Specific Patterns Research Articles

Harnessing the potential of de-sulfated heparin for targeted drug delivery: A three-component approach exemplified by conjugation with galactose and paclitaxel

Heparin, an anticoagulant with a century-long history of use, has been investigated over the past decade as a potential drug delivery vehicle. Despite its safety and efficacy, its interactions with many proteins through specific sulfate patterns can complicate drug delivery by mediating diverse biological functions. Here, we present the synthesis of a three-component drug delivery system comprising de-sulfated heparin as the carrier, galactose as the targeting moiety, and paclitaxel as the therapeutic drug. Removal of sulfates eliminated most of its anticoagulant effects in all intermediates. Through coupling with galactose and paclitaxel, the system improved the solubility of the drug and achieved selective targeting and efficient drug delivery to HepG2 cells, a liver carcinoma cell line with high galactose receptor expression. While the three-component system exhibited a slightly higher IC50 value than native paclitaxel, demonstrating its efficacy as a drug carrier, the IC50 value for the normal human liver cell line QSG7701 was significantly higher, indicating its selectivity and safety. Our study introduces a novel approach utilizing desulfated heparin as a carrier, warranting further investigation to unlock its potential in targeted drug delivery strategies.

The balance between memory and regulatory cell populations in kidney transplant recipients with operational tolerance.

Donor-reactive memory cells represent a barrier to long-term kidney graft survival. A better understanding of regulatory mechanisms that counterbalance alloreactive memory responses may help to identify patients with operational tolerance. This prospective study investigated the equilibrium between memory T-cell subsets and regulatory T or B cells (Tregs, Bregs) in peripheral blood of kidney transplant recipients with operational tolerance (N = 8), chronic rejection (N = 8), and different immunosuppressive treatment regimens (N = 81). Patients on hemodialysis and healthy individuals served as controls (N = 50). In addition, the expression of Treg- and Breg-associated molecule genes was analyzed. Patients with chronic rejection showed a disrupted memory T-cell composition with a significantly higher frequency of circulating CD8+ terminally differentiated effector memory (TEMRA) T cells than patients with operational tolerance, patients on hemodialysis, or healthy controls (P < 0.001). Low frequency of CD8+ TEMRA and high frequency of Tregs and transitional Bregs were found in operationally tolerant patients. Consequently, operationally tolerant patients showed, as compared to all other transplant recipients with different immunosuppressive regiments, the lowest ratios between CD8+ TEMRA T cells and Tregs or Bregs (for both P < 0.001). Moreover, a specific peripheral blood transcription pattern was found in operationally tolerant patients with an increased expression of Breg- and Treg-associated genes CD22 and FoxP3 and a decreased FcγRIIA/FcγRIIB transcript ratio (for all P < 0.001). In conclusion, monitoring the balance between circulating CD8+ TEMRA T cells and regulatory cell subsets and their transcripts may help to distinguish transplant recipients with operational tolerance from recipients at risk of graft loss.

Negative MRI and a seizure onset zone close to eloquent areas in FCD type II: Application of MRg-LiTT after a SEEG re-evaluation in pediatric patients with a previous failed surgery

