TP53 disruptive mutation predicts platinum-based chemotherapy and PD-1/PD-L1 blockade response in urothelial carcinoma.

TP53 mutation is one of the most common genetic alterations in urothelial carcinoma (UrCa), and heterogeneity of TP53 mutants leads to heterogeneous clinical outcomes. This study aimed to investigate the clinical relevance of specific TP53 mutations in UrCa. In this study, a total of eight cohorts were enrolled, along with matched clinical annotation. TP53 mutations were classified as disruptive and nondisruptive according to the degree of disturbance of p53 protein function and structure. We evaluated the clinical significance of TP53 mutations in our local datasets and publicly available datasets. The co-occurring events of TP53 mutations in UrCa, along with their therapeutic indications, functional effects, and the tumor immune microenvironment, were also investigated. TP53 mutations were identified in 49.7% of the UrCa patients. Within this group, 25.1% of patients carried TP53Disruptive mutations, a genetic alteration correlated with a significantly poorer overall survival (OS) when compared to individuals with TP53Nondisruptive mutations and those with wild-type TP53. Significantly, patients with TP53Disruptive mutations exhibit an increased probability of responding favorably to PD-1/PD-L1 blockade and chemoimmunotherapy. Meanwhile, there was no noteworthy distinction in OS among patients with varying TP53 mutation status who underwent chemotherapy. Samples with TP53Disruptive mutations showed an enriched APOBEC- and POLE-related mutational signature, as well as an elevated tumor mutation burden. The sensitivity to immunotherapy in tumors carrying TP53Disruptive mutation may be attributed to the inflamed tumor microenvironment characterized by increased CD8+T cell infiltration and interferon-gamma signaling activation. In conclusion, UrCa patients with TP53Disruptive mutations have shown reduced survival rates, yet they may respond well to PD-1/PD-L1 blockade therapy and chemoimmunotherapy. By distinguishing specific TP53 mutations, we can improve risk stratification and offer personalized genomics-guided therapy to UrCa patients. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Overall survival benefits of cancer drugs initially approved by the US Food and Drug Administration on the basis of immature survival data: a retrospective analysis.

BACKGROUND: New cancer drugs can be approved by the US Food and Drug Administration (FDA) on the basis of surrogate endpoints while data on overall survival are still incomplete or immature, with too few deaths for meaningful analysis. We aimed to evaluate whether clinical trials with immature survival data generated evidence of overall survival benefit during the period after marketing authorisation, and where that evidence was reported. METHODS: In this retrospective analysis, we searched Drugs@FDA to identify cancer drug indications approved between Jan 1, 2001, and Dec 31, 2018, on the basis of immature survival data. We systematically collected publicly available data on postapproval overall survival results in labelling (Drugs@FDA), journal publications (MEDLINE via PubMed), and clinical trial registries (ClinicalTrials.gov). The primary outcome was availability of statistically significant overall survival benefits during the period after marketing authorisation (until March 31, 2023). Additionally, we evaluated the availability and timing of overall survival findings in labelling, journal publications, and ClinicalTrials.gov records. FINDINGS: During the study period, the FDA granted marketing authorisation to 223 cancer drug indications, 95 of which had overall survival as an endpoint. 39 (41%) of these 95 indications had immature survival data. After a minimum of 4·3 years of follow-up during the period after marketing authorisation (and median 8·2 years [IQR 5·3-12·0] since FDA approval), additional survival data from the pivotal trials became available in either revised labelling or publications, or both, for 38 (97%) of 39 indications. Additional data on overall survival showed a statistically significant benefit in 12 (32%) of 38 indications, whereas mature data yielded statistically non-significant overall survival findings for 24 (63%) indications. Statistically significant evidence of overall survival benefit was reported in either labelling or publications a median of 1·5 years (IQR 0·8-2·3) after initial approval. The median time to availability of statistically non-significant overall survival results was 3·3 years (2·2-4·5). The availability of overall survival results on ClinicalTrials.gov varied considerably. INTERPRETATION: Fewer than a third of indications approved with immature survival data showed a statistically significant overall survival benefit after approval. Notable inconsistencies in timing and availability of information after approval across different sources emphasise the need for better reporting standards. FUNDING: None.

