Rac1 controls cell turnover and reversibility of the involution process in postpartum mammary glands.

Cell turnover in adult tissues is essential for maintaining tissue homeostasis over a life span and for inducing the morphological changes associated with the reproductive cycle. However, the underlying mechanisms that coordinate the balance of cell death and proliferation remain unsolved. Using the mammary gland, we have discovered that Rac1 acts as a nexus to control cell turnover. Postlactational tissue regression is characterised by the death of milk secreting alveoli, but the process is reversible within the first 48 h if feeding recommences. In mice lacking epithelial Rac1, alveolar regression was delayed. This defect did not result from failed cell death but rather increased cell turnover. Fitter progenitor cells inappropriately divided, regenerating the alveoli, but cell death also concomitantly accelerated. We discovered that progenitor cell hyperproliferation was linked to nonautonomous effects of Rac1 deletion on the macrophageal niche with heightened inflammation. Moreover, loss of Rac1 impaired cell death with autophagy but switched the cell death route to apoptosis. Finally, mammary gland reversibility failed in the absence of Rac1 as the alveoli failed to recommence lactation upon resuckling.

OX40 Ligand Contributes to Human Lupus Pathogenesis by Promoting T Follicular Helper Response.

Increased activity of T follicular helper (Tfh) cells plays a major pathogenic role in systemic lupus erythematosus (SLE). However, the mechanisms that cause aberrant Tfh cell responses in SLE remain elusive. Here we showed the OX40 ligand (OX40L)-OX40 axis contributes to the aberrant Tfh response in SLE. OX40L was expressed by myeloid antigen-presenting cells (APCs), but not B cells, in blood and in inflamed tissues in adult and pediatric SLE patients. The frequency of circulating OX40L-expressing myeloid APCs positively correlated with disease activity and the frequency of ICOS(+) blood Tfh cells in SLE. OX40 signals promoted naive and memory CD4(+) T cells to express multiple Tfh cell molecules and were sufficient to induce them to become functional B cell helpers. Immune complexes containing RNA induced OX40L expression on myeloid APCs via TLR7 activation. Our study provides a rationale to target the OX40L-OX40 axis as a therapeutic modality for SLE.

Human plasma cells express granzyme B.

While studying the plasma cell (PC) compartment in human tonsils, we identified that immunoglobulin kappa or lambda chain-expressing PCs are the main cells expressing granzyme B (GrzB). In vitro studies revealed that activated B cells differentiated into GrzB-expressing PCs when co-cultured with macrophages and follicular helper T cells. This effect could be reproduced on combined stimulation of IL-15 (produced by macrophages) and IL-21 (produced by T follicular helper cells) in a STAT3-dependent manner. Whereas IL-21 triggers the transcription of mRNA of GrzB, IL-15 synergizes the translation of GrzB proteins. The precise role of GrzB in PC biology remains to be understood and studies in mice will not help as their PCs do not express GrzB.

The MRI features of histologically proven ovarian cystadenofibromas-an assessment of the morphological and enhancement patterns.

OBJECTIVES: To assess the morphological and enhancement features of histologically proven cystadenofibromas (CAFs) on magnetic resonance imaging (MRI). METHODS: Forty-seven histologically proven CAFs (42 benign, five borderline) were retrospectively reviewed. One benign CAF had a synchronous adenocarcinoma in the same ovary. The morphological, signal and enhancement characteristics on MRI were recorded. RESULTS: The mean long axis diameter of the CAFs was 80 mm. The contralateral ovary was abnormal in 45 % of cases. A solid component was seen in 85 %, which returned low T2-weighted signal in 75 % of CAFs. Septa were seen in 74 % and one CAF was purely cystic. The majority of solid components and septa demonstrated enhancement that was less than the myometrium. Wash-in rates (WIR) of the solid tissue were available for measurement in nine patients with an average WIR of 3.2 l/s. CONCLUSION: This is the largest series describing MRI appearances of histologically proven CAFs. They are typically complex adnexal lesions containing septa, cystic components and solid tissue. The majority of solid components demonstrate low T2 signal and minimal enhancement. Almost half of the cases have an abnormal contralateral ovary.

Off-the-shelf adenoviral-mediated immunotherapy via bicistronic expression of tumor antigen and iMyD88/CD40 adjuvant.

