Single-Pixel Image Reconstruction Based on Block Compressive Sensing and Deep Learning

Single-pixel imaging (SPI) is a novel imaging technique whose working principle is based on the compressive sensing (CS) theory. In SPI, data is obtained through a series of compressive measurements and the corresponding image is reconstructed. Typically, the reconstruction algorithm such as basis pursuit relies on the sparsity assumption in images. However, recent advances in deep learning have found its uses in reconstructing CS images. Despite showing a promising result in simulations, it is often unclear how such an algorithm can be implemented in an actual SPI setup. In this paper, we demonstrate the use of deep learning on the reconstruction of SPI images in conjunction with block compressive sensing (BCS). We also proposed a novel reconstruction model based on convolutional neural networks that outperforms other competitive CS reconstruction algorithms. Besides, by incorporating BCS in our deep learning model, we were able to reconstruct images of any size above a certain smallest image size. In addition, we show that our model is capable of reconstructing images obtained from an SPI setup while being priorly trained on natural images, which can be vastly different from the SPI images. This opens up opportunity for the feasibility of pretrained deep learning models for CS reconstructions of images from various domain areas

Automated Pavement Crack Segmentation Using U-Net-based Convolutional Neural Network

Automated pavement crack image segmentation is challenging because of inherent irregular patterns, lighting conditions, and noise in images. Conventional approaches require a substantial amount of feature engineering to differentiate crack regions from non-affected regions. In this paper, we propose a deep learning technique based on a convolutional neural network to perform segmentation tasks on pavement crack images. Our approach requires minimal feature engineering compared to other machine learning techniques. We propose a U-Net-based network architecture in which we replace the encoder with a pretrained ResNet-34 neural network. We use a "one-cycle" training schedule based on cyclical learning rates to speed up the convergence. Our method achieves an F1 score of 96% on the CFD dataset and 73% on the Crack500 dataset, outperforming other algorithms tested on these datasets. We perform ablation studies on various techniques that helped us get marginal performance boosts, i.e., the addition of spatial and channel squeeze and excitation (SCSE) modules, training with gradually increasing image sizes, and training various neural network layers with different learning rates.Comment: Accepted for publication in IEEE Acces

Incorporation of dUTP does not mediate mutation of A:T base pairs in Ig genes in vivo

Activation-induced cytidine deaminase (AID) protein initiates Ig gene mutation by deaminating cytosines, converting them into uracils. Excision of AID-induced uracils by uracil-N-glycosylase is responsible for most transversion mutations at G:C base pairs. On the other hand, processing of AID-induced G:U mismatches by mismatch repair factors is responsible for most mutation at Ig A:T base pairs. Why mismatch processing should be error prone is unknown. One theory proposes that long patch excision in G1-phase leads to dUTP-incorporation opposite adenines as a result of the higher G1-phase ratio of nuclear dUTP to dTTP. Subsequent base excision at the A:U base pairs produced could then create non-instructional templates leading to permanent mutations at A:T base pairs (1). This compelling theory has remained untested. We have developed a method to rapidly modify DNA repair pathways in mutating mouse B cells in vivo by transducing Ig knock-in splenic mouse B cells with GFP-tagged retroviruses, then adoptively transferring GFP+ cells, along with appropriate antigen, into primed congenic hosts. We have used this method to show that dUTP-incorporation is unlikely to be the cause of AID-induced mutation of A:T base pairs, and instead propose that A:T mutations might arise as an indirect consequence of nucleotide paucity during AID-induced DNA repair

