A document by David Dingli. Click on the document to view its contents.

Accurate prediction of protein secondary structure (alpha-helix, beta-strand and coil) is a crucial step for protein inter-residue contact prediction and ab initio tertiary structure prediction. In a previous study, we developed a deep belief network-based protein secondary structure method (DNSS1) and successfully advanced the prediction accuracy beyond 80%. In this work, we developed multiple advanced deep learning architectures (DNSS2) to further improve secondary structure prediction. The major improvements over the DNSS1 method include (i) designing and integrating six advanced one-dimensional deep convolutional/recurrent/residual/memory/fractal/inception networks to predict secondary structure, and (ii) using more sensitive profile features inferred from Hidden Markov model (HMM) and multiple sequence alignment (MSA). Most of the deep learning architectures are novel for protein secondary structure prediction. DNSS2 was systematically benchmarked on two independent test datasets with eight state-of-art tools and consistently ranked as one of the best methods. Particularly, DNSS2 was tested on the 82 protein targets of 2018 CASP13 experiment and achieved the best Q3 score of 83.74% and SOV score of 72.46%. DNSS2 is freely available at: https://github.com/multicom-toolbox/DNSS2.

Brain mineralocorticoid receptors (MR) mediate effects of aldosterone in relation to salt homeostasis, and of glucocorticoid stress hormones corticosteroids in the context of stress adaptation. Brain stem MRs respond to aldosterone, while forebrain MRs mediate rapid and delayed MR-mediated glucocorticoids effects in conjunction with the glucocorticoid receptor. MR-mediated effects depend on gender, genetic variations and environmental influences. Disturbed MR activity by chronic stress or in certain (endocrine) diseases can cause deleterious effects on affective state, cognitive and behavioural function in susceptible individuals. High MR activation may have protective effects in healthy individuals, whereas dysregulated high MR activity during a stress response would require treatment with mineralocorticoid receptor antagonists (MRAs). Here, we discuss recent pharmacological and genetic developments, from the molecular underpinnings of MR signaling and function, to pharmacological interventions in the clinic. Improved understanding of MR dependent pathways will help to improve glucocorticoid therapy, unwanted side effects and psychiatric symptoms.

γ-Glutamyl carboxylase (GGCX) catalyses γ-carboxylation of 15 different vitamin K dependent (VKD) proteins. Pathogenic variants in GGCX cause a rare hereditary bleeding disorder called Vitamin K dependent coagulation factor deficiency type 1 (VKCFD1). In addition to bleedings, some VKCFD1 patients develop skin laxity and skeletal dysmorphologies. However, the pathophysiological mechanisms underlying these non-haemorrhagic phenotypes remain elusive. Therefore, we analyzed the effect of 22 GGCX pathogenic variants on γ-carboxylation of six non-haemostatic VKD proteins (UCMA/GRP, MGP, BGLAP, GAS6, PRGP1, TMG4) in a GGCX-/- HEK293T cell line by a functional ELISA. We observed that biallelic deficiency to γ-carboxylate Gla-rich protein lead to the development of skin laxity. Markedly reduced level of γ-carboxylated MGP is crucial but not exclusive for causing facial dysmorphologies. Moreover, we identified the vitamin K hydroquinone binding site in GGCX in an in silico model by docking studies, which was further validated by functional assays. Variants affecting this site result into loss-of-function or severely diminished ability to γ-carboxylate VKD proteins and hence are involved in the most severe phenotypes. This genotype-phenotype analysis will help to develop new treatment options for VKCFD1 patients, where individualized therapy with γ-carboxylated VKD proteins may represent a promising strategy.

Summary: This study evaluates through modeling the possible individual and combined effect of three populational parameters of pathogens (reproduction rate; rate of novelty emergence; and propagule size) on the colonization of new host species – putatively the most fundamental process leading to the emergence of new infectious diseases. The results are analyzed under the theoretical framework of the Stockholm Paradigm using IBM simulations to better understand the evolutionary dynamics of the pathogen population and the possible role of Ecological Fitting. The simulations suggest that all three parameters positively influence the success of colonization of new hosts by a novel parasite population but contrary to the prevailing belief, the rate of novelty emergence (e.g. mutations) is the least important factor. Maximization of all parameters result in a synergetic facilitation of the colonization and emulates the expected scenario for pathogenic microorganisms. The simulations also provide theoretical support for the retention of the capacity of fast-evolving lineages to retro-colonize their previous host species/lineage by ecological fitting. Capacity is, thus, much larger than we can anticipate. Hence, the results support the empirical observations that opportunity of encounter (i.e. the breakdown in mechanisms for ecological isolation) is a fundamental determinant to the emergence of new associations – especially Emergent Infectious Diseases - and the dynamics of host exploration, as observed in SARS-CoV-2. Insights on the dynamics of Emergent Infectious Diseases derived from the simulations and from the Stockholm Paradigm are discussed.

Background: Few and small studies have described the management of immunomodulant/immunosuppressive therapies or phototherapy in atopic dermatitis (AD) patients during coronavirus disease 2019 (COVID-19) pandemic. Methods: A national registry, named DA-COVID-19 and involving 35 Italian dermatology units, was established in order to evaluate the impact of COVID-19 pandemic on the management of adult AD patients treated with systemic immunomodulant/immunosuppressive medications or phototherapy. Demographic and clinical data were obtained at different timepoints by teledermatology during COVID-19 pandemic, when regular visits were not allowed due to sanitary restrictions. Disease severity was assessed by both physician- and patient-reported assessment scores evaluating itch intensity, sleep disturbances, and AD severity. Results: A total of 1831 patients were included, with 1580/1831 (86.3%) continuing therapy during pandemic. Most patients were treated with dupilumab (86.1%, 1576/1831) that was interrupted in only 9.9% (156/1576) of cases, while systemic immunosuppressive compounds were more frequently withdrawn. Treatment interruption was due to decision of the patient, general practitioner or dermatologist in 39.9% (114/286), 5.6% (16/286), and 30.1% (86/286) of cases, respectively. Fear of increased susceptibility to SARS-CoV-2 infection (24.8%, 71/286) was one of the main causes of interruption. Sixteen patients (0.9%) resulted positive to SARS-CoV-2 infection, 3 of them (0.2%) were hospitalized but no cases of COVID-related death occurred. Conclusions: Most AD patients continued systemic treatments during COVID pandemic and lockdown period, without high impact on disease control, particularly dupilumab-treated patients.

PURPOSE: We aim to do an efficacy-safety analysis of Mirabegron-Tamsulosin combination therapy versus tamsulosin-placebo monotherapy in a select subset of medication virgin BPH patients with coexisting predominantly overactive bladder symptoms (OABS). METHODS: After prior written informed consent and institutional ethics clearance, 80 patients of uncomplicated BPH with coexisting OABS and IPSS of >7 were computer randomized and allocated to receive therapy with either [50mg Mirabegronplus Tamsulosin 0.4 mg (Intervention arm)]or [Tamsulosin 0.4 mg plus capsule lactobacillus (Comparator arm)] once daily for a period of 8 weeks. Efficacy was evaluated using the OABS Score (OABSS), mean change in the frequency of nocturnal voiding, post void residue (PVR) and international prostate symptom score (IPSS) while safety was assessed by recording treatment emergent adverse events (TEAE). The protocol was registered prospectively with the clinical trials registry of India (CTRI/2018/12/016541). RESULTS: Significant improvements were visualised in the primary endpoint total OABS subscore (OABSS-ss) at the end of 8 weeks in the combination group (mean difference -5.62 vs -2.22p< 0.001).Similar significant improvements were seen with most of the secondary parameters such as the mean change in voiding episode/night, IPSS, IPSS-ss,OABS-ss, voided volume/micturition, Qmax, and Quality of Life (QOL) indices (p<0.001). No significant increase in PVR was observed in the Mirabegron arm and no patient developed urinary retention. The TEAE were minor, self-limiting and were managed symptomatically without any treatment discontinuity. CONCLUSION: Mirabegron was significantly efficacious and safe in ameliorating OABS induced by BPH versus placebo. This efficacy can be safely enhanced by initiating Mirabegron-Tamsulosin combination therapy from the start in medication virgin patients as opposed to the usual add on therapy protocol. This combination appeared to be superior in terms of overall safety, minimal side effects, better compliance and tolerability versus Tamsulosin monotherapy particularly in the select subset of patients of with BPH coexisting/predominant OABS.

Sex-specific ecology has management implications, but rapid sex-chromosome turnover in fishes hinders development of markers to sex monomorphic species. Here, we use annotated genomes and reduced-representation sequencing data for two Australian percichthyids, the Macquarie perch Macquaria australasica and the golden perch M. ambigua, and whole genome resequencing data for 50 Macquarie perch of each sex, to detect sex-linked loci, identify a candidate sex-determining gene and develop an affordable sexing assay. In-silico pool-seq tests of 1,492,004 Macquarie perch SNP loci revealed that a 275-Kb scaffold, containing the transcription factor SOX1b gene, was enriched for gametologous loci. Within this scaffold, 22 loci were sex-linked in a predominantly XY system, with females being homozygous at all 22, and males being heterozygous at two or more. Seven XY-gametologous loci were within a 146-bp region. Being ~38 Kb upstream of SOX1b, it might act as an enhancer controlling SOX1b transcription in the bipotential gonad that drives gonad differentiation. A PCR-RFLP sexing assay, targeting one of the Y-linked SNPs, tested in 66 known-sex Macquarie perch and two individuals of each sex of three confamilial species, and amplicon sequencing of 400 bp encompassing the 146-bp region, revealed that the few sex-linked positions differ between species and between Macquarie perch populations. This indicates sex-chromosome lability in Percichthyidae, also supported by non-homologous scaffolds containing sex-linked loci for Macquarie- and golden perches. The resources developed here will facilitate genomic research in Percichthyidae. Sex-linked markers will be useful for determining genetic sex in some populations and studying sex chromosome turnover.

Arctium lappa has a long medicinal and edible history with great economic importance. We combined Illumina and PacBio sequences to generate the first high-quality chromosome-level draft genome of A. lappa. The assembled genome is approximately 1.79 Gb with a N50 contig size of 6.88 Mb. Approximately 1.70 Gb (95.4%) of the contig sequences were anchored onto 18 chromosomes using Hi-C data; the scaffold N50 was improved to be 91.64 Mb. Furthermore, we obtained 1.12 Gb (68.46%) of repetitive sequences and 32,771 protein-coding genes; 616 positively selected candidate genes were identified. Additionally, we compared the transcriptomes of A. lappa roots at three different developmental stages and identified 8,943 differentially expressed genes (DEGs) in these tissues. Among candidate genes related to lignan biosynthesis, the following were found to be highly correlated with the accumulation of arctiin: 4-coumarate-CoA ligase (4CL), dirigent protein (DIR), and hydroxycinnamoyl transferase (HCT). These data can be utilized to identify genes related to A. lappa quality or provide a basis for molecular identification and comparative genomics among related species.

Fabricating a bonded magnet with a near-net shape in suitable thermoplastic polymer binders is of paramount importance in the development of cost-effective energy technologies. In this work, anisotropic Sm2Fe17N3 (Sm-Fe-N) bonded magnets are additively printed using Sm-Fe-N anisotropic magnetic particles in a polymeric binder polyamide-12 (PA12). The anisotropic bonded permanent magnets are fabricated by Big Area Additive Manufacturing followed by post-aligned in a magnetic field. Optimal post-alignment results in an enhanced remanence of ~ 0.68 T in PA12 reflected in a parallel-oriented (aligned) measured direction. The maximum energy product achieved for the additively printed anisotropic bonded magnet of Sm-Fe-N in PA12 polymer is 78.8 KJ m-3. Our results show advanced processing flexibility of additive manufacturing for the development of Sm-Fe-N bonded magnets in polymer media designed for applications with no critical rare earth magnets.

