DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images.

Breast cancer remains a critical global concern, underscoring the urgent need for early detection and accurate diagnosis to improve survival rates among women. Recent developments in deep learning have shown promising potential for computer-aided detection (CAD) systems to address this challenge. In this study, a novel segmentation method based on deep learning is designed to detect tumors in breast ultrasound images. Our proposed approach combines two powerful attention mechanisms: the novel Positional Convolutional Block Attention Module (PCBAM) and Shifted Window Attention (SWA), integrated into a Residual U-Net model. The PCBAM enhances the Convolutional Block Attention Module (CBAM) by incorporating the Positional Attention Module (PAM), thereby improving the contextual information captured by CBAM and enhancing the model's ability to capture spatial relationships within local features. Additionally, we employ SWA within the bottleneck layer of the Residual U-Net to further enhance the model's performance. To evaluate our approach, we perform experiments using two widely used datasets of breast ultrasound images and the obtained results demonstrate its capability in accurately detecting tumors. Our approach achieves state-of-the-art performance with dice score of 74.23% and 78.58% on BUSI and UDIAT datasets, respectively in segmenting the breast tumor region, showcasing its potential to help with precise tumor detection. By leveraging the power of deep learning and integrating innovative attention mechanisms, our study contributes to the ongoing efforts to improve breast cancer detection and ultimately enhance women's survival rates. The source code of our work can be found here: https://github.com/AyushRoy2001/DAUNet.

A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation.

Masi entropy is a popular criterion employed for identifying appropriate threshold values in image thresholding. However, with an increasing number of thresholds, the efficiency of Masi entropy-based multi-level thresholding algorithms becomes problematic. To overcome this, we propose a novel differential evolution (DE) algorithm as an effective population-based metaheuristic for Masi entropy-based multi-level image thresholding. Our ME-GDEAR algorithm benefits from a grouping strategy to enhance the efficacy of the algorithm for which a clustering algorithm is used to partition the current population. Then, an updating strategy is introduced to include the obtained clusters in the current population. We further improve the algorithm using attraction (towards the best individual) and repulsion (from random individuals) strategies. Extensive experiments on a set of benchmark images convincingly show ME-GDEAR to give excellent image thresholding performance, outperforming other metaheuristics in 37 out of 48 cases based on cost function evaluation, 26 of 48 cases based on feature similarity index, and 20 of 32 cases based on Dice similarity. The obtained results demonstrate that population-based metaheuristics can be successfully applied to entropy-based image thresholding and that strengthening both exploitation and exploration strategies, as performed in ME-GDEAR, is crucial for designing such an algorithm.

Enhanced nuclear protein export in premature aging and rescue of the progeria phenotype by modulation of CRM1 activity.

The study of Hutchinson-Gilford progeria syndrome (HGPS) has provided important clues to decipher mechanisms underlying aging. Progerin, a mutant lamin A, disrupts nuclear envelope structure/function, with further impairment of multiple processes that culminate in senescence. Here, we demonstrate that the nuclear protein export pathway is exacerbated in HGPS, due to progerin-driven overexpression of CRM1, thereby disturbing nucleocytoplasmic partitioning of CRM1-target proteins. Enhanced nuclear export is central in HGPS, since pharmacological inhibition of CRM1 alleviates all aging hallmarks analyzed, including senescent cellular morphology, lamin B1 downregulation, loss of heterochromatin, nuclear morphology defects, and expanded nucleoli. Exogenous overexpression of CRM1 on the other hand recapitulates the HGPS cellular phenotype in normal fibroblasts. CRM1 levels/activity increases with age in fibroblasts from healthy donors, indicating that altered nuclear export is a common hallmark of pathological and physiological aging. Collectively, our findings provide novel insights into HGPS pathophysiology, identifying CRM1 as potential therapeutic target in HGPS.

Publisher Correction: Retrograde trafficking of ß-dystroglycan from the plasma membrane to the nucleus.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

A novel bio-inspired optimization model based on Yellow Saddle Goatfish behavior.

