Feasibility Insights of the Green-Assisted Calcium-Phosphate Coating on Biodegradable Zinc Alloys for Biomedical Application: In Vitro and In Vivo Studies.

In the field of bone tissue engineering, recently developed Zn alloy scaffolds are considered potential candidates for biodegradable implants for bone regeneration and defect reconstruction. However, the clinical success of these alloys is limited due to their insufficient surface bioactivities. Further, the higher concentration of Zn2+ produced during degradation promotes antibacterial activity, but deteriorates osteogenic properties. This study fabricated an Azadirachta indica (neem)-assisted brushite-hydroxyapatite (HAp) coating on the recently developed Zn-2Cu-0.5Mg alloy to tackle the above dilemma. The microstructure, degradation behavior, antibacterial activity, and hemocompatibility, along with in vitro and in vivo cytocompatibility of the coated alloys, are systematically investigated. Microstructural analysis reveals flower-like morphology with uniformly grown flakes for neem-assisted deposition. The neem-assisted deposition significantly improves the adhesion strength from 12.7 to 18.8 MPa, enhancing the mechanical integrity. The potentiodynamic polarization study shows that the neem-assisted deposition decreases the degradation rate, with the lowest degradation rate of 0.027 mm/yr for the ZHN2 sample. In addition, the biomineralization process shows the apatite formation on the deposited coating after 21 days of immersion. In vitro cytotoxicity assay exhibits the maximum cell viability of 117% for neem-assisted coated alloy in 30% extract after 5d and the improved cytocompatibility which is due to the controlled release of Zn2+ ions. Meanwhile, neem-assisted coated alloy increases the ZOI by 32 and 24% for Gram-positive and Gram-negative bacteria, respectively. Acceptable hemolysis (<5%) and anticoagulation parameters demonstrate a promising hemocompatibility of the coated alloy. In vivo implantation illustrates a slight inflammatory response and vascularization after 2 weeks of subcutaneous implantation, and neo-bone formation in the defect areas of the rat femur. Micro-CT and histology studies demonstrate better osseointegration with satisfactory biosafety response for the neem-assisted coated alloy as compared to that without neem-assisted deposition. Hence, this neem-assisted brushite-Hap coating strategy elucidates a new perspective on the surface modification of biodegradable implants for the treatment of bone defects.

Electrophoretic Deposition of 58S Bioactive Glass- Polymer Composite Coatings on 316L Stainless Steel: An Optimization for Corrosion, Bioactivity, and Cytocompatibility.

This study presents a facile fabrication of 58S bioactive glass (BG)-polymer composite coatings on a 316L stainless steel (SS) substrate using the electrophoretic deposition technique. The suspension characteristics and deposition kinetics of BG, along with three different polymers, namely ethylcellulose (EC), poly(acrylic acid) (PAA), and polyvinylpyrrolidone (PVP), have been utilized to fabricate the coatings. Among all coatings, 58S BG and EC polymers are selected as the final composite coating (EC6) owing to their homogeneity and good adhesion. EC6 coating exhibits a thickness of ∼18 µm and an average roughness of ∼2.5 µm. Herein, EC6 demonstrates better hydroxyapatite formation compared to PAA and PVP coatings in simulated body fluid-based mineralization studies for a period of 28 days. Corrosion studies of EC6 in phosphate-buffered saline further confirm the higher corrosion resistance properties after 14 days. In vitro cytocompatibility studies using human placental mesenchymal stem cells demonstrate an increase in cellular viability, attachment, and higher proliferation compared to the bare SS substrate. EC6 coatings promote osteogenic differentiation, which is confirmed via the upregulation of the OPN and OCN genes. Moreover, the EC6 sample exhibits improved antibacterial properties against Escherichia coli and Staphylococcus aureus compared to the uncoated ones. The findings of this work emphasize the potential of electrophoretically fabricated BG-EC composite coatings on SS substrates for orthopedic applications.

Assessment of chitosan-coated zinc cobalt ferrite nanoparticle as a multifunctional theranostic platform facilitating pH-sensitive drug delivery and OCT image contrast enhancement.

