Anorectal Malformations: The Pivotal Role of the Good Clinical Practice

Anorectal malformations (ARM) without a fistula are a rare congenital condition. Although may seem more simple to repair compared with ARM with fistulas, surgery has proved to be challenging. We report the case of a newborn who presented a well-formed anus and normal genitalia; a blind-ending anal canal was detected after the insertion of a rectal probe, thus allowing the diagnosis of ARM. Anal probing straight after birth avoids the possible complications related to intestinal obstruction due to a missed diagnosis of ARM. Examination of the perineal region is an important step in the evaluation of the newborn and represents the tool for a prompt identification of ARM. Adding anal probing to accurate inspection perineum is a good clinical practice and should always be performed even in presence of a normal-looking perineum.

FLight Biofabrication Supports Maturation of Articular Cartilage with Anisotropic Properties

Tissue engineering approaches that recapitulate cartilage biomechanical properties are emerging as promising methods to restore the function of injured or degenerated tissue. However, despite significant progress in this research area, the generation of engineered cartilage constructs akin to native counterparts still represents an unmet challenge. In particular, the inability to accurately reproduce cartilage zonal architecture with different collagen fibril orientations is a significant limitation. The arrangement of the extracellular matrix (ECM) plays a fundamental role in determining the mechanical and biological functions of the tissue. In this study, it is shown that a novel light-based approach, Filamented Light (FLight) biofabrication, can be used to generate highly porous, 3D cell-instructive anisotropic constructs that lead to directional collagen deposition. Using a photoclick-based photoresin optimized for cartilage tissue engineering, a significantly improved maturation of the cartilaginous tissues with zonal architecture and remarkable native-like mechanical properties is demonstrated.

Synergizing Algorithmic Design, Photoclick Chemistry and Multi-Material Volumetric Printing for Accelerating Complex Shape Engineering

The field of biomedical design and manufacturing has been rapidly evolving, with implants and grafts featuring complex 3D design constraints and materials distributions. By combining a new coding-based design and modeling approach with high-throughput volumetric printing, a new approach is demonstrated to transform the way complex shapes are designed and fabricated for biomedical applications. Here, an algorithmic voxel-based approach is used that can rapidly generate a large design library of porous structures, auxetic meshes and cylinders, or perfusable constructs. By deploying finite cell modeling within the algorithmic design framework, large arrays of selected auxetic designs can be computationally modeled. Finally, the design schemes are used in conjunction with new approaches for multi-material volumetric printing based on thiol-ene photoclick chemistry to rapidly fabricate complex heterogeneous shapes. Collectively, the new design, modeling and fabrication techniques can be used toward a wide spectrum of products such as actuators, biomedical implants and grafts, or tissue and disease models.

A review of materials used in tomographic volumetric additive manufacturing

Volumetric additive manufacturing is a novel fabrication method allowing rapid, freeform, layer-less 3D printing. Analogous to computer tomography (CT), the method projects dynamic light patterns into a rotating vat of photosensitive resin. These light patterns build up a three-dimensional energy dose within the photosensitive resin, solidifying the volume of the desired object within seconds. Departing from established sequential fabrication methods like stereolithography or digital light printing, volumetric additive manufacturing offers new opportunities for the materials that can be used for printing. These include viscous acrylates and elastomers, epoxies (and orthogonal epoxy-acrylate formulations with spatially controlled stiffness) formulations, tunable stiffness thiol-enes and shape memory foams, polymer derived ceramics, silica-nanocomposite based glass, and gelatin-based hydrogels for cell-laden biofabrication. Here we review these materials, highlight the challenges to adapt them to volumetric additive manufacturing, and discuss the perspectives they present.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at10.1557/s43579-023-00447-x.

Metric Learning in Histopathological Image Classification: Opening the Black Box

The application of machine learning techniques to histopathology images enables advances in the field, providing valuable tools that can speed up and facilitate the diagnosis process. The classification of these images is a relevant aid for physicians who have to process a large number of images in long and repetitive tasks. This work proposes the adoption of metric learning that, beyond the task of classifying images, can provide additional information able to support the decision of the classification system. In particular, triplet networks have been employed to create a representation in the embedding space that gathers together images of the same class while tending to separate images with different labels. The obtained representation shows an evident separation of the classes with the possibility of evaluating the similarity and the dissimilarity among input images according to distance criteria. The model has been tested on the BreakHis dataset, a reference and largely used dataset that collects breast cancer images with eight pathology labels and four magnification levels. Our proposed classification model achieves relevant performance on the patient level, with the advantage of providing interpretable information for the obtained results, which represent a specific feature missed by the all the recent methodologies proposed for the same purpose.

pH-sensing hybrid hydrogels for non-invasive metabolism monitoring in tumor spheroids

The constant increase in cancer incidence and mortality pushes biomedical research towards the development of in vitro 3D systems able to faithfully reproduce and effectively probe the tumor microenvironment. Cancer cells interact with this complex and dynamic architecture, leading to peculiar tumor-associated phenomena, such as acidic pH conditions, rigid extracellular matrix, altered vasculature, hypoxic condition. Acidification of extracellular pH, in particular, is a well-known feature of solid tumors, correlated to cancer initiation, progression, and resistance to therapies. Monitoring local pH variations, non-invasively, during cancer growth and in response to drug treatment becomes extremely important for understanding cancer mechanisms. Here, we describe a simple and reliable pH-sensing hybrid system, based on a thermoresponsive hydrogel embedding optical pH sensors, that we specifically apply for non-invasive and accurate metabolism monitoring in colorectal cancer (CRC) spheroids. First, the physico-chemical properties of the hybrid sensing platform, in terms of stability, rheological and mechanical properties, morphology and pH sensitivity, were fully characterized. Then, the proton gradient distribution in the spheroids proximity, in the presence or absence of drug treatment, was quantified over time by time lapse confocal light scanning microscopy and automated segmentation pipeline, highlighting the effects of the drug treatment in the extracellular pH. In particular, in the treated CRC spheroids the acidification of the microenvironment resulted faster and more pronounced over time. Moreover, a pH gradient distribution was detected in the untreated spheroids, with more acidic values in proximity of the spheroids, resembling the cell metabolic features observed in vivo in the tumor microenvironment. These findings promise to shed light on mechanisms of regulation of proton exchanges by cellular metabolism being essential for the study of solid tumors in 3D in vitro models and the development of personalized medicine approaches.

