Molecular detection of Enterocytozoon bieneusi in bats from Portugal.

Enterocytozoon bieneusi is a microsporidia commonly found in the gastrointestinal tract of humans and a wide range of other animals, constituting a major cause of microsporidiosis in humans. Although E. bieneusi has been detected in humans, domestic, and wild animals in Portugal, and its presence in bats has been linked to zoonotic characteristics, its occurrence in bats within the country has not been reported. In this study, we investigated the presence of E. bieneusi in 380 bat fecal samples collected in mainland Portugal through a nested PCR assay targeting the internal transcribed spacer region and the flanking small and large subunits of the ribosomal RNA. Enterocytozoon bieneusi was detected in one bat sample (i.e., 0.26%; Pipistrellus pipistrellus). Additionally, another sample tested positive for Enterocytozoon sp. Phylogenetic analysis of the obtained ITS sequence of E. bieneusi revealed clustering within the potentially zoonotic Group 1. This study represents the first report of E. bieneusi in a bat from Europe. Findings presented here contribute to an enhanced understanding of E. bieneusi epidemiology.

Enterocytozoon bieneusi is the most frequent cause of microsporidiosis in humans. In this study, E. bieneusi, belonging to a potentially zoonotic Group, was detected in 0.26% bat samples from Portugal, highlighting bats' potential role in transmitting this microsporidia to humans and other animals.

First report of Enterocytozoon bieneusi in Erinaceus europaeus and Hemiechinus auritus Hedgehogs from recovery centers of Portugal.

Enterocytozoon bieneusi microsporidia are emerging pathogens infecting a wide range of vertebrate and invertebrate hosts, known to have zoonotic features since they infect both wild and domestic animals, and humans. Despite their significance, there is very limited epidemiological data on microsporidia in hedgehogs, especially European hedgehogs (Erinaceus europaeus) and long-eared hedgehogs (Hemiechinus auritus), the former known as synantropic hedgehogs, and the latter suited as pets. As such, the present study aimed to assess the presence of E. bieneusi in hedgehogs from Portugal. For this purpose, fecal samples from 110 hedgehogs of three species - E. europaeus (n=106), H. auritus (n=1), and Atelerix albiventris (n=3) - were collected and tested for E. bieneusi by PCR targeting the ITS region and the flanking small and large subunit of the rRNA. We found an overall occurrence of 22.7% (25/110; 95% [CI]: 15.28-31.70), with 22.6% (24/106; 95% [CI]: 15.08-31.79) in E. europaeus, 100% (1/1) in H. auritus, and 0% in A. albiventris. Interestingly, three novel genotypes were identified, all belonging to the potentially zoonotic Group 1. Our findings highlight the importance of hedgehogs as potential reservoirs for E. bieneusi and emphasize the need for further research to understand their role in transmission dynamics and assess the associated risks to public and veterinary health.

Synanthropic hedgehogs were tested for Enterocytozoon bieneusi, the main cause of human microsporidiosis. Results showed 22.7% of hedgehogs were shedding E. bieneusi spores, with three new genotypes from the zoonotic Group 1. Hedgehogs may transmit to humans/animals, warranting more research.

Storytelling increases oxytocin and positive emotions and decreases cortisol and pain in hospitalized children.

Storytelling is a distinctive human characteristic that may have played a fundamental role in humans' ability to bond and navigate challenging social settings throughout our evolution. However, the potential impact of storytelling on regulating physiological and psychological functions has received little attention. We investigated whether listening to narratives from a storyteller can provide beneficial effects for children admitted to intensive care units. Biomarkers (oxytocin and cortisol), pain scores, and psycholinguistic associations were collected immediately before and after storytelling and an active control intervention (solving riddles that also involved social interaction but lacked the immersive narrative aspect). Compared with the control group, children in the storytelling group showed a marked increase in oxytocin combined with a decrease in cortisol in saliva after the 30-min intervention. They also reported less pain and used more positive lexical markers when describing their time in hospital. Our findings provide a psychophysiological basis for the short-term benefits of storytelling and suggest that a simple and inexpensive intervention may help alleviate the physical and psychological pain of hospitalized children on the day of the intervention.

