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Extreme precipitation events have a significant impact on life and property. The U.S. experiences huge economic losses due to severe floods caused by extreme precipitation. With the complex terrain of the region, it becomes increasingly important to understand the spatial variability of extreme precipitation to conduct a proper risk assessment of natural hazards such as floods. In this work, we use a complex network-based approach to identify distinct regions exhibiting spatially coherent precipitation patterns due to various underlying climate mechanisms. To quantify interactions between event series of different locations, we use a nonlinear similarity measure, called the edit-distance method, which considers not only the occurrence of the extreme events but also their intensity, while measuring similarity between two event series. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by the landfall of atmospheric rivers in addition to those where the extreme precipitation due to storm track activity is modulated by different mountain ranges such as the Rockies and the Appalachians. Our approach provides a comprehensive picture of the spatial patterns of extreme winter precipitation in the U.S. due to various climate processes despite its vast, complex topography.

Background and purpose: No previous study has assessed the frequency and clinical– radiological characteristics of patients with diabetes mellitus (DM) and acute onset non-choreic and nonballistic movements. We conducted a prospective study to investigate the spectrum of acute onset movement disorders in DM.Methods: We recruited all the patients with acute onset movement disorders and hyper-glycemia who attended the wards of three hospitals in West Bengal, India from August 2014 to July 2021.Results: Among the 59 patients (mean age = 55.4± 14.3 years, 52.5% men) who were included, 41 (69.5%) had choreic or ballistic movements, and 18 (30.5%) had nonchoreic and nonballistic movements. Ballism was the most common movement disorder (n= 18, 30.5%), followed by pure chorea (n= 15, 25.4%), choreoathetosis (n= 8, 13.6%), tremor (n= 5, 8.5%), hemifacial spasm (n= 3, 5.1%), parkinsonism (n= 3, 5.1%), myoclonus (n= 3, 5.1%), dystonia (n= 2, 3.4%), and restless leg syndrome (n= 2, 3.4%). The mean duration of DM was 9.8 ± 11.4 years (89.8% of the patients had type 2 DM). Nonketotic hypergly-cemia was frequently (76.3%) detected. The majority (55.9%) had no magnetic resonance imaging (MRI) changes; the remaining showed striatal hyperintensity. Eight patients with MRI changes exhibited discordance with sidedness of movements. Most of the patients (76.3%) recovered completely.Conclusions: This is the largest clinical series depicting the clinical–radiological spectrum of acute onset movement disorders in DM. Of note was that almost one third of patients had nonchoreic and nonballistic movements. Our findings highlight the importance of a capillary blood glucose measurement in patients with acute or subacute onset movement disorders, irrespective of their past glycemic status.

In the recent years, wireless communications are extremely useful in many disciplines including health monitoring, environment monitoring, signal processing etc. State estimation and prediction are quite challenging tasks in wireless communications. Traditionally, in the literature, dynamic state-space models have been used for the state estimation and predic- tion purpose. The estimation method is based on Kalman-Filter which is computationally demanding. In this work, we consider computationally simpler Gibbs sampler algorithm for the state estimation. We consider three different cases, (i) continuous state values, (ii) binary (0/1) state values, and (iii) categorical state values with more than two categories. We consider a simple linear model for the prediction purpose, and the underlying regression coefcients are estimated by Gibbs sampler. We compute the misclassication proportions for assessing the practical usefulness of our estimation approach. Areal dataset where 200 wireless sensor nodes are used for measuring the temperature of a chamber is analysed in this work.

Cardiac anatomy and function vary considerably across the human population with important implications for clinical diagnosis and treatment planning. Consequently, many computer-based approaches have been developed to capture this variability for a wide range of applications, including explainable cardiac disease detection and prediction, dimensionality reduction, cardiac shape analysis, and the generation of virtual heart populations. In this work, we propose a variational mesh autoencoder (mesh VAE) as a novel geometric deep learning approach to model such population-wide variations in cardiac shapes. It embeds multi-scale graph convolutions and mesh pooling layers in a hierarchical VAE framework to enable direct processing of surface mesh representations of the cardiac anatomy in an efficient manner. The proposed mesh VAE achieves low reconstruction errors on a dataset of 3D cardiac meshes from over 1,000 patients with acute myocardial infarction, with mean surface distances between input and reconstructed meshes below the underlying image resolution. We also find that it outperforms a voxelgrid-based deep learning benchmark in terms of both mean surface distance and Hausdorff distance while requiring considerably less memory. Furthermore, we explore the quality and interpretability of the mesh VAE's latent space and showcase its ability to improve the prediction of major adverse cardiac events over a clinical benchmark. Finally, we investigate the method's ability to generate realistic virtual populations of cardiac anatomies and find good alignment between the synthesized and gold standard mesh populations in terms of multiple clinical metrics.

Introduction: The COVID-19 pandemic has caused severe disruption of healthcare services worldwide and interrupted patients’ access to essential services. During the first lockdown, many healthcare services were shut to all but emergencies. In this study, we aimed to determine the immediate and long-term indirect impact of COVID-19 health services utilisation on hepatocellular cancer (HCC) outcomes. Methods A prospective cohort study was conducted from March 1, 2020, until June 30, 2020 correlating to the first wave of the COVID-19 pandemic. Patients were enrolled from tertiary hospitals in the UK and Germany with dedicated HCC management services. All patients with current or past HCC who were discussed at a multidisciplinary meeting (MDM) were identified. Any delay to treatment (DTT) and the effect on survival at 1 year were reported. Results The median time to receipt of therapy following MDM discussion was 49 days. Patients with Barcelona Clinic Liver Cancer (BCLC) stages-A/B disease were more likely to experience DTT. Significant delays across all treatments for HCC were observed but delay was most marked for those undergoing curative therapies. Even though severe delays were observed in curative HCC treatments, this did not translate in reduced survival in patients. Conclusion Interruption of routine healthcare services because of the COVID-19 pandemic caused severe delays in HCC treatment. However, DTT did not translate to reduced survival. Longer follow is important given the delay to therapy in those receiving curative therapy.