1. Plant leaf stomata are the gatekeepers of the atmosphere-plant interface and are essential building blocks of land surface models as they control transpiration and photosynthesis. Although more stomatal trait data is needed to significantly reduce the error in these model predictions, recording these traits is time-consuming and no standardized protocol is currently available. Some attempts were made to automate stomatal detection from photomicrographs, however, these approaches have the disadvantage of using classic image processing or targeting a narrow taxonomic entity which makes these technologies less robust and generalizable to other plant species. We propose an easy-to-use and adaptable workflow from leaf to label. A methodology for automatic stomata detection was developed using deep neural networks according to the state-of-the-art and its applicability demonstrated across the phylogeny of the angiosperms. 2. We used a patch-based approach for training/tuning three different deep learning architectures. For training, we used 431 micrographs taken from leaf prints made according the nail polish method from herbarium specimens of 19 species. The best performing architecture was tested on 595 images of 16 additional species spread across the angiosperm phylogeny. 3. The nail polish method was successfully applied in 78% of the species sampled here. The VGG19 architecture slightly outperformed the basic shallow and deep architectures, with a confidence threshold equal to 0.7 resulting in an optimal trade-off between precision and recall. Applying this threshold the VGG19 architecture obtained an average F-score of 0.87, 0.89 and 0.67 on the training, validation and unseen test set, respectively. The average accuracy was very high (94%) for computed stomatal counts on unseen images of species used for training. 4. The leaf-to-label pipeline is an easy-to-use workflow for researchers of different areas of expertise interested in detecting stomata more efficiently. The described methodology was based on multiple species and well-established methods so that it can serve as a reference for future work.

To understand dynamics of the COVID-19 disease realistically, a new SEIAPHR model has been proposed in this article where the infectious individuals have been categorized as symptomatic, asymptomatic and super-spreaders. The model has been investigated for existence of a unique solution. To measure the contagiousness of COVID-19, reproduction number R0 is also computed using next generation matrix method. It is shown that model is locally stable at disease free equilibrium point when R0 <1 and unstable for R0 >1. The model has been analyzed for global stability at both of the disease free and endemic equilibrium points. Sensitivity analysis is also included to examine the effect of parameters of the model on reproduction number R0. Couple of optimal control problems have been designed to study the effect of control strategies for disease control and eradication from the society. Numerical results show that the adopted control approaches are much effective in reducing new infections.

Salt marshes are hotspots of nutrient processing en route to sensitive coastal environments. While our understanding of these systems has improved over the years, we still have limited knowledge of the spatiotemporal variability of critical biogeochemical processes within salt marshes. Sea-level rise will continue to force change on salt marsh functioning, highlighting the urgency of filling this knowledge gap. Our study was conducted in a central California estuary experiencing extensive marsh drowning and relative sea-level rise, making it a model system for such an investigation. Here we instrumented three marsh positions with different degrees of inundation (6.7%, 8.9%, and 11.2% of the time for the upper, middle, and lower marsh positions, respectively), providing locations with varied geochemical characteristics and hydrological interaction at the site. We continuously monitored redox potential (Eh) at depths of 0.1, 0.3, and 0.5 m, subsurface water levels (WL), and temperature at each marsh position to understand how drivers of subsurface biogeochemical processes fluctuate across tidal cycles, using wavelet analyses to explain the interactions between Eh and WL. We found that tidal forcing significantly affects biogeochemical processes by imparting controls on Eh variability, likely driving subsurface hydro-biogeochemistry of the salt marsh. Wavelet coherence showed that the Eh-WL relationship is non-linear, and their lead-lag relationship is variable. We found that precipitation events perturb Eh at depth over timescales of hours, even though WL show relatively minimal change during events. This work highlights the importance of high-frequency measurements, such as Eh, to help explain factors that govern subsurface geochemistry and hydrological processes in salt marshes.