ObjectiveNegative MRI and an epileptogenic zone (EZ) adjacent to eloquent areas are two main issues that can be encountered during pre-surgical evaluation for epilepsy surgery. Focal Cortical Dysplasia type II (FCD type II) is the most common aetiology underlying a negative MRI.The objective of this study is to present three cases of pediatric patients exhibiting negative MRI and a seizure onset zone close to eloquent areas, who previously underwent traditional open surgery or SEEG-guided radiofrequency thermocoagulations (RF-TC). After seizure seizure recrudescence, pre-surgical SEEG was re-evaluated and Magnetic Resonance-guided laser interstitial thermal therapy (MRg-LiTT) was performed.We discuss the SEEG patterns, the planning of laser probes trajectories and the outcomes one year after the procedure. MethodsPediatric patients who underwent SEEG followed by MRg-LiTT for drug-resistant epilepsy associated with FCD type II at our Centre were included. Pre-surgical videoEEG (vEEG), stereoEEG (sEEG), and MRI were reviewed. Post-procedure clinical outcome (measured by Engel score) and complications rates were evaluated. ResultsThree patients underwent 3 MRg-LiTT procedures from January 2022 to June 2022. Epileptogenic zone was previously studied via SEEG in all the patients. All the three patients pre-surgical MRI was deemed negative. Mean age at seizure onset was 47 months (21–96 months), mean age at MRg-LiTT was 12 years (10 years 10 months – 12 years 9 months). Engel class Ia outcome was achieved in patients #2 and #3, Engel class Ib in patient #1. Mean follow-up length was of 17 months (13 months – 20 months). Complications occurred in one patient (patient #2, extradural hematoma). ConclusionsThe combined use of SEEG and MRg-LiTT in complex cases can lead to good outcomes both as a rescue therapy after failed surgery, but also as an alternative to open surgery after a successful SEEG-guided Radiofrequency Thermocoagulation (RF-TC). Specific SEEG patterns and a previous good outcome from RF-TC can be predictors of a favourable outcome.

Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies.

A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow-up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three-dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF-based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months-12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro-organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age-matched controls in both ROI-based and tract analysis. In conclusion, MRF-based MWF provides myelin-specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children.

Specific codons control cellular resources and fitness.

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

“DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable. To meet additional needs, such descriptors should also be interpretable by medicinal chemists, and suitable for indexing databases with trillions of compounds. To this end, we developed—as integral part of EXSCALATE, Dompé’s end-to-end drug discovery platform—the DompeKeys (DK), a new substructure-based descriptor set, which encodes the chemical features that characterize compounds of pharmaceutical interest. DK represent an exhaustive collection of curated SMARTS strings, defining chemical features at different levels of complexity, from specific functional groups and structural patterns to simpler pharmacophoric points, corresponding to a network of hierarchically interconnected substructures. Because of their extended and hierarchical structure, DK can be used, with good performance, in different kinds of applications. In particular, we demonstrate how they are very well suited for effective mapping of chemical space, as well as substructure search and virtual screening. Notably, the incorporation of DK yields highly performing machine learning models for the prediction of both compounds’ activity and metabolic reaction occurrence. The protocol to generate the DK is freely available at https://dompekeys.exscalate.eu and is fully integrated with the Molecular Anatomy protocol for the generation and analysis of hierarchically interconnected molecular scaffolds and frameworks, thus providing a comprehensive and flexible tool for drug design applications.

Measuring attention of ADHD patients by means of a computer game featuring biometrical data gathering

ADHD is a neurodevelopmental disorder diagnosed mainly in children, marked by inattention and hyperactivity-impulsivity. The symptoms are highly variable, such as different ages of onset and potential comorbidities, contributing to frequent misdiagnoses. Professionals note a gap in modern diagnostic tools, making accurate identification challenging. To address this, recent studies recommend gamification for better ADHD diagnosis and treatment, though further research is essential to confirm its efficacy. This work aims to create a serious game, namely “Attention Slackline", to assess attention levels. The game, designed with expert input, requires players to concentrate on a specific point to recognize specific patterns while managing distractions. A controlled experiment tested its precision, and results were compared with established attention tests by a correlation analysis. Statistical analysis confirmed the game's validity, especially in tracking attention through correct responses and errors. Preliminary evidence suggests that “Attention Slackline" may serve as a credible instrument for the assessment of attentional capacities in individuals with ADHD, given that its outcomes have been empirically shown to correlate with those derived from a well-established attention assessment methodology.