IntroductionMyelitis is the least common neuropsychiatric manifestation in systemic lupus erythematosus (SLE). Magnetic resonance imaging (MRI)-negative myelitis is even rarer. Here, we present the largest cohort of MRI-negative lupus myelitis cases to assess their clinical and immunological profiles and outcome.MethodA single-center, observational study conducted over a period of 5 years (2017–2021) was undertaken to evaluate patients with MRI-negative lupus myelitis for the epidemiological, clinical, immunological, and radiological features at baseline and followed up at monthly intervals for a year, and the outcomes were documented. Among the 22 patients that presented with MRI-negative myelopathy (clinical features suggestive of myelopathy without signal changes on spinal-cord MRI [3Tesla], performed serially at the time of presentation and 7 days, 6 weeks, and 3 months after the onset of symptoms), 8 patients had SLE and were included as the study population.ResultsIn 8 of 22 patients presenting with MRI-negative myelopathy, the etiology was SLE. MRI-negative lupus myelitis had a female preponderance (male: female ratio, 1:7). Mean age at onset of myelopathy was 30.0 ± 8.93 years, reaching nadir at 4.9 ± 4.39 weeks (Median, 3.0; range, 1.25–9.75). Clinically, cervical cord involvement was observed in 75% of patients, and 62.5% had selective tract involvement. The mean double stranded deoxyribonucleic acid, C3, and C4 titers at onset of myelopathy were 376.0 ± 342.88 IU/ml (median, 247.0), 46.1 ± 17.98 mg/dL (median, 47.5), and 7.3 ± 3.55 mg/dL (median, 9.0), respectively, with high SLE disease activity index 2,000 score of 20.6 ± 5.9. Anti-ribosomal P protein, anti-Smith antibody, and anti-ribonuclear protein positivity was observed in 87.5, 75, and 75% of the patients, respectively. On follow-up, improvement of myelopathic features with no or minimal deficit was observed in 5 of the 8 patients (62.5%). None of the patients had recurrence or new neurological deficit over 1-year follow-up.ConclusionPersistently “MRI-negative” lupus myelitis presents with white matter dysfunction, often with selective tract involvement, in light of high disease activity, which follows a monophasic course with good responsiveness to immunosuppressive therapy. A meticulous clinical evaluation and a low index of suspicion can greatly aid in the diagnosis of this rare clinical condition in lupus.

Aims: To study the effect of Vitamin D replacement on glycaemic control and pregnancy outcomes in Gestational Diabetes Mellitus patient with Vitamin D deficiency. Methods: In this prospective, open-label interventional study 60 GDM subjects with Vitamin D deficiency were divided into 2 groups of 30 each, and the intervention group received 60,000 IU of cholecalciferol weekly for 6 weeks and then monthly for the duration of pregnancy. while the control group did not. Vitamin D status was re-assessed at 32 weeks of gestation for both groups. The glycaemic status was assessed using fasting plasma glucose and 1-hour and 2-hour postprandial glucose at 30 weeks of gestation and at time of delivery. Feto-maternal outcomes: Time of delivery (weeks of gestation) , method of delivery, pre-eclampsia, still-birth, neonatal hypoglycaemia, neonatal jaundice, birth weight, head circumference of the baby, APGAR score at 5 minutes in both groups were also assessed. Results: In the intervention group 87% (26 out of 30) of subjects had become vitamin D sufficient. None of the subjects in the control group had become vitamin D sufficient. Fasting Plasma Glucose was significantly lower in the intervention group as compared to the control group) at 30 weeks of gestation (99.57±18.12 vs. 107.90±17.53 mg/dl; p=0.039) and at time of delivery (98.53±15.41 vs. 104.47±18.71mg/dl; p=0.044) . Both 1 hour and 2-hour postprandial plasma glucose (136.81±20.29 vs. 152.58±16.76; p=0.004 and 118±22.10 vs. 132.64±18.48 mg/dl; p=0.017 respectively) values were also significantly lower in the intervention group at the time of delivery. Birth weight was significantly lower in the control group as compared to the intervention group (2348.13±388.965 vs. 2778.67±270.288 gm; p=0.034) . All other neonatal parameters were similar in the two groups. Two subjects in the control group had still-births. Conclusion: Correction of Vitamin D deficiency in GDM subjects may result in better control of their plasma glucose levels. Low Vitamin D levels in GDM subjects may be associated with lower birth weight. Disclosure A. Baidya: None. P. Gaikwad: None. N. Das: None. Y. Pathak: None. N. Sengupta: None. P. Sahana: None. S. Goswami: None. S. Tarenia: None. A. Banerjee: None. M. Chattopadhayay: None. D. Hathi: None.