Colorectal cancer (CC) is one of the most predominant malignancies in the world, with the current treatment regimen consisting of surgery, radiation therapy, and chemotherapy. Chemotherapeutic drugs, such as 5-fluorouracil (5-FU), have gained popularity as first-line antineoplastic agents against CC but have several drawbacks, including variable absorption through the gastrointestinal tract, inconsistent liver metabolism, short half-life, toxicological reactions in several organ systems, and others. Therefore, herein, we develop chitosan-coated zinc-substituted cobalt ferrite nanoparticles (CZCFNPs) for the pH-sensitive (triggered by chitosan degradation within acidic organelles of cells) and sustained delivery of 5-FU in CC cells in vitro. Additionally, the developed nanoplatform served as an excellent exogenous optical coherence tomography (OCT) contrast agent, enabling a significant improvement in the OCT image contrast in a CC tissue phantom model with a biomimetic microvasculature. Further, this study opens up new possibilities for using OCT for the non-invasive monitoring and/or optimization of magnetic targeting capabilities, as well as real-time tracking of magnetic nanoparticle-based therapeutic platforms for biomedical applications. Overall, the current study demonstrates the development of a CZCFNP-based theranostic platform capable of serving as a reliable drug delivery system as well as a superior OCT exogenous contrast agent for tissue imaging.

Urinary bladder involvement in IgG4-related disease: A case-based review.

Immunoglobulin G4-related disease (IgG4-RD) is an immune-driven fibroinflammatory disease that presents as tumefactive lesions that not only commonly affects the pancreas, lacrimal and salivary glands, lung, liver and kidney but can also affect any organs. However, involvement of the urinary bladder in IgG4-RD is rarely reported. We describe a case of IgG4-RD involving the urinary bladder mimicking carcinoma and review the published literature-a 39-year-old male presented with complaints of dysuria, urgency and hesitancy. Ultrasound revealed a hyperechoic lesion protruding from the anterior of the urinary bladder wall with partial obstruction to bladder outflow, likely to be a pedunculated bladder mass with high suspicion for malignancy. A contrast-enhanced computed tomography abdomen showed a large irregular lobulated heterogeneously enhancing lesion involving the anteroinferior wall of the urinary bladder extending from mid-body up to the neck region with significant perivesical fat stranding and multiple ill-defined perivesical deposits along with hypodense soft tissue lesion in the perigastric region at the level of the body of the stomach. CT-guided perigastric and ultrasound-guided biopsy from the urinary bladder mass confirmed the diagnosis of IgG4-RD. The patient was treated with glucocorticoids. He is doing well after a 1-year follow-up without recurrence, and a repeat ultrasound showed a significant reduction in the size of the urinary bladder mass. The diagnosis of IgG4-RD should be considered in the differential diagnosis of a urinary bladder mass. High index of suspicion and prompt initiation of therapy are required to minimise residual damage and the need for surgical intervention.

Generalized Bayes approach to inverse problems with model misspecification.

We propose a general framework for obtaining probabilistic solutions to PDE-based inverse problems. Bayesian methods are attractive for uncertainty quantification but assume knowledge of the likelihood model or data generation process. This assumption is difficult to justify in many inverse problems, where the specification of the data generation process is not obvious. We adopt a Gibbs posterior framework that directly posits a regularized variational problem on the space of probability distributions of the parameter. We propose a novel model comparison framework that evaluates the optimality of a given loss based on its "predictive performance". We provide cross-validation procedures to calibrate the regularization parameter of the variational objective and compare multiple loss functions. Some novel theoretical properties of Gibbs posteriors are also presented. We illustrate the utility of our framework via a simulated example, motivated by dispersion-based wave models used to characterize arterial vessels in ultrasound vibrometry.

Iodine functionalized 2,5-dimethoxy-2,5-dihydrofuran (DHFI) crosslinked whey protein-derived carbon nanodots (WCND) for antibacterial application.

Whey protein-derived carbon nanodots (WCND) were synthesized using the microwave irradiation method, and its amine-rich surface functionality was crosslinked with covalently bound Iodine functionalized 2,5-dimethoxy-2,5-dihydrofuran (DHFI) to produce WCND-DHFI. The physicochemical characterization of both WCND and WCND-DHFI was performed and compared to comprehend the consequence of iodination on the characteristics of WCND. The suitability of CND in biological environments was evaluated through in vitro cytocompatibility and Chorioallantoic Membrane (CAM) assay, as well as a hemocompatibility study. WCND-DHFI has shown enhanced cell viability against WCND. Further, the antibacterial properties of both CNDs were studied against both gram-positive and gram-negative bacterial strains, representing an enhancement in antibacterial activity after DHFI crosslinking. WCND-DHFI has depicted a stable and prominent bacteriostatic activity for up to 6 h for both strains of bacteria. WCND-DHFI has denoted a 99.996% and 99.999% loss of bacterial viability for gram-positive and negative strains, respectively. Novel surface functionalization portrays an improvement in antibacterial activity. Transmission and scanning electron microscopy represent the cell wall rupturing by the WCND-DHFI, resulting in bacterial death. The ROS-mediated bacteriostatic mechanism of WCND-DHFI has been explored through assessing lipid peroxidation and protein oxidation assay. Moreover, the oxidative damage of DNA also has been explored. WCND-DHFI is performing as a promising cytocompatible and hemocompatible material for antibacterial applications.

Alzheimer's Disease Protein Relevance Analysis Using Human and Mouse Model Proteomics Data.

The principles governing genotype-phenotype relationships are still emerging(1-3), and detailed translational as well as transcriptomic information is required to understand complex phenotypes, such as the pathogenesis of Alzheimer's disease. For this reason, the proteomics of Alzheimer disease (AD) continues to be studied extensively. Although comparisons between data obtained from humans and mouse models have been reported, approaches that specifically address the between-species statistical comparisons are understudied. Our study investigated the performance of two statistical methods for identification of proteins and biological pathways associated with Alzheimer's disease for cross-species comparisons, taking specific data analysis challenges into account, including collinearity, dimensionality reduction and cross-species protein matching. We used a human dataset from a well-characterized cohort followed for over 22 years with proteomic data available. For the mouse model, we generated proteomic data from whole brains of CVN-AD and matching control mouse models. We used these analyses to determine the reliability of a mouse model to forecast significant proteomic-based pathological changes in the brain that may mimic pathology in human Alzheimer's disease. Compared with LASSO regression, partial least squares discriminant analysis provided better statistical performance for the proteomics analysis. The major biological finding of the study was that extracellular matrix proteins and integrin-related pathways were dysregulated in both the human and mouse data. This approach may help inform the development of mouse models that are more relevant to the study of human late-onset Alzheimer's disease.

Organic-Inorganic Hybrid Nanocomposites for Nanotheranostics: Special Focus on Preventing Emerging Variants of SARS-COV-2.

The worldwide emerging cases of various respiratory viral diseases and the current escalation of novel coronavirus disease (COVID-19) make people considerably attentive to controlling these viruses through innovative methods. Most re-emerging respiratory diseases envelop RNA viruses that employ attachment between the virus and host cell to get an entry form using the host cell machinery. Emerging variants of COVD-19 also bring about a constant threat to public health as it has wide infectivity and can quickly spread to infect humans. This review focuses on insights into the current investigations to prevent the progression of incipient variants of Severe Acute Respiratory Syndrome Coronavirus (SARS-COV-2) along with similar enveloped RNA viruses that cause respiratory illness in humans and animals. Nanotheranostics is a trailblazing arena of nanomedicine that simultaneously helps prevent or treat diseases and diagnoses. Nanoparticle coating and nanofibers were extensively explored, preventing viral contaminations. Several studies have proven the virucidal activities of metal nanoparticles like copper, silver, and titanium against respiratory viral pathogens. Worldwide many researchers have shown surfaces coated with ionic nanoparticles like zinc or titanium act as potent antiviral agents against RNA viruses. Carbon nanotubes, quantum dots, silica nanoparticles (NPs), polymeric and metallic nanoparticles have also been explored in the field of nanotheranostics in viral detection. In this review, we have comprehensively discussed different types of metallic, ionic, organic nanoparticles and their hybrids showing substantial antiviral properties to stop the progression of the novel coronavirus disease focused on three key classes: prevention, diagnostics, and treatment.

Universal gut microbial relationships in the gut microbiome of wild baboons.

Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are 'universal'. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health.

Communities of bacteria living in the guts of humans and other animals perform essential services for their hosts such as digesting food, degrading toxins, or fighting viruses and other bacteria that cause disease. These services emerge from so-called 'ecological' relationships between different species of bacteria. One species, for example, may break down a molecule in human food into another compound that is, in turn, digested by another species into a small molecule that the human gut can absorb and use. The bacteria involved in such a process may become more or less common together in their host. In other situations, some bacteria may have opposing roles to each other, meaning that if one species becomes more abundant it may reduce the level of the other. However, it is not known if relationships between different bacteria are consistent across hosts (i.e., universal) or unique to each host (personalized). In other words, if a pair of bacteria increase and decrease in abundance together in one host, do they do the same in other hosts? Microbes often swap genes with each other to gain new traits; as each host harbors a distinctive set of gut microbes, it may be possible for microbial relationships to change depending on the bacterial species present in a specific environment. To investigate, Roche et al. studied the bacteria in thousands of samples of feces collected from 56 baboons over a 13-year period. These samples came from a long-term research project in Amboseli, Kenya which has been studying a population of wild baboons continuously since 1971. Roche et al. measured the abundance of hundreds of gut bacteria in the feces to understand the relationships between pairs. This revealed that connections between species were largely universal rather than personalized to each baboon. Furthermore, the pairs of bacteria with the strongest positive or negative associations had the most consistent relationships across the baboons. Microbial relationships that have strong effects on the microbiome's composition might therefore be especially universal. Further analyses measuring gut bacteria in human babies also found that relationships between pairs of bacteria were largely universal. Hence, individual species of bacteria may fill similar ecological roles in each host across humans and other primates, and perhaps also in other mammals. These findings suggest that it may be possible to leverage the ecological relationships between bacteria to develop universal therapies for human diseases associated with gut bacteria, such as inflammatory bowel disease or Clostridium difficile infection.

Optic nerve sheath diameter measurements using ultrasonography to diagnose raised intracranial pressure in preeclampsia: an observational study

Objective: To estimate the incidence of raised intracranial pressure (ICP) as evident by enlarged optic nerve sheath diameter (ONSD) by ocular ultrasound among patients with preeclampsia and its relationship to severity of disease. Material and Methods: Sixty pregnant mothers with preeclampsia were compared to 30 normotensive, uncomplicated pregnant controls. For ONSD measurement, a 7-MHZ linear probe was used and three values from each optic nerve were taken and the mean of six values of both eyes was recorded. All study subjects were followed until seven days after delivery. Results: Two cut off values (5.8 mm and 4.6 mm) were used to compare ONSD in severe and non-severe preeclampsia with that of healthy pregnant individuals. The incidence of raised ICP among severe preeclampsia above 5.8 mm and 4.6 mm cut-off were 43.3% and 90%, respectively, before delivery. ONSD was significantly elevated among preeclampsia subjects at both cut-off values at pre-delivery (p=0.004 for ONSD >5.8 mm and p<0.001 for ONSD >4.6 mm) compared to controls. There a significant association between presence of neurological manifestations and enlarged ONSD (p<0.001 for ONSD >5.8 mm and p=0.04 for ONSD >4.6 mm) before delivery. Conclusion: Severe preeclampsia with neurological features was associated with increased ONSD, reflecting raised ICP. Further studies are needed to compare ONSD values with invasive ICP monitoring for better understanding of this relationship.

Identifying Risk Factors for Blindness From Glaucoma at First Presentation to a Tertiary Clinic.

PURPOSE: Glaucoma is the leading cause of irreversible blindness, a crippling disability resulting in higher risks of chronic health conditions. To better understand disparities in blindness risk, we identified risk factors of blindness on first presentation to a glaucoma clinic using a large clinical database. DESIGN: Retrospective cross-sectional study. METHODS: We used electronic health records of glaucoma patients from the Duke Ophthalmic Registry. International Classification of Diseases codes were used to identify glaucoma and exclude concurrent diseases. Blindness classification was based on the definition of legal blindness. Risk factors included gender, race, marital status, age, intraocular pressure, diabetes history, income level, and education. Odds ratios (ORs) and 95% CIs were calculated for risk factors using univariable and multivariable logistic regression. RESULTS: Our cohort consisted of 3753 patients, with 192 (5%) blind on first presentation. In univariable models, African American / Black race (OR 2.48, 95% CI 1.83-3.36), single marital status (1.74, 95% CI 1.25-2.44), prior diabetes diagnosis (2.23, 95% CI 1.52-3.27), and higher intraocular pressure (1.29 per 1 SD higher, 95% CI 1.13-1.46) were associated with increased risk of presenting blind, whereas higher annual income (0.75, 95% CI 0.65-0.86) and education (0.77, 95% CI 0.69-0.85) were associated with lower risk. These associations remained significant and in the same direction in a multivariable model apart from income, which became insignificant. CONCLUSIONS: Using a large real-world clinical database, we identified risk factors associated with presentation with blindness among glaucoma patients. Our results highlight disparities in health care outcomes and indicate the importance of targeted education to reduce disparities in blindness.

Impact of COVID-19 pandemic on rheumatology trainees: an online survey.

To assess the impact of the COVID-19 pandemic on the training of rheumatology trainees. We conducted an observational cross-sectional study using an online survey-based questionnaire sent to rheumatology trainees in India. Rheumatology trainees from India, including DM/DNB residents and fellows, were included. A total of 78 trainees from 24 institutes in 12 states participated in the study. An overwhelming majority of residents (84%) felt COVID-19 Pandemic Negatively impacted their residency and their Physical (65%), Mental (74%) and Social well-being (80%); 79% of trainees felt burnt out. Majority of trainees felt the pandemic negatively impacted their training with clinical teaching (91%), Clinical examination skills (74%), current (80%) and future (70%) research opportunities suffering during the pandemic. Most had significant reduction in the overall footfall (72%) of patients in rheumatology including OPD (77%) and indoor (67%) admissions along with academics (35%), procedures (66%) and exposure to musculoskeletal ultrasound (71%). Almost 60% and 40% of trainees had OPDs, and indoor admissions stopped during COVID-19 pandemic of these 20% had OPDs, and Admissions closed for more than 6 months. 85% of participants had one or the other psychological symptoms with almost half experiencing anxiety (44%), low mood (47%) or lack of sleep (41%). We found The COVID-19 Pandemic has significantly affected the physical, social and mental well-being of Rheumatology trainees. Academic and clinical training reduced, current and future Research became difficult, disruptions in OPDs and Admissions, recurrent COVID postings and reduction in patient footfall, procedures and MSK-US have been detrimental to trainees.

Exploration of stochastic dynamics and complexity in an epidemic system.

We investigate the effect of noise in an epidemic system. We have studied dynamics and complexity for both the deterministic and its noise-induced model. We have verified the stochastic sensitivity under the variation of noise strength and changing the initial conditions of the noise-induced system. It confirms that noise can make significant perturbation in the stochastic sensitivity. To quantify the dynamics, phase space analysis is done under both noisy and noise free conditions. The transition between regular and chaotic dynamics has been examined by 0 - - 1 test. Corresponding complexity analysis is also done using the weighted recurrence entropy method. Numerical results confirm the chaotic dynamics in the noise-induced epidemic system within a larger region of parameters compared to the same in its noise free part.

The accuracy of absolute differential abundance analysis from relative count data.

Concerns have been raised about the use of relative abundance data derived from next generation sequencing as a proxy for absolute abundances. For example, in the differential abundance setting, compositional effects in relative abundance data may give rise to spurious differences (false positives) when considered from the absolute perspective. In practice however, relative abundances are often transformed by renormalization strategies intended to compensate for these effects and the scope of the practical problem remains unclear. We used simulated data to explore the consistency of differential abundance calling on renormalized relative abundances versus absolute abundances and find that, while overall consistency is high, with a median sensitivity (true positive rates) of 0.91 and specificity (1-false positive rates) of 0.89, consistency can be much lower where there is widespread change in the abundance of features across conditions. We confirm these findings on a large number of real data sets drawn from 16S metabarcoding, expression array, bulk RNA-seq, and single-cell RNA-seq experiments, where data sets with the greatest change between experimental conditions are also those with the highest false positive rates. Finally, we evaluate the predictive utility of summary features of relative abundance data themselves. Estimates of sparsity and the prevalence of feature-level change in relative abundance data give reasonable predictions of discrepancy in differential abundance calling in simulated data and can provide useful bounds for worst-case outcomes in real data.

Have the COVID-19 pandemic and lockdown affected children's mental health in the long term? A repeated cross-sectional study.

OBJECTIVE: The study aimed to evaluate the impact of the COVID-19 pandemic on levels of anxiety and depressive symptoms in children and adolescents. DESIGN: Cross-sectional surveys were carried out on the mental health of children; one survey was conducted before the COVID-19 pandemic and one into the pandemic, 15 months after the school closures and implementation of lockdown and social distancing. Demographic data and COVID-19 pandemic-related data were collected from specific parent-report and self-report questionnaires. PARTICIPANTS: Participants included children and adolescents between ages 6 and 16 years, attending a tertiary care hospital without any diagnosed major psychiatric or chronic disorder. ANALYSIS: Data were collected at two points (before the COVID-19 pandemic and during it) and compared. Levels of anxiety and depressive symptoms were compared and tested for statistically significant differences between these two points using appropriate statistical tests. Regression models were constructed to predict the factors affecting increased anxiety levels and depressive symptoms in the COVID-19 period. RESULTS: 832 and 1255 children/adolescents were included in the study during the pre-COVID-19 and COVID-19 times, respectively. The median age of the participants was 10 years (IQR=4 years). The median (IQR) Spence Children's Anxiety Scale score was 24 (12) at the pre-COVID-19 point and 31 (13) during the COVID-19 pandemic (p<0.001, r=-0.27). 11% and 16% of children reported being depressed at these two-time points, respectively (p=0.004, φc=-0.063). Regression analysis showed that many factors, including the duration of smartphone use, female gender and only child status, were associated with increased anxiety or depression levels. CONCLUSION: A large proportion of children had elevated anxiety and depressive symptoms during the pandemic relative to before the pandemic, suggesting a need for measures to engage children in healthy habits to protect children's mental health and continuous monitoring of children during such scenarios.

Synchrony and idiosyncrasy in the gut microbiome of wild baboons.

Human gut microbial dynamics are highly individualized, making it challenging to link microbiota to health and to design universal microbiome therapies. This individuality is typically attributed to variation in host genetics, diets, environments and medications but it could also emerge from fundamental ecological forces that shape microbiota more generally. Here, we leverage extensive gut microbial time series from wild baboons-hosts who experience little interindividual dietary and environmental heterogeneity-to test whether gut microbial dynamics are synchronized across hosts or largely idiosyncratic. Despite their shared lifestyles, baboon microbiota were only weakly synchronized. The strongest synchrony occurred among baboons living in the same social group, probably because group members range over the same habitat and simultaneously encounter the same sources of food and water. However, this synchrony was modest compared to each host's personalized dynamics. In support, host-specific factors, especially host identity, explained, on average, more than three times the deviance in longitudinal dynamics compared to factors shared with social group members and ten times the deviance of factors shared across the host population. These results contribute to mounting evidence that highly idiosyncratic gut microbiomes are not an artefact of modern human environments and that synchronizing forces in the gut microbiome (for example, shared environments, diets and microbial dispersal) are not strong enough to overwhelm key drivers of microbiome personalization, such as host genetics, priority effects, horizontal gene transfer and functional redundancy.

