Molecular rapid diagnostic testing for bloodstream infections: Nanopore targeted sequencing with pathogen-specific primers.

BACKGROUND: Nanopore sequencing, known for real-time analysis, shows promise for rapid clinical infection diagnosis but lacks effective assays for bloodstream infections (BSIs). METHODS: We prospectively assessed the performance of a novel nanopore targeted sequencing (NTS) assay in identifying pathogens and predicting antibiotic resistance in BSIs, analyzing 387 blood samples from December 2021 to April 2023. RESULTS: The positivity rate for NTS (69.5 %, 269/387) nearly matches that of metagenomic next-generation sequencing (mNGS) (74.7 %, 289/387; p = 0.128) and surpasses the positivity rate of conventional blood culture (BC) (33.9 %, 131/387; p < 0.01). Frequent pathogens detected by NTS included Klebsiella pneumoniae (n = 54), Pseudomonas aeruginosa (n = 36), Escherichia coli (n = 36), Enterococcus faecium(n = 30), Acinetobacter baumannii(n = 26), Staphylococcus aureus(n = 23), and Human cytomegalovirus (n = 37). Against a composite BSI diagnostic standard, NTS demonstrated a sensitivity and specificity of 84.0 % (95 % CI 79.5 %-87.7 %) and 90.1 % (95 % CI 81.7 %-88.5 %), respectively. The concordance between NTS and mNGS results (the percentage of total cases where both either detected BSI-related pathogens or were both negative) was 90.2 % (359/387), whereas the consistency between NTS and BC was only 60.2 % (233/387). In 80.6 % (50/62) of the samples with identical pathogens identified by both NTS tests and BCs, the genotypic resistance identified by NTS correlated with culture-confirmed phenotypic resistance. Using NTS, 95 % of samples can be tested and analyzed in approximately 7 h, allowing for early patient diagnosis. CONCLUSIONS: NTS is rapid, sensitive, and efficient for detecting BSIs and drug-resistant genes, making it a potential preferred diagnostic tool for early infection identification in critically ill patients.

MAGOH promotes gastric cancer progression via hnRNPA1 expression inhibition-mediated RONΔ160/PI3K/AKT signaling pathway activation.

BACKGROUND: Gastric cancer (GC) is associated with high mortality and heterogeneity and poses a great threat to humans. Gene therapies for the receptor tyrosine kinase RON and its spliceosomes are attracting increasing amounts of attention due to their unique characteristics. However, little is known about the mechanism involved in the formation of the RON mRNA alternative spliceosome RONΔ160. METHODS: Fourteen human GC tissue samples and six normal gastric tissue samples were subjected to label-free relative quantitative proteomics analysis, and MAGOH was identified as a candidate protein for subsequent studies. The expression of MAGOH in clinical specimens was verified by quantitative real-time PCR and western blotting. We then determined the biological function of MAGOH in GC through in vitro and in vivo experiments. RNA pulldown, RNA sequencing and RNA immunoprecipitation (RIP) were subsequently conducted to uncover the underlying mechanism by which MAGOH regulated the formation of RONΔ160. RESULTS: Proteomic analysis revealed that MAGOH, which is located at key nodes and participates in RNA processing and mRNA splicing, was upregulated in GC tissue and GC cell lines and was associated with poor prognosis. Functional analysis showed that MAGOH promoted the proliferation, migration and invasion of GC cells in vitro and in vivo. Mechanistically, MAGOH inhibited the expression of hnRNPA1 and reduced the binding of hnRNPA1 to RON mRNA, thereby promoting the formation of RONΔ160 to activate the PI3K/AKT signaling pathway and consequently facilitating GC progression. CONCLUSIONS: Our study revealed that MAGOH could promote the formation of RONΔ160 and activate the PI3K/AKT signaling pathway through the inhibition of hnRNPA1 expression. We elucidate a novel mechanism and potential therapeutic targets for the growth and metastasis of GC based on the MAGOH-RONΔ160 axis, and these findings have important guiding significance and clinical value for the future development of effective therapeutic strategies for GC.

