Concurrent Learning Approach for Estimation of Pelvic Tilt from Anterior–Posterior Radiograph

Data Availability Statement: Dataset available on request from the authors.Accurate and reliable estimation of the pelvic tilt is one of the essential pre-planning factors for total hip arthroplasty to prevent common post-operative complications such as implant impingement and dislocation. Inspired by the latest advances in deep learning-based systems, our focus in this paper has been to present an innovative and accurate method for estimating the functional pelvic tilt (PT) from a standing anterior–posterior (AP) radiography image. We introduce an encoder–decoder-style network based on a concurrent learning approach called VGG-UNET (VGG embedded in U-NET), where a deep fully convolutional network known as VGG is embedded at the encoder part of an image segmentation network, i.e., U-NET. In the bottleneck of the VGG-UNET, in addition to the decoder path, we use another path utilizing light-weight convolutional and fully connected layers to combine all extracted feature maps from the final convolution layer of VGG and thus regress PT. In the test phase, we exclude the decoder path and consider only a single target task i.e., PT estimation. The absolute errors obtained using VGG-UNET, VGG, and Mask R-CNN are 3.04 ± 2.49, 3.92 ± 2.92, and 4.97 ± 3.87, respectively. It is observed that the VGG-UNET leads to a more accurate prediction with a lower standard deviation (STD). Our experimental results demonstrate that the proposed multi-task network leads to a significantly improved performance compared to the best-reported results based on cascaded networks.This research received no external funding

Consensus clustering in complex networks

The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics.Comment: 11 pages, 12 figures. Published in Scientific Report

Prognostic value of prostate circulating cells detection in prostate cancer patients: a prospective study

In clinically organ-confined prostate cancer patients, bloodstream tumour cell dissemination generally occurs, and may be enhanced by surgical prostate manipulation. To evaluate cancer-cell seeding impact upon patient recurrence-free survival, 155 patients were prospectively enrolled then followed. Here, 57 patients presented blood prostate cell shedding preoperatively and intraoperatively (group I). Of the 98 preoperatively negative patients, 53 (54%) remained negative (group II) and 45 (46%) became intraoperatively positive (group III). Median biological and clinical recurrence-free time was far shorter in group I (36.2 months, P<0.0001) than in group II (69.6 months) but did not significantly differ in group II and III (69.6 months vs 65.0). Such 5-year follow-up data show that preoperative circulating prostate cells are an independent prognosis factor of recurrence. Moreover, tumour handling induces cancer-cell seeding but surgical blood dissemination does not accelerate cancer evolution

Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing [version 2; peer review: 2 approved]

Emerging and re-emerging viruses are a global health concern. Genome sequencing as an approach for monitoring circulating viruses is currently hampered by complex and expensive methods. Untargeted, metagenomic nanopore sequencing can provide genomic information to identify pathogens, prepare for or even prevent outbreaks. SMART (Switching Mechanism at the 5' end of RNA Template) is a popular approach for RNA-Seq but most current methods rely on oligo-dT priming to target polyadenylated mRNA molecules. We have developed two random primed SMART-Seq approaches, a sequencing agnostic approach 'SMART-9N' and a version compatible rapid adapters  available from Oxford Nanopore Technologies 'Rapid SMART-9N'. The methods were developed using viral isolates, clinical samples, and compared to a gold-standard amplicon-based method. From a Zika virus isolate the SMART-9N approach recovered 10kb of the 10.8kb RNA genome in a single nanopore read. We also obtained full genome coverage at a high depth coverage using the Rapid SMART-9N, which takes only 10 minutes and costs up to 45% less than other methods. We found the limits of detection of these methods to be 6 focus forming units (FFU)/mL with 99.02% and 87.58% genome coverage for SMART-9N and Rapid SMART-9N respectively. Yellow fever virus plasma samples and SARS-CoV-2 nasopharyngeal samples previously confirmed by RT-qPCR with a broad range of Ct-values were selected for validation. Both methods produced greater genome coverage when compared to the multiplex PCR approach and we obtained the longest single read of this study (18.5 kb) with a SARS-CoV-2 clinical sample, 60% of the virus genome using the Rapid SMART-9N method. This work demonstrates that SMART-9N and Rapid SMART-9N are sensitive, low input, and long-read compatible alternatives for RNA virus detection and genome sequencing and Rapid SMART-9N improves the cost, time, and complexity of laboratory work

Mesoscopic organization reveals the constraints governing C. elegans nervous system