A topological data analytic approach for discovering biophysical signatures in protein dynamics.

Identifying structural differences among proteins can be a non-trivial task. When contrasting ensembles of protein structures obtained from molecular dynamics simulations, biologically-relevant features can be easily overshadowed by spurious fluctuations. Here, we present SINATRA Pro, a computational pipeline designed to robustly identify topological differences between two sets of protein structures. Algorithmically, SINATRA Pro works by first taking in the 3D atomic coordinates for each protein snapshot and summarizing them according to their underlying topology. Statistically significant topological features are then projected back onto a user-selected representative protein structure, thus facilitating the visual identification of biophysical signatures of different protein ensembles. We assess the ability of SINATRA Pro to detect minute conformational changes in five independent protein systems of varying complexities. In all test cases, SINATRA Pro identifies known structural features that have been validated by previous experimental and computational studies, as well as novel features that are also likely to be biologically-relevant according to the literature. These results highlight SINATRA Pro as a promising method for facilitating the non-trivial task of pattern recognition in trajectories resulting from molecular dynamics simulations, with substantially increased resolution.

Mild and Expeditious Synthesis of Sulfenyl Enaminones of l-α-Amino Esters and Aryl/Alkyl Amines through NCS-Mediated Sulfenylation.

Sulfenylation or selenylation of enaminones of l-α-amino esters requires mild reaction conditions due to the presence of a racemization-prone chiral center and reactive side chains. An N-chlorosuccinimide (NCS)-mediated methodology has been developed for rapid sulfenylation of enaminones of l-α-amino esters and aryl/alkyl amines at room temperature in open air under metal-free conditions. Enaminones of l-α-amino esters bearing aliphatic, aromatic, and heterocyclic side chains react efficiently with diverse aryl/alkyl/heteroaryl thiols (R1SH) in the presence of NCS to afford a library of biologically important sulfenyl enaminones in good-to-excellent yields (71-90%). Under similar reaction conditions, the enaminones also react with benzeneselenol to produce selenyl enaminones in good yield (73-83%). The NCS-mediated pathway generates sulfenyl chloride (R1SCl) as an intermediate which leads to rapid sulfenylation of enaminones through cross-dehydrogenative coupling (CDC) under mild reaction conditions.

A Bayesian hierarchical model to estimate DNA methylation conservation in colorectal tumors.

MOTIVATION: Conservation is broadly used to identify biologically important (epi)genomic regions. In the case of tumor growth, preferential conservation of DNA methylation can be used to identify areas of particular functional importance to the tumor. However, reliable assessment of methylation conservation based on multiple tissue samples per patient requires the decomposition of methylation variation at multiple levels. RESULTS: We developed a Bayesian hierarchical model that allows for variance decomposition of methylation on three levels: between-patient normal tissue variation, between-patient tumor-effect variation and within-patient tumor variation. We then defined a model-based conservation score to identify loci of reduced within-tumor methylation variation relative to between-patient variation. We fit the model to multi-sample methylation array data from 21 colorectal cancer (CRC) patients using a Monte Carlo Markov Chain algorithm (Stan). Sets of genes implicated in CRC tumorigenesis exhibited preferential conservation, demonstrating the model's ability to identify functionally relevant genes based on methylation conservation. A pathway analysis of preferentially conserved genes implicated several CRC relevant pathways and pathways related to neoantigen presentation and immune evasion. Our findings suggest that preferential methylation conservation may be used to identify novel gene targets that are not consistently mutated in CRC. The flexible structure makes the model amenable to the analysis of more complex multi-sample data structures. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available in the NCBI GEO Database, under accession code GSE166212. The R analysis code is available at https://github.com/kevin-murgas/DNAmethylation-hierarchicalmodel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.