The biomarkers associated with epithelial-mesenchymal transition in human keloids.

INTRODUCTION: A keloid is a type of benign fibrotic disease with similar features to malignancies, including anti-apoptosis, over-proliferation, and invasion. Epithelial-mesenchymal transition (EMT) is a crucial mechanism that regulates the metastatic behavior of tumors. Thus, identifying EMT biomarkers is paramount in comprehensively understanding keloid pathogenesis. METHODS: To identify the differentially expressed genes (DEGs) GSE92566 dataset, with 3 normal skin and 4 keloid tissues, was downloaded from GEO databases to identify the differentially expressed genes (DEGs). Further, EMT-related genes were downloaded from dbEMT 2.0 databases and intersected with GSE92566 DEGs to identify EMT-related-DEGs (ERDEGs). Subsequently, the ERDEGs were used for GO, KEGG, gene set enrichment analysis (GSEA), protein-protein interaction (PPI), and miRNAs-mRNAs network analysis. To predict small molecules for EMT inhibition, the ERDEGs were imported to cMAP databases, whereas hub genes were imported to DGidb databases. Finally, we carried out qRT-PCR and in vitro experiments to validate our findings. RESULTS: A total of 122 ERDEGs were identified, including 59 upregulated and 63 down-regulated genes. Moreover, enrichment analysis revealed that focal adhesion, AMPK signal pathway, Wnt signal pathway, and EMT biological process were significantly enriched. STRING databases and Cytoscape software were used to construct the PPI network and EMT-related hub genes. Further, 3 modules were explored from the PPI network using the Molecular Complex Detection (MCODE) plugin. In the Cytohubba plugin, 10 hub genes were explored, including FN1, EGF, SOX9, CDH2, PROM1, EPCAM, KRT19, ITGB1, CD24, and KRT18. These genes were then enriched for the focal adhesion pathway. We constructed a microRNA (miRNA)-mRNA network, which predicted hsa-miR-155-5p (8 edges), hsa-miR-124-3p (7 edges), hsa-miR-145-5p (5 edges), hsa-miR-20a-5p (5 edges) and hsa-let-7b-5p (4 edges) as the most connected miRNAs regulating EMT. Based on the ERDEGs and 10 hub genes mentioned above, ribavirin demonstrated high drug-targeting relevance. Subsequently, qRT-PCR confirmed that the expression of FN1, ITGB1, CDH2, and EPCAM corroborated with previous findings. qRT-PCR also showed that the expression levels of hsa-miR-124-3p and hsa-miR-145-5p were significantly lower in keloids and hsa-miR-155-5p was upregulated in keloids. Finally, by treating human keloid fibroblasts (HKFs) with ribavirin in vitro, we confirmed that ribavirin could inhibit HKFs proliferation and EMT. CONCLUSION: In summary, this work provides novel EMT biomarkers in keloids and predicts new small target molecules for keloid therapy. Our findings improve the understanding of keloid pathogenesis, providing new treatment options.

ddPCR provides a sensitive test compared with GeneXpert MTB/RIF and mNGS for suspected Mycobacterium tuberculosis infection.

Introduction: The Metagenomics next-generation sequencing (mNGS) and GeneXpert MTB/RIF assay (Xpert) exhibited a sensitivity for tuberculosis (TB) diagnostic performance. Research that directly compared the clinical performance of ddPCR analysis, mNGS, and Xpert in mycobacterium tuberculosis complex (MTB) infection has not been conducted. Methods: The study aimed to evaluate the diagnostic performance of ddPCR compared to mNGS and Xpert for the detection of MTB in multiple types of clinical samples. The final clinical diagnosis was used as the reference standard. Results: Out of 236 patients with suspected active TB infection, 217 underwent synchronous testing for tuberculosis using ddPCR, Xpert, and mNGS on direct clinical samples. During follow-up, 100 out of 217 participants were diagnosed with MTB infection. Compared to the clinical final diagnosis, ddPCR produced the highest sensitivity of 99% compared with mNGS (86%) and Xpert (64%) for all active MTB cases. Discussion: Twenty-two Xpert-negative samples were positive in mNGS tests, which confirmed the clinical diagnosis results from ddPCR and clinical manifestation, radiologic findings. Thirteen mNGS-negative samples were positive in ddPCR assays, which confirmed the clinical final diagnosis.ddPCR provides a higher sensitive compared to Xpert and mNGS for MTB diagnosis, as defined by the high concordance between ddPCR assay and clinical final diagnosis.