Several species of fish live in groups to increase their foraging efficiency and reproduction rates. Such groups are considered self-organized since they can adopt different cooperative actions without the presence of an apparent leader. One of their most interesting collaborative behaviors found in fish is the hunting strategy presented by the Yellow Saddle Goatfish (Parupeneus cyclostomus). In this strategy, the complete group of fish is distributed in subpopulations to cover the whole hunting region. In each sub-population, all fish participate collectively in the hunt considering two different roles: chaser and blocker. In the hunt, a chaser fish actively tries to find the prey in a certain area whereas a blocker fish moves spatially to avoid the escape of the prey. In this paper, we develop the hunting model of Yellow Saddle Goatfish, which at some abstraction level can be characterized as a search strategy for optimization proposes. In the approach, different computational operators are designed in order to emulate this peculiar hunting behavior. With the use of this biological model, the new search strategy improves the optimization results in terms of accuracy and convergence in comparison to other popular optimization techniques. The performance of this method is tested by analyzing its results with other related evolutionary computation techniques. Several standard benchmark functions commonly used in the literature were considered to obtain optimization results. Furthermore, the proposed model is applied to solve certain engineering optimization problems. Analysis of the experimental results exhibits the efficiency, accuracy, and robustness of the proposed algorithm.

Giardipain-1, a protease secreted by Giardia duodenalis trophozoites, causes junctional, barrier and apoptotic damage in epithelial cell monolayers.

The adhesion of Giardia duodenalis trophozoites to intestinal epithelial cells allows the onset and maintenance of giardiasis. During these interactions, epithelial cells can be committed to apoptosis by enzymes secreted by the parasites, including cysteine proteases that are increasingly identified as virulence factors in parasitic protozoa. In this work, a monoclonal antibody (mAb1G3) raised against G. duodenalis surface components was found to react with a 25 kDa protein expressed in the cell surface and flagella of G. duodenalis trophozoites. When trophozoites expressing this protein were cultured with IEC-6 intestinal epithelial cell monolayers, a dynamic release of this protein was observed with mAbIG3. Proteomic analysis identified the protein as a mature cathepsin B-like (gCatB) enzyme, whose proteolytic activity, detected in zymograms, was eliminated by CatB inhibitor E-64. This protein was named giardipain-1 due to its functional papain-like features and was purified by affinity chromatography using mAbIG3. Upon exposure to the purified, mature and secreted forms of giardipain-1, IEC-6 epithelial cell monolayers displayed membrane blebbing and phosphatidylserine exposure on the outer cell surface, indicating an apoptotic process. In Madin Darby Canine Kidney (MDCK) cell monolayers, giardipain-1 leads to the appearance of pore-like regions and of gaps along cell-cell junctions, to decreased transepithelial electrical resistance (TER), caspase-3 activation and poly-ADP-ribose polymerase (PARP) fragmentation. At early times during exposure, giardipain-1 co-localized at cell-cell junctions, associated with occludin and induced the delocalization and degradation of tight junction proteins occludin and claudin-1. The damage caused to epithelial monolayers by giardipain-1 was blocked by pre-incubation with the CatB B Inhibitor E-64. Furthermore, silencing the giardipain-1 gene in trophozoites lowered the proteolytic activity of giardipain-1 and reduced the damage in IEC-6 monolayers. The damage observed appears to be specific to giardipain activity since almost no damage was observed when IEC-6 monolayers were incubated with papain, a non-related cysteine protease. Hence this study suggests that giardipain-1 triggers, in epithelial cells, degradation of cell-cell junctional components and apoptotic damage, supporting the notion of giardiapain-1 as a virulence factor of Giardia.

Quantification of the Campylobacter contamination on broiler carcasses during the slaughter of Campylobacter positive flocks in semi-industrialized slaughterhouses.

Campylobacter contamination of broiler carcasses has been little studied in semi-industrialized slaughterhouses in developing countries, where several steps are carried out manually or with limited technology. In this study, we performed quantification of the Campylobacter contamination on carcasses at four steps in the slaughter process in three Ecuadorian slaughterhouses. Therefore, 15 Campylobacter positive batches were sampled in three commercial slaughterhouses. For every batch, caecal content and five samples of breast skin were taken and examined for Campylobacter counts at the following steps: after plucking, after evisceration, after final washing and after water chilling. Slaughterhouse C was the only slaughterhouse in which Campylobacter counts increased significantly after evisceration. No significant differences were found between counts after evisceration and after final washing (P > 0.05). In all slaughterhouses, a significant reduction of Campylobacter counts (0.11 to 2.55 log10 CFU/g) was found after the chilling step. The presence of chlorine in the chilling water was associated with the highest reduction in Campylobacter counts on the carcasses. A high variability of Campylobacter counts was found within and between batches slaughtered in the same slaughterhouse. Campylobacter counts in caecal content samples were not correlated with counts on carcasses after plucking nor after evisceration.