Specification of neural circuit architecture shaped by context-dependent patterned LAR-RPTP microexons

LAR-RPTPs are evolutionarily conserved presynaptic cell-adhesion molecules that orchestrate multifarious synaptic adhesion pathways. Extensive alternative splicing of LAR-RPTP mRNAs may produce innumerable LAR-RPTP isoforms that act as regulatory “codes” for determining the identity and strength of specific synapse signaling. However, no direct evidence for this hypothesis exists. Here, using targeted RNA sequencing, we detected LAR-RPTP mRNAs in diverse cell types across adult male mouse brain areas. We found pronounced cell-type–specific patterns of two microexons, meA and meB, in Ptprd mRNAs. Moreover, diverse neural circuits targeting the same neuronal populations were dictated by the expression of different Ptprd variants with distinct inclusion patterns of microexons. Furthermore, conditional ablation of Ptprd meA+ variants at presynaptic loci of distinct hippocampal circuits impaired distinct modes of synaptic transmission and object-location memory. Activity-triggered alterations of the presynaptic Ptprd meA code in subicular neurons mediates NMDA receptor-mediated postsynaptic responses in CA1 neurons and object-location memory. Our data provide the evidence of cell-type- and/or circuit-specific expression patterns in vivo and physiological functions of LAR-RPTP microexons that are dynamically regulated.

Development of Collateral Vessels after Anterior Circulation Large Vessel Occlusion in Pediatric Arterial Ischemic Stroke Relates to Stroke Etiology: A Longitudinal Study.

The characteristics of large vessel occlusion (LVO) in the acute phase of pediatric arterial ischemic stroke and their natural history according to stroke etiology are poorly explored. This studied aimed at describing the prevalence and the radiological evolution of LVO in pediatric AIS. This single-center retrospective study included consecutive non-neonate children with acute arterial ischemic stroke, intracranial proximal LVO in the anterior circulation (MCA, anterior cerebral artery, and/or ICA), and clinical and imaging follow-up for at least 18 months, during a 9-year period. Intracranial LVO was observed in 24.8% of patients with anterior circulation arterial ischemic stroke and adequate follow-up (n = 26/105), with a median age of 4.2 years (IQR 0.8-9), sex ratio 1.16. The main stroke etiology associated with LVO was unilateral focal cerebral arteriopathy (n = 12, 46%). During follow-up, a specific pattern of unilateral poststroke anastomotic bridge was observed in 8/26 patients, with the poststroke development of nonperforating collaterals forming a bridge in bypass of the LVO site with visible distal flow, within a median delay of 11 months. The development of unilateral poststroke anastomotic bridge was only observed in patients with unilateral focal cerebral arteriopathy. No patient with this pattern experienced stroke recurrence or further progressive vascular modifications. After stroke, the development of unilateral poststroke anastomotic bridge is specifically observed in children with focal cerebral arteriopathy, appearing in the first year after stroke. This clinical-radiologic pattern was not associated with stroke recurrence or arterial worsening, differentiating it from progressive intracranial arteriopathy, such as Moyamoya angiopathy.

A Mathematical Algorithm for Dried Blood Spot Quality Assessment and Results concerning Quality from a Newborn Screening Program.

In addition to newborn screening, dried blood spots (DBSs) are used for a wide variety of analytes for clinical, epidemiological, and research purposes. Guidelines on DBS collection, storage, and transport are available, but it is suggested that each laboratory should establish its own acceptance criteria. An optical scanning device was developed to assess the quality of DBSs received in the newborn screening laboratory from 11 maternity wards between 2013 and 2018. The algorithm was adjusted to agree with the visual examination consensus of experienced laboratory personnel. Once validated, the algorithm was used to categorize DBS specimens as either proper or improper. Improper DBS specimens were further divided based on 4 types of specimen defects. In total, 27 301 DBSs were analyzed. Compared with an annual DBS rejection rate of about 1%, automated scanning rejected 26.96% of the specimens as having at least one defect. The most common specimen defect was multi-spotting (ragged DBS, 19.13%). Among maternity wards, improper specimen rates varied greatly between 5.70% and 49.92%. Improper specimen rates, as well as the dominant type of defect(s), are mainly institution-dependent, with various maternity wards consistently showing specific patterns of both parameters over time. Although validated in agreement with experienced laboratory personnel consensus, automated analysis rejects significantly more specimens. While continuous staff training, specimen quality monitoring, and problem-reporting to maternities is recommended, a thorough quality assessment strategy should also be implemented by every newborn screening laboratory. An important role in this regard may be played by automation in the form of optical scanning devices.

Monitoring of Thermoacoustic Combustion Instability via Recurrence Quantification Analysis and Optimized Deep Belief Network

Thermoacoustic oscillation is indeed a phenomenon characterized by the symmetric coupling of thermal and acoustic waves. This paper introduces a novel approach for monitoring and predicting thermoacoustic combustion instability using a combination of recurrence quantification analysis (RQA) and an optimized deep belief network (DBN). Six samples of combustion state data were collected using two distinct types of burners to facilitate the training and validation of GA-DBN. The proposed methodology leverages RQA to extract intricate patterns and dynamic features from time series data representing combustion behavior. By quantifying the recurrence plot of specific patterns, the analysis provides valuable insights into the underlying thermoacoustic dynamics. Among three different feature extraction methods, RQA stands out remarkably in performance. These RQA-derived features serve as input to a carefully tuned DBN, which is trained to learn the complex relationships within the combustion process. The classification accuracy of deep belief network optimized by genetic algorithm (GA-DBN) reached an impressive 99.8%. Subsequent multiple comparisons were conducted between GA-DBN, DBN, and support vector machine (SVM), revealing that GA-DBN consistently demonstrated satisfactory classification results. This method holds significant importance in monitoring intricate combustion states.

Development and validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method including 25 novel synthetic opioids in hair and subsequent analysis of a Swiss opioid consumer cohort.

Major public health concern is raised by the evidence that common drugs like heroin are now frequently laced or replaced with highly potent novel synthetic opioids (NSOs). The objective of this study was to explore the prevalence and patterns of NSOs in a cohort of Swiss opioid users by hair analysis. Hair analysis is considered an ideal tool for retrospective consumption monitoring. Hair samples from 439 opioid users in Zurich were analyzed. Study inclusion required a previous positive hair test result for heroin metabolites, oxycodone, fentanyl, methadone, or tramadol. The samples were extracted with a two-step extraction procedure, followed by a targeted LC-MS/MS (QTRAP® 6500+) analysis in multiple reaction monitoring mode for a total of 25 NSOs. The method underwent full validation and demonstrated good selectivity and sensitivity with limits of detection (LOD) as low as 0.1pg/mg. The analyzed sample cohort demonstrated a positivity rate for NSOs of 2.5%, including the following NSOs: butyrylfentanyl, acrylfentanyl, furanylfentanyl, methoxyacetylfentanyl, ocfentanil, U-47700, isobutyrylfentanyl and benzylfentanyl. Furthermore, we were able to identify specific consumption patterns among drug users. The results indicate that hair analysis is a valuable tool for investigating the prevalence of NSOs in drug-using populations, which seems to be low in the case of Swiss opioid users. Nevertheless, the results highlight the need for sensitive analytical detection methods in forensic toxicology to identify and monitor substance distribution in different populations.

Biological Markers of High-Risk Childhood Acute Lymphoblastic Leukemia.