Deubiquitinase OTUD5 promotes hepatitis B virus replication by removing K48-linked ubiquitination of HBV core/precore and upregulates HNF4ɑ expressions by inhibiting the ERK1/2/mitogen-activated protein kinase pathway.

Hepatitis B virus (HBV) infection is a major public health problem worldwide, causing nearly one million deaths annually. OTUD5 is a deubiquitinase associated with cancer development and innate immunity response. However, the regulatory mechanisms of OTUD5 underlying HBV replication need to be deeply elucidated. In the present investigation, we found that HBV induced significant up-regulation of OTUD5 protein in HBV-infected cells. Further study showed that OTUD5 interacted with HBV core/precore, removing their K48-linked ubiquitination chains and protecting their stability. Meanwhile, overexpression of OTUD5 could inhibit the MAPK pathway and then increase the expression of HNF4ɑ, and ERK1/2 signaling was required for OTUD5-mediated activation of HNF4α, promoting HBV replication. Together, these data indicate that OTUD5 could deubiquitinate HBV core protein degradation by its deubiquitinase function and promote HBV activity by up-regulating HNF4α expression via inhibition of the ERK1/2 pathway. These results might present a novel therapeutic strategy against HBV infection.

The Influence of Overminus Lens Therapy on Control of Intermittent Exotropia: A Meta-Analysis of Randomized Clinical Trials.

BACKGROUND: Intermittent exotropia (IXT) is the most common type of strabismus, overminus lens (OML) therapy is frequently prescribed to treat IXT. OBJECTIVES: The purpose of this study was to compare the effectiveness of OML and observation in the treatment of IXT. METHOD: An exhaustive search of the literature in PubMed, Embase, Web of Science, and Cochrane Library databases was performed until July 2022. No language restrictions were used. The literature was rigorously screened according to eligibility criteria. Weighted mean differences and 95% confidence intervals (CIs) were calculated. RESULTS: A total of 4 articles with 561 participants were included in this meta-analysis. Our pooled results showed that OML demonstrated superior outcomes compared with observation, with greater decreases in distance and near exodeviation control (MD = -1.08, 95% CI: -1.96 to -0.20, p = 0.02; MD, -0.64, 95% CI: -1.15 to -0.13, p < 0.001). Patients who received OML therapy had a greater decrease in the deviation at both distance and near (MD = -4.00, 95% CI: -7.03 to -0.98, p < 0.001; MD = -4.79, 95% CI: -6.29 to -3.30, p < 0.001). There was no statistical difference between the two groups in terms of post-treatment proximal stereopsis (MD, 0.00, 95% CI: -0.08 to 0.08, p = 1.00). CONCLUSIONS: The present meta-analysis indicated that OML therapy was effective in improving the control and decreasing exodeviation angle of IXT. However, it seemed not to be effective in improving the level of near stereopsis.

Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity.

The antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual's susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

2-Methoxyestradiol inhibits the proliferation level in keloid fibroblasts through p38 in the MAPK/Erk signaling pathway.

