Edge-colored directed subgraph enumeration on the connectome

Following significant advances in image acquisition, synapse detection, and neuronal segmentation in connectomics, researchers have extracted an increasingly diverse set of wiring diagrams from brain tissue. Neuroscientists frequently represent these wiring diagrams as graphs with nodes corresponding to a single neuron and edges indicating synaptic connectivity. The edges can contain "colors" or "labels", indicating excitatory versus inhibitory connections, among other things. By representing the wiring diagram as a graph, we can begin to identify motifs, the frequently occurring subgraphs that correspond to specific biological functions. Most analyses on these wiring diagrams have focused on hypothesized motifs-those we expect to find. However, one of the goals of connectomics is to identify biologically-significant motifs that we did not previously hypothesize. To identify these structures, we need large-scale subgraph enumeration to find the frequencies of all unique motifs. Exact subgraph enumeration is a computationally expensive task, particularly in the edge-dense wiring diagrams. Furthermore, most existing methods do not differentiate between types of edges which can significantly affect the function of a motif. We propose a parallel, general-purpose subgraph enumeration strategy to count motifs in the connectome. Next, we introduce a divide-and-conquer community-based subgraph enumeration strategy that allows for enumeration per brain region. Lastly, we allow for differentiation of edges by types to better reflect the underlying biological properties of the graph. We demonstrate our results on eleven connectomes and publish for future analyses extensive overviews for the 26 trillion subgraphs enumerated that required approximately 9.25 years of computation time.

AB0788 The International Map of Axial Spondyloarthritis (IMAS): a US patient perspective on diagnosis and burden of disease

Background

Axial spondyloarthritis (axSpA) is a chronic inflammatory disease encompassing radiographic (traditionally known as ankylosing spondylitis) and non-radiographic forms that lead to chronic pain, structural damage, and disability.1 The International Map of Axial Spondyloarthritis (IMAS) survey is an initiative developed to generate insights into the real-life experiences of people living with axSpA to ultimately improve quality of life.2

Objectives

To assess the burden and daily experience of patients with axSpA in the United States.

Methods

The IMAS survey generates a report on patient-reported aspects of disease burden and experience with axSpA using adaptations of the original Atlas of axSpA questionnaire developed in collaboration with patients, the Axial Spondyloarthritis International Federation, and clinical academic experts. In this US adaptation of the IMAS survey, a 30-minute quantitative online survey was administered to US patients aged ≥18 years who completed screening questions, self-reported having been diagnosed with axSpA by a healthcare provider, and were under the care of a healthcare provider between July 22, 2021, and November 10, 2021. Survey questions were tailored to reflect differences in the US healthcare systems and the availability of treatments. This analysis presents a portion of the US data describing patient demographics, clinical characteristics, journey to axSpA diagnosis, and the emotional impact and overall burden of disease on quality of life using the General Health Questionnaire 12 (GHQ-12), the Assessment of SpondyloArthritis international Society – Health Index (ASAS-HI), and a global limitation index of 18 activities of daily living. All results were reported descriptively using summary statistics.

Results

Survey data from 228 US patients with axSpA were collected in this analysis. The mean age was 45 years, 60% of patients were female, and the mean BMI was 27.7 kg/m2 (Table 1). Participating patients had an average of 5.6 comorbidities, with anxiety (43%), depression (41%), and hypertension (32%) as the most commonly reported comorbidities. Among all patients, the mean age at onset of first symptoms was 26 years and the mean age at diagnosis was 35 years; overall, mean diagnostic delay was greater in female than in male patients (11.2 vs 5.2 years; Figure 1A). According to the validated GHQ-12, over half of the patients (57%) were at risk for psychological distress (GHQ-12 score ≥3; Figure 1B). Patients who were older (>40 years old), physically inactive, or who had active disease (BASDAI ≥4) were at risk for psychological distress. Most patients (82%) suffered from a high degree of impairment (ASAS-HI ≥6), 47% had a medium or high limitation in activities of daily living, and 46% of patients were not employed at the time of the survey.

Table 1.

Patient Demographic and Clinical Characteristics

CharacteristicPatients with axSpA(N=228)Mean age, years45Female, %60White, %86Mean body mass index, kg/m227.7Nonsmoker, %62Alcohol consumption behavior, %Never19Every day9Mean number of comorbidities5.6Common comorbidities (≥20% of patients), %aAnxiety43Depression41Hypertension32Obesity/overweight31Sleep disorders30Hypercholesterolemia29Uveitis24Psoriatic arthritis23Fibromyalgia20Spinal or other fractures20Psoriasis20Employed, %54

axSpA, axial spondyloarthritis.

aRespondents could have selected ≥1 answer.