Recent modest successes in ex vivo dendritic cell (DC) immunotherapy have motivated continued innovation in the area of DC manipulation and activation. Although ex vivo vaccine approaches continue to be proving grounds for new DC manipulation techniques, the intrinsic limits of ex vivo therapy, including high cost, minimal standardization, cumbersome delivery, and poor accessibility, incentivizes the development of vaccines compatible with in vivo DC targeting. We describe here a method to co-deliver both tumor-specific antigen (TSA) and an iMyD88/CD40 adjuvant (iMC), to DCs that combines toll-like receptor (TLR) and CD40 signaling. In this study, we demonstrate that simple TSA delivery via adenoviral vectors results in strong antitumor immunity. Addition of iMC delivered in a separate vector is insufficient to enhance this effect. However, when delivered simultaneously with TSA in a single bicistronic vector (BV), iMC is able to significantly enhance antigen-specific cytotoxic T-cell (CTL) responses and inhibit established tumor growth. This study demonstrates the spatial-temporal importance of concurrent DC activation and TSA presentation. Further, it demonstrates the feasibility of in vivo molecular enhancement of DCs necessary for effective antitumor immune responses.

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning.

While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the task remains time-consuming and prone to human inconsistencies. This has an impact especially in cases of Acute Promyelocytic Leukemia (APL) that require urgent treatment. Integration of automated computational hematopathology into clinical workflows can improve the throughput of these services and reduce cognitive human error. However, a major bottleneck in deploying such systems is a lack of sufficient cell morphological object-labels annotations to train deep learning models. We overcome this by leveraging patient diagnostic labels to train weakly-supervised models that detect different types of acute leukemia. We introduce a deep learning approach, Multiple Instance Learning for Leukocyte Identification (MILLIE), able to perform automated reliable analysis of blood films with minimal supervision. Without being trained to classify individual cells, MILLIE differentiates between acute lymphoblastic and myeloblastic leukemia in blood films. More importantly, MILLIE detects APL in blood films (AUC 0.94 ± 0.04) and in bone marrow aspirates (AUC 0.99 ± 0.01). MILLIE is a viable solution to augment the throughput of clinical pathways that require assessment of blood film microscopy.

A Multi-Purpose Realistic Haze Benchmark With Quantifiable Haze Levels and Ground Truth.

Imagery collected from outdoor visual environments is often degraded due to the presence of dense smoke or haze. A key challenge for research in scene understanding in these degraded visual environments (DVE) is the lack of representative benchmark datasets. These datasets are required to evaluate state-of-the-art object recognition and other computer vision algorithms in degraded settings. In this paper, we address some of these limitations by introducing the first realistic haze image benchmark, from both aerial and ground view, with paired haze-free images, and in-situ haze density measurements. This dataset was produced in a controlled environment with professional smoke generating machines that covered the entire scene, and consists of images captured from the perspective of both an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). We also evaluate a set of representative state-of-the-art dehazing approaches as well as object detectors on the dataset. The full dataset presented in this paper, including the ground truth object classification bounding boxes and haze density measurements, is provided for the community to evaluate their algorithms at: https://a2i2-archangel.vision. A subset of this dataset has been used for the "Object Detection in Haze" Track of CVPR UG2 2022 challenge at https://cvpr2022.ug2challenge.org/track1.html.

Use of super resolution reconstruction MRI for surgical planning in Placenta accreta spectrum disorder: Case series.

INTRODUCTION: Comprehensive imaging using ultrasound and MRI of placenta accreta spectrum (PAS) aims to prevent catastrophic haemorrhage and maternal death. Standard MRI of the placenta is limited by between-slice motion which can be mitigated by super-resolution reconstruction (SRR) MRI. We applied SRR in suspected PAS cases to determine its ability to enhance anatomical placental assessment and predict adverse maternal outcome. METHODS: Suspected PAS patients (n = 22) underwent MRI at a gestational age (weeks + days) of (32+3±3+2, range (27+1-38+6)). SRR of the placental-myometrial-bladder interface involving rigid motion correction of acquired MRI slices combined with robust outlier detection to reconstruct an isotropic high-resolution volume, was achieved in twelve. 2D MRI or SRR images alone, and paired data were assessed by four radiologists in three review rounds. All radiologists were blinded to results of the ultrasound, original MR image reports, case outcomes, and PAS diagnosis. A Random Forest Classification model was used to highlight the most predictive pathological MRI markers for major obstetric haemorrhage (MOH), bladder adherence (BA), and placental attachment depth (PAD). RESULTS: At delivery, four patients had placenta praevia with no abnormal attachment, two were clinically diagnosed with PAS, and six had histopathological PAS confirmation. Pathological MRI markers (T2-dark intraplacental bands, and loss of retroplacental T2-hypointense line) predicting MOH were more visible using SRR imaging (accuracy 0.73), in comparison to 2D MRI or paired imaging. Bladder wall interruption, predicting BA, was only easily detected by paired imaging (accuracy 0.72). Better detection of certain pathological markers predicting PAD was found using 2D MRI (placental bulge and myometrial thinning (accuracy 0.81)), and SRR (loss of retroplacental T2-hypointense line (accuracy 0.82)). DISCUSSION: The addition of SRR to 2D MRI potentially improved anatomical assessment of certain pathological MRI markers of abnormal placentation that predict maternal morbidity which may benefit surgical planning.