BACKGROUND: The MAPK/Erk signaling pathway is a classic pathway in cell proliferation. Our former study showed that keloid tissue revealed a higher proliferation level than physiological scars and normal skin. As a natural metabolite of estradiol, 2-methoxyestradiol (2ME2) showed an inhibition proliferation effect on tumor cells. AIM: In this study, the treatment effect of 2ME2 and its potential mechanisms are explored. METHODS: Six keloid patients and six non-keloid patients were randomly selected from the Department of Plastic Surgery at our hospital during June 2021 to December 2021. Six groups were established: normal skin fibroblasts (N); keloid fibroblasts (K); keloid fibroblasts treated with 2ME2 (K + 2ME2); keloid fibroblasts treated with dimethyl sulfoxide (DMSO) (K + DMSO); keloid fibroblasts treated with doramapimod (K + IN); keloid fibroblasts treated with doramapimod (p38 inhibitor) and 2ME2 (K + IN+2ME2). The fibroblast activity and key factor expression of the MAPK/Erk signaling pathway were measured. RESULTS: In the results, 2ME2 significantly inhibited keloid fibroblast activity and key factor expression (except STAT1). CONCLUSION: The proliferation levels were reduced by both the p38 inhibitor and 2ME2, indicating 2ME2 may achieve an antiproliferation effect by targeting p38 in keloid fibroblasts.

Discovering the digital biomarker of hepatocellular carcinoma in serum with SERS-based biosensors and intelligence vision.

By its many virtues, non-biomarker-reliant molecular detection has recently shown bright prospects for cancer screening but its clinical application is hindered by the shortage of measurable criteria that are analogous to biomarkers. Here, we report a digital biomarker, as a new-concept serum biomarker, of hepatocellular carcinoma (HCC) found with SERS-based biosensors and a deep neural network "digital retina" for visualizing and explicitly defining spectral fingerprints. We validate the discovered digital biomarker (a collection of 10 characteristic peaks in the serum SERS spectra) with unsupervised clustering of spectra from an independent sample batch comprised normal individuals and HCC cases; the validation results show clustering accuracies of 95.71% and 100.00%, respectively. Furthermore, we find that the digital biomarker of HCC shares a few common peaks with three clinically applied serum biomarkers, which means it could convey essential biomolecular information similar to these biomarkers. Accordingly, we present an intelligent method for early HCC detection that leverages the digital biomarker with similar traits as biomarkers. Employing the digital biomarker, we could accurately stratify HCC, hepatitis B, and normal populations with linear classifiers, exhibiting accuracies over 92% and area under the receiver operating curve values above 0.93. It is anticipated that this non-biomarker-reliant molecular detection method will facilitate mass cancer screening.

New insight into desorption behavior and mechanism of oil from aged oil-contaminated soil in microemulsion.

The intractable nature of oil-contaminated soil (OS) constitutes the chief limiting factor for its remediation. Herein, the aging effect (i.e., oil-soil interactions and pore-scale effect) was investigated by analyzing the properties of aged OS and further demonstrated by investigating the desorption behavior of the oil from the OS. XPS was performed to detect the chemical environment of N, O, and Al, indicating the coordination adsorption of carbonyl groups (oil) on the soil surface. Alterations in the functional groups of the OS were detected using FT-IR, indicating that the oil-soil interactions were enhanced via wind-thermal aging. SEM and BET were used to analyze the structural morphology and pore-scale of the OS. The analysis revealed that aging promoted the development of the pore-scale effect in the OS. Moreover, the desorption behavior of oil molecules from the aged OS was investigated via desorption thermodynamics and kinetics. The desorption mechanism of the OS was elucidated via intraparticle diffusion kinetics. The desorption process of oil molecules underwent three stages: film diffusion, intraparticle diffusion, and surface desorption. Owing to the aging effect, the latter two stages constituted the major steps for controlling oil desorption. This mechanism provided theoretical guidance to apply microemulsion elution for remedying industrial OS.

Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.