Integration of CD4+ T cells and molecular subtype predicts benefit from PD-L1 blockade in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) is a disease characterized by molecular and clinical heterogeneity, posing challenges in selecting the most appropriate treatment in clinical settings. Considering the significant role of CD4+ T cells, there is an emerging need to integrate CD4+ T cells with molecular subtypes to refine classification. We conducted a comprehensive study involving 895 MIBC patients from four independent cohorts. The Zhongshan Hospital (ZSHS) and The Cancer Genome Atlas (TCGA) cohorts were included to investigate chemotherapeutic response. The IMvigor210 cohort was included to assess the immunotherapeutic response. NCT03179943 was used to evaluate the clinical response to a combination of immune checkpoint blockade (ICB) and chemotherapy. Additionally, we evaluated genomic characteristics and the immune microenvironment to gain deeper insights into the distinctive features of each subtype. We unveiled four immune-molecular subtypes, each exhibiting distinct clinical outcomes and molecular characteristics. These subtypes include luminal CD4+ Thigh, which demonstrated benefits from both immunotherapy and chemotherapy; luminal CD4+ Tlow, characterized by the highest level of fibroblast growth factor receptor 3 (FGFR3) mutation, thus indicating potential responsiveness to FGFR inhibitors; basal CD4+ Thigh, which could benefit from a combination of ICB and chemotherapy; and basal CD4+ Tlow, characterized by an immune suppression microenvironment and likely to benefit from transforming growth factor-ß (TGF-ß) inhibition. This immune-molecular classification offers new possibilities for optimizing therapeutic interventions in MIBC.

Integrative score based on CDK6, PD-L1 and TMB predicts response to platinum-based chemotherapy and PD-1/PD-L1 blockade in muscle-invasive bladder cancer.

BACKGROUND: Cyclin-dependent kinase 6 (CDK6) was proved to be an important regulator in the progression of cell cycle and has been a promising therapeutic target in cancer treatment. However, the clinical significance of CDK6 in muscle-invasive bladder cancer (MIBC) remains obscure. Herein, we attempt to explore the clinical relevance of CDK6 and assess the feasibility of the integrative model to predict immune checkpoint blockade (ICB) response. METHODS: This study enrolled 933 patients with muscle-invasive bladder cancer (MIBC) from Zhongshan Hospital (ZSHS), The Cancer Genome Atlas (TCGA), Chemo, IMvigor210 and UC-GENOME cohorts. Kaplan-Meier survival and Cox regression analyses were performed to assess clinical outcomes based on CDK6 expression. RESULTS: High CDK6 expression conferred poor prognosis and superior response to platinum-based chemotherapy but inferior response to ICB in MIBC. Furthermore, the integrative model named response score based on CDK6, PD-L1 and TMB could better predict the response to ICB and chemotherapy. Patients with higher response scores were characterised by inflamed immune microenvironment and genomic instability. CONCLUSIONS: CDK6 expression was correlated with prognosis and therapy response in MIBC. Integration of CDK6, PD-L1 and TMB could better identify patients who were most likely to benefit from ICB and chemotherapy.

Integrating molecular subtype and CD8+ T cells infiltration to predict treatment response and survival in muscle-invasive bladder cancer.

BACKGROUND: Luminal and Basal are the primary intrinsic subtypes of muscle-invasive bladder cancer (MIBC). The presence of CD8+ T cells infiltration holds significant immunological relevance, potentially influencing the efficacy of antitumor responses. This study aims to synergize the influence of molecular subtypes and CD8+ T cells infiltration in MIBC. METHODS: This study included 889 patients with MIBC from Zhongshan Hospital, The Cancer Genome Atlas, IMvigor210 and NCT03179943 cohorts. We classified the patients into four distinct groups, based on the interplay of molecular subtypes and CD8+ T cells and probed into the clinical implications of these subgroups in MIBC. RESULTS: Among patients with Luminal-CD8+Thigh tumors, the confluence of elevated tumor mutational burden and PD-L1 expression correlated with a heightened potential for positive responses to immunotherapy. In contrast, patients featured by Luminal-CD8+Tlow displayed a proclivity for deriving clinical advantages from innovative targeted interventions. The Basal-CD8+Tlow subgroup exhibited the least favorable three-year overall survival outcome, whereas their Basal-CD8+Thigh counterparts exhibited a heightened responsiveness to chemotherapy. CONCLUSIONS: We emphasized the significant role of immune-molecular subtypes in shaping therapeutic approaches for MIBC. This insight establishes a foundation to refine the process of selecting subtype-specific treatments, thereby advancing personalized interventions for patients.