Conclusion

This study showed that a high proportion of US patients with axSpA report impaired function and are at risk for psychological distress. Patients also experienced a substantial delay in the time to axSpA diagnosis, with longer delays than those reported in the European Union. Delays were twice as long in women compared to men. These findings highlight the large impact of disease on daily activities and mental distress in US patients with axSpA.

References

[1]Sieper J, Poddubnyy D. Lancet. 2017;390:73-84.

[2]Garrido-Cumbrera M, et al. Curr Rheumatol Rep. 2019;21:19.

Acknowledgements

This study was funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA. Medical writing support was provided by Charli Dominguez, PhD, of Health Interactions, Inc, Hamilton, NJ, USA, and was funded by Novartis Pharmaceuticals Corporation. This abstract was developed in accordance with Good Publication Practice (GPP3) guidelines. Authors had full control of the content and made the final decision on all aspects of this publication.

Disclosure of Interests

Marina Magrey Consultant of: Received consulting fees from Eli Lilly and Novartis, Grant/research support from: Received research grants from AbbVie, Amgen, and UCB, Jessica A. Walsh Consultant of: Received consulting fees from Amgen, Janssen, Eli Lilly, Novartis, Pfizer, and UCB, Grant/research support from: Received research funding from AbbVie, Merck, and Pfizer, Sandra Flierl Employee of: Employee of Ipsos, Renato Calheiros Employee of: Employee of Novartis, David Wei Employee of: Employee of Novartis, Muhammad Asim Khan Consultant of: Has served as a consultant for Novartis

Texture-based Error Analysis for Image Super-Resolution

Evaluation practices for image super-resolution (SR) use a single-value metric, the PSNR or SSIM, to determine model performance. This provides little insight into the source of errors and model behavior. Therefore, it is beneficial to move beyond the conventional approach and reconceptualize evaluation with interpretability as our main priority. We focus on a thorough error analysis from a variety of perspectives. Our key contribution is to leverage a texture classifier, which enables us to assign patches with semantic labels, to identify the source of SR errors both globally and locally. We then use this to determine (a) the semantic alignment of SR datasets, (b) how SR models perform on each label, (c) to what extent high-resolution (HR) and SR patches semantically correspond, and more. Through these different angles, we are able to highlight potential pitfalls and blindspots. Our overall investigation highlights numerous unexpected insights. We hope this work serves as an initial step for debugging blackbox SR networks.

POS0966 DEVELOPMENT AND VALIDATION OF AN ANKYLOSING SPONDYLITIS RISK PREDICTION MODEL USING LONGITUDINAL REAL-WORLD DATA FROM A LARGE INTEGRATED HEALTHCARE DELIVERY SYSTEM

Background

Early detection and diagnosis of Ankylosing spondylitis (AS) is challenging due to heterogeneity in disease presentation, lack of specific biomarkers and high prevalence of mechanical back-pain that is difficult to distinguish from inflammatory back-pain. However, if diagnosed and treated early, the risk of AS complications and disease progression can be slowed.

Objectives

To develop and validate a risk prediction model for early identification of patients at high risk of AS, using a large longitudinal real-world clinical data in the US.

Methods

This retrospective study included all members aged ≥ 21 years with back pain symptoms who were enrolled in the Kaiser Permanente Southern California health plan between 01/2009-12/2013. Patients who presented with back pain symptoms at a physician visit were followed until 12/2020 to see if they subsequently developed AS. The cohort was randomly divided into a training (60%) and a validation (40%) sample. A proportional odds model was specified to create a risk score for AS in the training sample. Best fit model was determined based on Area Under the Curve (AUC) and Akaike Information Criterion (AIC). The cut off threshold of “high-risk” was based on Youden’s (1950) index.1 We assessed the model performance for internal validity using split-samples. The model was further validated using manual chart review of 900 patient records. These 900 records were selected such that 70% (N=630) met the high-risk cut-off and the remainder had scores below the cut-off. We also derived the probability of AS in each chart reviewed case using the method proposed by Feldtkeller et al. (2013) and Rudwaleit et al. (2006).2,3

Results

The cohort comprised 527,509 members with mean age 54 years and majority female (58%). Sixty-six percent were White race and 33% were Hispanic ethnicity. The crude incidence of AS was 1% and increased steadily during the follow-up period (Figure 1). The final risk prediction model included 15 risk factors and had an AUC of 0.72 (Table 1). Using Youden’s index, a cut-off value of 11 or higher was identified as the threshold to define high-risk. No evidence of overfitting to our training sample was observed based on the split-sample analysis. The model validation based on manual chart review of 900 records showed sufficient ability to discriminate between those at high-risk vs those not identified to be high-risk. When a concrete rule out or rule in determination could be made using Feldtkeller et al. approach, our model correctly classified 75% of such records.

