Coupled CP tensor decomposition with shared and distinct components for multi-task fMRI data fusion

Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tasks in functional Magnetic Resonance Imaging (fMRI) data. Coupled matrix and tensor factorization approaches have been useful for flexible data fusion, or decomposition to extract features that can be used in multiple ways. However, existing methods do not directly recover shared and dataset-specific components, which requires post-processing steps involving additional hyperparameter selection. In this paper, we propose a tensor-based framework for multi-task fMRI data fusion, using a partially constrained canonical polyadic (CP) decomposition model. Differently from previous approaches, the proposed method directly recovers shared and dataset-specific components, leading to results that are directly interpretable. A strategy to select a highly reproducible solution to the decomposition is also proposed. We evaluate the proposed methodology on real fMRI data of three tasks, and show that the proposed method finds meaningful components that clearly identify group differences between patients with schizophrenia and healthy controls

A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis

[Abstract]: Joint blind source separation (JBSS) has wide applications in modeling latent structures across multiple related datasets. However, JBSS is computationally prohibitive with high-dimensional data, limiting the number of datasets that can be included in a tractable analysis. Furthermore, JBSS may not be effective if the data’s true latent dimensionality is not adequately modeled, where severe overparameterization may lead to poor separation and time performance. In this paper, we propose a scalable JBSS method by modeling and separating the “shared” subspace from the data. The shared subspace is defined as the subset of latent sources that exists across all datasets, represented by groups of sources that collectively form a low-rank structure. Our method first provides the efficient initialization of the independent vector analysis (IVA) with a multivariate Gaussian source prior (IVA-G) specifically designed to estimate the shared sources. Estimated sources are then evaluated regarding whether they are shared, upon which further JBSS is applied separately to the shared and non-shared sources. This provides an effective means to reduce the dimensionality of the problem, improving analyses with larger numbers of datasets. We apply our method to resting-state fMRI datasets, demonstrating that our method can achieve an excellent estimation performance with significantly reduced computational costs.The computational hardware used is part of the UMBC High Performance Computing Facility (HPCF), supported by the US NSF through the MRI and SCREMS programs (grants CNS-0821258, CNS-1228778, OAC-1726023, CNS-1920079, DMS-0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). This work was supported by the grants NIH R01 MH118695, NIH R01 MH123610, and NIH R01 AG073949. Xunta de Galicia was supported by a postdoctoral grant No. ED481B 2022/012 and the Fulbright Program, sponsored by the US Department of State.Xunta de Galicia; ED481B 2022/01

Consecutive Independence and Correlation Transform for Multimodal Data Fusion: Discovery of One-to-Many Associations in Structural and Functional Imaging Data

Brain signals can be measured using multiple imaging modalities, such as magnetic resonance imaging (MRI)-based techniques. Different modalities convey distinct yet complementary information; thus, their joint analyses can provide valuable insight into how the brain functions in both healthy and diseased conditions. Data-driven approaches have proven most useful for multimodal fusion as they minimize assumptions imposed on the data, and there are a number of methods that have been developed to uncover relationships across modalities. However, none of these methods, to the best of our knowledge, can discover “one-to-many associations”, meaning one component from one modality is linked with more than one component from another modality. However, such “one-to-many associations” are likely to exist, since the same brain region can be involved in multiple neurological processes. Additionally, most existing data fusion methods require the signal subspace order to be identical for all modalities—a severe restriction for real-world data of different modalities. Here, we propose a new fusion technique—the consecutive independence and correlation transform (C-ICT) model—which successively performs independent component analysis and independent vector analysis and is uniquely flexible in terms of the number of datasets, signal subspace order, and the opportunity to find “one-to-many associations”. We apply C-ICT to fuse diffusion MRI, structural MRI, and functional MRI datasets collected from healthy controls (HCs) and patients with schizophrenia (SZs). We identify six interpretable triplets of components, each of which consists of three associated components from the three modalities. Besides, components from these triplets that show significant group differences between the HCs and SZs are identified, which could be seen as putative biomarkers in schizophrenia