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results. Materials and Methods This secondary analysis of a prospective registry included consecutive patients with suspected or known PCa who underwent mpMRI, US-guided systematic biopsy, or combined systematic and MRI/US fusion-guided biopsy between April 2019 and September 2022. All lesions were prospectively evaluated using Prostate Imaging Reporting and Data System version 2.1. The lesion- and participant-level performance of a previously developed cascaded deep learning algorithm was compared with histopathologic outcomes and radiologist readings using sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC). Results A total of 658 male participants (median age, 67 years [IQR, 61-71 years]) with 1029 MRI-visible lesions were included. At histopathologic analysis, 45% (294 of 658) of participants had lesions of International Society of Urological Pathology (ISUP) grade group (GG) 2 or higher. The algorithm identified 96% (282 of 294; 95% CI: 94%, 98%) of all participants with clinically significant PCa, whereas the radiologist identified 98% (287 of 294; 95% CI: 96%, 99%; P = .23). The algorithm identified 84% (103 of 122), 96% (152 of 159), 96% (47 of 49), 95% (38 of 40), and 98% (45 of 46) of participants with ISUP GG 1, 2, 3, 4, and 5 lesions, respectively. In the lesion-level analysis using radiologist ground truth, the detection sensitivity was 55% (569 of 1029; 95% CI: 52%, 58%), and the PPV was 57% (535 of 934; 95% CI: 54%, 61%). The mean number of false-positive lesions per participant was 0.61 (range, 0-3). The lesion segmentation DSC was 0.29. Conclusion The AI algorithm detected cancer-suspicious lesions on biparametric MRI scans with a performance comparable to that of an experienced radiologist. Moreover, the algorithm reliably predicted clinically significant lesions at histopathologic examination. ClinicalTrials.gov Identifier: NCT03354416 © RSNA, 2024 Supplemental material is available for this article.

Spermacoce alata Aubl. Essential Oil: Chemical Composition, In Vitro Antioxidant Activity, and Inhibitory Effects of Acetylcholinesterase, α-Glucosidase and ß-Lactamase.

Spermacoce alata Aubl. is widely available in the market as traditional Chinese medicine and animal feed, due to its properties of clearing heat and treating malaria and its high-protein and crude fiber content. In this study, the essential oil of S. alata was obtained through hydrodistillation. GC-MS and GC-FID methods were used to identify the chemical components and their relative abundance. Furthermore, the antioxidant capacity was measured using DPPH, ABTS, and FRAP assays, and the inhibitory effects of acetylcholinesterase, α-glucosidase, and ß-lactamase were also evaluated. A total of 67 compounds were identified, with the major constituents being palmitic acid (30.74%), linoleic acid (16.13%), and phenylheptatriyne (8.07%). The essential oil exhibited moderate antioxidant activity against DPPH (IC50 > 10 mg/mL), while the IC50 value for the ABTS assay was 3.84 ± 2.12 mg/mL and the FRAP assay value was 87.22 ± 12.22 µM/g. Additionally, the essential oil showed moderate anti-acetylcholinesterase activity (IC50 = 286.0 ± 79.04 µg/mL), significant anti-α-glucosidase activity (IC50 = 174.7 ± 13.12 µg/mL), and potent anti-ß-lactamase activity (IC50 = 37.56 ± 3.48 µg/mL). The results suggest that S. alata has the potential for application in pharmacology, warranting further exploration and investigation.

Insights into the regulatory role of RNA methylation modifications in glioma.

Epitranscriptomic abnormalities, which are highly prevalent in primary central nervous system malignancies, have been identified as crucial contributors to the development and progression of gliomas. RNA epitranscriptomic modifications, particularly the reversible modification methylation, have been observed throughout the RNA cycle. Epitranscriptomic modifications, which regulate RNA transcription and translation, have profound biological implications. These modifications are associated with the development of several cancer types. Notably, three main protein types-writers, erasers, and readers, in conjunction with other related proteins, mediate these epitranscriptomic changes. This review primarily focuses on the role of recently identified RNA methylation modifications in gliomas, such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), and N1-methyladenosine (m1A). We delved into their corresponding writers, erasers, readers, and related binding proteins to propose new approaches and prognostic indicators for patients with glioma.