Impact of different Meloidogyne species on the development of sugarcane plants.

This study aimed to evaluate the impact of Meloidogyne javanica, Meloidogyne incognita, and Meloidogyne arenaria on different aspects of the development of sugarcane plants under greenhouse conditions. For this purpose, seedlings of the RB867515 genotype were individually inoculated with 5,000 eggs + second-stage juveniles of their respective nematodes/plant, and non-inoculated plants were used as control. After 330 days of inoculation, the plants were removed from the pots, and the following characteristics were evaluated: fresh mass of the aerial part and root system; leaf area; leaf chlorophyll index; culm diameter; fresh mass of culms; broth volume; contents of neutral and acid detergent fiber, cellulose, hemicellulose, lignin, apparent sucrose in broth, and reducing sugars in broth; total soluble solids concentration. Subsequently, the final population of nematodes in the root system of inoculated plants was determined to calculate the reproduction factor of nematodes. The results showed that all tested Meloidogyne species negatively affected plant development and the composition of some analyzed fractions, in comparison to the non-inoculated control. However, the presence of the root-knot nematode in sugarcane plants increased the contents of neutral and acid detergent fiber, cellulose, hemicellulose, lignin, and reducing sugars, regardless of the Meloidogyne species.

Stress symptoms occur in patients undergoing chemotherapy treatment independently of the level of physical activity.

The cancer patient is undergoing a set of procedures that affect the physical and psychological balance, which can generate stressful situations in the organism. In turn, physical activity helps to treat stress, promoting well-being and reducing anxiety. Our study aimed to verify the influence of physical activity practice on stress symptoms in patients undergoing oncological chemotherapy treatment. For this, we used Lipp's Inventory of Stress Symptoms (ISSL) and the International Physical Activity Questionnaire (IPAQ) in 56 patients with cancer. Our data show that 45.4% of the participants exhibited stress scores, of which, 21.8% were at near to exhaustion, and 23.6% at exhaustion. We observed that 30% of them are considered sufficiently active, 25% insufficiently active, 45% sedentary. No association was observed between physical activity and stress. These findings indicate that stress symptoms occur in patients undergoing chemotherapy treatment regardless of the level of physical activity.

SHA-256 Hardware Proposal for IoT Devices in the Blockchain Context.

This work proposes an implementation of the SHA-256, the most common blockchain hash algorithm, on a field-programmable gate array (FPGA) to improve processing capacity and power saving in Internet of Things (IoT) devices to solve security and privacy issues. This implementation presents a different approach than other papers in the literature, using clustered cores executing the SHA-256 algorithm in parallel. Details about the proposed architecture and an analysis of the resources used by the FPGA are presented. The implementation achieved a throughput of approximately 1.4 Gbps for 16 cores on a single FPGA. Furthermore, it saved dynamic power, using almost 1000 times less compared to previous works in the literature, making this proposal suitable for practical problems for IoT devices in blockchain environments. The target FPGA used was the Xilinx Virtex 6 xc6vlx240t-1ff1156.

Predicting the pulse of the Amazon: Machine learning insights into deforestation dynamics.

This study aims to analyze deforestation in the Brazilian Amazon from 1999 to 2020 using machine learning techniques to assess 16 critical factors. Our approach leverages the capabilities of machine learning, particularly Random Forest, which proved to be the most accurate model in terms of determination coefficient, mean squared error, and mean absolute error. The analysis revealed that the harvested area of permanent crops is the most influential variable in predicting deforestation, followed by the area of temporary crops. Furthermore, our findings indicate a significant inverse relationship between public spending and deforestation rates. These results contribute to understanding deforestation dynamics and offer potential strategies for improving conservation efforts.

Clean and accurate soil quality monitoring in mining areas under environmental rehabilitation in the Eastern Brazilian Amazon.