Table 1.

Final Model Coefficients and Derived Risk Score

Model CoefficientPr(>|z|)Risk ScoreAge above 45 years0.1460.0111.46Male Sex-0.292<0.001-2.92White Race0.259<0.0012.59Non-Hispanic Ethnicity0.177<0.0011.77Corticosteroid Use (Yes/No)0.235<0.0012.35*NSAID User (Yes/No)0.202<0.0012.02Opioid Analgesic User (Yes/No)0.416<0.0014.16Had Enthesitis (Yes/No)0.298<0.0012.98Had Disorders of the Back (Yes/No)0.973<0.0019.73Had Fatigue and/or Malaise (Yes/No)0.1550.0561.55Had Psoriasis (Yes/No)0.2880.0082.88Had Spondylosis (Yes/No)0.838<0.0018.38Had Synovitis (Yes/No)0.1430.0661.43Had Uveitis (Yes/No)0.6210.0076.21Depression Diagnosis (Yes/No)0.0990.0170.99

* NSAID: Non-steroidal anti-inflammatory drugs

Figure 1.

Cumulative Incidence Over Time (in Days)

Conclusion

To aid early detection, we have developed and validated an AS risk prediction model with an easy to implement scoring system using demographics, medication use and diagnosis data that is routinely collected in clinical practice.

References:

[1]Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32-35.

[2]Feldtkeller E, Rudwaleit M, Zeidler H. Easy probability estimation of the diagnosis of early axial spondyloarthritis by summing up scores. Rheumatology (Oxford, England). 2013;52(9):1648-1650

[3]Rudwaleit M, Feldtkeller E, Sieper J. Easy assessment of axial spondyloarthritis (early ankylosing spondylitis) at the bedside. Ann Rheum Dis 2006;65:1251-2.

Disclosure of Interests

Aniket Kawatkar Grant/research support from: Novartis, Medac, Esther Yi Employee of: Novartis, Erika Estrada Grant/research support from: Novartis, Jose Pio Grant/research support from: Novartis, Cecilia Portugal Grant/research support from: Novartis, David Yi Grant/research support from: Novartis, Talar Habeshian Grant/research support from: Novartis, David Wei Employee of: Novartis, Steven Lee Grant/research support from: Novartis

Adsorption of copper (II) and cadmium (II) ions by in situ doped nano-calcium carbonate high-intensity chitin hydrogels

Most natural polymers exhibit limited functional groups, which is not favourable for the adsorption of various ions and their utilisation. To overcome this drawback, a novel in-situ-doped nano-calcium carbonate (CaCO₃) chitin hydrogel was synthesised as an efficient adsorbent for Cu (II) and Cd (II) ions. Scanning electron microscopy and Brunauer-Emmett-Teller results revealed that the synthesised CaCO₃/chitin hydrogel exhibited loose macropores and mesopores. Subsequently, Fourier transform infrared, Raman, and X-ray diffraction characterisation characterisation proved that chitin was successfully doped with nano-CaCO₃. The mechanical properties of CaCO₃/chitin hydrogel were superior to those of the unmodified chitin hydrogel and could efficiently adsorb Cu (II) and Cd (II) ions in water. The effect of pH, initial concentration, adsorbent dosage, and temperature was assessed to determine the adsorption properties of the hydrogel. Under suitable experimental conditions, the maximum adsorption rate of the CaCO₃/chitin hydrogel was approximately 96%. The time-dependent adsorption kinetics followed a quasi-second order model, and the adsorption process followed the Langmuir model. The maximum adsorption capacities of Cu (II) and Cd (II) according to the Langmuir curve were 194.61 and 191.58 mg/g, respectively. Compared with the binary competitive system, the material exhibited a specific selectivity to the adsorption of Cu (II). X-ray photoelectron spectroscopy (XPS) revealed that nitrogen and oxygen atoms were involved in chelation with the metal ions. The successful compounding of calcium carbonate nanoparticles provided more active adsorption sites for the gel. The novel material exhibited excellent adsorption effects on Cu (II) and Cd (II) ions when applied to a water sample. Thus, the novel material exhibits excellent potential for application. The Cu (II) and Cd (II)ion removal efficiencies after five successive adsorption cycles were higher than 90%, which indicated that the composite material exhibited excellent stability and reproducibility.

Negative associations of morning serum cortisol levels with obesity: the Henan rural cohort study

AIMS

To evaluate the associations of morning serum cortisol levels with obesity defined by different indices in Chinese rural populations.

MATERIALS AND METHODS

A cross-sectional study was performed including 6198 participants (2566 males and 3632 females). Serum cortisol was collected in morning and quantified by liquid chromatography-tandem mass spectrometry. Obesity was defined by body mass index (BMI), body fat percentage (BFP), waist-to-height ratio (WHtR), waist circumference (WC), visceral fat index (VFI) and waist-to-hip ratio (WHR). Both multivariable liner regression, logistic regression and restrictive cubic splines models were used to estimate the gender-specific relationships between cortisol levels and obesity defined by different indices, respectively.

RESULTS

After adjusting for potential confounders, serum cortisol was negatively associated with different obesity measures, except obese females defined by BFP (for instance, overall obesity defined by BMI, Quartile 4 vs. Quartile 1, odds ratio (OR) = 0.25, 95% confidence interval (CI):0.15, 0.41 in males, and OR = 0.58, 95% CI: 0.42,0.80 in females, central obesity defined by WC, OR = 0.52, 95% CI:0.39,0.69 in males and OR = 0.63, 95% CI:0.51,0.77 in females). Similarly, restrictive cubic splines showed the nonlinear relationship between high levels of cortisol and different obesity indices. Furthermore, ROC curve analysis indicated that cortisol could improve the discrimination of model with common biomarkers.

CONCLUSION

Morning serum cortisol were negatively related to obesity defined by different indices in Chinese rural populations. In addition, cortisol could be as a biomarker for prediction of obesity in males.

lnc94638 is a testis-specific long non-coding RNA involved in spermatozoa formation in Zeugodacus cucurbitae (Coquillett)

Long non-coding RNAs (lncRNAs) generally display tissue-specific distributions, and testis-specific lncRNAs form the highest proportion of lncRNAs in many species. Here, we presented a detailed analysis of testis-specific lncRNAs in the melon fly, Zeugodacus cucurbitae, a highly destructive insect pest of cucurbitaceous and other related crops. Most testis-specific lncRNAs were found to be long intergenic non-coding RNAs (lincRNA). The size distribution of these lncRNAs ranged between 600 and 1000 nucleotides. Testis-specific lncRNAs that harboured one isoform number and two exons were the most abundant. Compared to other male tissues, the testis had more highly expressed lncRNAs. The quantitative real-time polymerase chain reaction results of 10 randomly selected testis-specific lncRNAs showed expression patterns consistent with RNA-seq data. Further analysis of the most highly expressed testis-specific lncRNA, lnc94638, was undertaken. Fluorescent in situ hybridization assays localized lnc94638 to the apical region of the testis that contains mature spermatozoa. RNA interference-mediated knockdown of lnc94638 expression reduced spermatozoa numbers and impaired the fertility of Z. cucurbitae male. This study provides a catalogue of testis-specific lncRNAs, shows that the testis-specific lnc94638 is involved in spermatogenesis and has the potential to be used for treating male sterility.

Associations of maternal hypertensive disorders during pregnancy with offspring risks of ischemic heart disease and stroke: a Nordic cohort study

Background

A substantial body of evidence suggests that children exposed to maternal hypertensive disorders during pregnancy (HDP) have increased risks of preterm birth, fetal growth restriction and several cardiovascular risk factors (e.g., hypertension, obesity, diabetes) later in life. However, the direct evidence on the link between maternal HDP and the risk of severe cardiovascular diseases such as ischemic heart disease (IHD) and stroke in the offspring is very limited.

Objective

To investigate the associations between maternal HDP and the risk of IHD and stroke in the offspring.

Methods

We conducted a population-based cohort study by linking several national registers in Sweden and Finland. Live singleton births from the Swedish Medical Birth Register (1973–2014) and the Finnish Medical Birth Register (1987- 2014) were followed for IHD and stroke until 2014 by the national patient and cause of death registers. We performed Cox regression models to examine the association between maternal HDP and its subtypes, i.e., pre-existing chronic hypertension, gestational hypertension, and preeclampsia, and the risk of IHD, and stroke in the offspring while adjusting for relevant maternal and pregnancy-related confounders. We conducted sibling analyses to control for unmeasured shared familial (genetic and/or environmental) risk factors.

Results

Among the 5,807,122 singletons included in the study, 218,322 (3.76%) children were born to mothers with HDP. During the up to 41 years of follow-up, 2,340 (0.04%) offspring were diagnosed with IHD and 5,360 (0.09%) were diagnosed with stroke. Offspring exposed to maternal HDP had an increased risk of IHD (adjusted hazard ratio (aHR), 1.29; 95% confidence interval (CI), 1.01–1.63), and stroke (aHR,1.33; 95% CI, 1.14–1.56). Significantly increased rates of stroke were also observed in children exposed to the subtypes of maternal HDP: pre-existing chronic hypertension (aHR, 1.64; 95% CI, 1.03–2.60), gestational hypertension (HR, 1.38; 95% CI, 1.08–1.77), and preeclampsia (HR, 1.26; 95% CI, 1.02–1.55). The associations between maternal HDP and offspring's IHD and stroke were independent of preterm birth and small for gestational age at birth. Maternal HDP remained associated with stroke in the offspring (aHR, 1.94; 95% CI, 1.16–3.22), but not with IHD (aHR, 0.89; 95% CI, 0.47–1.67) in the sibling analyses.

Conclusion

Children to mothers with HDP have increased rates of IHD and stroke from childhood to young adulthood. While the link between maternal HDP and IHD in the offspring seemed to be attributed to confounding by familial factors, the relation between maternal HDP and stroke persisted even when considering such confounding. Persons born to mothers with HDP may benefit from early screening and prevention efforts to reduce the risk of IHD and stroke later in life.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Swedish Heart and Lung Foundation

Death of a child and the risk of heart failure: a population-based cohort study from Denmark and Sweden

Background

Increasing evidence suggests that the death of a child is associated with increased risks of ischemic heart diseases and atrial fibrillation and the association is in part attributable to stress-related mechanisms. However, knowledge regarding the risk of heart failure (HF) after the death of a child is very limited.

Purpose

To study the association between the death of a child and the parents' risk of HF.

Methods

We conducted a population-based cohort study involving parents of live-born children recorded in the Danish and Swedish Medical Birth Registers during 1973–2016 and 1973–2014, respectively (n=6,717,531). We retrieved information on child death, HF diagnosis and parents' sociodemographic characteristics from several nationwide registries. We performed Poisson regression models to estimate incidence rate ratio (IRR) and 95% confidence intervals (CI) for HF.

Results

A total of 129,829 (1.9%) parents lost at least one child during the follow-up. Bereaved parents had a 35% higher risk of HF than non-bereaved parents [IRR (95% CI): 1.35 (1.29–1.41)]. The association was present not only if the child died due to cardiovascular or other natural causes [IRR (95% CI): 1.48 (1.25–1.75) and 1.35 (1.27–1.44), respectively], but also in case of unnatural deaths [IRR (95% CI): 1.32 (1.24–1.42)]. There was a trend toward a U-shaped association according to the deceased child's age at loss and the risk of HF. Bereaved parents who lost their only child or had three or more remaining live children at the time of loss had higher HF risk than those with one or two live children at the time of loss. We found no clear evidence for a difference in the association of interest over time.

Conclusions

The death of a child was associated with an increased risk of HF. The finding that not only cardiovascular and other natural deaths, but also unnatural deaths were associated with HF suggests that stress-related mechanisms may contribute to the development of HF.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Swedish Council for Working Life and Social Research and Karolinska Institutet's Research Foundation

Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution

Deep convolutional neural networks (CNNs) have pushed forward the frontier of super-resolution (SR) research. However, current CNN models exhibit a major flaw: they are biased towards learning low-frequency signals. This bias becomes more problematic for the image SR task which targets reconstructing all fine details and image textures. To tackle this challenge, we propose to improve the learning of high-frequency features both locally and globally and introduce two novel architectural units to existing SR models. Specifically, we propose a dynamic highpass filtering (HPF) module that locally applies adaptive filter weights for each spatial location and channel group to preserve high-frequency signals. We also propose a matrix multi-spectral channel attention (MMCA) module that predicts the attention map of features decomposed in the frequency domain. This module operates in a global context to adaptively recalibrate feature responses at different frequencies. Extensive qualitative and quantitative results demonstrate that our proposed modules achieve better accuracy and visual improvements against state-of-the-art methods on several benchmark datasets.

Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field

The developmental process of embryos follows a monotonic order. An embryo can progressively cleave from one cell to multiple cells and finally transform to morula and blastocyst. For time-lapse videos of embryos, most existing developmental stage classification methods conduct per-frame predictions using an image frame at each time step. However, classification using only images suffers from overlapping between cells and imbalance between stages. Temporal information can be valuable in addressing this problem by capturing movements between neighboring frames. In this work, we propose a two-stream model for developmental stage classification. Unlike previous methods, our two-stream model accepts both temporal and image information. We develop a linear-chain conditional random field (CRF) on top of neural network features extracted from the temporal and image streams to make use of both modalities. The linear-chain CRF formulation enables tractable training of global sequential models over multiple frames while also making it possible to inject monotonic development order constraints into the learning process explicitly. We demonstrate our algorithm on two time-lapse embryo video datasets: i) mouse and ii) human embryo datasets. Our method achieves 98.1% and 80.6% for mouse and human embryo stage classification, respectively. Our approach will enable more pro-found clinical and biological studies and suggests a new direction for developmental stage classification by utilizing temporal information.

Association of maternal gestational weight gain with intellectual developmental disorder in the offspring: a nationwide follow-up study in Sweden

OBJECTIVES

To investigate the association between maternal gestational weight gain (GWG) and offspring's intellectual developmental disorders (IDD); how this association is modified by maternal early-pregnancy BMI.

DESIGN

Population-based cohort study.

SETTING AND POPULATION

All liveborn singletons with information on maternal GWG in the Swedish Medical Register during 1992-2006 (n = 467 485).

METHODS

We used three GWG classifications, (1) Institute of Medicine (IOM) guidelines ('ideal' GWG: maternal underweight = 12.7-18.1 kg; normal = 11.3-15.9 kg; overweight = 6.8-11.3 kg; obesity = 5.0-9.1 kg), (2) LifeCycle project recommendation ('ideal' GWG: maternal underweight = 14.0-16.0 kg; normal = 10.0-18.0 kg; overweight = 2.0-16.0 kg; obesity class I = 2.0-6.0 kg; obesity class II ≤0.0-4.0 kg; obesity class III ≤0.0-6.0 kg) and (3) GWG centiles. Hazard ratio (HR) and 95% CI for offspring's IDD risk using Cox regression.

MAIN OUTCOME MEASURES

IDD was extracted from Swedish National Patient Register (code ICD-9:317-319/ICD-10:F70-F79).

RESULTS

Forty-one per cent of children were born to mothers with excessive GWG, 32.8% with ideal GWG and 26.2% with inadequate GWG according to IOM guidelines. Inadequate GWG was associated with 21% higher risk of offspring's IDD (95% CI 1.11-1.31) relative to ideal GWG. In contrast, when using the LifeCycle classification, children of mothers with inadequate GWG (HR 1.14, 95% CI 1.05-1.24) or excessive GWG (HR 1.09, 95% CI 1.01-1.17) had higher risks of IDD than those of mothers with ideal GWG. When using GWG centiles, extremely low GWG (<20th centile) and low GWG (20th-40th centile) were associated with elevated offspring's IDD risk. Further stratified analysis by maternal early-pregnancy body mass index (BMI) showed that overweight/obese mothers (BMI ≥25 kg/m² ) with extremely excessive GWG (>25 kg) was associated with an increased offspring's IDD.

CONCLUSION

Our findings suggest that inadequate maternal GWG may increase offspring's IDD risk, irrespective of maternal early-pregnancy BMI. Extremely excessive GWG (>25 kg) may increase offspring's IDD risk, but only among mothers with an early-pregnancy BMI ≥25 kg/m² .

TWEETABLE ABSTRACT

Inadequate maternal weight gain during pregnancy may increase the risk of offspring's intellectual disability, regardless of maternal BMI.

Coordination of primary metabolism and virulence factors expression mediates the virulence of Vibrio parahaemolyticus towards cultured shrimp (Penaeus vannamei)

AIMS

Acute hepatopancreatic necrosis disease (AHPND) caused by Vibrio parahaemolyticus has emerged as a severe bacterial disease of cultured shrimp. To identify the key virulence factors, two AHPND-causing V. parahaemolyticus (Vp_AHPND ) strains (123 and 137) and two non-Vp_AHPND strains (HZ56 and ATCC 17082) were selected.

METHODS AND RESULTS

Challenge tests showed that the four strains exhibited different virulence towards shrimp with cumulative mortalities at 48 h postinfection (hpi) ranging from 10 to 92%. The expression of pirAB^VP in strain 123 and 137 was not significantly different. Genomic analysis revealed that the two Vp_AHPND strains contain a plasmid with the PirAB^VP toxins (pirAB^VP ) flanked by the insertion sequence (ISVal1) that has been identified in various locations of chromosomes in Vp_AHPND strains. The two Vp_AHPND strains possessed almost identical virulence factors, while ISVal1 disrupted three genes related to flagellar motility in strain 137. Phenotype assay showed that strain 123 possessed the highest growth rate and swimming motility, followed by strain 137, suggesting that the disruption of essential genes mediated by ISVal1 significantly affected the virulence level. Transcriptome analysis of two Vp_AHPND strains (123 and 137) further suggested that virulence genes related to the capsule, flagella and primary metabolism were highly expressed in strain 123.

CONCLUSIONS

Here for the first time, it is demonstrated that the virulence of Vp_AHPND is not only determined by the expression of pirAB^VP , but also is mediated by ISVal1 which affects the genes involved in flagellar motility and primary metabolism.

SIGNIFICANCE AND IMPACT OF THE STUDY

The genomic and transcriptomic analysis of Vp_AHPND strains provides valuable information on the virulence factors affecting the pathogenicity of Vp_AHPND.

Community diversity and abundance of ammonia-oxidizing archaea and bacteria in shrimp pond sediment at different culture stages

AIMS

Ammonia oxidation is a significant process of nitrogen cycles in a lot of ecosystems sediments while there are few studies in shrimp culture pond (SCP) sediments. This paper attempted to explore the community diversity and abundance of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in SCP sediments at different culture stages.

METHODS AND RESULTS

We collected SCP sediments and analysed the community diversity and abundance of AOA and bacteria in shrimp pond sediment at different culture stages using the ammonia monooxygenase (amoA) gene with quantitative PCR (qPCR) and 16S rRNA gene sequencing. The AOB-amoA gene abundance was showed higher than AOA-amoA gene abundance in SCP sediments on Day 50 and Day 60 after shrimp larvae introducing into the pond, and the diversity of AOA in SCP sediments was higher than that of AOB. The phylogenetic tree revealed that the most of AOA were the member of Nitrosopumilus and Nitrososphaera, and the majority of AOB sequences were clustered into Nitrosospira, Nitrosomonas clusters 6a and 7. The AOA community has close relationship with total organic carbon (TOC), pH, total phosphorus (TP), nitrate reductase, urease, acid phosphatase and β-glucosidase. The AOB community was related to TOC, C/N and nitrate reductase.

CONCLUSIONS

AOA and AOB play the different ecological roles in SCP sediments at different culture stages.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our results suggested that the different community diversity and abundance of AOA and AOB in SCP sediments, which may improve our ecological cognition of shrimp culture stages in SCP ecosystems.

MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM Images

Electron microscopy (EM) allows the identification of intracellular organelles such as mitochondria, providing insights for clinical and scientific studies. However, public mitochondria segmentation datasets only contain hundreds of instances with simple shapes. It is unclear if existing methods achieving human-level accuracy on these small datasets are robust in practice. To this end, we introduce the MitoEM dataset, a 3D mitochondria instance segmentation dataset with two (30μm)3 volumes from human and rat cortices respectively, 3, 600× larger than previous benchmarks. With around 40K instances, we find a great diversity of mitochondria in terms of shape and density. For evaluation, we tailor the implementation of the average precision (AP) metric for 3D data with a 45× speedup. On MitoEM, we find existing instance segmentation methods often fail to correctly segment mitochondria with complex shapes or close contacts with other instances. Thus, our MitoEM dataset poses new challenges to the field. We release our code and data: https://donglaiw.github.io/page/mitoEM/index.html.

Automated Measurements of Key Morphological Features of Human Embryos for IVF

A major challenge in clinical In-Vitro Fertilization (IVF) is selecting the highest quality embryo to transfer to the patient in the hopes of achieving a pregnancy. Time-lapse microscopy provides clinicians with a wealth of information for selecting embryos. However, the resulting movies of embryos are currently analyzed manually, which is time consuming and subjective. Here, we automate feature extraction of time-lapse microscopy of human embryos with a machine-learning pipeline of five convolutional neural networks (CNNs). Our pipeline consists of (1) semantic segmentation of the regions of the embryo, (2) regression predictions of fragment severity, (3) classification of the developmental stage, and object instance segmentation of (4) cells and (5) pronuclei. Our approach greatly speeds up the measurement of quantitative, biologically relevant features that may aid in embryo selection.

Analysis of the clinicopathological characteristics and prognosis of adenoid cystic carcinoma of the intraoral minor salivary glands: a retrospective study of 40 cases

The clinicopathological aspects and prognostic factors of 40 patients with adenoid cystic carcinoma (ACC) of the intraoral minor salivary glands, treated between 2007 and 2017 at a single institution, were evaluated retrospectively. Twenty-six were female and 14 were male, and they ranged in age from 26 to 81 years (median 55 years). ACC occurred mainly in the palate, with 54.8% of cases presenting T3-T4 lesions. Curative surgery was performed in all patients, and 62.5% of patients were treated with postoperative adjuvant radiotherapy. In the final analysis, positive surgical margins were noted in 57.5% of cases and perineural invasion in 70%. Follow-up was at least 13 months (range 13-141 months, median 59 months). Nineteen patients (47.5%) developed recurrent disease after initial surgery and nine patients had died at the end of follow-up. The 5- and 10-year overall survival rates were 88.3% and 25.6%, respectively. The 5- and 10-year disease-free survival rates were 75.6% and 34.0%, respectively. Patients with a tumour size >4cm and those with positive surgical margins showed a significantly higher risk of local recurrence. Elective neck dissection is suggested for patients with clinically positive lymph nodes or a locally advanced tumour, especially those undergoing microvascular reconstruction. The survival analysis results are similar to those reported previously in the literature.

Hepatitis E virus infection in buffaloes in South China

ABSTRACT Hepatitis E virus (HEV) infection is an important global public health issue. HEV infections are recognized as a zoonotic disease. Swine are believed to be the main reservoir of HEV. Recently, yaks, cows, and yellow cattle have been reported as new reservoirs of HEV. However, whether other species of cattle and buffaloes are sensitive to HEV infection is unknown. To investigate the prevalence of HEV infection in buffaloes, enzyme-linked immunosorbent assay (ELISA) and reverse transcription-nested polymerase chain reaction (RT-nPCR) were performed. Only one buffalo was positive to anti-HEV IgM antibody (1/106, 0.94%), and none were positive for anti-HEV IgG antibody. To our surprise, five serum (5/106, 4.72%) and three milk samples (3/40, 7.50%) from buffaloes were positive to HEV RNA. All strains of HEV isolated from buffaloes belong to genotype 4. Results indicate that buffaloes may be a new reservoir of HEV.

Two Stream Active Query Suggestion for Active Learning in Connectomics

For large-scale vision tasks in biomedical images, the labeled data is often limited to train effective deep models. Active learning is a common solution, where a query suggestion method selects representative unlabeled samples for annotation, and the new labels are used to improve the base model. However, most query suggestion models optimize their learnable parameters only on the limited labeled data and consequently become less effective for the more challenging unlabeled data. To tackle this, we propose a two-stream active query suggestion approach. In addition to the supervised feature extractor, we introduce an unsupervised one optimized on all raw images to capture diverse image features, which can later be improved by fine-tuning on new labels. As a use case, we build an end-to-end active learning framework with our query suggestion method for 3D synapse detection and mitochondria segmentation in connectomics. With the framework, we curate, to our best knowledge, the largest connectomics dataset with dense synapses and mitochondria annotation. On this new dataset, our method outperforms previous state-of-the-art methods by 3.1% for synapse and 3.8% for mitochondria in terms of region-of-interest proposal accuracy. We also apply our method to image classification, where it outperforms previous approaches on CIFAR-10 under the same limited annotation budget. The project page is https://zudi-lin.github.io/projects/#two_stream_active.

Downregulation of CDCA3 expression inhibits tumor formation in pancreatic cancer

Downregulation of cell division cycle-associated 3 (CDCA3) markedly inhibited cell growth and induced apoptosis in tumors. However, the effect of CDCA3 in pancreatic cancer (PAC) was rarely investigated. Therefore, this study attempted to clarify the role of CDCA3 in PAC. The mRNA and protein expression of CDCA3 were examined in PAC cell lines and tumor tissues by using real-time quantitative PCR (RT-qPCR), western blotting (WB), and immunohistochemistry (IHC). The effects of CDCA3 downregulation on cell proliferation, apoptosis, and colony information were investigated through MTT assay, Annexin V-APC single staining cell apoptosis detection, and colony formation test. The microarray and ingenuity pathway analysis were employed to explore the potential regulatory relation. The tumor xenograft model was established for determining the effect of CDCA3 downregulation on the growth of PAC in vivo. The results showed that the expression of CDCA3 in tumor tissues was higher than that of normal tissues (p<0.05). In addition, the mRNA expression of CDCA3 was markedly increased in PANC-1 cells and SW 1990 cells when compared with human pancreatic duct epithelial (HPDE) cells (p<0.05). MTT assay showed that the cell proliferation of PANC-1 cells and SW 1990 cells was significantly inhibited after the lentivirus transfection of CDCA3 knockdown (p<0.05). Annexin V-APC apoptosis assays suggested that the apoptotic cell number was markedly increased in the shCDCA3 group compared to that in the shCtrl group in SW 1990 cells and PANC-1 cells (p<0.05). Meanwhile, the activity of caspase-3/7 was obviously elevated in the shCDCA3 group compared to the shCtrl group (p<0.05). The colony formation was notably inhibited in the shCDCA3 group relative to the shCtrl group in SW 1990 cells (p<0.05). Moreover, the tumor growth was evidently suppressed in the shCDCA3 group compared with the shCtrl group in vivo (p<0.05). These findings revealed that CDCA3 plays a crucial role in the progress of PCA by regulating cell apoptosis and proliferation, which may serve as a potential target for PAC treatment.