Background Pseudohypoparathyroidism (PHP) is a heterogeneous group of disorders in which resistance to parathyroid hormone (PTH) in the proximal renal tubules leads to hypocalcemia, hyperphosphatemia, and impaired 1,25(OH)2 vitamin D production. Clinical Case A 2-month-old child presented with history of recurrent focal seizures since last 10 days. During the first episode, the child was treated with anti- convulsant by paediatrician. Five days later she again developed focal seizures, this time the child was evaluated and serum calcium was 5.6 mg/dl (normal, 8.6-10.2 mg/dl), phosphorus 7.5 mg/dL (normal, 4. 0-7. 0 mg/dL), and magnesium 2. 0 mg/dL (normal 1.8-2.4 mg/dL). In view of symptomatic hypocalcemia, she was treated with I. V. 10% calcium gluconate and oral calcifediol (800 IU/day). The child was seizure free but still had hypocalcemia - serum calcium-6.8 mg/dl, hence the child was evaluated further- serum PTH was 561 pg/mL (normal, 9-91 pg/mL), 25-hydroxyvitamin D was 54.1 ng/mL (normal, 5-60 ng/mL), 1,25 Vit D-6.28 pg/mL (normal, 19.9-79.3pg/mL), TSH-2.69 μUI/mL (normal, 0.35-8. 00 μUI/mL), FT4 was 1.2 ug/dL (normal, 0.9-1.8 ug/dL). Physical examination was unremarkable, and there were no stigmata of AHO, rachitic rosary, or congenital malformations. EEG was normal and CT brain did not show any intraventricular haemorrhage or basal ganglia calcification. Consistent with hypocalcaemia, hyperphosphatemia, high serum PTH levels, and lack of stigmata of AHO, we considered PHP type Ib. Her parents refused further examinations, so PTH infusion and molecular analysis of the GNAS gene could not be performed. The child was discharged in good clinical condition on calcitriol 0.25 ug/day and calcium (elemental calcium 625 mg/day) supplementation. He had no further seizures and normal serum electrolyte levels till 9 months of age. European Pseudohypoparathyroidism Network (EuroPHP Network) has recently proposed a new classification system to cover all disorders of the PTH pathway. Inactivating PTH/PTH-related protein signaling disorder (iPPSD) is the new name proposed for these disorders. iPPSDs can be further divided into subtypes: iPPSD1 to iPPSD6. A minimum of one major criterion is mandatory for the clinical diagnosis of iPPSD. Applying iPPSD criteria to this case, one can observe that they all had persistent hypocalcemia and PTH resistance but no other major or minor criteria. Nevertheless, we speculate whether neonatal transient pseudohypoparathyroidism (ntPHP) could be included among iPPSDs, specifically in the group of unknown molecular defects. Conclusion To the best of our knowledge, this is the second report in which the new classification of iPPSD has been applied and the child has been diagnosed a case of ntPHP. Presentation: No date and time listed

Introduction Rathke's cleft cysts (RCC) are cystic sellar and suprasellar lesion derived from remnant of Rathke's pouch. RCC are mainly asymptomatic, but can present with headache, visual disturbance, panhypopituitarism, hypothalamic dysfunction when it enlarges causing compression to the surrounding structure. Diabetes insipidus as a presenting feature of RCC is rare. Even it presents with diabetes insipidus, it occurs more in elderly. Clinical Case A 32-year-old married female, mother of one child, having normal menstrual cycle presented with polyuria, polydipsia of recent onset. Clinical examinations was normal. Serum creatinine, potassium, calcium, plasma glucose were within normal range. Anterior pituitary hormonal evaluation was normal. Serum sodium was in the upper range of normal. Basal urine osmolality and serum osmolality were 87.49 mosm/kg (150 -1150 mOsm/kg) and 287 mOsm/kg (275 -295 mOsm/kg) respectively. Water deprivation test followed by vasopressin challenge test was done, which revealed partial central DI. Magnetic resonance imaging revealed a sellar cystic lesion hyperintense on both T1 and T2 weighted images, suggestive of rathke's cleft cyst and posterior pituitary bright spot was not visible. Tablet desmopressin 50 mcg twice daily was given and within two days patient responded well to the treatment. Urine volume reduced to 2.5 litres/day and water intake reduced to 3. 0 litres/day. Conclusion This is a rare case of Rathke's cleft cyst, presenting as diabetes insipidus as the sole manifestation in a young lady. Presentation: No date and time listed

Background & aimsPancreatic ductal adenocarcinoma (PDAC) continues to be a devastating disease with late diagnosis and poor overall survival, complicated by clinical presentations similar to benign pancreatic diseases. We aimed to analyse clinical parameters with the goal of developing a prediction model for differentiating suspected PDAC from benign pancreatic conditions.Methods and resultsWe used a prospectively recruited cohort of patients with pancreatic disease (n=762) enrolled at the Barts Pancreas Tissue Bank between January 1, 2008 and September 21, 2021 to perform a case-control study examining the association of PDAC (n=340) with predictor variables including demographics, comorbidities, lifestyle factors, presenting symptoms and commonly performed blood tests. Using a machine learning approach, candidate PDAC risk-prediction algorithms were trained on 75% of the cohort, using a subset of the predictor variables identified from a preliminary observational association study. Models were assessed on the remaining 25%. Multiple imputed datasets were used for both training and validation to accommodate for unknown data.Age (over 55), weight loss in hypertensive patients, recent symptom of jaundice, high serum bilirubin, low serum creatinine, high serum alkaline phosphatase, low lymphocyte count and low serum sodium were the most important features when separating putative PDAC cases from less severe pancreatic conditions. A simple logistic regression model had the best performance with an area under the curve (AUC) of 0.88. Setting a probability threshold of 0.17 guided by the maximum F2 score, a sensitivity of 95.6% was reached in the full cohort which could lead to early detection of around 84% of the PDAC patients.ConclusionThe resultant prediction model significantly outperformed the current UK guidelines for suspected pancreatic cancer referral and could improve detection rates of PDAC in the community. After further work this approach could lead to an easy to understand, utilisable risk score to be applied in the primary and secondary care setting for referring patients to specialist hepato-pancreatico-biliary services.