Control of nuclear ß-dystroglycan content is crucial for the maintenance of nuclear envelope integrity and function.

ß-Dystroglycan (ß-DG) is a plasma membrane protein that has ability to target to the nuclear envelope (NE) to maintain nuclear architecture. Nevertheless, mechanisms controlling ß-DG nuclear localization and the physiological consequences of a failure of trafficking are largely unknown. We show that ß-DG has a nuclear export pathway in myoblasts that depends on the recognition of a nuclear export signal located in its transmembrane domain, by CRM1. Remarkably, NES mutations forced ß-DG nuclear accumulation resulting in mislocalization and decreased levels of emerin and lamin B1 and disruption of various nuclear processes in which emerin (centrosome-nucleus linkage and ß-catenin transcriptional activity) and lamin B1 (cell cycle progression and nucleoli structure) are critically involved. In addition to nuclear export, the lifespan of nuclear ß-DG is restricted by its nuclear proteasomal degradation. Collectively our data show that control of nuclear ß-DG content by the combination of CRM1 nuclear export and nuclear proteasome pathways is physiologically relevant to preserve proper NE structure and activity.

Retrograde trafficking of ß-dystroglycan from the plasma membrane to the nucleus.

ß-Dystroglycan (ß-DG) is a transmembrane protein with critical roles in cell adhesion, cytoskeleton remodeling and nuclear architecture. This functional diversity is attributed to the ability of ß-DG to target to, and conform specific protein assemblies at the plasma membrane (PM) and nuclear envelope (NE). Although a classical NLS and importin α/ß mediated nuclear import pathway has already been described for ß-DG, the intracellular trafficking route by which ß-DG reaches the nucleus is unknown. In this study, we demonstrated that ß-DG undergoes retrograde intracellular trafficking from the PM to the nucleus via the endosome-ER network. Furthermore, we provided evidence indicating that the translocon complex Sec61 mediates the release of ß-DG from the ER membrane, making it accessible for importins and nuclear import. Finally, we show that phosphorylation of ß-DG at Tyr890 is a key stimulus for ß-DG nuclear translocation. Collectively our data describe the retrograde intracellular trafficking route that ß-DG follows from PM to the nucleus. This dual role for a cell adhesion receptor permits the cell to functionally connect the PM with the nucleus and represents to our knowledge the first example of a cell adhesion receptor exhibiting retrograde nuclear trafficking and having dual roles in PM and NE.

Prevalence, antimicrobial resistance and genetic diversity of Campylobacter coli and Campylobacter jejuni in Ecuadorian broilers at slaughter age.

Thermotolerant Campylobacter spp. are a major cause of foodborne gastrointestinal infections worldwide. The linkage of human campylobacteriosis and poultry has been widely described. In this study we aimed to investigate the prevalence, antimicrobial resistance and genetic diversity of C. coli and C. jejuni in broilers from Ecuador. Caecal content from 379 randomly selected broiler batches originating from 115 farms were collected from 6 slaughterhouses located in the province of Pichincha during 1 year. Microbiological isolation was performed by direct plating on mCCDA agar. Identification of Campylobacter species was done by PCR. Minimum inhibitory concentration (MIC) values for gentamicin, ciprofloxacin, nalidixic acid, tetracycline, streptomycin, and erythromycin were obtained. Genetic variation was assessed by RFLP-flaA typing and Multilocus Sequence Typing (MLST) of selected isolates. Prevalence at batch level was 64.1%. Of the positive batches 68.7% were positive for C. coli, 18.9% for C. jejuni, and 12.4% for C. coli and C. jejuni. Resistance rates above 67% were shown for tetracycline, ciprofloxacin, and nalidixic acid. The resistance pattern tetracycline, ciprofloxin, and nalidixic acid was the dominant one in both Campylobacter species. RFLP-flaA typing analysis showed that C. coli and C. jejuni strains belonged to 38 and 26 profiles respectively. On the other hand MLST typing revealed that C. coli except one strain belonged to CC-828, while C. jejuni except 2 strains belonged to 12 assigned clonal complexes (CCs). Furthermore 4 new sequence types (STs) for both species were described, whereby 2 new STs for C. coli were based on new allele sequences. Further research is necessary to estimate the impact of the slaughter of Campylobacter positive broiler batches on the contamination level of carcasses in slaughterhouses and at retail in Ecuador.