Perceptions of the Impact of Climate Change on Performance of Fish Hatcheries in Bangladesh: An Empirical Study

The impacts of climate change (CC) on all spheres of human life are evident worldwide. Fish is the premier protein source, and its production in Bangladesh is mainly dependent on hatchery-based seed production. However, hatchery productivity is disrupted every year due to CC. This study assesses the impacts of CC on fish seed production in hatcheries from the perspective of hatchery owners. A semi-structured questionnaire survey was conducted with 60 hatchery owners in five sub-districts (Trishal, Mymensingh Sadar, Gouripur, Fulbaria, and Muktagacha) of the Mymensingh district, the highest aquaculture-producing zone in Bangladesh. Characteristically, hatchery owners are middle-aged and highly educated, with over a decade of experience in fish hatchery management. Likert scale results showed that hatchery owners concur with the evidence of CC, as seen by changes in air and water temperatures, rainfall, and sunlight intensity, as well as frequent natural disasters. Regression analysis showed that erratic rainfall, high temperature, and high solar radiation significantly influenced the hatchery owners’ perceptions of CC. Principal component analysis (PCA) was used to divide the impact of CC into 12 components. Maximum variance (>70%) observed could be explained by problems related to embryonic and physiological development of fish fry, environmental changes, disease outbreaks, and poor growth of broodfish. The first PCA explained over 50% of the variances, with significantly higher factor loadings, comprising poor gonadal maturation, low hatching rate, poor egg and seed quality, low fecundity, and poor sperm quality of broodfish. The first PCA confirmed that the impacts of CC on fish hatchery operations were severe. Planting trees on the hatchery premises, aeration of brood ponds, increased water supply, and temperature control can be implemented to address the negative impacts on fish hatcheries. Further research in the laboratory and hatchery environments is needed

Assessment of Embryonic and Larval Development of Nile Tilapia under the Traditional and Re-Circulatory Thermostatic System in Relation to Climatic and Water Quality Variations

Embryonic and larval development of tilapia (Oreochromis niloticus) is very vulnerable to climate change. This study was conducted for an assessment of the embryonic and larval development of Nile tilapia in traditional hatchery and re-circulatory thermostatic systems. Daily changes in embryonic and larval development were measured through microscopic observation and image analysis in the laboratory. Climatic data and water quality parameters were measured every day using appropriate devices. Water temperature was varied with room temperature at the traditional hatchery system while it was maintained at 28.50 °C in the re-circulatory thermostatic system. A total of 200 unhatched eggs were stocked in every three trays of both systems. The egg diameters of the gastrula, segmentation, and pharyngula stages were measured at higher (2261.47 ± 81.66 µm, 2646.24 ± 17.98 µm, and 2710.90 ± 16.60 µm) in the re-circulatory thermostatic system than in the traditional hatchery system (2261.07 ± 81.52 µm, 2645.47 ± 18.24 µm, and 2710.01 ± 16.45 µm), respectively. For both systems, egg colors, egg size, black pigments, germinal ring, eye shape, tail, and heartbeat were determined through microscopic observation. Higher hatching and survival rates were found under the re-circulatory thermostatic system (95% and 97%) than under the traditional hatchery system (85% and 81%). About 6 h less hatching time was required under the re-circulatory thermostatic system than under the traditional system. At the end of 30 DAH (Days After Hatching), larval length and weight under the re-circulatory thermostatic system were found to be higher (15.736 ± 0.424 mm and 0.0528 ± 0.004 g) than under the traditional hatchery system (15.518 ± 0.415 mm and 0.050 ± 0.004 g), respectively. Larval growth patterns for both systems were found to have an exponential trend. PCA analysis revealed that two components were identified, one primarily associated with morphometric characteristics and the other with climatic and water quality parameters. These components showed that there were several interrelationships between the morphometric changes and the climatic and water quality parameters. The characteristic changes of larval development under the re-circulatory thermostatic system and the traditional hatchery system were found to be remarkably similar except for some deformities denoted under the traditional hatchery system. The changes of yolk sac, body pigmentation, dorsal and caudal fin shape, eye size, and head length and width were determined from 1 DAH to 30 DAH. After absorbing the yolk sac, ready-made feed was provided. The water temperature was varied from 30.50 °C to 35.50 °C in the traditional hatchery system. The highest air temperature and humidity were 33.87 °C and 69.94% while the lowest were 29.63 °C and 45.62%, respectively, in the traditional hatchery system. There has been no such comprehensive comparative study on hatchery production in Bangladesh, and therefore, further research might be carried out on broader aspects. This research would be highly beneficial for improving seed production at the tilapia fish hatchery level in the country