DNA-Dependent Protein Kinase Inhibits AID-Induced Antibody Gene Conversion

Affinity maturation and class switching of antibodies requires activation-induced cytidine deaminase (AID)-dependent hypermutation of Ig V(D)J rearrangements and Ig S regions, respectively, in activated B cells. AID deaminates deoxycytidine bases in Ig genes, converting them into deoxyuridines. In V(D)J regions, subsequent excision of the deaminated bases by uracil-DNA glycosylase, or by mismatch repair, leads to further point mutation or gene conversion, depending on the species. In Ig S regions, nicking at the abasic sites produced by AID and uracil-DNA glycosylases results in staggered double-strand breaks, whose repair by nonhomologous end joining mediates Ig class switching. We have tested whether nonhomologous end joining also plays a role in V(D)J hypermutation using chicken DT40 cells deficient for Ku70 or the DNA-dependent protein kinase catalytic subunit (DNA-PKcs). Inactivation of the Ku70 or DNA-PKcs genes in DT40 cells elevated the rate of AID-induced gene conversion as much as 5-fold. Furthermore, DNA-PKcs-deficiency appeared to reduce point mutation. The data provide strong evidence that double-strand DNA ends capable of recruiting the DNA-dependent protein kinase complex are important intermediates in Ig V gene conversion

Delayed Onset of a Daytime Nap Facilitates Retention of Declarative Memory

BACKGROUND: Learning followed by a period of sleep, even as little as a nap, promotes memory consolidation. It is now generally recognized that sleep facilitates the stabilization of information acquired prior to sleep. However, the temporal nature of the effect of sleep on retention of declarative memory is yet to be understood. We examined the impact of a delayed nap onset on the recognition of neutral pictorial stimuli with an added spatial component. METHODOLOGY/PRINCIPAL FINDINGS: Participants completed an initial study session involving 150 neutral pictures of people, places, and objects. Immediately following the picture presentation, participants were asked to make recognition judgments on a subset of "old", previously seen, pictures versus intermixed "new" pictures. Participants were then divided into one of four groups who either took a 90-minute nap immediately, 2 hours, or 4 hours after learning, or remained awake for the duration of the experiment. 6 hours after initial learning, participants were again tested on the remaining "old" pictures, with "new" pictures intermixed. CONCLUSIONS/SIGNIFICANCE: Interestingly, we found a stabilizing benefit of sleep on the memory trace reflected as a significant negative correlation between the average time elapsed before napping and decline in performance from test to retest (p = .001). We found a significant interaction between the groups and their performance from test to retest (p = .010), with the 4-hour delay group performing significantly better than both those who slept immediately and those who remained awake (p = .044, p = .010, respectively). Analysis of sleep data revealed a significant positive correlation between amount of slow wave sleep (SWS) achieved and length of the delay before sleep onset (p = .048). The findings add to the understanding of memory processing in humans, suggesting that factors such as waking processing and homeostatic increases in need for sleep over time modulate the importance of sleep to consolidation of neutral declarative memories

Mechanical Strain Regulates Osteoblast Proliferation through Integrin-Mediated ERK Activation

Mechanical strain plays a critical role in the proliferation, differentiation and maturation of bone cells. As mechanical receptor cells, osteoblasts perceive and respond to stress force, such as those associated with compression, strain and shear stress. However, the underlying molecular mechanisms of this process remain unclear. Using a four-point bending device, mouse MC3T3-E1 cells was exposed to mechanical tensile strain. Cell proliferation was determined to be most efficient when stimulated once a day by mechanical strain at a frequency of 0.5 Hz and intensities of 2500 µε with once a day, and a periodicity of 1 h/day for 3 days. The applied mechanical strain resulted in the altered expression of 1992 genes, 41 of which are involved in the mitogen-activated protein kinase (MAPK) signaling pathway. Activation of ERK by mechanical strain promoted cell proliferation and inactivation of ERK by PD98059 suppressed proliferation, confirming that ERK plays an important role in the response to mechanical strain. Furthermore, the membrane-associated receptors integrin β1 and integrin β5 were determined to regulate ERK activity and the proliferation of mechanical strain-treated MC3T3-E1 cells in opposite ways. The knockdown of integrin β1 led to the inhibition of ERK activity and cell proliferation, whereas the knockdown of integrin β5 led to the enhancement of both processes. This study proposes a novel mechanism by which mechanical strain regulates bone growth and remodeling

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio