Genome sequencing of pancreatic cancer: differential expression by location

The results demonstrated that pancreatic ductal carcinoma (PDAC) of the body/tail was associated with more transcriptional and genomic changes, and correlated with worse prognosis, than PDAC of the pancreatic head. The different mutation types and gene expression of tumour locations provide deep insight into the carcinogenesis or metastasis of PDAC, and suggest different early diagnostic and therapeutic strategies. SNV, single-nucleotide variations; NLS, Nuclear localization sequence; MB, million base-pairs; UTR, untranslated region.

Mitochondrial Chaperones and Proteases in Cardiomyocytes and Heart Failure

Heart failure is one of the leading causes of morbidity and mortality worldwide. In cardiomyocytes, mitochondria are not only essential organelles providing more than 90% of the ATP necessary for contraction, but they also play critical roles in regulating intracellular Ca²⁺ signaling, lipid metabolism, production of reactive oxygen species (ROS), and apoptosis. Because mitochondrial DNA only encodes 13 proteins, most mitochondrial proteins are nuclear DNA-encoded, synthesized, and transported from the cytoplasm, refolded in the matrix to function alone or as a part of a complex, and degraded if damaged or incorrectly folded. Mitochondria possess a set of endogenous chaperones and proteases to maintain mitochondrial protein homeostasis. Perturbation of mitochondrial protein homeostasis usually precedes disruption of the whole mitochondrial quality control system and is recognized as one of the hallmarks of cardiomyocyte dysfunction and death. In this review, we focus on mitochondrial chaperones and proteases and summarize recent advances in understanding how these proteins are involved in the initiation and progression of heart failure.

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

We present the first joint analysis of cluster abundances and auto or cross-correlations of three cosmic tracer fields: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis (4×2pt+N) of cluster abundances, three cluster cross-correlations, and the auto correlations of the galaxy density measured from the first year data of the Dark Energy Survey, we obtain Ω_{m}=0.305_{-0.038}^{+0.055} and σ_{8}=0.783_{-0.054}^{+0.064}. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat νΛCDM model. Consequently, we combine cluster abundances and all two-point correlations from across all three cosmic tracer fields (6×2pt+N) and find improved constraints on cosmological parameters as well as on the cluster observable-mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multiprobe analyses of upcoming wide imaging surveys.

Histone Lysine Methyltransferase SETD2 Regulates Coronary Vascular Development in Embryonic Mouse Hearts

Congenital heart defects are the most common birth defect and have a clear genetic component, yet genomic structural variations or gene mutations account for only a third of the cases. Epigenomic dynamics during human heart organogenesis thus may play a critical role in regulating heart development. However, it is unclear how histone mark H3K36me3 acts on heart development. Here we report that histone-lysine N-methyltransferase SETD2, an H3K36me3 methyltransferase, is a crucial regulator of the mouse heart epigenome. Setd2 is highly expressed in embryonic stages and accounts for a predominate role of H3K36me3 in the heart. Loss of Setd2 in cardiac progenitors results in obvious coronary vascular defects and ventricular non-compaction, leading to fetus lethality in mid-gestation, without affecting peripheral blood vessel, yolk sac, and placenta formation. Furthermore, deletion of Setd2 dramatically decreased H3K36me3 level and impacted the transcriptional landscape of key cardiac-related genes, including Rspo3 and Flrt2. Taken together, our results strongly suggest that SETD2 plays a primary role in H3K36me3 and is critical for coronary vascular formation and heart development in mice.

Tobacco smoking confers risk for severe COVID-19 unexplainable by pulmonary imaging

BACKGROUND

COVID-19 is a new pneumonia. It has been hypothesized that tobacco smoking history may increase severity of this disease in the patients once infected by the underlying coronavirus SARS-CoV-2 because smoking and COVID-19 both cause lung damage. However, this hypothesis has not been tested.

OBJECTIVE

Current study was designed to focus on smoking history in patients with COVID-19 and test this hypothesis that tobacco smoking history increases risk for severe COVID-19 by damaging the lungs.