Quantifying heterogeneity to drug response in cancer-stroma kinetics

A crucial challenge in medicine is choosing which drug (or combination) will be the most advantageous for a particular patient. Usually, drug response rates differ substantially, and the reasons for this response unpredictability remain ambiguous. Consequently, it is central to classify features that contribute to the observed drug response variability. Pancreatic cancer is one of the deadliest cancers with limited therapeutic achievements due to the massive presence of stroma that generates an environment that enables tumor growth, metastasis, and drug resistance. To understand the cancer-stroma cross talk within the tumor microenvironment and to develop personalized adjuvant therapies, there is a necessity for effective approaches that offer measurable data to monitor the effect of drugs at the single-cell level. Here, we develop a computational approach, based on cell imaging, that quantifies the cellular cross talk between pancreatic tumor cells (L3.6pl or AsPC1) and pancreatic stellate cells (PSCs), coordinating their kinetics in presence of the chemotherapeutic agent gemcitabine. We report significant heterogeneity in the organization of cellular interactions in response to the drug. For L3.6pl cells, gemcitabine sensibly decreases stroma-stroma interactions but increases stroma-cancer interactions, overall enhancing motility and crowding. In the AsPC1 case, gemcitabine promotes the interactions among tumor cells, but it does not affect stroma-cancer interplay, possibly suggesting a milder effect of the drug on cell dynamics.

From Free-Radical to Radical-Free: A Paradigm Shift in Light-Mediated Biofabrication

In recent years, the development of novel photocrosslinking strategies and photoactivatable materials has stimulated widespread use of light-mediated biofabrication techniques. However, despite great progress toward more efficient and biocompatible photochemical strategies, current photoresins still rely on photoinitiators (PIs) producing radical-initiating species to trigger the so-called free-radical crosslinking/polymerization. In the context of bioprinting, where cells are encapsulated in the bioink, the presence of radicals raises concerns of potential cytotoxicity. In this work, a universal, radical-free (RF) photocrosslinking strategy to be used for light-based technologies is presented. Leveraging RF uncaging mechanisms and Michael addition, cell-laden constructs are photocrosslinked by means of one- and two-photon excitation with high biocompatibility. A hydrophilic coumarin-based group is used to cage a universal RF photocrosslinker based on 4-arm-PEG-thiol (PEG4SH). Upon light exposure, thiols are uncaged and react with an alkene counterpart to form a hydrogel. RF photocrosslinker is shown to be highly stable, enabling potential for off-the-shelf products. While PI-based systems cause a strong upregulation of reactive oxygen species (ROS)-associated genes, ROS are not detected in RF photoresins. Finally, optimized RF photoresin is successfully exploited for high resolution two-photon stereolithography (2P-SL) using remarkably low polymer concentration (<1.5%), paving the way for a shift toward radical-free light-based bioprinting.

Filamented Light (FLight) Biofabrication of Highly Aligned Tissue-Engineered Constructs

Cell-laden hydrogels used in tissue engineering generally lack sufficient 3D topographical guidance for cells to mature into aligned tissues. A new strategy called filamented light (FLight) biofabrication rapidly creates hydrogels composed of unidirectional microfilament networks, with diameters on the length scale of single cells. Due to optical modulation instability, a light beam is divided optically into FLight beams. Local polymerization of a photoactive resin is triggered, leading to local increase in refractive index, which itself creates self-focusing waveguides and further polymerization of photoresin into long hydrogel microfilaments. Diameter and spacing of the microfilaments can be tuned from 2 to 30 µm by changing the coherence length of the light beam. Microfilaments show outstanding cell instructive properties with fibroblasts, tenocytes, endothelial cells, and myoblasts, influencing cell alignment, nuclear deformation, and extracellular matrix deposition. FLight is compatible with multiple types of photoresins and allows for biofabrication of centimeter-scale hydrogel constructs with excellent cell viability within seconds (<10 s per construct). Multidirectional microfilaments are achievable within a single hydrogel construct by changing the direction of FLight projection, and complex multimaterial/multicellular tissue-engineered constructs are possible by sequentially exchanging the cell-laden photoresin. FLight offers a transformational approach to developing anisotropic tissues using photo-crosslinkable biomaterials.

Macroporous Aligned Hydrogel Microstrands for 3D Cell Guidance

Tissue engineering strongly relies on the use of hydrogels as highly hydrated 3D matrices to support the maturation of laden cells. However, because of the lack of microarchitecture and sufficient porosity, common hydrogel systems do not provide physical cell-instructive guidance cues and efficient transport of nutrients and oxygen to the inner part of the construct. A controlled, organized cellular alignment and resulting alignment of secreted ECM are hallmarks of muscle, tendons, and nerves and play an important role in determining their functional properties. Although several strategies to induce cellular alignment have been investigated in 2D systems, the generation of cell-instructive 3D hydrogels remains a challenge. Here, we report on the development of a simple and scalable method to efficiently generate highly macroporous constructs featuring aligned guidance cues. A precross-linked bulk hydrogel is pressed through a grid with variable opening sizes, thus deconstructing it into an array of aligned, high aspect ratio microgels (microstrands) with tunable diameter that are eventually stabilized by a second photoclick cross-linking step. This method has been investigated and optimized both in silico and in vitro, thereby leading to conditions with excellent viability and organized cellular alignment. Finally, as proof of concept, the method has been shown to direct aligned muscle tissue maturation. These findings demonstrate the 3D physical guidance potential of our system, which can be used for a variety of anisotropic tissues and applications.

A pH-sensor scaffold for mapping spatiotemporal gradients in three-dimensional in vitro tumour models

The detection of extracellular pH at single cell resolution is challenging and requires advanced sensibility. Sensing pH at high spatial and temporal resolution might provide crucial information in understanding the role of pH and its fluctuations in a wide range of physio-pathological cellular processes, including cancer. Here, a method to embed silica-based fluorescent pH sensors into alginate-based three-dimensional (3D) microgels tumour models, coupled with a computational method for fine data analysis, is presented. By means of confocal laser scanning microscopy, live-cell time-lapse imaging of 3D alginate microgels was performed and the extracellular pH metabolic variations were monitored in both in vitro 3D mono- and 3D co-cultures of tumour and stromal pancreatic cells. The results show that the extracellular pH is cell line-specific and time-dependent. Moreover, differences in pH were also detected between 3D monocultures versus 3D co-cultures, thus suggesting the existence of a metabolic crosstalk between tumour and stromal cells. In conclusion, the system has the potential to image multiple live cell types in a 3D environment and to decipher in real-time their pH metabolic interplay under controlled experimental conditions, thus being also a suitable platform for drug screening and personalized medicine.