Childhood acute lymphoblastic leukemia (ALL) has witnessed substantial improvements in prognosis; however, a subset of patients classified as high-risk continues to face higher rates of relapse and increased mortality. While the National Cancer Institute (NCI) criteria have traditionally guided risk stratification based on initial clinical information, recent advances highlight the pivotal role of biological markers in shaping the prognosis of childhood ALL. This review delves into the emerging understanding of high-risk childhood ALL, focusing on molecular, cytogenetic, and immunophenotypic markers. These markers not only contribute to unraveling the underlying mechanisms of the disease, but also shed light on specific clinical patterns that dictate prognosis. The paradigm shift in treatment strategies, exemplified by the success of tyrosine kinase inhibitors in Philadelphia chromosome-positive leukemia, underscores the importance of recognizing and targeting precise risk factors. Through a comprehensive exploration of high-risk childhood ALL characteristics, this review aims to enhance our comprehension of the disease, offering insights into its molecular landscape and clinical intricacies in the hope of contributing to future targeted and tailored therapies.

Stability of executive function in children born at risk of neonatal hypoglycemia

ABSTRACT Executive function plays an important role in promoting learning and social-emotional development in children. Neonatal hypoglycemia associates with executive function difficulties at 4.5 years, but little is known about the development of executive function over time in children born at risk of neonatal hypoglycemia. We aimed to describe the stability of executive function from early to mid-childhood in children born at risk of neonatal hypoglycemia and its association with neonatal hypoglycemia. Participants in a prospective cohort study of infants born at risk for neonatal hypoglycemia were assessed at ages 2, 4.5, and 9–10 years. We assessed executive function with batteries of performance-based and questionnaire-based measures, and classified children into one of four stability groups (persistent typical, intermittent typical, intermittent difficulty, and persistent difficulty) based on dichotomized scores (typical versus low at each age). Multinomial logistic regression was used to determine the associations between neonatal hypoglycemia and executive function stability groups. Three hundred and nine children, of whom 197 (64%) experienced neonatal hypoglycemia were assessed. The majority of children had stable and typical performance-based (63%) and questionnaire-based (68%) executive function across all three ages. Around one-third (30–36%) of children had transient difficulties, and only a few (0.3–1.9%) showed persistent difficulties in executive function at all ages. There was no consistent evidence of an association between neonatal hypoglycemia and the stability of executive function. Neonatal hypoglycemia does not appear to predict a specific pattern of development of executive function in children born at risk.

Cognitive domains affected post-COVID-19; a systematic review and meta-analysis.

This review aims to characterize the pattern of post-COVID-19 cognitive impairment, allowing better prediction of impact on daily function to inform clinical management and rehabilitation. A systematic review and meta-analysis of neurocognitive sequelae following COVID-19 was conducted, following PRISMA-S guidelines. Studies were included if they reported domain-specific cognitive assessment in patients with COVID-19 at >4 weeks post-infection. Studies were deemed high-quality if they had >40 participants, utilized healthy controls, had low attrition rates and mitigated for confounders. Five of the seven primary Diagnostic and Statistical Manual of Mental Disorders (DSM-5) cognitive domains were assessed by enough high-quality studies to facilitate meta-analysis. Medium effect sizes indicating impairment in patients post-COVID-19 versus controls were seen across executive function (standardised mean difference (SMD) -0.45), learning and memory (SMD -0.55), complex attention (SMD -0.54) and language (SMD -0.54), with perceptual motor function appearing to be impacted to a greater degree (SMD -0.70). A narrative synthesis of the 56 low-quality studies also suggested no obvious pattern of impairment. This review found moderate impairments across multiple domains of cognition in patients post-COVID-19, with no specific pattern. The reported literature was significantly heterogeneous, with a wide variety of cognitive tasks, small sample sizes and disparate initial disease severities limiting interpretability. The finding of consistent impairment across a range of cognitive tasks suggests broad, as opposed to domain-specific, brain dysfunction. Future studies should utilize a harmonized test battery to facilitate inter-study comparisons, whilst also accounting for the interactions between COVID-19, neurological sequelae and mental health, the interplay between which might explain cognitive impairment.