Chemical Composition and In Vitro Antioxidant Activity and Anti-Acetylcholinesterase Activity of Essential Oils from Tadehagi triquetrum (L.) Ohashi.

The present study aimed to determine the chemical compositions of essential oils (EOs) from Tadehagi triquetrum (L.) Ohashi and evaluate their antioxidant and anti-cholinesterase activity under the comprehensive influence of chemical components. The essential oils were extracted from T. triquetrum (L.) Ohashi by hydrodistillation. A total of 58 organic compounds were identified by GC-FID and GC-MS analysis. The major components of T. triquetrum (L.) Ohashi EOs were identified as palmitic acid (22.46%), 1-Octen-3-ol (14.07%), Caryophyllene (7.20%), (Z)-18-Octadec-9-enolide (6.04%), and 3-Hexen-1-ol (4.55%). The antioxidant activity of the essential oils was determined by using ABTS assay, DPPH assay, and FRAP assay, with IC50 values of 2.12 ± 0.05 mg/mL, 4.73 ± 0.91 mg/mL against the ABTS, DPPH, and FRAP value 117.42 ± 8.10 mM/g. The result showed that it had moderate antioxidant activities in the experiment, which why it is likely that it will be used as an antioxidant. At the same time, the EOs also showed moderate anti-acetylcholinesterase activity. This study expands the chemical and biological knowledge of the EOs of T. triquetrum.

A 30% Efficient High-Output Voltage Fully Integrated Self-Biased Gate RF Rectifier Topology for Neural Implants.

This paper presents a fully integrated RF energy harvester (EH) with 30% end-to-end power harvesting efficiency (PHE) and supports high output voltage operation, up to 9.3V, with a 1.07 GHz input and under the electrode model for neural applications. The EH is composed of a novel 10-stage self-biased gate (SBG) rectifier with an on-chip matching network. The SBG topology elevates the gate-bias of transistors in a non-linear manner to enable higher conductivity. The design also achieves >20% PHE range of 12-dB. The design was fabricated in 65 nm CMOS technology and occupies an area of 0.0732-mm2 with on-chip matching network. In addition to standalone EH characterization measurement results, animal tissue stimulation test was performed to evaluate its performance in a realistic neural implant application.

Structural Design and Application of Desensitized FBG Force-Measuring Bolt.

Bolt-supporting technology has been widely used in mine roadway support, and its own working conditions have important reference value for roadway safety support. In order to realize the continuous and reliable monitoring of the bolt rod's working condition, this paper analyzes the existing problems of the existing fiber Bragg grating force-measuring bolt (FBG-FMB), and proposes a fiber grating strain desensitization sensing theory. Based on this theory, a desensitized FBG-FMB is developed with the spring as the elastic sensitive element. A mechanical analysis and drawing test show that the strain of the force-measuring bolt is greater than 60 times the micro-strain of the fiber grating, which verifies the feasibility of the structure design of the FBG-FMB. Finally, through the field application in the coal mine roadway, the working conditions of the bolt body at the two measuring points of the roadway are obtained to verify the reliability of the force-measuring bolt. In addition, the desensitized FBG-FMB can be widely used in the supporting fields of underground engineering such as slopes, tunnels, and foundation pits.

Research on Straightness Perception Compensation Model of FBG Scraper Conveyor Based on Rotation Error Angle.

The accurate perception of straightness of a scraper conveyor is important for the construction of intelligent working faces in coal mines. In this paper, we propose a precision compensation model based on rotation error angle to improve the accuracy of the fiber Bragg grating (FBG) curvature sensor of a scraper conveyor. The correctness of the model is verified by theoretical analysis, numerical simulation, and experiments. Finally, the feasibility of the model is analyzed and discussed for field application in a coal mine. When the rotation error angle is within the range of 0~90°, according to the strain of FBG obtained by numerical simulation, the radius of the curvature is inversely calculated by the compensation model. The relative error of each discrete point is within ±0.9%, and the relative error after fitting is less than 0.2%. The experiment shows that the relative error of the curvature radius after fitting according to the theoretical formula is less than ±3%, and the relative error of the curvature radius value obtained by the inverse deduction of each discrete point is less than ±6%, which verifies the correctness and applicability of the compensation model. In addition, the compensation model with the FBG curvature sensor has broad application prospects in coal mine underground conveyors, submarine pipelines and ground pipelines.