Soil quality monitoring in mining rehabilitation areas is a crucial step to validate the effectiveness of the adopted recovery strategy, especially in critical areas for environmental conservation, such as the Brazilian Amazon. The use of portable X-ray fluorescence (pXRF) spectrometry allows a rapid quantification of several soil chemical elements, with low cost and without residue generation, being an alternative for clean and accurate environmental monitoring. Thus, this work aimed to assess soil quality in mining areas with different stages of environmental rehabilitation based on predictions of soil fertility properties through pXRF along with four machine learning algorithms (projection pursuit regression, PPR; support vector machine, SVM; cubist regression, CR; and random forest, RF) in the Eastern Brazilian Amazon. Sandstone and iron mines in different chronological stages of rehabilitation (initial, intermediate, and advanced) were evaluated, in addition to non-rehabilitated and native forest areas. A total of 81 soil samples (26 from sandstone mine and 55 from iron mine) were analyzed by both traditional wet-chemistry methods and pXRF. The available/exchangeable contents of K, Ca, B, Fe, and Al, in addition to H+Al, cation exchange capacity at pH = 7, Al saturation, soil organic matter, pH, sum of bases, base saturation, clay, and sand were accurately predicted (R2 > 0.70) using pXRF data, with emphasis on the prediction of Fe (R2 = 0.93), clay content (R2 = 0.81), H+Al (R2 = 0.81), and K+ (R2 = 0.85). The best predictive models were developed by RF and CR (86%) and when considering pXRF data + mining area + stage of rehabilitation (73%). The results highlight the potential of pXRF to accurately assess soil properties in environmental rehabilitation areas in the Amazon region (yet scarcely evaluated under this approach), promoting a more agile and cheaper preliminary diagnosis compared to traditional methods.

A mechanistic insight for the biosynthesis of N,N-dimethyltryptamine: An ONIOM theoretical approach.

Psychoactive natural products are potent serotonergic agonists capable of modulating brain functions such as memory and cognition. These substances have shown therapeutic potential for treating various mental disorders. The fact that N,N-dimethyltryptamine (DMT) is produced endogenously in several plants and animals, including humans, makes it particularly attractive. As an amino acid-derived alkaloid, the DMT biosynthetic pathway is part of the L-tryptophan biochemical cascade and can be divided into the decarboxylation by an aromatic L-amino acid decarboxylase (AADC) for tryptamine formation and the subsequent double-methylation by the indolethylamine-N-methyltransferase (INMT) through the cofactor S-adenosyl-L-methionine (SAM), a methyl donor. Unlike the decarboxylation mechanism of L-tryptophan, the molecular details of the double methylation of tryptamine have not been elucidated. Therefore, we propose an in silico model using molecular dynamics (MD), non-covalent interaction index (NCI) and density functional theory (DFT) calculations with the ONIOM QM:MM B3LYP/6-31+G(d,p):MM/UFF level of theory. Based on the obtained energetic data, the potential energy surface (PES) indicates an SN2 mechanism profile, with the second methylation energy barrier being the rate-limiting step with δG‡=60kJ∙mol-1 larger than the previous methylation, following the NCI analysis showing more repulsive interactions for the second transition state. In addition, the hybridization information of each reaction step provides geometric details about the double-methylation.

Clean quality control of agricultural and non-agricultural lime by rapid and accurate assessment of calcium and magnesium contents via proximal sensors.

Ca and Mg are the most important chemical elements in lime. Properly measuring Ca and Mg contents is essential to assess the quality of lime products. Quality control guarantees the adequate use of lime in industrial processes, in soils, and helps avoiding adulteration. Proximal sensors can aid in this process by determining Ca and Mg contents easily, rapidly and without producing chemical waste. The objective of this study was to evaluate the use an environmentally-friendly method of analyzing the quality of lime. We studied 1) the use of portable X-ray fluorescence (pXRF) to predict concentrations of Ca and Mg in lime, 2) tested if NixPro™ sensor can improve prediction accuracy and 3) tested if sample preparation methods (grinding) affect analyses. 74 samples of lime were analyzed by two different laboratories (lab. 1 = 38, lab. 2 = 36). All samples submitted to pXRF and NixPro™ analyses. Sensor analyses were done in whole (CP) and ground (AQ) samples to test the effect of sample preparation in prediction performance. High correlation was found between Ca and Mg contents measured via pXRF and laboratory analyses. Mg-CP presented the highest correlation coefficient (r = 0.81); Mg-AQ, the lowest (0.57). Predictions presented good performance (R2 > 0.68); Mg had the best results (0.86). Separating models per laboratory showed that some datasets are harder to model, probably due to variability in the source material (limestone). The addition of NixPro™ data contributed to improve prediction accuracy, although slightly. Predictions using CP samples presented the best results, especially for Mg, indicating that grinding is not necessary. This pioneer study demonstrated that fused proximal sensors can be used to rapidly and easily determine contents of Ca and Mg in soil amendments without producing chemical waste.