Embryonic and Larval Development of Stinging Catfish, <i>Heteropneustes fossilis</i>, in Relation to Climatic and Water Quality Parameters

In terms of hatchery-based seed production, one of the most important aquaculture species in Bangladesh is the stinging catfish (Heteropneustes fossilis). Scientific and evidence-based embryonic and larval development research on this fish species in the context of climate change is limited. This experimental study was conducted via induced breeding of stinging catfish using a conventional hatchery system, rearing the larvae in hapas placed in ponds. A series of microscopic observations using a trinocular digital microscope and an analysis of the relationship between larval growth and climate-driven water quality parameters such as temperature, pH, dissolved oxygen, total dissolved solids, alkalinity, and ammonia were performed. During embryonic development, the first cleavage was observed between 30 and 35 min of post-fertilization. Embryonic development (ranging from the 2-cell to the pre-hatching stage) took 21:00 h. Hatching occurred at 22:30 to 23:00 h after fertilization, with an average larvae length of 2.78 ± 0.04 mm. In the post-hatching stage, four pairs of tiny barbels appeared at 36:00 h, and the larvae started feeding exogenously after 72:00 h. These larvae fully absorbed their yolk sacs on the 6th day and attained an average length of 6.44 ± 0.06 mm. Aerial respiration of the larvae was investigated through naked-eye observation on the 10th day of hatching. The average length of the larvae was 32.00 ± 2.0 mm at the end of the 30-day post-hatching observation period. Bivariate correlation analysis showed significant correlations between key climatic variables and water quality parameters under hapa-based larval-rearing conditions. According to canonical correlation analysis, the first canonical function revealed the highest significant correlation between the two sets of variables (r1 = 0.791). The response variable weight of larvae (6.607) was linked to two explanatory variables: pH (0.321) and dissolved oxygen (0.265). For the second canonical correlation function, a positive correlation (0.431) was observed between the two sets of variables. Larval weight (−18.304) was observed to be linked to climatic variables, including air temperature (−0.316) and surface pressure (0.338). Results of this study reveal the subtle correlation between larval growth and water quality driven by climatic variables

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)

BJS commission on surgery and perioperative care post-COVID-19

Background: Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues experiences and published evidence. Methods: In late 2020, BJS contacted colleagues across the global surgical community and asked them to describe how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had affected their practice. In addition to this, the Commission undertook a literature review on the impact of COVID-19 on surgery and perioperative care. A thematic analysis was performed to identify the issues most frequently encountered by the correspondents, as well as the solutions and ideas suggested to address them. Results: BJS received communications for this Commission from leading clinicians and academics across a variety of surgical specialties in every inhabited continent. The responses from all over the world provided insights into multiple facets of surgical practice from a governmental level to individual clinical practice and training. Conclusion: The COVID-19 pandemic has uncovered a variety of problems in healthcare systems, including negative impacts on surgical practice. Global surgical multidisciplinary teams are working collaboratively to address research questions about the future of surgery in the post-COVID-19 era. The COVID-19 pandemic is severely damaging surgical training. The establishment of a multidisciplinary ethics committee should be encouraged at all surgical oncology centres. Innovative leadership and collaboration is vital in the post-COVID-19 era

BJS commission on surgery and perioperative care post-COVID-19

Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues' experiences and published evidence