Cicatelli Associates

Less well known in the parasitological community than in the entomological community are the wonderfully complex systems of army ants and the multitude of taxa that associate with them, collectively termed guests. Guests include vertebrates such as antbirds, but also a diversity of arthropods such as beetles, flies, wasps, millipedes, thysanurans, and collembolans. In addition, a wide variety of mites live on the bodies of army ants and appear to have become modified in form to conform with a particular site on their ant host. The nature of the relationships between army ants and many of their guest taxa remains to be definitively determined. Nonetheless, relationships involving commensalism, mutualism, parasitism, parasitoidism, and phoresy have all been described. The Carl W. and Marian E. Rettenmeyer Army Ant Guest Collection (AAGC) is largely the result of 55 yr of fieldwork (from 1951 to 2004) by the Rettenmeyers in the jungles of Central and South America. It was donated to the Biodiversity Research Collection at the University of Connecticut in 2016 and has since been stabilized and almost fully digitized. This multifaceted resource includes specimens of army ants and their guests housed in 7,310 vials and 278 jars of ethanol, 5,500 microscope slides of guests, and 108 Cornell-style drawers of pinned specimens. We estimate that it includes over 2,000,000 specimens representing 40 species of army ants and their numerous species of guests and prey. Ancillary material includes data from, and images of, 6,246 Kodachrome slides and 9,500 field cards that provide detailed observations on the members of these systems in the field. An online database consisting of 4 modules (i.e., Specimens, Colonies, Kodachromes, and Field Cards) provides digital access to these materials. Because of its interconnected and detailed nature, the AAGC can serve as an unprecedented resource not only for expanding understanding of multiple aspects of the associations between army ants and their guests, but also for helping to inform fundamental questions about the evolution of interspecific interactions and, of primary interest to this audience, parasitism and parasitoidism.

Abstract. Achieving net-zero emissions over the coming decades requires unprecedented reductions in anthropogenic emissions of greenhouse gases (GHGs) complemented by a rapid ramp-up in the magnitude of global carbon dioxide removal (CDR). The carbon credit market (CCM) is emerging as a means to finance both emissions reductions and carbon dioxide removal from the atmosphere. To achieve necessary growth on these fronts, the total scope and diversity of projects that are candidates for inclusion in the CCM must expand, necessitating a means of comprehensively assessing the quality of carbon credit projects (CCPs) based on their ability to make quantifiable reductions to GHG concentrations in the atmosphere. Toward a comprehensive quality assessment, we propose a framework to assess and differentiate CCPs based on their estimated impact on atmospheric GHG composition. In parallel, we propose a path towards verification of the aggregated atmospheric impact of CCM actions, since a detectable and attributable signal in atmospheric GHG composition can be viewed as the clearest measure of their climate forcing and, therefore, effectiveness.

The main aim of this study is to come up with a smart machine learning driven system that can provide a good estimate of the costs involved in constructing a house and predict the most efficient space use under the stipulated parameters that are provided by the user like the area of land, budget, and orientation. The proposed system combines predictive modeling and data-driven learning to overcome the drawbacks of the conventional traditional approach of using simple estimation, which typically does not consider interdependent design and financial factors. The two machine learning models, a gradient boosting regressor (GBR) to estimate the cost of the house and a support vector regressor (SVR) to optimize the spatial, were trained on a dataset of 500 completed projects of houses. Each of the models was compared based on the mean absolute error (MAE) and the R 2-score to determine the level of estimation. The experimental results demonstrate that the proposed system has high reliability, scalability and flexibility in its cost and utilization efficiency estimation. It has been established that increased plot sizes and correct orientations result in optimized space and cost estimation. The study offers a decision-support process that facilitates planning of construction, efficiency of resources, as well as smarter management to open the path to data-driven and intelligent construction design.

This open-label phase 1/2 clinical study uses a novel recombinant vector, rAAV-Olig001, with selective tropism for oligodendrocytes, to deliver gene therapy for Canavan disease (CD), a rare leukodystrophy characterized by defective aspartoacylase and elevated N-acetyl-aspartic acid (NAA) concentrations. A total of 8 participants received intracranial doses of 3.7 × 1013 vector genomes (vg) of rAAV-Olig001-ASPA (MYR-101), with an interim analysis at 12 months. The primary objective was to assess the safety of intracranial dosing of MYR-101 in children with typical CD. Efficacy measures included Mullen Scales of Early Learning (MSEL), Gross Motor Function Measure (GMFM) and analysis of NAA, myelination, white matter and extracellular water content in the brain. The participants were White; 5 (62.5%) were male. Of the participants, 7 (87.5%) experienced ≥1 serious adverse event, none of which were considered MYR-101 related. All participants experienced ≥1 adverse event. All adverse events and serious adverse events resolved fully. Treatment reduced NAA concentrations in cerebrospinal fluid (P = 0.0008), increased myelination (P = 0.0137) and improved MSEL developmental outcomes (P = 0.0171). Thus, interim results suggest that gene therapy with MYR-101 is well tolerated and shows early effects in CD. While these findings are preliminary, reductions in NAA concentrations indicate ASPA expression and increases in myelination and imply successful targeting of oligodendrocytes. These results may support the development of similar gene therapy strategies for other demyelinating and metabolic brain disorders. ClinicalTrials.gov registration: NCT04833907 .

This paper provides a comprehensive analysis of modern techniques used in the assessment of cutaneous flaps in reconstructive surgery. It emphasizes the importance of preoperative planning and intra- and perioperative assessment of flap perfusion to ensure successful outcomes. Despite technological advancements, direct clinical assessment remains the gold standard. We categorized assessment techniques into non-invasive and invasive modalities, discussing their strengths and weaknesses. Non-invasive methods, such as Acoustic Doppler Sonography, Near-Infrared Spectroscopy, Hyperspectral Imaging Thermal Imaging, and remote-Photoplethysmography, offer accessibility and safety but may sacrifice specificity. Invasive techniques, including Contrast-Enhanced Ultrasound, Computed Tomography Angiography, Near-Infrared Fluorescence Angiography with Indocyanine Green, and Implantable Doppler Probe, provide high accuracy but introduce additional risks. We emphasize the need for a tailored decision-making process based on specific clinical scenarios, patient characteristics, procedural requirements, and surgeon expertise. It also discusses potential future advancements in flap assessment, including the integration of artificial intelligence and emerging technologies.

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