities or as a supplement to RNA detection.

A Phenotype-Based Approach for the Substrate Water Status Forecast of Greenhouse Netted Muskmelon.

Cultivation substrate water status is of great importance to the production of netted muskmelon (Cucumis melo L. var. reticulatus Naud.). A prediction model for the substrate water status would be beneficial in irrigation schedule guidance. In this study, the machine learning random forest model was used to forecast plant substrate water status given the phenotypic traits throughout the muskmelon growing season. Here, two varieties of netted muskmelon, "Wanglu" and "Arus", were planted in a greenhouse under four substrate water treatments and their phenotypic traits were measured by taking the images within the visible and near-infrared spectrums, respectively. Results showed that a simplified model outperformed the original model in forecasting speed, while it only uses the top five most significant contribution traits. The forecast accuracy reached up to 77.60%, 94.37%, and 90.01% for seedling, vine elongation, and fruit growth stages, respectively. Combining the imaging phenotypic traits and machine learning technique would provide a robust forecast of water status around the plant root zones.

MiR-223 inhibits proliferation and steroid hormone synthesis of ovarian granulosa cell via the AKT signaling pathway by targeting CRIM1 in chicken.

Within the poultry industry, hens' reproductive performance is of great economic significance. The development and growth of follicles is a key aspect of hen egg production, and ovarian follicle growth and development are closely associated with granulosa cells (GCs) proliferation and the synthesis of steroid hormones. It has been confirmed by numerous studies that microRNAs (miRNAs) play important roles in the steroid hormone synthesis and proliferation of GCs. In this study, we examined the main miRNAs influencing hens' ability to reproduce, identified the miR-223 that is mainly expressed in atretic follicles based on sequencing, and investigated its role in GCs. Then, we used miR-223 mimic and inhibitor to knockdown or overexpress miR-223 expression. The result showed that miR-223 significantly inhibits both the steroid hormone synthesis and the proliferation of GCs. Subsequently, the results of the dual luciferase reporter experiment and bioinformatics prediction demonstrated that cysteine rich transmembrane BMP regulator 1 (CRIM1) was a downstream target gene of miR-223, and overexpression of miR-223 prevented CRIM1 expression. The function of CRIM1 was further investigated, and we observed a significant reduction in the synthesis of steroid hormones and the proliferation of GCs after transfection with CRIM1 siRNA. The opposite function of miR-223 was observed for CRIM1 in our study. Additionally, we demonstrated the involvement of the miR-223/CRIM1 axis in GCs through modulation of the AKT signaling pathway. Our data demonstrate the pivotal role of the miR-223 in the proliferation and steroid hormone synthesis of chicken GCs, which helps to explain how non-coding RNA (ncRNA) affects chicken reproductive function.

CircRAB11A act as miR-24-5p sponge promotes proliferation and resists apoptosis of chicken granulosa cell via EGFR/ERK1/2 and RAB11A/ PI3K/AKT pathways.

Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs that have been implicated in mediating granulosa cell (GC) proliferation and apoptosis. CircRAB11A was found to have a significantly higher expression in normal follicles compared to atrophic follicles. In this study, we determined that the knockdown of circRAB11A resulted in the inhibition of proliferation and promotion of apoptosis in GCs of chicken. Moreover, circRAB11A was found to act as a sponge for miR-24-5p, both member RAS oncogene family (RAB11A) and epidermal growth factor receptor (EGFR) were revealed to be targets of miR-24-5p through a dual-luciferase reporter assay. RAB11A or EGFR promoted proliferation and suppressed apoptosis in GCs through the phosphatidylinositol-kinase (PI3K)/AKT or extracellular signal-regulated kinase (ERK)1/2 pathway. These findings suggest that circRAB11A may function as a competing endogenous RNA (ceRNA) by targeting the miR-24-5p/RAB11A and miR-24-5p/EGFR axes and activating the ERK1/2 and PI3K/AKT pathways, offering a potential avenue for exploring the mechanism of follicle development.

Rapid detection of duck ingredient in adulterated foods by isothermal recombinase polymerase amplification assays.

Duck is often used in meat fraud as a substitute for more expensive meats. Rapid detection of duck ingredient in meat products is of great significance for combating meat fraud and safeguarding the interests of consumers. Therefore, we aim to develop duck-specific recombinase polymerase amplification (RPA)-based assays for the rapid detection of duck ingredient in animal-derived foods. Using Cytb gene as target, the real-time RPA and RPA combined with lateral flow strips (LFS RPA) were developed successfully for the rapid detection of ducks in 20 min at 39 °C and 40 °C, respectively. The assays did not show cross-reactions with 6 other livestock and poultry. The developed RPA assays could detect 10 pg duck genomic DNA per reaction and 0.1 % (w/w) duck ingredient in duck and mutton mixed powder within 30 min, including a rapid nucleic acid extraction. Furthermore, duck ingredient could be detected in 30 different actual foods including heat-processed meats and blood products. Therefore, duck-specific real-time RPA and LFS RPA assays were successfully developed with good specificity and sensitivity, which could enable rapid detection of duck ingredient in the field and provide technical support for combating the meat fraud.

Rapid detection of Cryptosporidium spp. in diarrheic cattle feces by isothermal recombinase polymerase amplification assays.