Polycystic ovary syndrome (PCOS) is an endocrinopathy common among women of reproductive age. Some women with PCOS have cysts on their ovaries. That’s why it’s called “polycystic.” But the name is misleading because many women with PCOS don’t have cysts. Women with PCOS may have infrequent or prolonged menstrual periods or excess male hormone (androgen) levels. It is characterized by anovulation, infertility, hyperandrogenism, and frequently insulin resistance. Although the role of genetic factors in PCOS is strongly supported, the genes that are involved in the etiology of the syndrome have not been fully investigated until now, as well as the environmental contribution in their expression. Some genes have shown altered expression suggesting that the genetic abnormality in PCOS affects signal transduction pathways controlling steroidogenesis, steroid hormones action, gonadotrophin action and regulation, insulin action and secretion, energy homeostasis, chronic inflammation and others. Because the primary cause of PCOS is unknown, treatment is directed at the symptoms. Insulin-sensitizing agents are indicated for most women with polycystic ovary syndrome because they have positive effects on insulin resistance, menstrual irregularities, anovulation, hirsutism, and obesity. Metformin has the most data supporting its effectiveness. Rosiglitazone and pioglitazone are also effective for ameliorating hirsutism and insulin resistance. Metformin and clomiphene, alone or in combination, are first-line agents for ovulation induction. Insulin-sensitizing agents, oral contraceptives, spironolactone, and topical eflornithine can be used in patients with hirsutism.

X-ray angiography is the most commonly used imaging modality for the detection of coronary stenoses due to its high spatial and temporal resolution of lumen contour and its utility to guide coronary interventions in real time. However, the high inter- and intra-observer variability in interpreting the geometry of 3D vascular structure based on multiple 2D image projections is a limitation in the accurate determination of lesion severity. This could be addressed by the 3D reconstruction of the coronary arterial (CA) tree. The automated reconstruction of 3D CA tree from 2D projections is challenging due to the existence of several imaging artifacts, such as vessel overlap, foreshortening, and most importantly respiratory and cardiac motion. Along with these artifacts, the acquisition geometry introduces the possibility of generating false vessel segments in the reconstruction. Our approach aims to reduce the motion artifacts in angiographic projections by developing a new method for rigid and non-rigid motion correction. A novel point-cloud based approach is subsequently introduced for reconstruction of 3D vessel centerlines by iteratively minimizing the reconstruction error. The performance of the proposed 3D reconstruction is evaluated using angiographic projections from 45 patients, producing average reprojection errors of ${0.092} \pm {0.055}$ mm and ${0.910} \pm {0.352}$ mm for 3D centerlines reconstruction, when co-registered with the parent vessels on projection planes that were/were not used to derive the 3D reconstruction, respectively. A comparison of the reconstructed 3D lumen surface with optical coherence tomography (OCT) measurements has been performed, showing no statistically significant difference in the luminal cross-sections reconstructed with our method, compared to OCT.

Extreme precipitation events have a significant impact on life and property. The United States experiences huge economic losses due to severe floods caused by extreme precipitation. With the varied terrain, it becomes increasingly important to understand the spatial variability of extreme precipitation to conduct a proper risk assessment of natural hazards such as floods. In this work, we use a complex network based approach to identify distinct regions exhibiting spatially coherent precipitation patterns due to various underlying climate mechanisms. To quantify interactions between event series of different locations, we use a nonlinear similarity measure, called the edit-distance method, which considers not only the occurrence of the extreme events but also their intensity while measuring similarity. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by landfall of atmospheric rivers in addition to those regions where the extreme precipitation due to storm track activity is modulated by different mountain ranges such as the Rockies and the Appalachians. Our approach provides a comprehensive picture of the spatial patterns of extreme winter precipitation in the United States due to various climate processes despite its vast complex topography

The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.

Introduction Preliminary data in human suggest that both Intracardiac echocardiography (ICE) and Intravascular ultrasound (IVUS) can be used for real-time information on the left atrial (LA) wall thickness and on the acute tissue changes produced by energy delivery. This pilot study was conducted to compare ICE and IVUS for real-time LA wall imaging and assessment of acute tissue changes produced by radiofrequency (RF), cryo and laser catheter ablation. Methods Patients scheduled for RF, cryoballoon or laser balloon Pulmonary Vein Isolation (PVI) catheter ablation were enrolled. Each pulmonary vein (PV) was imagedimmediately before and after ablation with either ICE or IVUS. The performance of ICE and IVUS for imaging were compared. Pre- and post-ablation measurements (lumen and vessel diameters, areas and sphericity indexes, wall thickness and muscular sleeve thickness) were taken at the level of each PV ostium.Results A total of 48 PVs in 12 patients were imaged before and after ablation. Compared to IVUS, ICE showedhigherimaging quality and inter-observer reproducibility of the PV measurements obtained. Acute wall thickening suggestive of oedema was observed after RF treatment (p = 0.003) and laser treatment (p = 0.003) but not after cryoablation (p = 0.69). Conclusions Our pilot study suggests that ICE is preferable to IVUS for LA wall thickness imaging at the LA-PV junctions during ablation. Ablation causes acute wall thickening when using RF or laser energy, but not cryoenergy delivery. Larger studies are needed to confirm these preliminary findings.