Unmasking the immune microecology of ductal carcinoma in situ with deep learning.

Despite increasing evidence supporting the clinical relevance of tumour infiltrating lymphocytes (TILs) in invasive breast cancer, TIL spatial variability within ductal carcinoma in situ (DCIS) samples and its association with progression are not well understood. To characterise tissue spatial architecture and the microenvironment of DCIS, we designed and validated a new deep learning pipeline, UNMaSk. Following automated detection of individual DCIS ducts using a new method IM-Net, we applied spatial tessellation to create virtual boundaries for each duct. To study local TIL infiltration for each duct, DRDIN was developed for mapping the distribution of TILs. In a dataset comprising grade 2-3 pure DCIS and DCIS adjacent to invasive cancer (adjacent DCIS), we found that pure DCIS cases had more TILs compared to adjacent DCIS. However, the colocalisation of TILs with DCIS ducts was significantly lower in pure DCIS compared to adjacent DCIS, which may suggest a more inflamed tissue ecology local to DCIS ducts in adjacent DCIS cases. Our study demonstrates that technological developments in deep convolutional neural networks and digital pathology can enable an automated morphological and microenvironmental analysis of DCIS, providing a new way to study differential immune ecology for individual ducts and identify new markers of progression.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Can quantitative dynamic contrast-enhanced MRI independently characterize an ovarian mass?

OBJECTIVES: Our aim was to establish threshold criteria based on quantitative DCE-MRI data as independent predictors of malignancy in a complex (solid, solid/cystic) ovarian mass. METHODS: The MRI of 26 lesions in 25 patients with a complex ovarian mass (age range, 17-80 years; mean 43 years) was retrospectively reviewed and correlated with histology following resection. Cases with solid tumour components, definitive histology and relevant dynamic imaging were included. These were categorised into two groups, benign (N = 14) and malignant (N = 12). Following dynamic contrast-enhanced imaging, regions of interest were drawn around the solid tumour component. Maximum actual enhancement (SImax), maximum relative enhancement (SIrel), wash-in rate (WIR) and SImax (tumour)/SImax (psoas) ratio were analysed. Threshold criteria for malignancy were established. RESULTS: There was a significant difference in SImax (p < 0.001), SIrel (p < 0.05), WIR (p < 0.001) and SImax (tumour)/SImax (psoas) between the two groups. Optimal threshold criteria for malignancy were established; SImax > or = 250 or SImax (tumour)/SImax (psoas) > or = 2.35 divided the two groups with 100% sensitivity, specificity and accuracy. CONCLUSION: Threshold criteria established in this preliminary study using quantitative DCE-MRI provide an accurate method for the prediction of malignancy, particularly in preoperative indeterminate cases.

Pearls and pitfalls of MR lymphography in gynecologic malignancy.

Dissemination of tumor to lymph nodes is one of the principal routes of metastatic disease. The presence or absence of nodal disease is an important prognostic factor in gynecologic malignancies; thus, nodal staging is an integral part of the pretreatment assessment. It is vital that pretreatment nodal staging be accurate and reliable. Current imaging techniques such as computed tomography and magnetic resonance (MR) imaging have limitations because they rely almost exclusively on size criteria. MR lymphography uses a lymph node-specific contrast agent (ferumoxtran-10) composed of ultrasmall superparamagnetic iron oxide particles. The contrast agent is taken up by macrophages within benign lymph nodes and allows differentiation from malignant nodes on the basis of alterations in signal intensity. This technique has been shown to increase the sensitivity and specificity of detection of lymph node metastases independent of nodal size. However, as with any technique, there are pitfalls that the radiologist must be aware of to avoid interpretative errors.