METHODS AND RESULTS

This was a single-site, retrospective case series study of clinical associations, between epidemiological findings and clinical manifestations, radiographical or laboratory results. In our well-characterized cohort of 954 patients including 56 with tobacco smoking history, smoking history increased the risk for severe COVID-19 with an odds ratio (OR) of 5.5 (95% CI: 3.1-9.9; P = 7.3 × 10^-8 ). Meta-analysis of ten cohorts for 2891 patients together obtained an OR of 2.5 (95% CI: 1.9-3.3; P < 0.00001). Semi-quantitative analysis of lung images for each of five lobes revealed a significant difference in neither lung damage at first examination nor dynamics of the lung damage at different time-points of examinations between the smoking and nonsmoking groups. No significant differences were found either in laboratory results including D-dimer and C-reactive protein levels except different covariances for density of the immune cells lymphocyte (P = 3.8 × 10^-64 ) and neutrophil (P = 3.9 × 10^-46 ).

CONCLUSION

Tobacco smoking history increases the risk for great severity of COVID-19 but this risk is achieved unlikely by affecting the lungs.

An image-based approach for quantitative assessment of uniformity in particle distribution of noise reduction material

Under the background of noise pollution caused by railway development, noise reduction material is worthy of in-depth study. A uniform distribution of particles in the material has an important influence on sound absorption property. In this article, the relevant image processing technology is applied to get structure information to quantify the uniformity. The main contributions of this study are: (a) In the preprocessing stage, SEM cross-sectional image of material is processed by mean filter and histogram equalization. Therefore, the grayscale and the contrast between target and background are enhanced, and a low-quality image is transformed into a high-quality one. (b) In the locating stage, local details of the image are considered to discriminate each particle from the whole image. When a global threshold is combined with the local iteration threshold, an improved Otsu algorithm is designed to binarize the image. Through morphology transforming, area filtering, and hole filling, the connected domain of target can be found and particles are located. (c) In the assessing stage, area index, number index and local distance index are established for assessing the uniformity of pore distribution. The experimental results indicate that statistical analysis is consistent with human visual observation. The smaller the porosity is, the better the uniformity is. Compared with some important methods, the effectiveness and efficiency of the proposed approach could be illustrated.

Atypical protein kinase C is essential for embryonic vascular development in mice

The atypical PKC (aPKC) subfamily constitutes PKCζ and PKCλ in mice, and both aPKC isoforms have been proposed to be involved in regulating various endothelial cell (EC) functions. However, the physiological function of aPKC in ECs during embryonic development has not been well understood. To address this question, we utilized Tie2-Cre to delete PKCλ alone (PKCλ-SKO) or both PKCλ and PKCζ (DKO) in ECs, and found that all DKO mice died at around the embryonic day 11.5 (E11.5), whereas a small proportion of PKCλ-SKO mice survived till birth. PKCλ-SKO embryos also exhibited less phenotypic severity than DKO embryos at E10.5 and E11.5, suggesting a potential compensatory role of PKCζ for PKCλ in embryonic ECs. We then focused on DKO embryos and investigated the effects of aPKC deficiency on embryonic vascular development. At E9.5, deletion of both aPKC isoforms reduced the diameters of vitelline artery and vein, and decreased branching from both vitelline vessels in yolk sac. Ablation of both aPKC isoforms also disrupted embryonic angiogenesis in head and trunk at the same stage, increasing apoptosis of both ECs and non-ECs. Taken together, our results demonstrated that aPKC in ECs plays an essential role in regulating cell apoptosis, angiogenesis, and embryonic survival.

Emerging Evidence for Neuropsycho-Consequences of COVID-19

The pandemic novel coronavirus disease (COVID-19) has become a global concern in which the respiratory system is not the only one involved. Previous researches have presented the common clinical manifestations including respiratory symptoms (i.e., fever and cough), fatigue and myalgia. However, there is limited evidence for neurological and psychological influences of SARS-CoV-2. In this review, we discuss the common neurological manifestations of COVID-19 including acute cerebrovascular disease (i.e., cerebral hemorrhage) and muscle ache. Possible viral transmission to the nervous system may occur via circulation, an upper nasal transcribrial route and/or conjunctival route. Moreover, we cannot ignore the psychological influence on the public, medical staff and confirmed patients. Dealing with public psychological barriers and performing psychological crisis intervention are an important part of public health interventions.

Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy

Objective: Intractable epilepsy and uncontrolled seizures could affect cardiac function and the autonomic nerve system with a negative impact on children's growth. The aim of this study was to investigate the variability and complexity of cardiac autonomic function in pre-school children with pediatric intractable epilepsy (PIE). Methods: Twenty four-hour Holter electrocardiograms (ECGs) from 93 patients and 46 healthy control subjects aged 3-6 years were analyzed by the methods of traditional heart rate variability (HRV), multiscale entropy (MSE), and Kurths-Wessel symbolization entropy (KWSE). Receiver operating characteristic (ROC) curve analysis was used to estimate the overall discrimination ability. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) models were also analyzed. Results: Pre-school children with PIE had significantly lower HRV measurements than healthy controls in time (Mean_RR, SDRR, RMSSD, pNN50) and frequency (VLF, LF, HF, LF/HF, TP) domains. For the MSE analysis, area 1_5 in awake state was lower, and areas 6_15 and 6_20 in sleep state were higher in PIE with a significant statistical difference. KWSE in the PIE group was also inferior to that in healthy controls. In ROC curve analysis, pNN50 had the greatest discriminatory power for PIE. Based on both NRI and IDI models, the combination of MSE indices (wake: area1_5 and sleep: area6_20) and KWSE (m = 2, τ = 1, α = 0.16) with traditional HRV measures had greater discriminatory power than any of the single HRV measures. Significance: Impaired HRV and complexity were found in pre-school children with PIE. HRV, MSE, and KWSE could discriminate patients with PIE from subjects with normal cardiac complexity. These findings suggested that the MSE and KWSE methods may be helpful for assessing and understanding heart rate dynamics in younger children with epilepsy.

Mild manifestations of COVID-19 in healthcare workers

Medical staff treating Coronavirus Disease 2019 (COVID-19) patients are at high risk for exposure to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and many have been infected, which may cause panic among medical workers, their relatives, health professionals, and government leaders. We report the epidemiologic and clinical characteristics of healthcare workers and that the majority of infected medical staff had milder symptoms/conditions with a better prognosis than admitted patients. Timely improvement to medical staff’s working conditions such as allowing adequate rest and providing sufficient medical protection is extremely important.

Dynamic Changes in the Gut Microbiome at the Acute Stage of Ischemic Stroke in a Pig Model

Stroke is a major cause of death and long-term disability affecting seven million adults in the United States each year. Recently, it has been demonstrated that neurological diseases, associated pathology, and susceptibility changes correlated with changes in the gut microbiota. However, changes in the microbial community in stroke has not been well characterized. The acute stage of stroke is a critical period for assessing injury severity, therapeutic intervention, and clinical prognosis. We investigated the changes in the gut microbiota composition and diversity using a middle cerebral artery (MCA) occlusion ischemic stroke pig model. Ischemic stroke was induced by cauterization of the MCA in pigs. Blood samples were collected prestroke and 4 h, 12 h, 1 day, and 5 days poststroke to evaluate circulating proinflammatory cytokines. Fecal samples were collected prestroke and 1, 3, and 5 days poststroke to assess gut microbiome changes. Results showed elevated systemic inflammation with increased plasma levels of tumor necrosis factor alpha at 4 h and interleukin-6 at 12 h poststroke, relative to prestroke. Microbial diversity and evenness were reduced at 1 day poststroke compared to prestroke. Microbial diversity at 3 days poststroke was negatively correlated with lesion volume. Moreover, beta-diversity analysis revealed trending overall differences over time, with the most significant changes in microbial patterns observed between prestroke and 3 days poststroke. Abundance of the Proteobacteria was significantly increased, while Firmicutes decreased at 3 days poststroke, compared to prestroke populations. Abundance of the lactic acid bacteria Lactobacillus was reduced at 3 days poststroke. By day 5, the microbial pattern returned to similar values as prestroke, suggesting the plasticity of gut microbiome in an acute period of stroke in a pig model. These findings provide a basis for characterizing gut microbial changes during the acute stage of stroke, which can be used to assess stroke pathology and the potential development of therapeutic targets.

[Investigation of 603 medical staff occupational exposure with blood-borne pathogens]

Objective: To investigate the occupational exposure with blood-borne pathogens of medical staff, and explore the protective strategy. Methods: Using cluster sampling method, 603 medical staff with occupational exposure with blood-borne pathogens were analyzed, from July 2014 to July 2018 in a tertiary hospital. Results: In total of 603 occupational exposure incidents, 70.98% (428/603) were freshmen younger than 30 years old. 48.92% (295/603) nurses. The most cases of occupational exposure were in surgery (35.16%, 212/603) . Sharp injury was the major contact manner (86.90%, 524/603) . Hands were the main contact parts (90.38%, 545/603) . Ward (53.57%, 323/603) and the operating room (22.72%, 137/603) were the high-risk place. The most dangerous actions were needle injection (34.83%, 210/603) , surgery (20.89%, 126/603) and finishing/cleaning items (19.73%, 119/603) . The main items lead to injuries were scalp needles (34.73%, 182/524) . The most exposure source was hepatitis B virus (HBV) which occupied 39.30% (237/603) . Exposure source mainly comes from medical devices containing blood (81.92%, 494/603) . To compared the groups (χ(2)=19.940, P<0.01) and titer (t=-8.592, P<0.01) of hepatitis B surface antibody (HBsAb) before and after used prophylactics, the differences were statistically significant. Conclusion: Comprehensive strategies of occupational exposure protection education, operation norms and monitoring management were effective methods to reduce the occupational exposure in the medical staff with blood-borne pathogens.