Chemical Composition and In Vitro Antioxidant Activity of Sida rhombifolia L. Volatile Organic Compounds.

In the current study, the phytochemical constituents of volatile organic compounds (VOCs) obtained from Sida rhombifolia L. were identified by GC-FID and GC-MS analysis. A total of 73 volatile organic compounds were identified. The major components of S. rhombifolia VOCs were identified as palmitic acid (21.56%), phytol (7.02%), 6,10,14-trimethyl-2-pentadecanone (6.30%), oleic acid (5.48%), 2-pentyl-furan (5.23%), and linoleic acid (3.21%). The VOCs are rich in fatty acids (32.50%), olefine aldehyde (9.59%), ketone (9.41%), enol (9.02%), aldehyde (8.63%), and ketene (6.41%). The antioxidant capacity of S. rhombifolia VOCs was determined by 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH), 2,2-azinobis-(3-ethylbenzothiazolin-6-sulfonic acid) diammonium salt (ABTS), and ferric reducing/antioxidant power (FRAP) methods with butylated hydroxytoluene (BHT) and Trolox as standard. The VOCs showed dose-dependent antioxidant activity with IC50 (50% inhibitory concentration) values of 5.48 ± 0.024 and 1.47 ± 0.012 mg/mL for DPPH and ABTS assays, respectively. FRAP antioxidant capacity was 83.10 ± 1.66 mM/g. The results show that the VOCs distilled from S. rhombifolia have a moderate antioxidant property that can be utilized as a natural botanical supplement or an antioxidant.

CT and clinical assessment in asymptomatic and pre-symptomatic patients with early SARS-CoV-2 in outbreak settings.

OBJECTIVES: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. METHODS: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. RESULTS: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. CONCLUSIONS: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. KEY POINTS: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1-5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

Water-Soluble Flexible Organic Frameworks That Include and Deliver Proteins.

Four water-soluble hydrazone-based three-dimensional (3D) flexible organic frameworks FOF-1-4 have been synthesized from a semirigid tetracationic tetraaldehyde and four flexible dihydrazides. 1H NMR spectroscopy indicated the quantitative formation of FOF-1-4 in D2O, while dynamic light scattering experiments revealed that, depending on the concentration, these porous frameworks display hydrodynamic diameters ranging from 50 to 120 nm. The porosity of the frameworks is confirmed by ethanol vapor adsorption experiments of the solid samples as well as the high loading capacity for a 2.3 nm porphyrin guest in water. The new water-soluble frameworks exhibit low cytotoxicity and form inherent pores with diameters of 5.3 or 6.7 nm, allowing rapid inclusion of proteins such as bovine serum albumin and green and orange fluorescent proteins, and efficient delivery of the proteins into normal and cancer cells. Flow cytometric analysis reveals percentages of the delivered cells up to 99.8%.

Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit.

BACKGROUND AND AIMS: Artificial intelligence (AI), specifically deep learning, offers the potential to enhance the field of GI endoscopy in areas ranging from lesion detection and classification to quality metrics and documentation. Progress in this field will be measured by whether AI implementation can lead to improved patient outcomes and more efficient clinical workflow for GI endoscopists. The aims of this article are to report the findings of a multidisciplinary group of experts focusing on issues in AI research and applications related to gastroenterology and endoscopy, to review the current status of the field, and to produce recommendations for investigators developing and studying new AI technologies for gastroenterology. METHODS: A multidisciplinary meeting was held on September 28, 2019, bringing together academic, industry, and regulatory experts in diverse fields including gastroenterology, computer and imaging sciences, machine learning, computer vision, U.S. Food and Drug Administration, and the National Institutes of Health. Recent and ongoing studies in gastroenterology and current technology in AI were presented and discussed, key gaps in knowledge were identified, and recommendations were made for research that would have the highest impact in making advances and implementation in the field of AI to gastroenterology. RESULTS: There was a consensus that AI will transform the field of gastroenterology, particularly endoscopy and image interpretation. Powered by advanced machine learning algorithms, the use of computer vision in endoscopy has the potential to result in better prediction and treatment outcomes for patients with gastroenterology disorders and cancer. Large libraries of endoscopic images, "EndoNet," will be important to facilitate development and application of AI systems. The regulatory environment for implementation of AI systems is evolving, but common outcomes such as colon polyp detection have been highlighted as potential clinical trial endpoints. Other threshold outcomes will be important, as well as clarity on iterative improvement of clinical systems. CONCLUSIONS: Gastroenterology is a prime candidate for early adoption of AI. AI is rapidly moving from an experimental phase to a clinical implementation phase in gastroenterology. It is anticipated that the implementation of AI in gastroenterology over the next decade will have a significant and positive impact on patient care and clinical workflows. Ongoing collaboration among gastroenterologists, industry experts, and regulatory agencies will be important to ensure that progress is rapid and clinically meaningful. However, several constraints and areas will benefit from further exploration, including potential clinical applications, implementation, structure and governance, role of gastroenterologists, and potential impact of AI in gastroenterology.

Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model.

OBJECTIVE. Deep learning applications in radiology often suffer from overfitting, limiting generalization to external centers. The objective of this study was to develop a high-quality prostate segmentation model capable of maintaining a high degree of performance across multiple independent datasets using transfer learning and data augmentation. MATERIALS AND METHODS. A retrospective cohort of 648 patients who underwent prostate MRI between February 2015 and November 2018 at a single center was used for training and validation. A deep learning approach combining 2D and 3D architecture was used for training, which incorporated transfer learning. A data augmentation strategy was used that was specific to the deformations, intensity, and alterations in image quality seen on radiology images. Five independent datasets, four of which were from outside centers, were used for testing, which was conducted with and without fine-tuning of the original model. The Dice similarity coefficient was used to evaluate model performance. RESULTS. When prostate segmentation models utilizing transfer learning were applied to the internal validation cohort, the mean Dice similarity coefficient was 93.1 for whole prostate and 89.0 for transition zone segmentations. When the models were applied to multiple test set cohorts, the improvement in performance achieved using data augmentation alone was 2.2% for the whole prostate models and 3.0% for the transition zone segmentation models. However, the best test-set results were obtained with models fine-tuned on test center data with mean Dice similarity coefficients of 91.5 for whole prostate segmentation and 89.7 for transition zone segmentation. CONCLUSION. Transfer learning allowed for the development of a high-performing prostate segmentation model, and data augmentation and fine-tuning approaches improved performance of a prostate segmentation model when applied to datasets from external centers.

Mycobacterium tuberculosis dysregulates MMP/TIMP balance to drive rapid cavitation and unrestrained bacterial proliferation.

Active tuberculosis (TB) often presents with advanced pulmonary disease, including irreversible lung damage and cavities. Cavitary pathology contributes to antibiotic failure, transmission, morbidity and mortality. Matrix metalloproteinases (MMPs), in particular MMP-1, are implicated in TB pathogenesis. We explored the mechanisms relating MMP/TIMP imbalance to cavity formation in a modified rabbit model of cavitary TB. Our model resulted in consistent progression of consolidation to human-like cavities (100% by day 28), with resultant bacillary burdens (>10(7) CFU/g) far greater than those found in matched granulomatous tissue (10(5) CFU/g). Using a novel, breath-hold computed tomography (CT) scanning and image analysis protocol, we showed that cavities developed rapidly from areas of densely consolidated tissue. Radiological change correlated with a decrease in functional lung tissue, as estimated by changes in lung density during controlled pulmonary expansion (R(2) = 0.6356, p < 0.0001). We demonstrated that the expression of interstitial collagenase (MMP-1) was specifically greater in cavitary compared to granulomatous lesions (p < 0.01), and that TIMP-3 significantly decreased at the cavity surface. Our findings demonstrated that an MMP-1/TIMP imbalance is associated with the progression of consolidated regions to cavities containing very high bacterial burdens. Our model provided mechanistic insight, correlating with human disease at the pathological, microbiological and molecular levels. It also provided a strategy to investigate therapeutics in the context of complex TB pathology. We used these findings to predict a MMP/TIMP balance in active TB and confirmed this in human plasma, revealing the potential of MMP/TIMP levels as key components of a diagnostic matrix aimed at distinguishing active from latent TB (PPV = 92.9%, 95% CI 66.1-99.8%, NPV = 85.6%; 95% CI 77.0-91.9%).