Eco-friendly and sustainable energy harvests that can alleviate concerns on the energy crisis and environmental pollution are in demand. Exploiting nature-derived biomaterials is imperative to develop these carbon-neutral energy harvesters. In this study, lignin/polycaprolactone nanofiber (NF)-based triboelectric nanogenerators (TENGs) are fabricated using an electrospinning technique. Nanotextured morphology of electrospun lignin/polycaprolactone NFs and wettability modification of lignin into hydrophilicity can significantly enhance electron transfer between tribopositive and tribonegative materials, resulting in the highest energy-harvesting efficiency in their class. The output voltage of the lignin-based TENG exceeds 95 V despite relatively low tapping force of 9 N and frequency of 9 Hz. Various mechanical and physicochemical characterizations, including scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) spectroscopy, X-ray diffraction (XRD) analysis, Fourier transform infrared (FTIR) analysis, and atomic force microscopy (AFM), are performed, confirming the mechanical durability, biocompatibility, and industrial viability of lignin-based TENG developed here.

Nutcracker syndrome refers to symptomatic compression of left renal vein. There are many reasons for that. We report a case that the enlargement of splenic vein has caused to nutcracker syndrome. Results implies that not firm venous structures can be cause of nutcracker syndrome.

Ralstonia solanacearum is a rod-shaped phytopathogenic bacterium that causes lethal wilt disease in many plants. On solid agar growth medium, in the early hour of the growth of the bacterial colony, the type IV pili-mediated twitching motility, which is important for its virulence and biofilm formation, is prominently observed under the microscope. In this study, we have done a detailed observation of twitching motility in R. solanacearum colony. In the beginning, twitching motility in microcolonies was observed as a density-dependent phenomenon that influences the shape and sizes of the microcolonies. No such phenomenon was observed in Escherichia coli, where twitching motility is absent. In the early phase of colony growth, twitching motility exhibited by the cells at the peripheral region of the colony was more prominent than the cells towards the centre of the colony. Using a time scale photography and merging those into a video, twitching motility was observed as an intermittent phenomenon that progresses in layers in all directions as finger-like projections at the peripheral region of a bacterial colony. Each layer of bacteria twitches on top of the other and produces a multi-layered film-like appearance. We found that the duration between the emergence of each layer diminishes progressively as the colony becomes older. This study on twitching motility demonstrates distinctly heterogeneity among the cells within a colony regarding their dynamics and the influence of microcolonies on each other regarding colony shape and size.

The utilization of lignin remains a great challenge due to its complex non-repetitive structure and the lack of efficient catalyst. Herein, a single-atom catalyst Ni@N-C was designed via a facile chelation-anchored strategy. Ni atoms were immobilized on the N-doped carbon carrier by a two-stage pyrolysis of a mixture of D-glucosamine hydrochloride, nickel acetate and melamine. D-glucosamine hydrochloride as a chelating agent prevented the aggregation of Ni2+, and melamine provided enough N to anchor Ni by forming Ni-N4 structure. Ni@N-C gave a 31.2% yield of aromatic compounds from lignin hydrogenolysis, which was twice higher than that achieved by Ni cluster catalyst. Based on the experimental and DFT calculation results, the higher activity of Ni@N-C was attributed to its lower H2 dissociation energy and the reduced energy barriers of the transition states. The strategy described opens an efficient green avenue for preparing single-atom catalyst that possesses outstanding activity in lignin depolymerization.

Quantitative risk assessments of chemicals are routinely performed in rodents; however, there is growing recognition that non-animal approaches can be human-relevant alternatives. There is an urgent need to build confidence in non-animal alternatives given the international support to reduce the use of animals in toxicity testing where possible. In order for scientists and risk assessors to prepare for this paradigm shift in toxicity assessment, standardization and consensus on in vitro testing strategies and data interpretation will need to be established. To address this issue, an Expert Working Group (EWG) of the 8th International Workshop on Genotoxicity Testing (IWGT) evaluated the utility of quantitative in vitro genotoxicity concentration-response data for risk assessment. The EWG first evaluated available in vitro methodologies and then examined the variability and maximal response of in vitro tests to estimate biologically relevant values for the critical effect sizes considered adverse or unacceptable. Next, the EWG reviewed the approaches and computational models employed to provide human-relevant dose context to in vitro data. Lastly, the EWG evaluated risk assessment applications for which in vitro data are ready for use and applications where further work is required. The EWG concluded that in vitro genotoxicity concentration-response data can be interpreted in a risk assessment context. However, prior to routine use in regulatory settings, further research will be required to address the remaining uncertainties and limitations.