Multi-Organ Segmentation Over Partially Labeled Datasets With Multi-Scale Feature Abstraction

Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation. In this paper, we propose a unified training strategy that enables a novel multi-scale deep neural network to be trained on multiple partially labeled datasets for multi-organ segmentation. In addition, a new network architecture for multi-scale feature abstraction is proposed to integrate pyramid input and feature analysis into a U-shape pyramid structure. To bridge the semantic gap caused by directly merging features from different scales, an equal convolutional depth mechanism is introduced. Furthermore, we employ a deep supervision mechanism to refine the outputs in different scales. To fully leverage the segmentation features from all the scales, we design an adaptive weighting layer to fuse the outputs in an automatic fashion. All these mechanisms together are integrated into a Pyramid Input Pyramid Output Feature Abstraction Network (PIPO-FAN). Our proposed method was evaluated on four publicly available datasets, including BTCV, LiTS, KiTS and Spleen, where very promising performance has been achieved. The source code of this work is publicly shared at https://github.com/DIAL-RPI/PIPO-FAN to facilitate others to reproduce the work and build their own models using the introduced mechanisms.

Increased expression of CXCL2 in ACPA-positive rheumatoid arthritis and its role in osteoclastogenesis

Anti-citrullinated protein/peptide antibodies (ACPA) play important roles in the pathogenesis of rheumatoid arthritis (RA). ACPA-positive (ACPA⁺ ) and ACPA-negative (ACPA^- ) RA were suggested to be different disease subsets, with distinct differences in genetic variation and clinical outcomes. The aims of the present study were to compare gene expression profiles in ACPA⁺ and ACPA^- RA, and to identify novel candidate gene signatures that might serve as therapeutic targets. Comprehensive transcriptome analysis of peripheral blood mononuclear cells (PBMCs) from ACPA⁺ and ACPA^- RA patients and healthy controls was performed via RNA sequencing. A validation cohort was used to further investigate differentially expressed genes via polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA). Spearman's correlation test was used to evaluate the correlation of differentially expressed genes and the clinical and laboratory data of the patients. The role of differentially expressed genes in osteoclastogenesis was further investigated. Expression of C-X-C motif chemokine ligand 2 (CXCL2) was significantly increased in ACPA⁺ RA than in ACPA^- RA, which was validated in PBMCs and serum. CXCL2 promoted the migration of CD14⁺ monocytes and increased osteoclastogenesis in RA patients. RAW264.7 macrophages were used to investigate specific mechanisms, and the results suggested that CXCL2 stimulated osteoclastogenesis via extracellular receptor kinase (ERK) mitogen-activated protein kinase (MAPK) and nuclear factor kappa B pathways. In conclusion, CXCL2 was highly expressed in ACPA⁺ RA than in ACPA^- RA. CXCL2 promoted osteoclastogenesis and was related to bone erosion in RA, which suggests that the blockade of CXCL2 might be a novel strategy for the treatment of RA.

Integrative analysis for COVID-19 patient outcome prediction

While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome prediction. Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally. Therefore, an accurate prediction of disease progression with baseline imaging at the time of the initial presentation can help in patient management. In lieu of only size and volume information of pulmonary abnormalities and features through deep learning based image segmentation, here we combine radiomics of lung opacities and non-imaging features from demographic data, vital signs, and laboratory findings to predict need for intensive care unit (ICU) admission. To our knowledge, this is the first study that uses holistic information of a patient including both imaging and non-imaging data for outcome prediction. The proposed methods were thoroughly evaluated on datasets separately collected from three hospitals, one in the United States, one in Iran, and another in Italy, with a total 295 patients with reverse transcription polymerase chain reaction (RT-PCR) assay positive COVID-19 pneumonia. Our experimental results demonstrate that adding non-imaging features can significantly improve the performance of prediction to achieve AUC up to 0.884 and sensitivity as high as 96.1%, which can be valuable to provide clinical decision support in managing COVID-19 patients. Our methods may also be applied to other lung diseases including but not limited to community acquired pneumonia. The source code of our work is available at https://github.com/DIAL-RPI/COVID19-ICUPrediction.