Anxious about rejection, avoidant of neglect: Infant marmosets tune their attachment based on individual caregiver’s parenting style

Children’s secure attachment with their primary caregivers is crucial for physical, cognitive, and emotional maturation. Yet, the causal links between specific parenting behaviors and infant attachment patterns are not fully understood. Here we report infant attachment in New World monkeys common marmosets, characterized by shared infant care among parents and older siblings and complex vocal communications. By integrating natural variations in parenting styles and subsecond-scale microanalyses of dyadic vocal and physical interactions, we demonstrate that marmoset infants signal their needs through context-dependent call use and selective approaches toward familiar caregivers. The infant attachment behaviors are tuned to each caregiver’s parenting style; infants use negative calls when carried by rejecting caregivers and selectively avoid neglectful and rejecting caregivers. Family-deprived infants fail to develop such adaptive uses of attachment behaviors. With these similarities with humans, marmosets offer a promising model for investigating the biological mechanisms of attachment security.

Crow search algorithm with deep transfer learning driven skin lesion detection on dermoscopic images

The early diagnosis of skin cancer is of paramount importance for effective patient treatment. Dermoscopy, a non-surgical technique, utilizes precise equipment to examine the skin and plays a crucial role in identifying specific features and patterns that may indicate the presence of skin carcinoma. In recent times, machine learning (ML) methods have been developed to recognize and classify dermoscopic images as either malignant or benign. Deep learning (DL) systems, including Convolutional Neural Networks (CNNs), as well as various ML models like Random Forest (RF) classifiers and Support Vector Machine (SVM), are employed to extract relevant features from these images. This study introduces the Crow Search Algorithm with Deep Transfer Learning Driven Skin Lesion Detection on Dermoscopic Images (CSADTL-SLD) technique. The CSADTL-SLD method starts with the application of a median filter (MF) to remove noise from the images and utilizes the GoogleNet model for feature extraction. GoogleNet is well-regarded for its capacity to capture intricate and meaningful patterns within the data, which are essential for accurate lesion characterization. Furthermore, the CSADTL-SLD technique applies the Crow Search Algorithm (CSA) for parameter tuning of the GoogleNet model. After feature selection, the system employs the MLP classification model for precise lesion categorization. The comprehensive results of this research demonstrate the superiority of the CSADTL-SLD algorithm, showing significant enhancements in skin lesion detection accuracy and robustness when compared to existing methods. This approach holds promise as an effective solution for automating the detection and classification of skin lesions in dermoscopic images.

Decreased skin colonization with Malassezia spp. and increased skin colonization with Candida spp. in patients with severe atopic dermatitis.

Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease in which patients are sensitized towards a plethora of allergens. The hosts fungal microbiota, the mycobiota, that is believed to be altered in patients suffering from AD acts as such an allergen. The correlation context of specific sensitization, changes in mycobiota and its impact on disease severity however remains poorly understood. We aim to enhance the understanding of the specific sensitization towards the mycobiota in AD patients in relation to their fungal skin colonization. Sensitization pattern towards the Malassezia spp. and Candida albicans of 16 AD patients and 14 healthy controls (HC) were analyzed with the newly developed multiplex-assay ALEX2® and the established singleplex-assay ImmunoCAP®. We compared these findings with the fungal skin colonization analyzed by DNA sequencing of the internal transcribed spacer region 1 (ITS1). Sensitization in general and towards Malassezia spp. and C. albicans is increased in AD patients compared to HC with a quantitative difference in severe AD when compared to mild to moderate AD. Further we saw an association between sensitization towards and skin colonization with Candida spp. yet a negative correlation between sensitization towards and skin colonization with Malassezia spp. We conclude that AD in general and severe AD in particular is associated with increased sensitization towards the hosts own mycobiota. There is positive correlation in Candida spp. skin colonization and negative in Malassezia spp. skin colonization when compared to AD, AD severity as well as to specific sensitization patterns.

Ancestry Specific Polygenic Risk Score, Dietary Patterns, Physical Activity, and Cardiovascular Disease.