One of the biggest challenges in biology is to understand how activity at the cellular level of neurons, as a result of their mutual interactions, leads to the observed behavior of an organism responding to a variety of environmental stimuli. Investigating the intermediate or mesoscopic level of organization in the nervous system is a vital step towards understanding how the integration of micro-level dynamics results in macro-level functioning. In this paper, we have considered the somatic nervous system of the nematode Caenorhabditis elegans, for which the entire neuronal connectivity diagram is known. We focus on the organization of the system into modules, i.e., neuronal groups having relatively higher connection density compared to that of the overall network. We show that this mesoscopic feature cannot be explained exclusively in terms of considerations, such as optimizing for resource constraints (viz., total wiring cost) and communication efficiency (i.e., network path length). Comparison with other complex networks designed for efficient transport (of signals or resources) implies that neuronal networks form a distinct class. This suggests that the principal function of the network, viz., processing of sensory information resulting in appropriate motor response, may be playing a vital role in determining the connection topology. Using modular spectral analysis, we make explicit the intimate relation between function and structure in the nervous system. This is further brought out by identifying functionally critical neurons purely on the basis of patterns of intra- and inter-modular connections. Our study reveals how the design of the nervous system reflects several constraints, including its key functional role as a processor of information.Comment: Published version, Minor modifications, 16 pages, 9 figure

Mice do not require auditory input for the normal development of their ultrasonic vocalizations

<p>Abstract</p> <p>Background</p> <p>Transgenic mice have become an important tool to elucidate the genetic foundation of the human language faculty. While learning is an essential prerequisite for the acquisition of human speech, it is still a matter of debate whether auditory learning plays any role in the development of species-specific vocalizations in mice. To study the influence of auditory input on call development, we compared the occurrence and structure of ultrasonic vocalizations from deaf otoferlin-knockout mice, a model for human deafness DFNB9, to those of hearing wild-type and heterozygous littermates.</p> <p>Results</p> <p>We found that the occurrence and structure of ultrasonic vocalizations recorded from deaf otoferlin-knockout mice and hearing wild-type and heterozygous littermates do not differ. Isolation calls from 16 deaf and 15 hearing pups show the same ontogenetic development in terms of the usage and structure of their vocalizations as their hearing conspecifics. Similarly, adult courtship 'songs' produced by 12 deaf and 16 hearing males did not differ in the latency to call, rhythm of calling or acoustic structure.</p> <p>Conclusion</p> <p>The results indicate that auditory experience is not a prerequisite for the development of species-specific vocalizations in mice. Thus, mouse models are of only limited suitability to study the evolution of vocal learning, a crucial component in the development of human speech. Nevertheless, ultrasonic vocalizations of mice constitute a valuable readout in studies of the genetic foundations of social and communicative behavior.</p

The stellar halo of the Galaxy

Stellar halos may hold some of the best preserved fossils of the formation history of galaxies. They are a natural product of the merging processes that probably take place during the assembly of a galaxy, and hence may well be the most ubiquitous component of galaxies, independently of their Hubble type. This review focuses on our current understanding of the spatial structure, the kinematics and chemistry of halo stars in the Milky Way. In recent years, we have experienced a change in paradigm thanks to the discovery of large amounts of substructure, especially in the outer halo. I discuss the implications of the currently available observational constraints and fold them into several possible formation scenarios. Unraveling the formation of the Galactic halo will be possible in the near future through a combination of large wide field photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes. Full-resolution version available at http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd

Diabetes Is the Main Factor Accounting for Hypomagnesemia in Obese Subjects

OBJECTIVE: Type 2 diabetes (T2DM) and obesity are associated with magnesium deficiency. We aimed to determine whether the presence of type 2 diabetes and the degree of metabolic control are related to low serum magnesium levels in obese individuals. METHODS: A) Case-control study: 200 obese subjects [50 with T2DM (cases) and 150 without diabetes (controls)] prospectively recruited. B) Interventional study: the effect of bariatric surgery on serum magnesium levels was examined in a subset of 120 obese subjects (40 with type 2 diabetes and 80 without diabetes). RESULTS: Type 2 diabetic patients showed lower serum magnesium levels [0.75±0.07 vs. 0.81±0.06 mmol/L; mean difference -0.06 (95% CI -0.09 to -0.04); p<0.001] than non-diabetic patients. Forty-eight percent of diabetic subjects, but only 15% of non-diabetic subjects showed a serum magnesium concentration lower than 0.75 mmol/L. Significant negative correlations between magnesium and fasting plasma glucose, HbA1c, HOMA-IR, and BMI were detected. Multiple linear regression analysis showed that fasting plasma glucose and HbA1c independently predicted serum magnesium. After bariatric surgery serum magnesium increased only in those patients in whom diabetes was resolved, but remain unchanged in those who not, without difference in loss weight between groups. Changes in serum magnesium negatively correlated with changes in fasting plasma glucose and HbA1c. Absolute changes in HbA1c independently predicted magnesium changes in the multiple linear regression analysis. CONCLUSIONS: Our results provide evidence that the presence of diabetes and the degree of metabolic control are essential in accounting for the lower levels of magnesium that exist in obese subjects