BACKGROUND: Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can interfere with DL-CAD assessments and impair performance. This study aims to compare PCa detection of DL-CAD between zoomed-field-of-view echo-planar DWI (z-DWI) and full-field-of-view DWI (f-DWI) and find the risk factors affecting DL-CAD diagnostic efficiency. METHODS: This retrospective study enrolled 354 consecutive participants who underwent MRI including T2WI, f-DWI, and z-DWI because of clinically suspected PCa. A DL-CAD was used to compare the performance of f-DWI and z-DWI both on a patient level and lesion level. We used the area under the curve (AUC) of receiver operating characteristics analysis and alternative free-response receiver operating characteristics analysis to compare the performances of DL-CAD using f- DWI and z-DWI. The risk factors affecting the DL-CAD were analyzed using logistic regression analyses. P values less than 0.05 were considered statistically significant. RESULTS: DL-CAD with z-DWI had a significantly better overall accuracy than that with f-DWI both on patient level and lesion level (AUCpatient: 0.89 vs. 0.86; AUClesion: 0.86 vs. 0.76; P < .001). The contrast-to-noise ratio (CNR) of lesions in DWI was an independent risk factor of false positives (odds ratio [OR] = 1.12; P < .001). Rectal susceptibility artifacts, lesion diameter, and apparent diffusion coefficients (ADC) were independent risk factors of both false positives (ORrectal susceptibility artifact = 5.46; ORdiameter, = 1.12; ORADC = 0.998; all P < .001) and false negatives (ORrectal susceptibility artifact = 3.31; ORdiameter = 0.82; ORADC = 1.007; all P ≤ .03) of DL-CAD. CONCLUSIONS: Z-DWI has potential to improve the detection performance of a prostate MRI based DL-CAD. TRIAL REGISTRATION: ChiCTR, NO. ChiCTR2100041834 . Registered 7 January 2021.

Role of HIF-1α in pathogenic mechanisms of keloids.

BACKGROUDS AND OBJECTIVE: Keloids are defined as overrepairing products that develop after skin lesions. Keloids are characterized by the proliferation of fibroblasts and the overaccumulation of extracellular matrix components (mainly collagen), leading to a locally hypoxic microenvironment. Hence, this article was aimed to review hypoxia in pathogenesis of keloids. METHODS: We reviewed and summarized the relevant published studies. RESULTS: Hypoxia results in the accumulation of hypoxia-inducible factor 1α (HIF-1α) in keloids, contributing to overactivation of the fibrotic signaling pathway, epithelial-mesenchymal transition, and changes in metabolism, eventually leading to aggravated fibrosis, infiltrative growth, and radiotherapy resistance. CONCLUSION: It is, therefore, essential to understand the role of HIF-1α in the pathogenic mechanisms of keloids in order to develop new therapeutic approaches.

Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems.

PURPOSE: We developed a deep neural network that queries the lung computed tomography-derived feature space to identify radiation sensitivity parameters that can predict treatment failures and hence guide the individualization of radiotherapy dose. In this article, we examine the transportability of this model across health systems. METHODS: This multicenter cohort-based registry included 1,120 patients with cancer in the lung treated with stereotactic body radiotherapy. Pretherapy lung computed tomography images from the internal study cohort (n = 849) were input into a multitask deep neural network to generate an image fingerprint score that predicts time to local failure. Deep learning (DL) scores were input into a regression model to derive iGray, an individualized radiation dose estimate that projects a treatment failure probability of < 5% at 24 months. We validated our findings in an external, holdout cohort (n = 271). RESULTS: There were substantive differences in the baseline patient characteristics of the two study populations, permitting an assessment of model transportability. In the external cohort, radiation treatments in patients with high DL scores failed at a significantly higher rate with 3-year cumulative incidences of local failure of 28.5% (95% CI, 19.8 to 37.8) versus 10.2% (95% CI, 5.9 to 16.2; hazard ratio, 3.3 [95% CI, 1.74 to 6.49]; P < .001). A model that included DL score alone predicted treatment failures with a concordance index of 0.68 (95% CI, 0.59 to 0.77), which had a similar performance to a nested model derived from within the internal cohort (0.70 [0.64 to 0.75]). External cohort patients with iGray values that exceeded the delivered doses had proportionately higher rates of local failure (P < .001). CONCLUSION: Our results support the development and implementation of new DL-guided treatment guidance tools in the image-replete and highly standardized discipline of radiation oncology.

A comparison of proliferation levels in normal skin, physiological scar and keloid tissue.