It is unknown whether the impact of high diet quality and physical activity depends on the level of polygenic risk score (PRS) in different ancestries. Our cross-sectional study utilized de-identified data from 1987-2010 for self-reported European Americans (n = 6575) and African Americans (n = 1606). The high-risk PRS increased ASCVD risk by 59% (Risk Ratio (RR) = 1.59; 95% Confidence Interval:1.16-2.17) in the highest tertile for African Americans and by 15% (RR = 1.15; 1.13-1.30) and 18% (RR = 1.18; 1.04-1.35) in the second and highest tertiles compared to the lowest tertile in European Americans. Within the highest PRS tertiles, high physical activity-diet combinations (Dietary Approaches to Stop High Blood Pressure (DASH), Mediterranean, or Southern) reduced ASCVD risks by 9% (RR = 0.91; 0.85-0.96) to 15% (RR = 0.85; 0.80-0.90) in European Americans; and by 13% (RR = 0.87; 0.78-0.97) and 18% (RR = 0.82; 0.72-0.95) for DASH and Mediterranean diets, respectively, in African Americans. Top molecular pathways included fructose metabolism and catabolism linked to obesity, insulin resistance, and type 2 diabetes. Additional molecular pathways for African Americans were Vitamin D linked to depression and aging acceleration and death signaling associated with cancer. Effects of high diet quality and high physical activity can counterbalance the influences of genetically high-risk PRSs on ASCVD risk, especially in African Americans.

Molecular Face-Rotating Polyhedra: Chiral Cages Inspired by Mathematics.

ConspectusMolecular polyhedral cages, notable for their enclosed inner cavities, can possess varying degrees of symmetry, spanning from regular Platonic polyhedra to lower symmetry forms that may display chirality. Crafting chiral molecular cages typically involves using building blocks containing stereogenic elements or arranging achiral components in a manner that lacks mirror and inversion symmetries. Achieving precise control over their chirality poses both significance and challenges.In this Account, we present an overview of our research endeavors in the realm of chiral molecular polyhedral cages, drawing inspiration from Buckminster Fuller's "Face-Rotating Polyhedra (FRP)". Mathematically, FRP introduce a unique form of chirality distinguished by a rotating pattern around the center of each face, setting it apart from regular polyhedra.Molecular FRP can be constructed using two types of facial building blocks. The first includes rigid, planar molecules such as truxene and triazatruxene, which exhibit either clockwise or counterclockwise rotations in two dimensions. The second category involves propeller-like molecules, e.g., tetraphenylethylene, 1,2,3,4,5-penta(4-phenylaldehyde)pyrrole, and tridurylborane, displaying dynamic stereochemistry.The synthesis of FRP may potentially yield a diverse array of stereoisomers. Achieving high stereoselectivity becomes feasible through the selection of building blocks with specific substitution patterns and rigidity. Prominent noncovalent repulsive forces within the resulting cages often play a pivotal role in the dynamic covalent assembly process, ultimately leading to the formation of thermodynamically stable FRP products.The capacity to generate a multitude of stereoisomers, combined with the integration of chiral vertices, has facilitated investigations into phenomena such as chiral self-sorting and the "sergeant and soldiers" chiral amplification effect in FRP. Even the inclusion of one chiral vertex significantly impacts the stereochemical configuration of the entire cage. While many facial building blocks establish a stable rotational pattern in FRP, other units, such as tridurylborane, can dynamically transition between P and M configurations within the cage structures. The kinetic characteristics of such stereolabile FRP can be elucidated through physicochemical investigations.Our research extends beyond the FRP concept to encompass mathematical analysis of these structures. Graph theory, particularly the coloring problem, sheds light on the intricate facial patterns exhibited by various FRP stereoisomers and serves as an efficient tool to facilitate the discovery of novel FRP structures. This approach offers a fresh paradigm for designing and analyzing chiral molecular polyhedral cages, showcasing in our work the synergy between mathematics and molecular design.