Gut dysbacteriosis and intestinal disease: mechanism and treatment

The gut microbiome functions like an endocrine organ, generating bioactive metabolites, enzymes or small molecules that can impact host physiology. Gut dysbacteriosis is associated with many intestinal diseases including (but not limited to) inflammatory bowel disease, primary sclerosing cholangitis-IBD, irritable bowel syndrome, chronic constipation, osmotic diarrhoea and colorectal cancer. The potential pathogenic mechanism of gut dysbacteriosis associated with intestinal diseases includes the alteration of composition of gut microbiota as well as the gut microbiota-derived signalling molecules. The many correlations between the latter and the susceptibility for intestinal diseases has placed a spotlight on the gut microbiome as a potential novel target for therapeutics. Currently, faecal microbial transplantation, dietary interventions, use of probiotics, prebiotics and drugs are the major therapeutic tools utilized to impact dysbacteriosis and associated intestinal diseases. In this review, we systematically summarized the role of intestinal microbiome in the occurrence and development of intestinal diseases. The potential mechanism of the complex interplay between gut dysbacteriosis and intestinal diseases, and the treatment methods are also highlighted.

Integrative Analysis for COVID-19 Patient Outcome Prediction

While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome prediction. Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally. Therefore, an accurate prediction of disease progression with baseline imaging at the time of the initial presentation can help in patient management. In lieu of only size and volume information of pulmonary abnormalities and features through deep learning based image segmentation, here we combine radiomics of lung opacities and non-imaging features from demographic data, vital signs, and laboratory findings to predict need for intensive care unit (ICU) admission. To our knowledge, this is the first study that uses holistic information of a patient including both imaging and non-imaging data for outcome prediction. The proposed methods were thoroughly evaluated on datasets separately collected from three hospitals, one in the United States, one in Iran, and another in Italy, with a total 295 patients with reverse transcription polymerase chain reaction (RT-PCR) assay positive COVID-19 pneumonia. Our experimental results demonstrate that adding non-imaging features can significantly improve the performance of prediction to achieve AUC up to 0.884 and sensitivity as high as 96.1%, which can be valuable to provide clinical decision support in managing COVID-19 patients. Our methods may also be applied to other lung diseases including but not limited to community acquired pneumonia. The source code of our work is available at https://github.com/DIAL-RPI/COVID19-ICUPrediction.

[Blood pressure control and influencing factors in hypertension patients with metabolic syndrome]

Objective: To investigate the blood pressure control and its influencing factors in hypertension patients with MS. Methods: Between January 2017 and December 2018, more than 78 000 residents aged 35-75 years selected through convenient sampling were invited to participant in China Patient-Centered Evaluative Assessment of Cardiac Event Million Persons Project in Fujian province, physical and laboratory tests were conducted for them, and their basic information were recorded. A total of 5 281 hypertension patients with MS were included in the study. Results: The treatment rate of hypertension patients with MS was 55.5%, and the control rate was 7.2%. The control rate was higher in patients who were older, women, had advanced education level, had history or family history of cardiovascular disease. The results of multivariate analysis indicated that living area (urban or rural), cardiovascular history, diabetes, urine protein, BMI had impacts on both treatment and control of hypertension. Family history of cardiovascular disease, age, self-management of hypertension, dyslipidemia, waist circumference and drinking had impacts on the treatments, and gender had effects on the control. Conclusions: The treatment rate of hypertension patients with MS was unsatisfactory and the control rate was low. Intervention should be strengthened in rural area, males and young age groups, and activity of self-management group of hypertension should be conducted regularly.

A numerical study of spin torque oscillators based on IMA/PMA bilayer nano-pillars

In this paper, the magnetization dynamics of bilayer structured nano-pillars containing a fixed layer with perpendicular magnetic anisotropy (PMA) and a free layer with in-plane magnetic anisotropy (IMA) are studied using the micro-magnetic simulation method. Unlike typical sandwich-structured spin-torque nano-pillar oscillators (STNOs), the proposed structure does not contain any nonmagnetic spacer layer. It is found that a stable oscillation with a significant amplitude can be established fast after driving out the vortex core by an in-plane magnetic pulse field. The oscillation frequency and amplitude can be easily manipulated by adjusting the side-length of the nanopillar, the thickness and saturation magnetization of the IMA layer, and an applied magnetic field along z axis. In an array with an adequate inter-pillar distance, the mutual interaction between the nano-pillars will lead the oscillations to be phase-locked, resulting in a considerable enhancement of total amplitude. As it is easy to fabricate these kinds of bi-layer nano-pillars and assemble them in arrays, they may have widespread applications in STNOs.