Acute myocardial infarction rapidly increases blood neutrophils (2 hours). Release from bone marrow, in response to chemokine elevation, has been considered their source, but chemokine levels peak up to 24 hours after injury, and after neutrophil elevation. This suggests that additional non-chemokine-dependent processes may be involved. Endothelial cell (EC) activation promotes the rapid (30 minutes) release of extracellular vesicles (EVs), which have emerged as an important means of cell-cell signalling and are thus a potential mechanism for communicating with remote tissues.Here, we show that injury to the myocardium rapidly mobilises neutrophils from the spleen to peripheral blood and induces their transcriptional activation prior to arrival at the injured tissue. Time course analysis of plasma EV composition revealed a rapid and selective increase in EVs bearing VCAM-1. These EVs, which were also enriched for miRNA-126, accumulated preferentially in the spleen where they induced local inflammatory gene and chemokine protein expression, and mobilised splenic-neutrophils to peripheral blood. Using CRISPR/Cas9 genome editing we generated VCAM-1-deficient EC-EVs and showed that its deletion removed the ability of EC-EVs to provoke the mobilisation of neutrophils. Furthermore, inhibition of miRNA-126 in vivo reduced myocardial infarction size in a mouse model.Our findings show a novel EV-dependent mechanism for the rapid mobilisation of neutrophils to peripheral blood from a splenic reserve and establish a proof of concept for functional manipulation of EV-communications through genetic alteration of parent cells.Peripheral blood neutrophils are rapidly elevated following acute myocardial infarction (AMI) and prior to alterations in systemic cytokines. Extracellular vesicles (EVs) are membrane enclosed particles that carry protein and miRNAs and are rapidly liberated from endothelial cells (EC). Here, we show that following AMI EC-derived-EVs (EC-EVs) mediate neutrophil mobilisation from the spleen via EC-EV-VCAM-1 and induce transcriptional activation of neutrophils in the blood to favour miRNA-126-mRNA targets; miRNA-126 antagomir treatment lowers infarct size. EC-EV-VCAM-1 and EC-EV-miRNA-126 are novel mechanisms that mobilise splenic reserve of neutrophils, a previously unidentified source of neutrophils in sterile ischaemic injury.

There have been numerous risk tools developed to enable triaging of SARS-CoV-2 positive patients with diverse levels of complexity. Here we presented a simplified risk-tool based on minimal parameters and chest X-ray (CXR) image data that predicts the survival of adult SARS-CoV-2 positive patients at hospital admission. We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS-CoV-2 positive patients, respectively. External validation of the final model was conducted on 741 Accident and Emergency (A&E) admissions with suspected SARS-CoV-2 infection from a separate NHS Trust. The LUCAS mortality score included five strongest predictors (Lymphocyte count, Urea, C-reactive protein, Age, Sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the area under the receiving operating characteristics curve (AUC-ROC) in development cohort 0.765 (95% confidence interval (CI): 0.738–0.790), in internal validation cohort 0.744 (CI: 0.673–0.808), and in external validation cohort 0.752 (CI: 0.713–0.787). The discriminatory power of LUCAS increased slightly when including the CXR image data. LUCAS can be used to obtain valid predictions of mortality in patients within 60 days of SARS-CoV-2 RT-PCR results into low, moderate, high, or very high risk of fatality.

Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Oxford Biomedical Research Centre Introduction Early evidence of pulmonary vein triggers initiating AF has led to focus on the left atrium (LA). Little work has been done to characterise the role of the right atrium (RA) in AF maintenance. Purpose To characterise the relative roles of the LA and RA in maintenance of atrial fibrillation and explore mechanisms of AF propagation. Methods Simultaneous bi-atrial mapping was carried out in patients undergoing first time catheter ablation using 2 linked non-contact charge density mapping systems to obtain 30-second recordings during AF. The predominant channel of communication between chambers was identified and the time difference across this channel measured (see figure). The proportion of signals earlier in each chamber was calculated and a dominant chamber identified if preceding the opposite chamber for ≥60% of the recording. AF was characterised in each chamber according to frequency of specific propagation patterns (localised rotational activation (LRA) and focal firing (FF)). The difference in AF characteristics in the LA and RA according to acute procedural outcome (termination with ablation vs. DCCV) was measured using 2-way ANOVA and predictors of AF termination identified using binomial logistic regression. Results Twenty-one patients were included (16 persistent AF, 5 paroxysmal AF, 11 in sinus rhythm at baseline) with 41 maps obtained prior to ablation. A dominant chamber was identified in 11 maps (in 9 patients). Of these, 5 maps (in 4 patients) were LA dominant, and 6 maps (in 5 patients) were RA dominant. The remainder showed balanced interatrial propagation. For patients with persistent AF, in the RA, those needing DCCV had more LRA than those with termination with ablation (79 activations, (95% CI 65-93) vs. 51 (30-71); p = 0.025). There was no difference in the LA in the two groups (77 vs 59, p = 0.541). There were fewer FFs in the RA vs LA in patients needing DCCV (123 (106-140) vs. 155 (137-172), p = 0.012)(see panel F). No differences in distribution of LIA were observed. The frequency of LRA (p = 0.003) and FF (p = 0.004) in the RA, and RA AFCL (p = 0.041), were predictors of acute procedural outcome. Conclusions Our novel approach of simultaneous bi-atrial mapping revealed that mechanisms responsible for AF maintenance were evenly distributed between atria whilst acute AF termination with left atrial ablation was dependent on the contribution of right atrial substrate. Strategies incorporating right atrial mechanisms may result in improved outcomes from AF ablation. Abstract Figure.