Fistulas in malignant gynecologic disease: etiology, imaging, and management.

A fistula that occurs in association with a malignancy of the female reproductive tract may be caused by a primary or recurrent tumor or may be a complication of surgery or radiation therapy. Identification of the cause, complexity, and location of a fistula is essential for optimal management planning. Radiologic imaging, particularly with computed tomography and magnetic resonance techniques, is invaluable for the assessment of gynecologic fistulas and may help direct the clinician toward the most appropriate management pathway. The modality and technique selected for the initial imaging evaluation depend largely on the clinical history and manifestations. However, imaging with a combination of techniques often is required for accurate diagnosis and effective treatment planning. Radiologists should be familiar with suggestive clinical signs and symptoms as well as with the characteristic appearances of rectovaginal, vesicovaginal, ureterovaginal, enterovesical, enterocutaneous, and other pelvic fistulas at multimodality imaging.

Proliferation Tumour Marker Network (PTM-NET) for the identification of tumour region in Ki67 stained breast cancer whole slide images.

Uncontrolled proliferation is a hallmark of cancer and can be assessed by labelling breast tissue using immunohistochemistry for Ki67, a protein associated with cell proliferation. Accurate measurement of Ki67-positive tumour nuclei is of critical importance, but requires annotation of the tumour regions by a pathologist. This manual annotation process is highly subjective, time-consuming and subject to inter- and intra-annotator experience. To address this challenge, we have developed Proliferation Tumour Marker Network (PTM-NET), a deep learning model that objectively annotates the tumour regions in Ki67-labelled breast cancer digital pathology images using a convolution neural network. Our custom designed deep learning model was trained on 45 immunohistochemical Ki67-labelled whole slide images to classify tumour and non-tumour regions and was validated on 45 whole slide images from two different sources that were stained using different protocols. Our results show a Dice coefficient of 0.74, positive predictive value of 70% and negative predictive value of 88.3% against the manual ground truth annotation for the combined dataset. There were minimal differences between the images from different sources and the model was further tested in oestrogen receptor and progesterone receptor-labelled images. Finally, using an extension of the model, we could identify possible hotspot regions of high proliferation within the tumour. In the future, this approach could be useful in identifying tumour regions in biopsy samples and tissue microarray images.

Gauging possibilities for action based on friction underfoot.

Standing and walking generate information about friction underfoot. Five experiments examined whether walkers use such perceptual information for prospective control of locomotion. In particular, do walkers integrate information about friction underfoot with visual cues for sloping ground ahead to make adaptive locomotor decisions? Participants stood on low-, medium-, and high-friction surfaces on a flat platform and made perceptual judgments for possibilities for locomotion over upcoming slopes. Perceptual judgments did not match locomotor abilities: Participants tended to overestimate their abilities on low-friction slopes and underestimate on high-friction slopes (Experiments 1-4). Accuracy improved only for judgments made while participants were in direct contact with the slope (Experiment 5), highlighting the difficulty of incorporating information about friction underfoot into a plan for future actions.

The role of 18F-FDG PET CT in common gynaecological malignancies.

[fluorine-18]-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET CT) has increasing clinical applications supplementing conventional TVUS, CT and MRI imaging in assessing ovarian, cervical and endometrial cancer. The published literature on the applications of 18F-FDG PET CT shows its use can have significant impact on patient management by improving staging of the cancers, influencing patient selection for treatment and in detecting early recurrent disease. However, the increasing clinical use of PET CT does not always align with the guidelines, recommendations or expert opinion in the use of PET CT. This article summarizes the existing evidence base for the established clinical applications and the emerging roles for 18F-FDG PET CT in the common gynaecological malignancies.

Diagnostic utility of whole body Dixon MRI in multiple myeloma: A multi-reader study.