Fully Automated Computational Approach for Precisely Measuring Organelle Acidification with Optical pH Sensors

pH balance and regulation within organelles are fundamental to cell homeostasis and proliferation. The ability to track pH in cells becomes significantly important to understand these processes in detail. Fluorescent sensors based on micro- and nanoparticles have been applied to measure intracellular pH; however, an accurate methodology to precisely monitor acidification kinetics of organelles in living cells has not been established, limiting the scope of this class of sensors. Here, silica-based fluorescent microparticles were utilized to probe the pH of intracellular organelles in MDA-MB-231 and MCF-7 breast cancer cells. In addition to the robust, ratiometric, trackable, and bioinert pH sensors, we developed a novel dimensionality reduction algorithm to automatically track and screen massive internalization events of pH sensors. We found that the mean acidification time is comparable among the two cell lines (ΔT_MCF-7 = 16.3 min; ΔT_MDA-MB-231 = 19.5 min); however, MCF-7 cells showed a much broader heterogeneity in comparison to MDA-MB-231 cells. The use of pH sensors and ratiometric imaging of living cells in combination with a novel computational approach allow analysis of thousands of events in a computationally inexpensive and faster way than the standard routes. The reported methodology can potentially be used to monitor pH as well as several other parameters associated with endocytosis.

Factors associated with fertility abnormalities in women with systemic lupus erythematosus: a systematic review and meta-analysis

BACKGROUND

Fertility is thought to be not affected in women with systemic lupus erythematosus (SLE), however disease-related factors, psychosocial effects of chronic disease, as well as medications exposure might impair gonadal function.

OBJECTIVE

This systematic literature review (SLR) aimed to explore clinical, hormonal, serological and treatment factors associated with fertility outcomes in women of childbearing age with SLE.

METHODS

This SLR was conducted following the Preferred Reporting Items for systematic reviews and Meta-analysis (PRISMA) statement. All articles available in English (1972 - 30th April 2021) in Pubmed, EMBASE, Scopus and Cochrane Library were screened. Study selection and data collection were performed by two independent reviewers. All data were extracted using a standardized template. The risk of bias of the included studies was assessed using the NIH risk-of-bias tool.

RESULTS

Of 789 abstracts evaluated, we included in this review 46 studies, of which 1 SLR, 16 cross-sectional studies, 18 cohort studies, 10 observational studies and 1 case-series, with data pertaining to 4704 patients (mean age 31.5 ± 3.7 years, disease duration 83.27 ± 38.3 months). Definitions of premature ovarian failure (POF) adopted in the studies varied in terms of the number of months of amenorrhea considered and the age of onset of amenorrhea. Clinical factors associated with the development of POF were older age at the time of initiation of therapy, and older age at the onset of SLE disease. Cyclophosphamide exposure (CYC) and its cumulative dose influenced gonadal function in SLE women, leading to amenorrhoea and POF, as reported in 19 studies. Mycophenolate, azathioprine, calcineurin inhibitors and steroids associated with a lower risk of POF compared to CYC. POF was less frequent in patients co-treated with CYC and gonadotropin-releasing hormone analogues (GnRH-a) compared with patients not receiving GnRH-a (risk ratio 0.798, 95%-CI [0.1417; 0.5525]). 11 studies evaluated the impact of damage accrual and disease activity on ovarian reserve with conflicting evidence. Finally, 18 studies investigated exposure to hormonal and serological factors and, among others, neither Anti-Müllerian Hormone nor anti-corpus luteum antibodies were associated with POF.

CONCLUSION

The strongest evidence regarding management factors associated with fertility in SLE women of childbearing age remains the treatment with CYC, as well as its cumulative dosage. Hormonal and serological factors appeared not to impact fertility outcomes, but they might be used as a surrogate of fertility, especially during the treatment with disease-specific drugs.

Optimized Photoclick (Bio)Resins for Fast Volumetric Bioprinting

Volumetric printing (VP) is a light-mediated technique enabling printing of complex, low-defect 3D objects within seconds, overcoming major drawbacks of layer-by-layer additive manufacturing. An optimized photoresin is presented for VP in the presence of cells (volumetric bioprinting) based on fast thiol-ene step-growth photoclick crosslinking. Gelatin-norbornene (Gel-NB) photoresin shows superior performance, both in physicochemical and biocompatibility aspects, compared to (meth-)acryloyl resins. The extremely efficient thiol-norbornene reaction produces the fastest VP reported to date (≈10 s), with significantly lower polymer content, degree of substitution (DS), and radical species, making it more suitable for cell encapsulation. This approach enables the generation of cellular free-form constructs with excellent cell viability (≈100%) and tissue maturation potential, demonstrated by development of contractile myotubes. Varying the DS, polymer content, thiol-ene ratio, and thiolated crosslinker allows fine-tuning of mechanical properties over a broad stiffness range (≈40 Pa to ≈15 kPa). These properties are achieved through fast and scalable methods for producing Gel-NB with inexpensive, off-the-shelf reagents that can help establish it as the gold standard for light-mediated biofabrication techniques. With potential applications from high-throughput bioprinting of tissue models to soft robotics and regenerative medicine, this work paves the way for exploitation of VPs unprecedented capabilities.

76 PREDICTIVE MODEL FOR MOBILITY DECLINE: INDIVIDUAL TRIAL MISTAKE THRESHOLDS IN SUSTAINED ATTENTION TO RESPONSE TASK (SART)

Background

The Sustained Attention to Response Task (SART) is a standard computer-based cognitive test designed to measure the sustained attention, fundamental for completing tasks that require supervision over time (Robertson et al., 1997). However, commonly used average features may result in loss of information and data misinterpretation, leading to inability to detect clinically expected associations (O’Halloran et al., 2014).

Methods

Here, we present a new method to visualise the full information obtained from the SART test, ordering by age, and categorising in groups based on mobility status in a large population-based study of ageing in Ireland. A new threshold, derived from the visualisation and based on the individual trial number of mistakes, was employed to individuate poorer SART performances, and to predict mobility and cognitive decline after 4 years in binary logistic regression models.

Results

Raw SART data were available for 4,864 participants aged 50 years and over at baseline. The new variable bad performances, expressing the number of SART trials with at least 4 mistakes, was the most significant predictor of mobility decline, defined as the transition from Timed Up-and-Go (TUG) &lt; 12 to TUG ≥12 seconds (Odds Ratio (OR) = 1.29; 95% Confidence Interval (CI) 1.14–1.46; p &lt; 0.001), and the only significant predictor of new falls (OR = 1.11; 95% CI 1.03–1.21; p = 0.011) compared to traditional SART variables in models adjusted for multiple covariates. No SART-related variables resulted significant predictors of cognitive decline, defined as a decrease of at least 2 points in the Mini-Mental State Examination (MMSE) score.

Conclusion

This multimodal visualisation and the new threshold approach could help clinicians to easily develop relevant hypotheses, and better identify subjects at higher risk of future mobility decline.

136 ASSOCIATIONS OF FRAILTY WITH CONSECUTIVE GAIT SPEED TRAILS MEASURED BOTH WITH AND WITHOUT ADDITIONAL STRESSORS

Background

Frailty is associated with gait speed and is defined as increased vulnerability to stressors. While usual gait speed is often measured, gait speed under additional stressors such as simultaneously reciting alternate letters of the alphabet (cognitive dual task) or walking at maximum pace are also measured. Consecutive trials may introduce an additional temporal stressor and we hypothesise that frailty may be associated with a greater reduction in walking speed across trials.

Methods

Data from community-dwelling adults aged 50+ years at Wave 3 of The Irish Longitudinal Study on Ageing were utilized. Using a 32-item frailty index (FI) we derived non-frail, pre-frail and frail groups. Gait speeds were measured using a 4.88 m walkway (GAITRite, CIR Systems, NY, USA). We examined differences in gait speed between two consecutive walks in three conditions (usual pace, cognitive dual task, and maximum pace) for the entire cohort, and by frailty group. Related-samples Wilcoxon signed rank tests were employed, with statistical significance set at P &lt; 0.05.

Results

For the entire cohort, walk 2 speed for usual and cognitive conditions was higher by 1.0 cm/s (N = 4,097) and 1.1 cm/s (N = 3,927) respectively, and lower by 1.9 cm/s for maximum (N = 3,926). Stratified by FI, all groups walked more quickly in normal (1.0, 1.1, 1.2, respectively) and cognitive (1.3, 0.8, 0.5), and more slowly in maximum (−2.2, −1.6, −1.0).

Conclusion

In our analyses, higher frailty seemed to be associated with a higher increase for the usual walk, a smaller increase for the cognitive walk, and a smaller decrease in maximum speed. The clinical significance of the differences was very small. However, our results support that in research and clinical practice, frailty by FI should not be expected to lead to a different pattern of gait speed change across consecutive trials.

81 LONGER CHAIR-STAND TIME IS ASSOCIATED WITH ORTHOSTATIC INTOLERANCE IN AN OLDER IRISH POPULATION

Background

Hospital admissions for orthostatic hypotension (OH) have risen more than two-fold in the past ten years. OH can lead to orthostatic intolerance (OI), and both OH and OI are common causes of falls and injuries in older persons. Sarcopenia is also common in older persons and associated with adverse health outcomes. The 5-chair stand test (5-CST) can be used as a marker of sarcopenia and a cut-off of 15 s has been proposed. We hypothesized that those with a worse performance on the 5-CST would be at greater risk of OH and sought to investigate this in an older Irish population cohort study.

Methods

5-CST was measured in keeping with a standardised protocol. Beat-to-beat blood pressure was measured with the Finometer device according to the active stand protocol. Multivariable logistic regressions were performed to investigate the associations between OH at 40 seconds after standing (OH40), OI (dizziness after standing), and 5-CST time. Potential confounders were controlled for in the model including age, sex, education, body mass index and medications.

Results

Data from 3,119 participants were available for analysis. Mean age was 63.8 years, 55% were female, 25% took longer than 15s on the 5-CST and mean baseline blood pressure was 141/76 mmHg. Proportion of OH40 was 12.5% and 4.4% reported OI. In the multivariable model, OH40 was not independently associated with 5-CST time after controlling for age (p &gt; 0.05). Worse performance on the chair stands test was however an independent predictor of OI (odds ratio 1.06, p = 0.039).

Conclusion

Longer time taken on the 5-CST, a marker of sarcopenia, was an independent predictor of OI in a large population study. The relationship between sarcopenia and orthostatic blood pressure response is not well elucidated. We plan to further investigate this area in a future clinical cohort.

123 ACUTE-PHASE BED-REST DURATION WAS ASSOCIATED WITH LOWER GRIP STRENGTH IN A POST-COVID-19 COHORT

Background

Though age-related muscle loss is traditionally associated with older cohorts, strong evidence suggests a life-spanning precipitation of decreasing muscle mass and strength beginning as early as the fourth decade of life, with established deleterious consequences for later-life morbidity and mortality. Periods of low activity and bed rest (LA/BR) can further compound this depletion of muscle strength. Our aim was to examine such associations in a post-COVID-19 cohort.

Methods

Participants reporting ongoing symptomatology and fatigue post COVID-19 underwent assessments of grip strength via hand-held dynamometry (2 measures on each hand). Demographics of COVID-19 illness, including time since diagnosis, duration of LA/BR during acute illness, and levels of fatigue were captured via self-reported questionnaires. Independent predictors of mean grip strength were investigated using a linear regression model.

Results

Forty-nine participants underwent assessments (69% female, mean age 44(12) years). At the time of assessment, days post COVID-19 diagnosis ranged from 39–522 (mean 262(140)). The mean self-reported period of LA/BR during the acute illness was 15(18) days. In general, participants reported significant levels of fatigue (median Chalder Fatigue Scale score 22(8)). Mean grip strength was 41.3(6.3) Kg for men and 22.8(6.7) Kg for women. When predictors of grip strength were investigated, an increased duration of LA/BR was found to be associated with lower grip strength, independently of age, gender, time since COVID-19 diagnosis, and self-reported fatigue (Beta = −0.158, 95% Confidence Interval − 0.242 to −0.074, p = 0.001).

Conclusion

In this cohort, every day of LA/BR during acute COVID-19 illness was independently associated with subsequent lower grip strength of approximately 150 g. These results underscore the importance of early mobilization and discouraging bed rest in the acute phase of COVID-19. Patients who are isolating should be encouraged to maintain physical activity and muscle strength as part of a modified isolation-friendly rehabilitation programme.

78 HIGHER NEUROVASCULAR SIGNAL ENTROPY IS ASSOCIATED WITH ACCELERATED BRAIN AGEING

Background

Often chronological age is not the most accurate marker of an individual’s health status since ageing is a heterogeneous process across individuals. Machine learning can be used to quantify the relationship between structural brain MRI data and chronological age, to estimate an individual’s ‘brain age’, which, when subtracted from chronological age, provides a brain predicted-age difference score (BrainPAD) [1]. BrainPAD reflects the biological ageing of the brain. Increased complexity in neurovascular signals has been shown to be associated with poorer cognitive performance and physical frailty [2]. The aim of this study was to investigate associations between the complexity of frontal-lobe oxygenation (tissue saturation index (TSI)) data and BrainPAD in a cohort of older community-dwelling adults.

Methods

To calculate BrainPAD, machine learning was applied to 1,359 T1-weighted MRI brain scans from various open-access repositories, and this model was subsequently applied to MRI data acquired from the study cohort. TSI was non-invasively measured in the left frontal lobe using near-infrared spectroscopy. TSI data were acquired continuously during five minutes of supine rest and the last minute was utilized in this analysis. The complexity of TSI signals was quantified using sample entropy (SampEn). Multivariable linear regression was employed, controlling for age, sex, education, antihypertensive medications, diabetes, cardiovascular conditions, smoking, alcohol, depression, BMI, physical activity, and blood pressure.

Results

Complete data were available for 397 individuals (age: 67.9 ± 7.7 years; 53.7% female). An increase in TSI SampEn of 0.1 was associated with an increase in BrainPAD of 0.9 years (P = 0.007, 95%CIs: 0.3 to 1.6). Similar results were found with and without the inclusion of chronological age in the models.

Conclusion

This study reports significant associations between higher complexity in peripherally measured frontal lobe oxygenation concentration and accelerated brain ageing.

References

1. Boyle R. et al. Brain Imaging and Behavior. 15,327–345 (2021) https://doi.org/10.1007/s11682-020-00260-3.

2. Knight S. et al. Entropy. 23(1):4 (2021) https://doi.org/10.3390/e23010004.

GRASP55 regulates intra-Golgi localization of glycosylation enzymes to control glycosphingolipid biosynthesis

The Golgi apparatus, the main glycosylation station of the cell, consists of a stack of discontinuous cisternae. Glycosylation enzymes are usually concentrated in one or two specific cisternae along the cis‐trans axis of the organelle. How such compartmentalized localization of enzymes is achieved and how it contributes to glycosylation are not clear. Here, we show that the Golgi matrix protein GRASP55 directs the compartmentalized localization of key enzymes involved in glycosphingolipid (GSL) biosynthesis. GRASP55 binds to these enzymes and prevents their entry into COPI‐based retrograde transport vesicles, thus concentrating them in the trans‐Golgi. In genome‐edited cells lacking GRASP55, or in cells expressing mutant enzymes without GRASP55 binding sites, these enzymes relocate to the cis‐Golgi, which affects glycosphingolipid biosynthesis by changing flux across metabolic branch points. These findings reveal a mechanism by which a matrix protein regulates polarized localization of glycosylation enzymes in the Golgi and controls competition in glycan biosynthesis.

Highly Sensitive Fluorescent pH Microsensors Based on the Ratiometric Dye Pyranine Immobilized on Silica Microparticles

Pyranine (HPTS) is a remarkably interesting pH-sensitive dye that has been used for plenty of applications. Its high quantum yield and extremely sensitive ratiometric fluorescence against pH change makes it a very favorable for pH-sensing applications and the development of pH nano-/microsensors. However, its strong negative charge and lack of easily modifiable functional groups makes it difficult to use with charged substrates such as silica. This study reports a methodology for noncovalent HPTS immobilization on silica microparticles that considers the retention of pH sensitivity as well as the long-term stability of the pH microsensors. The study emphasizes the importance of surface charge for governing the sensitivity of the immobilized HPTS dye molecules on silica microparticles. The importance of the immobilization methodology, which preserves the sensitivity and stability of the microsensors, is also assessed.

Preparation and Characterization of Salt-Mediated Injectable Thermosensitive Chitosan/Pectin Hydrogels for Cell Embedding and Culturing

In recent years, growing attention has been directed to the development of 3D in vitro tissue models for the study of the physiopathological mechanisms behind organ functioning and diseases. Hydrogels, acting as 3D supporting architectures, allow cells to organize spatially more closely to what they physiologically experience in vivo. In this scenario, natural polymer hybrid hydrogels display marked biocompatibility and versatility, representing valid biomaterials for 3D in vitro studies. Here, thermosensitive injectable hydrogels constituted by chitosan and pectin were designed. We exploited the feature of chitosan to thermally undergo sol-gel transition upon the addition of salts, forming a compound that incorporates pectin into a semi-interpenetrating polymer network (semi-IPN). Three salt solutions were tested, namely, beta-glycerophosphate (βGP), phosphate buffer (PB) and sodium hydrogen carbonate (SHC). The hydrogel formulations (i) were injectable at room temperature, (ii) gelled at 37 °C and (iii) presented a physiological pH, suitable for cell encapsulation. Hydrogels were stable in culture conditions, were able to retain a high water amount and displayed an open and highly interconnected porosity and suitable mechanical properties, with Young's modulus values in the range of soft biological tissues. The developed chitosan/pectin system can be successfully used as a 3D in vitro platform for studying tissue physiopathology.

Highly Sensitive Fluorescent pH Microsensors Based on the Ratiometric Dye Pyranine Immobilized on Silica Microparticles

Invited for the cover of this issue are Anil Chandra, Loretta L. del Mercato and co-workers at the Institute of Nanotechnology of National Research Council and the University of Salento. The image depicts how negatively charged pH-sensitive pyranine (HPTS) molecules were successfully immobilized on silica microparticles (SMPs) without compromising the molecules' pH sensitivity. These resulting sensors can be used to measure pH in vitro and in vivo due to the cytocompatibility of HPTS molecules and SMPs. Read the full text of the article at 10.1002/chem.202101568.

Factor XIII Cross-Linked Adhesive Chitosan Hydrogels

Biomedical adhesives have been found to be an attractive alternative to suturing in several circumstances. However, to date most of the clinically approved formulations are based on synthetic and highly reactive toxic chemicals. In this work, we aimed to combine for the first time the bioactive properties of the cationic polysaccharide chitosan and its intrinsic electrostatic binding to negatively charged tissues with the biocompatible and clinically compliant enzymatic cross-linking scheme of fibrin glue. This synergistic activity led to the generation of a transglutaminase Factor XIII cross-linkable chitosan formulation with fast gelation kinetics, tunable mechanical properties, antibacterial activity, and strong adhesion to cartilage.

Golgi maturation-dependent glycoenzyme recycling controls glycosphingolipid biosynthesis and cell growth via GOLPH3

Glycosphingolipids are important components of the plasma membrane where they modulate the activities of membrane proteins including signalling receptors. Glycosphingolipid synthesis relies on competing reactions catalysed by Golgi-resident enzymes during the passage of substrates through the Golgi cisternae. The glycosphingolipid metabolic output is determined by the position and levels of the enzymes within the Golgi stack, but the mechanisms that coordinate the intra-Golgi localisation of the enzymes are poorly understood. Here, we show that a group of sequentially-acting enzymes operating at the branchpoint among glycosphingolipid synthetic pathways binds the Golgi-localised oncoprotein GOLPH3. GOLPH3 sorts these enzymes into vesicles for intra-Golgi retro-transport, acting as a component of the cisternal maturation mechanism. Through these effects, GOLPH3 controls the sub-Golgi localisation and the lysosomal degradation rate of specific enzymes. Increased GOLPH3 levels, as those observed in tumours, alter glycosphingolipid synthesis and plasma membrane composition thereby promoting mitogenic signalling and cell proliferation. These data have medical implications as they outline a novel oncogenic mechanism of action for GOLPH3 based on glycosphingolipid metabolism.

The Revolutionary Roads to Study Cell-Cell Interactions in 3D In Vitro Pancreatic Cancer Models

Pancreatic cancer, the fourth most common cancer worldwide, shows a highly unsuccessful therapeutic response. In the last 10 years, neither important advancements nor new therapeutic strategies have significantly impacted patient survival, highlighting the need to pursue new avenues for drug development discovery and design. Advanced cellular models, resembling as much as possible the original in vivo tumor environment, may be more successful in predicting the efficacy of future anti-cancer candidates in clinical trials. In this review, we discuss novel bioengineered platforms for anticancer drug discovery in pancreatic cancer, from traditional two-dimensional models to innovative three-dimensional ones.

CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification

BACKGROUND

Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data.

RESULTS

In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel levels are devoted to catching both non periodic and periodic DNA string features. A dense layer is devoted to their combination to give a final classification.

CONCLUSIONS

Results computed on public data sets of different organisms show that CORENup is a state of the art methodology for nucleosome positioning identification based on a Deep Neural Network architecture. The comparisons have been carried out using two groups of datasets, currently adopted by the best performing methods, and CORENup has shown top performance both in terms of classification metrics and elapsed computation time.

BITS2019: the sixteenth annual meeting of the Italian society of bioinformatics

The 16th Annual Meeting of the Bioinformatics Italian Society was held in Palermo, Italy, on June 26-28, 2019. More than 80 scientific contributions were presented, including 4 keynote lectures, 31 oral communications and 49 posters. Also, three workshops were organised before and during the meeting. Full papers from some of the works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting.

miRTissue ce: extending miRTissue web service with the analysis of ceRNA-ceRNA interactions

BACKGROUND

Non-coding RNAs include different classes of molecules with regulatory functions. The most studied are microRNAs (miRNAs) that act directly inhibiting mRNA expression or protein translation through the interaction with a miRNAs-response element. Other RNA molecules participate in the complex network of gene regulation. They behave as competitive endogenous RNA (ceRNA), acting as natural miRNA sponges to inhibit miRNA functions and modulate the expression of RNA messenger (mRNA). It became evident that understanding the ceRNA-miRNA-mRNA crosstalk would increase the functional information across the transcriptome, contributing to identify new potential biomarkers for translational medicine.

RESULTS

We present miRTissue ce, an improvement of our original miRTissue web service. By introducing a novel computational pipeline, miRTissue ce provides an easy way to search for ceRNA interactions in several cancer tissue types. Moreover it extends the functionalities of previous miRTissue release about miRNA-target interaction in order to provide a complete insight about miRNA mediated regulation processes. miRTissue ce is freely available at http://tblab.pa.icar.cnr.it/mirtissue.html .

CONCLUSIONS

The study of ceRNA networks and its dynamics in cancer tissue could be applied in many fields of translational biology, as the investigation of new cancer biomarker, both diagnostic and prognostic, and also in the investigation of new therapeutic strategies of intervention. In this scenario, miRTissue ce can offer a powerful instrument for the analysis and characterization of ceRNA-ceRNA interactions in different tissue types, representing a fundamental step in order to understand more complex regulation mechanisms.

Primary headache in childhood associated with psychiatric disturbances: an update

OBJECTIVE

Primary headache disorders in children are one of the most prominent topics in the pediatric neurology literature. However, there are many unsolved aspects, including the conditions associated with migraine. The present study aims to report on the frequency of behavioral comorbidities in the setting of primary headache in childhood.

PATIENTS AND METHODS

In this study, we enlisted 475 children (290 males and 185 females; ratio 1.6:1), aged 4 to 14 years, who were affected by primary headache. In direct interviews, children and parents gave information on the association of their headache with, attention-deficit/hyperactivity disorder, learning disabilities, tics, anxiety, depression, and obsessive-compulsive disorder. Other 475 children with no history of headache or recognized neurological conditions were matched for age, sex, race, and socioeconomic status and were used as controls.

RESULTS

A significant association of primary headache was found with anxiety and depression (p-value <0.001); overall, behavioral disorders were more common in children who experienced headache than in controls (p-value <0.001).

CONCLUSIONS

Primary headache in children is not associated with most of the common behavioral conditions. On the contrary, there was a significant association with anxiety and depression, as reported in adults.

Morphogenesis Guided by 3D Patterning of Growth Factors in Biological Matrices

Three-dimensional (3D) control over the placement of bioactive cues is fundamental to understand cell guidance and develop engineered tissues. Two-photon patterning (2PP) provides such placement at micro- to millimeter scale, but nonspecific interactions between proteins and functionalized extracellular matrices (ECMs) restrict its use. Here, a 2PP system based on nonfouling hydrophilic photocages and Sortase A (SA)-based enzymatic coupling is presented, which offers unprecedented orthogonality and signal-to-noise ratio in both inert hydrogels and complex mammalian matrices. Improved photocaged peptide synthesis and protein functionalization protocols with broad applicability are introduced. Importantly, the method enables 2PP in a single step in the presence of fragile biomolecules and cells, and is compatible with time-controlled growth factor presentation. As a corollary, the guidance of axons through 3D-patterned nerve growth factor (NGF) within brain-mimetic ECMs is demonstrated. The approach allows for the interrogation of the role of complex signaling molecules in 3D matrices, thus helping to better understand biological guidance in tissue development and regeneration.

Author Correction: Constitutive alterations in vesicular trafficking increase the sensitivity of cells from celiac disease patients to gliadin

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Wearable, Fiber-less, Multi-Channel System for Continuous Wave Functional Near Infrared Spectroscopy Based on Silicon Photomultipliers Detectors and Lock-In Amplification

Development and in-vivo validation of a Continuous Wave (CW) functional Near Infrared Spectroscopy (fNIRS) system is presented. The system is wearable, fiber-less, multi-channel (16×16, 256 channels) and expandable and it relies on silicon photomultipliers (SiPMs) for light detection. SiPMs are inexpensive, low voltage and resilient semiconductor light detectors, whose performances are analogous to photomultiplier tubes (PMTs). The advantage of SiPMs with respect to PMTs is that they allow direct contact with the scalp and avoidance of optical fibers. In fact, the coupling of SiPMs and light emitting diodes (LEDs) allows the transfer of the analog signals to and from the scalp through thin electric cables that greatly increase the system flexibility. Moreover, the optical probes, mechanically resembling electroencephalographic electrodes, are robust against motion artifacts. In order to increase the signal-to-noise-ratio (SNR) of the fNIRS acquisition and to decrease ambient noise contamination, a digital lock-in technique was implemented through LEDs modulation and SiPMs signal processing chain. In-vivo validation proved the system capabilities of detecting functional brain activity in the sensorimotor cortices. When compared to other state-of-the-art wearable fNIRS systems, the single photon sensitivity and dynamic range of SiPMs can exploit the long and variable interoptode distances needed for estimation of brain functional hemodynamics using CW-fNIRS.

Auto-regulation of Secretory Flux by Sensing and Responding to the Folded Cargo Protein Load in the Endoplasmic Reticulum

Maintaining the optimal performance of cell processes and organelles is the task of auto-regulatory systems. Here we describe an auto-regulatory device that helps to maintain homeostasis of the endoplasmic reticulum (ER) by adjusting the secretory flux to the cargo load. The cargo-recruiting subunit of the coatomer protein II (COPII) coat, Sec24, doubles as a sensor of folded cargo and, upon cargo binding, acts as a guanine nucleotide exchange factor to activate the signaling protein Gα12 at the ER exit sites (ERESs). This step, in turn, activates a complex signaling network that activates and coordinates the ER export machinery and attenuates proteins synthesis, thus preventing large fluctuations of folded and potentially active cargo that could be harmful to the cell or the organism. We call this mechanism AREX (autoregulation of ER export) and expect that its identification will aid our understanding of human physiology and diseases that develop from secretory dysfunction.

MiRNA therapeutics based on logic circuits of biological pathways

BACKGROUND

In silico experiments, with the aid of computer simulation, speed up the process of in vitro or in vivo experiments. Cancer therapy design is often based on signalling pathway. MicroRNAs (miRNA) are small non-coding RNA molecules. In several kinds of diseases, including cancer, hepatitis and cardiovascular diseases, they are often deregulated, acting as oncogenes or tumor suppressors. miRNA therapeutics is based on two main kinds of molecules injection: miRNA mimics, which consists of injection of molecules that mimic the targeted miRNA, and antagomiR, which consists of injection of molecules inhibiting the targeted miRNA. Nowadays, the research is focused on miRNA therapeutics. This paper addresses cancer related signalling pathways to investigate miRNA therapeutics.

RESULTS

In order to prove our approach, we present two different case studies: non-small cell lung cancer and melanoma. KEGG signalling pathways are modelled by a digital circuit. A logic value of 1 is linked to the expression of the corresponding gene. A logic value of 0 is linked to the absence (not expressed) gene. All possible relationships provided by a signalling pathway are modelled by logic gates. Mutations, derived according to the literature, are introduced and modelled as well. The modelling approach and analysis are widely discussed within the paper. MiRNA therapeutics is investigated by the digital circuit analysis. The most effective miRNA and combination of miRNAs, in terms of reduction of pathogenic conditions, are obtained. A discussion of obtained results in comparison with literature data is provided. Results are confirmed by existing data.

CONCLUSIONS

The proposed study is based on drug discovery and miRNA therapeutics and uses a digital circuit simulation of a cancer pathway. Using this simulation, the most effective combination of drugs and miRNAs for mutated cancer therapy design are obtained and these results were validated by the literature. The proposed modelling and analysis approach can be applied to each human disease, starting from the corresponding signalling pathway.

Translation of genome to glycome: role of the Golgi apparatus

Glycans are one of the four biopolymers of the cell and they play important roles in cellular and organismal physiology. They consist of both linear and branched structures and are synthesized in a nontemplated manner in the secretory pathway of mammalian cells with the Golgi apparatus playing a key role in the process. In spite of the absence of a template, the glycans synthesized by a cell are not a random collection of possible glycan structures but a distribution of specific glycans in defined quantities that is unique to each cell type (Cell type here refers to distinct cell forms present in an organism that can be distinguished based on morphological, phenotypic and/or molecular criteria.) While information to produce cell type-specific glycans is encoded in the genome, how this information is translated into cell type-specific glycome (Glycome refers to the quantitative distribution of all glycan structures present in a given cell type.) is not completely understood. We summarize here the factors that are known to influence the fidelity of glycan biosynthesis and integrate them into known glycosylation pathways so as to rationalize the translation of genetic information to cell type-specific glycome.

Analysis of HLA-G expression in renal tissue in lupus nephritis: a pilot study

BACKGROUND

The study aimed to investigate whether HLA-G antigen is expressed in the kidneys of patients affected by lupus nephritis (LN) and whether its detection in renal biopsies could be adopted as a marker of treatment response and prognosis.

METHODS

Thirty renal biopsies from patients with LN were selected and analyzed through immunohistochemistry. Laboratory and clinical data were retrospectively collected at baseline, 6 and 12 months and at the latest clinical appointment. A number of patients (63.3%) were treated with rituximab (RTX) +/- methylprednisolone in the induction phase. The expression of HLA-G in glomeruli, tubules and infiltrating cells was examined and compared between lupus patients who achieved either complete or partial renal response and those who did not respond to treatment.

RESULTS

HLA-G staining was observed in the glomeruli of 20 of 30 samples from patients with LN. The expression of the antigen was detected in podocytes, along glomerular capillary walls, on parietal glomerular epithelial cells and within the juxtaglomerular apparatus. Seventy per cent of patients whose glomeruli expressed HLA-G achieved partial or complete response at 6 months and 75% at the latest available follow up compared with 30% and 40%, respectively, of those who did not show any expression. The pattern of staining in tubules and infiltrating cells was highly variable precluding any clinical correlation.

CONCLUSION

This study demonstrates that HLA-G is expressed in renal tissue in LN. Our retrospective data suggest that its expression could correlate with response to treatment.

Hyperkinetic movement disorders in congenital disorders of glycosylation

BACKGROUND AND PURPOSE

Congenital disorders of glycosylation (CDG) represent an increasing number of rare inherited metabolic diseases associated with abnormal glycan metabolism and disease onset in infancy or early childhood. Most CDG are multisystemic diseases mainly affecting the central nervous system. The aim of the current study was to investigate hyperkinetic movement disorders in patients affected by CDG and to characterize phenomenology based on CDG subtypes.

METHODS

Subjects were identified from a cohort of patients with CDG who were referred to the University Hospital of Catania, Italy. Patients were evaluated by neurologists with expertise in movement disorders and videotaped using a standardized protocol.

RESULTS

A variety of hyperkinetic movement disorders was detected in eight unrelated CDG patients. Involuntary movements were generally observed early in childhood, maintaining a clinical stability over time. Distribution ranged from a generalized, especially in younger subjects, to a segmental/multifocal involvement. In patients with phosphomannomutase 2 CDG, the principal movement disorders included dystonia and choreo-athetosis. In patients affected by other CDG types, the movement disorders ranged from pure generalized chorea to mixed movement disorders including dystonia and complex stereotypies.

CONCLUSIONS

Hyperkinetic movement disorder is a key clinical feature in patients with CDG. CDG should be considered in the differential diagnosis of childhood-onset dyskinesia, especially when associated with ataxia, developmental delay, intellectual disability, autism or seizure disorder.

Constitutive alterations in vesicular trafficking increase the sensitivity of cells from celiac disease patients to gliadin

Celiac Disease (CD) is an autoimmune disease characterized by inflammation of the intestinal mucosa due to an immune response to wheat gliadins. Some gliadin peptides (e.g., A-gliadin P57-68) induce an adaptive Th1 pro-inflammatory response. Other gliadin peptides (e.g., A-gliadin P31-43) induce a stress/innate immune response involving interleukin 15 (IL15) and interferon α (IFN-α). In the present study, we describe a stressed/inflamed celiac cellular phenotype in enterocytes and fibroblasts probably due to an alteration in the early-recycling endosomal system. Celiac cells are more sensitive to the gliadin peptide P31-43 and IL15 than controls. This phenotype is reproduced in control cells by inducing a delay in early vesicular trafficking. This constitutive lesion might mediate the stress/innate immune response to gliadin, which can be one of the triggers of the gliadin-specific T-cell response.

The 2017 Network Tools and Applications in Biology (NETTAB) workshop: aims, topics and outcomes

The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Also, three tutorials were organised before and after the workshop. Full papers from some of the best works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting.

Robot-assisted resection of gastric duplication cysts in a child: a detailed case report

Gastric duplication cysts (GDCs) represent 4-9% of alimentary tract duplications. Early diagnosis and surgical excision are essential to avoid morbidity or neoplastic degeneration. Roboticassisted excision of GDCs has never been described in childhood. We report an asymptomatic male patient with 2 gastric cystic masses at ultrasonography (US)-study (diameter 25mm and 8mm), increasing in size at follow-up. At 20 months of age, magnetic- resonance-imaging-scan confirmed 2 round gastric masses (44×35mm and 16×12mm, respectively). Two months later, an elective robotic-assisted excision of GDCs was completed without complications. The patient was discharged at day 6 after procedure. Histology confirmed the diagnosis of GDCs. At a 2-year follow- up, US-study did not evidence any issue. In this first reported case of robotic-assisted cystectomy for CGD in childhood, the procedure seems safe, effective, and feasible. This approach improves the movements of the surgical instruments with better 3- D visualization in comparison with the laparoscopic approach.

Deep learning architectures for prediction of nucleosome positioning from sequences data

Background

Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several biological studies have shown that the nucleosome positioning influences the regulation of cell type-specific gene activities. Moreover, computational studies have shown evidence of sequence specificity concerning the DNA fragment wrapped into nucleosomes, clearly underlined by the organization of particular DNA substrings. As the main consequence, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using a sequence features representation.

Results

In this work, we propose a deep learning model for nucleosome identification. Our model stacks convolutional layers and Long Short-term Memories to automatically extract features from short- and long-range dependencies in a sequence. Using this model we are able to avoid the feature extraction and selection steps while improving the classification performances.

Conclusions

Results computed on eleven data sets of five different organisms, from Yeast to Human, show the superiority of the proposed method with respect to the state of the art recently presented in the literature.

Deep learning models for bacteria taxonomic classification of metagenomic data

Background

An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions. The above mentioned two sequencing technologies, SG and AMP, are used alternatively, for this reason in this work we propose a deep learning approach for taxonomic classification of metagenomic data, that can be employed for both of them.

Results

To test the proposed pipeline, we simulated both SG and AMP short-reads, from 1000 16S full-length sequences. Then, we adopted a k-mer representation to map sequences as vectors into a numerical space. Finally, we trained two different deep learning architecture, i.e., convolutional neural network (CNN) and deep belief network (DBN), obtaining a trained model for each taxon. We tested our proposed methodology to find the best parameters configuration, and we compared our results against the classification performances provided by a reference classifier for bacteria identification, known as RDP classifier. We outperformed the RDP classifier at each taxonomic level with both architectures. For instance, at the genus level, both CNN and DBN reached 91.3% of accuracy with AMP short-reads, whereas RDP classifier obtained 83.8% with the same data.

Conclusions

In this work, we proposed a 16S short-read sequences classification technique based on k-mer representation and deep learning architecture, in which each taxon (from phylum to genus) generates a classification model. Experimental results confirm the proposed pipeline as a valid approach for classifying bacteria sequences; for this reason, our approach could be integrated into the most common tools for metagenomic analysis. According to obtained results, it can be successfully used for classifying both SG and AMP data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2182-6) contains supplementary material, which is available to authorized users.