A Multiobjective Approach to Homography Estimation.

In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data. A method to find such estimation is the random sampling consensus (RANSAC); in this, the goal is to maximize the number of matching points given a permissible error (Pe), according to a candidate model. However, those objectives are in conflict: a low Pe value increases the accuracy of the model but degrades its generalization ability that refers to the number of matching points that tolerate noisy data, whereas a high Pe value improves the noise tolerance of the model but adversely drives the process to false detections. This work considers the estimation process as a multiobjective optimization problem that seeks to maximize the number of matching points whereas Pe is simultaneously minimized. In order to solve the multiobjective formulation, two different evolutionary algorithms have been explored: the Nondominated Sorting Genetic Algorithm II (NSGA-II) and the Nondominated Sorting Differential Evolution (NSDE). Results considering acknowledged quality measures among original and transformed images over a well-known image benchmark show superior performance of the proposal than Random Sample Consensus algorithm.

Localization of α-Dystrobrevin in Cajal Bodies and Nucleoli: A New Role for α-Dystrobrevin in the Structure/Stability of the Nucleolus.

α-Dystrobrevin (α-DB) is a cytoplasmic component of the dystrophin-associated complex involved in cell signaling; however, its recently revealed nuclear localization implies a role for this protein in the nucleus. Consistent with this, we demonstrated, in a previous work that α-DB1 isoform associates with the nuclear lamin to maintain nuclei morphology. In this study, we show the distribution of the α-DB2 isoform in different subnuclear compartments of N1E115 neuronal cells, including nucleoli and Cajal bodies, where it colocalizes with B23/nucleophosmin and Nopp140 and with coilin, respectively. Recovery in a pure nucleoli fraction undoubtedly confirms the presence of α-DB2 in the nucleolus. α-DB2 redistributes in a similar fashion to that of fibrillarin and Nopp140 upon actinomycin-mediated disruption of nucleoli and to that of coilin after disorganization of Cajal bodies through ultraviolet-irradiation, with relocalization of the proteins to the corresponding reassembled structures after cessation of the insults, which implies α-DB2 in the plasticity of these nuclear bodies. That localization of α-DB2 in the nucleolus is physiologically relevant is demonstrated by the fact that downregulation of α-DB2 resulted in both altered nucleoli structure and decreased levels of B23/nucleophosmin, fibrillarin, and Nopp140. Since α-DB2 interacts with B23/nucleophosmin and overexpression of the latter protein favors nucleolar accumulation of α-DB2, it appears that targeting of α-DB2 to the nucleolus is dependent on B23/nucleophosmin. In conclusion, we show for the first time localization of α-DB2 in nucleoli and Cajal bodies and provide evidence that α-DB2 is involved in the structure of nucleoli and might modulate nucleolar functions.

An improved computer vision method for white blood cells detection.

The automatic detection of white blood cells (WBCs) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and computer vision alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elements. This paper presents an algorithm for the automatic detection of WBC embedded in complicated and cluttered smear images that considers the complete process as a multiellipse detection problem. The approach, which is based on the differential evolution (DE) algorithm, transforms the detection task into an optimization problem whose individuals represent candidate ellipses. An objective function evaluates if such candidate ellipses are actually present in the edge map of the smear image. Guided by the values of such function, the set of encoded candidate ellipses (individuals) are evolved using the DE algorithm so that they can fit into the WBCs which are enclosed within the edge map of the smear image. Experimental results from white blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique in terms of its accuracy and robustness.

White blood cell segmentation by circle detection using electromagnetism-like optimization.

Medical imaging is a relevant field of application of image processing algorithms. In particular, the analysis of white blood cell (WBC) images has engaged researchers from fields of medicine and computer vision alike. Since WBCs can be approximated by a quasicircular form, a circular detector algorithm may be successfully applied. This paper presents an algorithm for the automatic detection of white blood cells embedded into complicated and cluttered smear images that considers the complete process as a circle detection problem. The approach is based on a nature-inspired technique called the electromagnetism-like optimization (EMO) algorithm which is a heuristic method that follows electromagnetism principles for solving complex optimization problems. The proposed approach uses an objective function which measures the resemblance of a candidate circle to an actual WBC. Guided by the values of such objective function, the set of encoded candidate circles are evolved by using EMO, so that they can fit into the actual blood cells contained in the edge map of the image. Experimental results from blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique regarding detection, robustness, and stability.