Many important cardiac biomarkers used in clinical practice describe cardiac anatomy and function in three dimensions (3D). However, common cardiac magnetic resonance imaging (MRI) protocols often only generate two-dimensional (2D) image slices of the underlying 3D anatomy and are susceptible to various types of motion artifacts causing slice misalignment. In this paper, we propose a deep learning method acting directly on point clouds to reconstruct a dense 3D biventricular heart model from misaligned 2D cardiac MR image contours. The method is able to reduce mild, medium, and strong slice misalignments (mean translation $\sim 3.5$ mm; mean rotation $\sim 2.5^{\circ})$ to a Chamfer distance below image resolution (1.25 mm) with high robustness (standard deviation 0.18 mm) on a statistical shape model dataset. It also manages to reconstruct smooth 3D shapes with accurate left ventricular volumes from cine MR images of the UK Biobank study.

Extreme events such as earthquakes, tsunamis, heat weaves, droughts, floods, heavy precipitation, or tornados -- affect the human communities and cause tremendous loss of property and wealth, but can be related to multiple and complex sources. For example, a flood is a natural event caused by many drivers such as extreme precipitation, soil moisture, or temperature. We are interested in understanding the direct and indirect coupling between flood events with different climatological and hydrological drivers such as soil moisture and temperature.We use multivariate recurrence plot and recurrence quantification analysis as a powerful framework to study the couplings between the different systems, especially the direction of coupling. The standard delay-embedding method is not a suitable for the recurrence analysis of event-like data. Therefore, we apply the novel edit-distance method to compute recurrence plots of time series of flood events and use the standard recurrence plot method for the continuous varying time series such as soil moisture and temperature. The coupling analysis is performed using the mean conditional probabilities of recurrence derived from the different recurrence plots. We demonstrate this approach on a prototype system and apply it on the hydrological data. Using this approach we are able to indicate the coupling direction and lag between the different coupled systems.

Following an unprecedented drought, Australia's 2019/2020 “Black Summer” fire season caused severe damage, gravely impacting both humans and ecosystems, and increasing susceptibility to other hazards. Heavy precipitation in early 2020 led to flooding and runoff that entrained ash and soil in burned areas, increasing sediment concentration in rivers, and reducing water quality. We exemplify this hazard cascade in a catchment in New South Wales by mapping burn severity, flood, and rainfall recurrence; estimating changes in soil erosion; and comparing them with river turbidity data. We show that following the extreme drought and wildfires, even moderate rain and floods led to undue increases in soil erosion and reductions in water quality. While natural risk analysis and planning commonly focuses on a single hazard, we emphasize the need to consider the entire hazard cascade, and highlight the impacts of ongoing climate change beyond its direct effect on wildfires.

Acute myocardial infarction rapidly increases blood neutrophils (

The identification of recurrences at various time scales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyse extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in USA, and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.

Graph-based approaches of feature selection have found their application in diverse areas owing to their efficacy to detect potential connections among the features. In this paper, we propose a hybrid graph-based approach for selecting a subset of features in the context of supervised learning. The novelty of this approach lies in the utilisation of graph-theoretic concepts of degree centrality as well as eigenvector centrality to assess the relative importance of features. Additionally, entropy-based measures have been used. The performance of the proposed approach is compared to that of the existing benchmark algorithms using publicly available datasets. The results have come out to be quite encouraging.

Microsporidia are ubiquitous fungi that may infect animals, fish, insects as well as humans. Human infection is uncommon and only seen in the immunocompromised individual. Here, we report the case of a 40-year-old known AIDS patient presented with severe myalgia and inability to walk. Investigations revealed microsporidial myositis. Her treatment was further complicated by the development of acute inflammatory demyelinating polyneuropathy (AIDP) 2 weeks later. However, treating human immunodeficiency virus, microsporidiosis, and AIDP as a consequence of immune reconstitution inflammatory syndromeconcomitantly led to clinical improvement.

Rough clustering is one of the principal research areas in data mining, machine learning, pattern recognition, and bioinformatics. Among different variants of rough clustering, rough-probabilistic clustering is a new concept introduced recently. In rough-probabilistic clustering, a class is defined as the union of two disjoint regions, namely, a crisp lower approximation region and a probabilistic boundary region. In this regard, stomped normal (SN) distribution provides a statistical modeling of the data set in rough-probabilistic clustering framework. The SN distribution models the central tendency, dispersion, and width of the lower approximation region of each class using its mean, variance, and width parameter, respectively. However, it does not take into consideration the property of kurtosis of the class distribution, which controls the concentration of values around mean and shape of the tail of data distribution. In this background, a novel probability distribution, named stomped-t (St) distribution, is introduced in the paper for rough-probabilistic clustering. The proposed probability distribution incorporates the property of kurtosis into the SN framework. The proposed St probability distribution is then integrated within the rough-probabilistic clustering framework for precise and robust clustering of the data. The efficacy of the proposed clustering algorithm is demonstrated for unsupervised data clustering and image segmentation problems, along with a comparative performance analysis with related algorithms.