OBJECTIVE: To determine which of four Dixon image types [in-phase (IP), out-of-phase (OP), fat only (FO) and water-only (WO)] is most sensitive for detecting multiple myeloma (MM) focal lesions on whole body MRI (WB-MRI) images. METHODS: Thirty patients with clinically-suspected MM underwent WB-MRI at 3 Tesla. Unenhanced IP, OP, FO and WO Dixon images were generated and read by four radiologists. On each image type, each radiologist identified and labelled all visible myeloma lesions in the bony pelvis. Each identified lesion was compared with a reference standard consisting of pre- and post-contrast Dixon and diffusion weighted imaging (read by a further consultant radiologist) to determine whether the lesion was truly positive. Lesion count, true positives, sensitivity, and positive predictive value were compared across the four Dixon image types. RESULTS: Lesion count, true positives, sensitivity and confidence scores were all significantly higher on FO images than on IP images (p>0.05). DISCUSSION: FO images are more sensitive than other Dixon image types for MM focal lesions, and should be preferentially read by radiologists to improve diagnostic accuracy and reporting efficiency.

Occurrence of Gnathostoma spinigerum in a leopard cat from Wayanad Wildlife Sanctuary, Kerala.

The post-mortem examination of a leopard cat from Wayanad Wildlife Sanctuary, Kerala, died in a road accident, revealed presence of gastric tumours containing worms which were identified as Gnathostoma spinigerum based on morphological characteristics.

Improved segmentation of cerebellar structures in children.

BACKGROUND: Consistent localization of cerebellar cortex in a standard coordinate system is important for functional studies and detection of anatomical alterations in studies of morphometry. To date, no pediatric cerebellar atlas is available. NEW METHOD: The probabilistic Cape Town Pediatric Cerebellar Atlas (CAPCA18) was constructed in the age-appropriate National Institute of Health Pediatric Database asymmetric template space using manual tracings of 16 cerebellar compartments in 18 healthy children (9-13 years) from Cape Town, South Africa. The individual atlases of the training subjects were also used to implement multi atlas label fusion using multi atlas majority voting (MAMV) and multi atlas generative model (MAGM) approaches. Segmentation accuracy in 14 test subjects was compared for each method to 'gold standard' manual tracings. RESULTS: Spatial overlap between manual tracings and CAPCA18 automated segmentation was 73% or higher for all lobules in both hemispheres, except VIIb and X. Automated segmentation using MAGM yielded the best segmentation accuracy over all lobules (mean Dice Similarity Coefficient 0.76; range 0.55-0.91; mean Hausdorff distance 0.9 mm; range 0.8-2.7 mm). COMPARISON WITH EXISTING METHODS: In all lobules, spatial overlap of CAPCA18 segmentations with manual tracings was similar or higher than those obtained with SUIT (spatially unbiased infra-tentorial template), providing additional evidence of the benefits of an age appropriate atlas. MAGM segmentation accuracy was comparable to values reported recently by Park et al. (Neuroimage 2014;95(1):217) in adults (across all lobules mean DSC=0.73, range 0.40-0.89). CONCLUSIONS: CAPCA18 and the associated multi-subject atlases of the training subjects yield improved segmentation of cerebellar structures in children.

Timing of motor cortical stimulation during planar robotic training differentially impacts neuroplasticity in older adults.

OBJECTIVE: The objective was to determine how stimulation timing applied during reaching influenced neuroplasticity related to practice. Older adult participants were studied to increase relevance for stroke rehabilitation and aging. METHODS: Sixteen participants completed 3 sessions of a reaching intervention with 480 planar robotic movement trials. Sub-threshold, single-pulse transcranial magnetic stimulations (TMS) were delivered during the late reaction time (LRT) period, when muscle activity exceeded a threshold (EMG-triggered), or randomly. Assessments included motor evoked potentials (MEP), amplitude, and direction of supra-threshold TMS-evoked movements and were calculated as change scores from baseline. RESULTS: The direction of TMS-evoked movements significantly changed after reaching practice (p<0.05), but was not significantly different between conditions. Movement amplitude changes were significantly different between conditions (p<0.05), with significant increases following the LRT and random conditions. MEP for elbow extensors and flexors, and the shoulder muscle that opposed the practice movement were significantly different between conditions with positive changes following LRT, negative changes following EMG-triggered, and no changes following the random condition. Motor performance including movement time and peak velocity significantly improved following the training but did not differ between conditions. CONCLUSIONS: The responsiveness of the motor cortex to stimulation was affected positively by stimulation during the late motor response period and negatively during the early movement period, when stimulation was combined with robotic reach practice. SIGNIFICANCE: The sensitivity of the activated motor cortex to additional stimulation is highly dynamic.