As a zoonotic parasite, Cryptosporidium spp. could cause severe diarrhea mainly in calves and children globally. Monitoring and prevention of Cryptosporidium spp.'s prevalence is of great significance in both economy and public health aspects. In this study, specific primers and probes were designed within the conserved region of 18S rRNA gene for Cryptosporidium spp. and recombinase polymerase amplification assays based on the fluorescence monitoring (real-time RPA) as well as combined with a lateral flow strip (LFS RPA) were developed. Both of the two RPA assays allowed the exponential amplification of the target fragment within 20 min. After incubation on a metal bath at 42 °C, the LFS RPA results were displayed on the lateral flow strip within 5 min while real-time RPA allowed the real-time observation of the results in Genie III at 39 °C. The RPA assays showed high specificity for Cryptosporidium spp. without any cross-reaction with other tested pathogens causing diarrhea in cattle. With the recombinant plasmid DNA containing the 18S rRNA gene of Cryptosporidium spp. serving as a template, the limit of detection for real-time RPA and LFS RPA assays were 14.6 and 12.7 copies/reaction, respectively. Moreover, the RPA assays were validated by testing diarrheic cattle fecal samples and compared with a real-time PCR. The positive ratio of Cryptosporidium spp. was 24.04 % (44/183) and 26.23 % (48/183) in both RPA assays and real-time PCR assay, respectively, and the kappa coefficient value was 0.942. The diagnostic specificity and diagnostic sensitivity of both RPA assays were 100 % and 91.67 %, respectively. Forty-one of 48 positive samples were successfully sequenced and four Cryptosporidium species were detected, including C. parvum (n = 20), C. andersoni (n = 17), C. bovis (n = 3) and C. ryanae (n = 1). The developed RPA assays are easy to operate and faster to obtain the detection results, and they are suiting for the point-of-care detection and facilitating the prevention and control of Cryptosporidium spp. infections.

Radiation-induced occult insufficiency fracture or bone metastasis after radiotherapy for cervical cancer? The nomogram based on quantitative apparent diffusion coefficients for discrimination.

BACKGROUND: Radiation-induced insufficiency fractures (IF) is frequently occult without fracture line, which may be mistaken as metastasis. Quantitative apparent diffusion coefficient (ADC) shows potential value for characterization of benign and malignant bone marrow diseases. The purpose of this study was to develop a nomogram based on multi-parametric ADCs in the differntiation of occult IF from bone metastasis after radiotherapy (RT) for cervical cancer. METHODS: This study included forty-seven patients with cervical cancer that showed emerging new bone lesions in RT field during the follow-up. Multi-parametric quantitative ADC values were measured for each lesion by manually setting region of interests (ROIs) on ADC maps, and the ROIs were copied to adjacent normal muscle and bone marrow. Six parameters were calculated, including ADCmean, ADCmin, ADCmax, ADCstd, ADCmean ratio (lesion/normal bone) and ADCmean ratio (lesion/muscle). For univariate analysis, receiver operating characteristic curve (ROC) analysis was performed to assess the performance. For combined diagnosis, a nomogram model was developed by using a multivariate logistic regression analysis. RESULTS: A total of 75 bone lesions were identified, including 48 occult IFs and 27 bone metastases. There were significant differences in the six ADC parameters between occult IFs and bone metastases (p < 0.05), the ADC ratio (lesion/ muscle) showed an optimal diagnostic efficacy, with an area under ROC (AUC) of 0.887, the sensitivity of 95.8%, the specificity of 81.5%, respectively. Regarding combined diagnosis, ADCstd and ADCmean ratio (lesion/muscle) were identified as independent factors and were selected to generate a nomogram model. The nomogram model showed a better performance, yielded an AUC of 0.92, the sensitivity of 91.7%, the specificity of 96.3%, positive predictive value (PPV) of 97.8% and negative predictive value (NPV) of 86.7%, respectively. CONCLUSIONS: Multi-parametric ADC values demonstrate potential value for differentiating occult IFs from bone metastasis, a nomogram based on the combination of ADCstd and ADCmean ratio (lesion/muscle) may provide an improved classification performance.

LASS2 inhibits proliferation and induces apoptosis in HepG2 cells by affecting mitochondrial dynamics, the cell cycle and the nuclear factor­κB pathways.

LAG1 longevity assurance homolog 2 (LASS2) is a candidate biomarker in cancer that is dysregulated in various types of tumor, potentially affecting cell growth, invasion and migration. Although its effects on liver cancer metastasis and invasion have been reported, specific phenotypic studies and potential molecular mechanisms have not been completely elucidated in hepatoblastoma (HB). In the present study, the effect of LASS2 on the proliferation, apoptosis and cell cycle of HepG2 HB cells was assessed, and the underlying mechanisms were investigated. The human LASS2 coding sequence was inserted into an adenovirus vector and transduced into HepG2 cells. It was determined that the overexpression of LASS2 inhibited HepG2 cell viability and proliferation, as determined by cell counting kit­8 and colony formation assays, and induced apoptosis by increasing reactive oxygen species, reducing mitochondrial membrane potential and inducing intracellular Ca2+ overload. In addition, the overexpression of LASS2 induced G0/G1 cell cycle arrest through modulating the expression of cell cycle regulatory proteins, including p27, cyclin D1 and cyclin­dependent kinase 4. Immunofluorescence was used to determine that nuclear factor (NF)­κB p­p65 was primarily expressed in the cytoplasm rather than in the nucleus; western blot analysis demonstrated that LASS2 downregulated the expression of NF­κB p­p65 relative to its inactive form in HepG2 cells. These findings suggest that LASS2 inhibits proliferation and induces apoptosis in HepG2 HB cells through the mitochondrial apoptotic, NF­κB and cell cycle signaling pathways.