Homozygous G650del nexilin variant causes cardiomyopathy in mice

Nexilin (NEXN) was recently identified as a component of the junctional membrane complex required for development and maintenance of cardiac T-tubules. Loss of Nexn in mice leads to a rapidly progressive dilated cardiomyopathy (DCM) and premature death. A 3 bp deletion (1948-1950del) leading to loss of the glycine in position 650 (G650del) is classified as a variant of uncertain significance in humans and may function as an intermediate risk allele. To determine the effect of the G650del variant on cardiac structure and function, we generated a G645del-knockin (G645del is equivalent to human G650del) mouse model. Homozygous G645del mice express about 30% of the Nexn expressed by WT controls and exhibited a progressive DCM characterized by reduced T-tubule formation, with disorganization of the transverse-axial tubular system. On the other hand, heterozygous Nexn global KO mice and genetically engineered mice encoding a truncated Nexn missing the first N-terminal actin-binding domain exhibited normal cardiac function, despite expressing only 50% and 20% of the Nexn, respectively, expressed by WT controls, suggesting that not only quantity but also quality of Nexn is necessary for a proper function. These findings demonstrated that Nexn G645 is crucial for Nexn's function in tubular system organization and normal cardiac function.

Perinatal Docosahexaenoic Acid Supplementation Improves Cognition and Alters Brain Functional Organization in Piglets

Epidemiologic studies associate maternal docosahexaenoic acid (DHA)/DHA-containing seafood intake with enhanced cognitive development; although, it should be noted that interventional trials show inconsistent findings. We examined perinatal DHA supplementation on cognitive performance, brain anatomical and functional organization, and the brain monoamine neurotransmitter status of offspring using a piglet model. Sows were fed a control (CON) or a diet containing DHA (DHA) from late gestation throughout lactation. Piglets underwent an open field test (OFT), an object recognition test (ORT), and magnetic resonance imaging (MRI) to acquire anatomical, diffusion tensor imaging (DTI), and resting-state functional MRI (rs-fMRI) at weaning. Piglets from DHA-fed sows spent 95% more time sniffing the walls than CON in OFT and exhibited an elevated interest in the novel object in ORT, while CON piglets demonstrated no preference. Maternal DHA supplementation increased fiber length and tended to increase fractional anisotropy in the hippocampus of offspring than CON. DHA piglets exhibited increased functional connectivity in the cerebellar, visual, and default mode network and decreased activity in executive control and sensorimotor network compared to CON. The brain monoamine neurotransmitter levels did not differ in healthy offspring. Perinatal DHA supplementation may increase exploratory behaviors, improve recognition memory, enhance fiber tract integrity, and alter brain functional organization in offspring at weaning.

A soft manipulator for efficient delicate grasping in shallow water: Modeling, control, and real-world experiments

Collecting in shallow water (water depth: ~30 m) is an emerging field that requires robotics for replacing human divers. Soft robots have several promising features (e.g., safe interaction with the environments, lightweight, etc.) for performing such tasks. In this article, we developed an underwater robotic system with a three-degree-of-freedom (3-DoF) soft manipulator for spatial delicate grasping in shallow water. First, we present the design and fabrication of the soft manipulator with an opposite-bending-and-stretching structure (OBSS). Then, we proposed a simple and efficient kinematics method for controlling the spatial location and trajectory of the soft manipulator’s end effector. The inverse kinematics of the OBSS manipulator can be solved efficiently (computation time: 8.2 ms). According to this inverse kinematics method, we demonstrated that the OBSS soft manipulator could track complex two-dimensional and three-dimensional trajectories, including star, helix, etc. Further, we performed real-time closed-loop pick-and-place experiments of the manipulator with binocular and on-hand cameras in a lab aquarium. Hydrodynamic experiments showed that the OBSS soft manipulator produced little force (less than 0.459 N) and torque (less than 0.228 N·m), which suggested its low-inertia feature during the underwater operation. Finally, we demonstrated that the underwater robotic system with the OBSS soft manipulator successfully collected seafood animals at the bottom of the natural oceanic environment. The robot successfully collected eight sea echini and one sea cucumber within 20 minutes at a water depth of around 10 m.