Proliferation is an important characteristic of life, and many signaling pathways participate in this complicated process. The MAPK/Erk pathway is a classic pathway in cell proliferation. In this study, expression levels of key factors in the MAPK/Erk pathway were measured to assess the proliferation level among normal skin, physiological scar, and keloid tissue. Thirty patients were selected randomly from the Department of Plastic Surgery at Peking Union Medical College Hospital from January 2019 to December 2020. Histological appearance and fiber tissue content were observed by Hematoxylin and eosin staining and Masson staining. Expression levels of key factors in the MAPK/Erk pathway (ATF2, c-Jun, c-Myc, p38 and STAT1) and relative proteins (HIF-1α and PCNA) in tissues were detected by immunohistochemistry and analyzed as the percentage of positively stained cells in both the tissue epidermis and dermis. Western blot was used for quantitative analysis of the above factors. In results, keloid tissue showed a significantly higher fiber and less cell content. In the immunohistochemical result, higher expression of key factors was observed in the epidermis than in the dermal layer, and the expression of all factors was increased remarkably in keloid tissue. In western blot analysis, all factors (except STAT1) showed higher expression in keloid tissue. In our former research, keloid showed similar apoptosis level as physiological scar and normal skin. On combining our former conclusion and results in this study, an imbalance condition between the high proliferation level and normal apoptosis level may lead to the growth characteristics of keloid.

A new photodynamic therapy photosensitizer (p1) promotes apoptosis of keloid fibroblasts by targeting caspase-8.

Photodynamic therapy (PDT) is a new therapy for treating cancer with less toxicity, high selectivity, good cooperativity, and repetitive usability. However, keloid treatment by PDT is mainly focused on clinical appearance, and few studies have been conducted on the mechanisms of PDT. In this study, key factors of the classical mitochondrial apoptosis signaling pathway were measured to assess the effect of a new PDT photosensitizer (p1). A specific inhibitor of caspase-8 (Z-IETD-FMK) was also used to verify the possible mechanisms. Twelve samples were obtained from 12 patients (six with keloids and six without) selected randomly from the Department of Plastic Surgery at Peking Union Medical College Hospital from January to December 2020. After cell culture, fibroblasts were divided into 13 groups. The morphology of fibroblasts in each group was observed by microscopy. Cell activity was measured by cell counting kit-8, and cell apoptotic morphology was observed by TUNEL staining. The reactive oxygen species (ROS) relative value was measured by a ROS test kit. The expression levels of key mitochondrial factors (caspase-3, caspase-8, cytochrome-c, Bax, and Bcl-2) were assessed by western blot, and mRNA expression of caspase-3 and caspase-8 was measured by RT-qPCR. We showed that p1 had a satisfactory proapoptotic effect on keloid fibroblasts by increasing the expression of ROS, caspase-3, caspase-8, and cytochrome-c, and decreasing the Bcl-2/Bax ratio; however, this effect was partially inhibited by Z-IETD-FMK, indicating that caspase-8 may be one of the p1's targets to achieve the proapoptotic effect.

Prostate gland volume estimation: anteroposterior diameters measured on axial versus sagittal ultrasonography and magnetic resonance images.

PURPOSE: The aim of this study was to evaluate the accuracy of prostate volume estimates calculated from the ellipsoid formula using the anteroposterior (AP) diameter measured on axial and sagittal images obtained through ultrasonography (US) and magnetic resonance imaging (MRI). METHODS: This retrospective study included 456 patients with transrectal US and MRI from two university hospitals. Two radiologists independently measured the prostate gland diameters on US and MRI: AP diameters on axial and sagittal images, transverse, and longitudinal diameters on midsagittal images. The volume estimates, volumeax and volumesag, were calculated from the ellipsoid formula by using the AP diameter on axial and sagittal images, respectively. The prostate volume extracted from MRI-based whole-gland segmentation was considered the gold standard. The intraclass correlation coefficient (ICC) was used to evaluate the inter-method agreement between volumeax and volumesag, and agreement with the gold standard. The Wilcoxon signedrank test was used to analyze the differences between the volume estimates and the gold standard. RESULTS: The prostate gland volume estimates showed excellent inter-method agreement, and excellent agreement with the gold standard (ICCs >0.9). Compared with the gold standard, the volume estimates were significantly larger on MRI and significantly smaller on US (P<0.001). The volume difference (segmented volume-volume estimate) was greater in patients with larger prostate glands, especially on US. CONCLUSION: Volumeax and volumesag showed excellent inter-method agreement and excellent agreement with the gold standard on both US and MRI. However, prostate volume was overestimated on MRI and underestimated on US.