The finite Gaussian mixture model is one of the most popular frameworks to model classes for probabilistic model-based image segmentation. However, the tails of the Gaussian distribution are often shorter than that required to model an image class. Also, the estimates of the class parameters in this model are affected by the pixels that are atypical of the components of the fitted Gaussian mixture model. In this regard, the paper presents a novel way to model the image as a mixture of finite number of Student’s t-distributions for image segmentation problem. The Student’s t-distribution provides a longer tailed alternative to the Gaussian distribution and gives reduced weight to the outlier observations during the parameter estimation step in finite mixture model. Incorporating the merits of Student’s t-distribution into the hidden Markov random field framework, a novel image segmentation algorithm is proposed for robust and automatic image segmentation, and the performance is demonstrated on a set of HEp-2 cell and natural images. Integrating the bias field correction step within the proposed framework, a novel simultaneous segmentation and bias field correction algorithm has also been proposed for segmentation of magnetic resonance (MR) images. The efficacy of the proposed approach, along with a comparison with related algorithms, is demonstrated on a set of real and simulated brain MR images both qualitatively and quantitatively.

Background Diabetes mellitus (DM) significantly increases mortality following myocardial infarction (MI). The underlying mechanism explaining this adverse prognosis is not completely understood. Purpose This study sought to investigate the characteristics of myocardial healing after MI in DM patients. Methods 62 recruited ST-elevation myocardial infarction (STEMI) patients (21 with DM and 41 controls) underwent acute (1–3 days post-STEMI) and 6 months (6M) follow-up cardiac magnetic resonance scans (CMR). Control cases were matched for the peak troponin levels and area at risk on the acute CMR scans. Blood samples were obtained 6, 24, 48 hours and 6 months after STEMI. Results Despite similar severity of the initial ischaemic injury, DM patients had lower myocardial salvage index (MSI) and as a result larger final infarct size at 6 months. Further segment-based analysis of the acute CMR scans showed significantly prolonged T1-mapping values in all segments including non-ischaemic myocardium in DM patients and poorer recovery of the late gadolinium enhancement (LGE) of the infarcted segments in that group. Additionally, DM patients had higher monocyte counts 24 hours post-MI (1.2±0.4x109/μl DM vs 0.88±0.3 x109/μl control, p=0.001). We found that HbA1C correlated with monocyte count measured 24 hours after STEMI (r=0.577, p=0.006, n=21). HbA1C also predicted myocardial salvage index (MSI) at 6M post STEMI in the DM patients (r=0.891, p=0.017, n=13). Conclusions DM patients presenting with STEMI have increased peripheral blood monocytosis and larger final infarct size compared with STEMI patients without DM. Poorly controlled DM predisposes to adverse cardiac remodelling after STEMI. Acknowledgement/Funding OHSRC Research Grant, National Institute for Health Research (NIHR), British Heart Foundation Centre of Excellence Oxford

Background Acute myocardial infarction (AMI) induces transcriptional activation of monocyte en route to the injured myocardium, possibly through interactions involving plasma liberated extracellular vesicles (EVs), which are enriched for proteins and microRNAs (miRNAs) post-AMI. Neutrophils are the first immune cells to arrive at sites of injury and mediate further damage to the ischaemic myocardium. Here, we describe neutrophil-deployment from the spleen in AMI and by endothelial cell (EC) derived-EVs. Methods Patients presenting AMI provided informed consent as part of the Oxford Acute Myocardial Infarction Study (OxAMI). Plasma EV were isolated by differential ultra-centrifugation (120,000g, 2 hours) followed by washing and characterised for: morphology using transmission electron microscopy (TEM), size and concentration profiling by Nanoparticle Tracking Analysis, EV markers (TSG101, ALIX, CD9, HSP70) by western blot, and miRNAs by RT-qPCR. Mouse and human EC were used in vitro to derive EC-EV under control conditions or after inflammatory stimulation with tumour necrosis factor-alpha (TNF-α) (10ng/mL) and from CRISPR-edited miRNA-126 knock-out ECs. EC-EVs were tail vein injected into wild-type mice or exposed to primary human peripheral blood neutrophils in vitro. Results Patients presenting with AMI (N=15) have significantly more plasma EV at time of injury vs a 6-month follow-up measurement (2.2-fold more, P=0.008). Plasma EVs at the time of AMI presentation correlate significantly with the extent of ischaemic injury (R=0.046, P=0.006) and plasma neutrophils (R=0.37, P=0.017). Experimental AMI in wild-type mice induced a significant increase in peripheral blood neutrophils and a simultaneous reduction in splenic-neutrophils, suggesting splenic-neutrophil deployment (P=0.004). Human plasma EV are enriched for vascular cell adhesion molecule-1 (VCAM-1) and EC-associated miR-126 post-AMI (Akbar et al 2017). miRNA-126-mRNA targets are significantly over represented when compared to neutrophil Gene Ontology terms for: degranulation (P Conclusions Neutrophil deployment from the spleen is a novel finding in acute injury and interactions with EC-EV may mediate their splenic liberation and transcriptional programming following AMI, en route to the injured myocardium. The splenic neutrophil reserve may be a novel therapeutic target in AMI to modulate the inflammatory response before recruitment of cells to sites of injury. Acknowledgement/Funding British Heart Foundation Project Grant and Centre for Research Excellence Awards (RE/13/1/30181), Nuffield Benefaction for Medicine and ISSF

Automated estimation of 3D centerlines is necessary to transform angiographic projections into accurate 3D reconstructions. Although several methods exist for 3D centerline reconstruction, most of them are sensitive to the motion in coronary arteries when images are acquired by a single-plane rotational X-ray system. The objective of the proposed method is to rectify the motion-related deformations in coronary vessels from 2D projections and subsequently achieve an optimal 3D centerline reconstruction. Rigid motion in arteries is removed by estimating the optimal rigid transformation from all projection planes. The remaining non-rigid motion at end-diastole is modelled by a radial basis function based warping of 2D centerlines. Point correspondences are then generated from all projection planes by least squares matching. The final 3D centerlines are obtained by 3D non-uniform rational basis splines fitting over generated point correspondences. Experimental analysis over 20 coronary vessel trees (12 right coronary artery: RCA and 8 left coronary artery: LCA) demonstrates that the rigid transformation is able to reduce the coronary vessel movements to 0.72 mm average, while the final 3D centerline reconstruction achieves an average rms error of 0.31 mm, when backprojected on angiographic planes.

Graphical abstractDisplay Omitted The segmentation of images into different meaningful classes is an important task for automatic image analysis technique. The finite Gaussian mixture model is one of the popular models for parametric model based image segmentation. However, the normality assumption of this model induces certain limitations as a single representative value is considered to represent each class. In this regard, the paper presents a new clustering algorithm, termed as rough-probabilistic clustering, integrating judiciously the merits of rough sets and a new probability distribution, called stomped normal (SN) distribution. The intensity distribution of a class is represented by SN distribution, where each class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of any image is modeled as a mixture of finite number of SN distributions. The expectation-maximization algorithm is used to estimate the parameters of each class. Incorporating hidden Markov random field framework into rough-probabilistic clustering, a new method is proposed for accurate and robust segmentation of images. The performance of the proposed segmentation approach, along with a comparison with related methods, is demonstrated on a set of HEp-2 cell images, and synthetic and real brain MR images for different bias fields and noise levels.

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

Aneuploidy, defined as the loss and gain of whole and part chromosomes, is a near-ubiquitous feature of cancer genomes, and has clinical relevance as a prognostic marker and potential therapeutic target. We have previously shown that in colorectal cancer (CRC), aneusomies largely occur upon the transition from benign adenoma to invasive carcinoma (Cross et al., 2018), however the temporal evolutionary dynamics that select for aneuploidy throughout CRC progression remain broadly uncharacterised. We performed multi-region genomic analysis of 755 samples from a total of 167 patients with colorectal-derived neoplastic lesions that cross-sectionally represent the distinct stages of CRC progression, and longitudinally tracked 22 individual CRC tumours through metastasis and treatment. Genetic diversity measures revealed that although adenomas exhibited low levels of aneuploidy (8.5% genome altered), they harboured high intra-tumour heterogeneity (ITH), whereas cancers had significantly higher aneuploidy (27.2% genome altered) but proportionally lower ITH (p=0.0017), indicating that progression to malignancy is through a genetic bottleneck that suppresses diversity. We generated genome-wide copy number profiles from individual CRC glands, and showed that glands from the same tumour had similar karyotypes, yet displayed ongoing instability at the single cell level. Remarkably, we found that aneuploid genomes were broadly stable in metastatic lesions, even after chemo- or targeted therapies, and in recurrences detected many years after the primary diagnosis. Computational modelling of the dynamics of aneusomy accrual during CRC progression to metastasis was consistent with stabilising selection acting to ‘trap’ cancer cell genomes on a fitness peak defined by the optimal patterns of aneuploidy. These data show that although a genetic bottleneck underlies the initial progression from adenoma to CRC, further evolution of CRC is constrained largely by stabilising selection, even through metastatic dissemination and therapeutic resistance. References Cross, W., Kovac, M., Mustonen, V., Temko, D., Davis, H., Baker, A.-M., … Tomlinson, I. P. M. (2018). The evolutionary landscape of colorectal tumorigenesis. Nature Ecology & Evolution, 2(10), 1661–1672. https://doi.org/10.1038/s41559-018-0642-z Citation Format: Salpie Nowinski, William Cross, Maximilian Mossner, George Cresswell, Abhirup Banerjee, Marc Williams, Laura Gay, Ann-Marie Baker, Binxgin Lu, Christopher Kimberley, Hayley Davis, Nik Matthews, Miangela M. Lacle, Ian P.M. Tomlinson, Marnix Jansen, Alan Watson, Chris Barnes, Nicholas A. Wright, John Bridgewater, Manuel Rodriguez-Justo, Hemant Kocher, Simon J. Leedham, Andrea Sottoriva, Trevor A. Graham. Stabilising selection causes grossly altered but stable karyotypes in metastatic colorectal cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR06.

Necrolytic Migratory Erythema Associated with Glucagonoma A 48-year-old man with newly diagnosed diabetes mellitus presented with weight loss and an erythematous rash. Evaluation showed elevated se...

Chronic pancreatitis (CP) often leads to obstruction of one or all the components of the spleno-mesenterico-portal (SMP) axis. This is often due to the ongoing inflammatory process which may lead to thrombosis of the surrounding veins. However, the inflammation also leads to progressive fibrosis and occlusion of the veins without thrombosis. This fibrosis is also responsible for the duodenal obstruction and biliary strictures associated with CP. These patients, with simple occlusion or encasement of one or a combination of components of the SMP axis, can be treated with venous stenting. Here, we present the case of a 58-year-old gentleman with portal vein occlusion and portal biliopathy secondary to CP. This patient was successfully treated with percutaneous transhepatic portal vein stenting and a subsequent surgical biliary bypass. In conclusion, portal venous obstruction in CP may be just due to local fibrosis and is amenable to treatment with a percutaneously placed portal venous stent.