Sphingomyelin synthase 2 is a positive regulator of the CSF1R-STAT3 pathway in pancreatic cancer-associated macrophage.

Background: Tumor-associated macrophages (TAMs) are one of the most abundant immune cells in the pancreatic cancer stroma and are related to the poor prognosis of pancreatic ductal adenocarcinoma (PDAC) patients. Therefore, targeting tumor-associated macrophages is a possible strategy for the treatment of pancreatic cancer. Purpose: We would like to investigate the role of sphingomyelin synthase 2 (SMS2) and the effect of the synthase 2 selective inhibitor YE2 in TAMs and the pancreatic tumor microenvironment. In addition, we also would like to investigate the mechanism by which YE2 attenuates macrophage M2 polarization. Methods: YE2 was utilized to treat macrophages (in vitro) and mice (in vivo). Western blotting and real-time PCR were used to detect the protein levels and mRNA levels of macrophage M2 polarization markers and their downstream signaling pathways. Sphingomyelin synthase 2 gene knockout (KO) mice and their controls were used to establish a PANC-02 orthotopic pancreatic cancer model, and immune cell infiltration in the tumor tissue was analyzed by immunohistochemistry (IHC). Results: We found that sphingomyelin synthase 2 mRNA expression is positively correlated with tumor-associated macrophages, the immunosuppressive microenvironment, and poor prognosis in pancreatic ductal adenocarcinoma patients. Sphingomyelin synthase 2 deficiency was confirmed to have an inhibitory effect on the growth of orthotopic PANC-02 tumors in vivo. The deficiency not only reduced the infiltration of tumor-associated macrophages but also regulated other immune components in the tumor microenvironment. In tissue culture, YE2 inhibited M2 polarization in both bone marrow-derived macrophages (BMDMs) and THP-1 macrophages and eliminated the protumor effect of M2 macrophages. In the mouse model, YE2 treatment reduced the infiltration of TAMs and regulated other immune components in the tumor microenvironment, slowing the progression of PANC-02 tumors. In terms of mechanism, we found that the inhibition of sphingomyelin synthase 2 could downregulate the expression of IL4Rα and CSF1R, thereby attenuating M2 polarization. Conclusion: The sphingomyelin synthase 2 inhibitor YE2 or sphingomyelin synthase 2 deficiency can prevent macrophage M2 polarization in pancreatic cancer, and sphingomyelin synthase 2 could be a new potential target for the treatment of pancreatic cancer.

Lpcat3 deficiency promotes palmitic acid-induced 3T3-L1 mature adipocyte inflammation through enhanced ROS generation.

Phosphatidylcholines (PCs) are major phospholipids in the mammalian cell membrane. Structural remodeling of PCs is associated with many biological processes. Lysophosphatidylcholine acyltransferase 3 (Lpcat3), which catalyzes the incorporation of polyunsaturated fatty acyl chains into the sn-2 site of PCs, plays an important role in maintaining plasma membrane fluidity. Adipose tissue is one of the main distribution organs of Lpcat3, while the relationship between Lpcat3 and adipose tissue dysfunction during overexpansion remains unknown. In this study, we reveal that both polyunsaturated PC content and Lpcat3 expression are increased in abdominal adipose tissues of high-fat diet-fed mice when compared with chow-diet-fed mice, indicating that Lpcat3 is involved in adipose tissue overexpansion and dysfunction. Our experiments in 3T3-L1 adipocytes show that inhibition of Lpcat3 does not change triglyceride accumulation but increases palmitic acid-induced inflammation and lipolysis. Conversely, Lpcat3 overexpression exhibits anti-inflammatory and anti-lipolytic effects. Furthermore, mechanistic studies demonstrate that Lpcat3 deficiency promotes reactive oxygen species (ROS) generation by increasing NOX enzyme activity by facilitating the translocation of NOX4 to lipid rafts, thereby aggregating 3T3-L1 adipocyte inflammation induced by palmitic acid. Moreover, overexpression of Lpcat3 exhibits the opposite effects. These findings suggest that Lpcat3 protects adipocytes from inflammation during adipose tissue overexpansion by reducing ROS generation. In conclusion, our study demonstrates that Lpcat3 deficiency promotes palmitic acid-induced inflammation in 3T3-L1 adipocytes by enhancing ROS generation.

Deterministic small-scale undulations of image-based risk predictions from the deep learning of lung tumors in motion.

INTRODUCTION: Deep learning (DL) models that use medical images to predict clinical outcomes are poised for clinical translation. For tumors that reside in organs that move, however, the impact of motion (i.e., degenerated object appearance or blur) on DL model accuracy remains unclear. We examine the impact of tumor motion on an image-based DL framework that predicts local failure risk after lung stereotactic body radiotherapy (SBRT). METHODS: We input pre-therapy free breathing (FB) computed tomography (CT) images from 849 patients treated with lung SBRT into a multitask deep neural network to generate an image fingerprint signature (or DL score) that predicts time-to-event local failure outcomes. The network includes a convolutional neural network encoder for extracting imaging features and building a task-specific fingerprint, a decoder for estimating handcrafted radiomic features, and a task-specific network for generating image signature for radiotherapy outcome prediction. The impact of tumor motion on the DL scores was then examined for a holdout set of 468 images from 39 patients comprising: (1) FB CT, (2) four-dimensional (4D) CT, and (3) maximum-intensity projection (MIP) images. Tumor motion was estimated using a 3D vector of the maximum distance traveled, and its association with DL score variance was assessed by linear regression. FINDINGS: The variance and amplitude in 4D CT image-derived DL scores were associated with tumor motion (R2  = 0.48 and 0.46, respectively). Specifically, DL score variance was deterministic and represented by sinusoidal undulations in phase with the respiratory cycle. DL scores, but not tumor volumes, peaked near end-exhalation. The mean of the scores derived from 4D CT images and the score obtained from FB CT images were highly associated (Pearson r = 0.99). MIP-derived DL scores were significantly higher than 4D- or FB-derived risk scores (p < 0.0001). INTERPRETATION: An image-based DL risk score derived from a series of 4D CT images varies in a deterministic, sinusoidal trajectory in a phase with the respiratory cycle. These results indicate that DL models of tumors in motion can be robust to fluctuations in object appearance due to movement and can guide standardization processes in the clinical translation of DL models for patients with lung cancer.

Dynamic Alterations in the Respiratory Tract Microbiota of Patients with COVID-19 and its Association with Microbiota in the Gut.

The role of respiratory tract microbes and the relationship between respiratory tract and gut microbiomes in coronavirus disease 2019 (COVID-19) remain uncertain. Here, the metagenomes of sputum and fecal samples from 66 patients with COVID-19 at three stages of disease progression are sequenced. Respiratory tract, gut microbiome, and peripheral blood mononuclear cell (PBMC) samples are analyzed to compare the gut and respiratory tract microbiota of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between respiratory tract microbiome and immune response. In the respiratory tract, significantly fewer Streptococcus, Actinomyces, Atopobium, and Bacteroides are found in ICU than in nICU patients, while Enterococcus and Candida increase. In the gut, significantly fewer Bacteroides are found in ICU patients, while Enterococcus increases. Significant positive correlations exist between relative microbiota abundances in the respiratory tract and gut. Defensin-related pathways in PBMCs are enhanced, and respiratory tract Streptococcus is reduced in patients with COVID-19. A respiratory tract-gut microbiota model identifies respiratory tract Streptococcus and Atopobium as the most prominent biomarkers distinguishing between ICU and nICU patients. The findings provide insight into the respiratory tract and gut microbial dynamics during COVID-19 progression, considering disease severity, potentially contributing to diagnosis, and treatment strategies.