Proximal sensing provides clean, fast, and accurate quality control of organic and mineral fertilizers.

Farms use large quantities of fertilizers from many sources, making quality control a challenging task, as the traditional wet-chemistry analyses are expensive, time consuming and not environmentally-friendly. As an alternative, this work proposes the use of portable X-ray fluorescence (pXRF) spectrometry and machine learning algorithms for rapid and low-cost estimation of macro and micronutrient contents in mineral and organic fertilizers. Four machine learning algorithms were tested. Whole (i.e., as delivered by the manufacturer) (CP) and ground (AQ) samples (429 in total) were analyzed to test the effect of fertilizer granulometry in prediction performance. Model validation indicated highly accurate predictions of macro (N: R2 = 0.92; P: 0.97; K: 0.99; Ca: 0.94, Mg: 0.98; S: 0.96) and micronutrients (B: 0.99; Cu: 0.99; Fe: 0.98; Mn: 0.91; Zn: 0.94) for both organic and mineral fertilizers. RPD values ranged from 2.31 to 9.23 for AQ samples, and Random Forest and Cubist Regression were the algorithms with the best performances. Even samples analyzed as they were received from the manufacturer (i.e., no grinding) provided accurate predictions, which accelerate the confirmation of nutrient contents contained in fertilizers. Results demonstrated the potential of pXRF data coupled with machine learning algorithms to assess nutrient composition in both mineral and organic fertilizers with high accuracy, allowing for clean, fast and accurate quality control. Sensor-driven quality assessment of fertilizers improves soil and plant health, crop management efficiency and food security with a reduced environmental footprint.

Detailed characterization of iron-rich tailings after the Fundão dam failure, Brazil, with inclusion of proximal sensors data, as a secure basis for environmental and agricultural restoration.

Following the Fundão dam failure in Brazil, 60 million m3 of iron-rich tailings were released impacting an extensive area. After this catastrophe, a detailed characterization and monitoring of iron-rich tailings is required for agronomic and environmental purposes. This can be facilitated by using proximal sensors which have been an efficient, fast, and cost-effective tool for eco-friendly analysis of soils and sediments. This work hypothesized that portable X-ray fluorescence (pXRF) spectrometry combined with a pocket-sized (Nix™ Pro) color sensor and benchtop magnetic susceptibilimeter can produce substantial data for fast and clean characterization of iron-rich tailings. The objectives were to differentiate impacted and non-impacted areas (soils and sediments) based on proximal sensors data, and to predict attributes of agronomic and environmental importance. A total of 148 composite samples were collected on totally impacted, partially impacted, and non-impacted areas (natural soils). The samples were analyzed via pXRF to obtain the total elemental composition; via Nix™ Pro color sensor to obtain the red (R), green (G), and blue (B) parameters; and assessed for magnetic susceptibility (MS). The same samples used for analyses via the aforementioned sensors were wet-digested (USEPA 3051a method) followed by ICP-OES quantification of potentially toxic elements. Principal component analysis was performed to differentiate impacted and non-impacted areas. The pXRF data alone or combined with other sensors were used to predict soil agronomic properties and semi-total concentration of potentially toxic elements via random forest regression. For that, samples were randomly separated into modeling (70%) and validation (30%) datasets. The pXRF proved to be an efficient method for rapid and eco-friendly characterization of iron-rich tailings, allowing a clear differentiation of impacted and non-impacted areas. Also, important soil agronomic properties (clay, cation exchange capacity, soil organic carbon, pH and macronutrients availability) and semi-total concentrations of Ba, Pb, Cr, V, Cu, Co, Ni, Mn, Ti, and Li were accurately predicted (based upon the lowest RMSE and highest R2 and RPD values). Sensor data fusion (pXRF + Nix Pro + MS) slightly improved the accuracy of predictions. This work highlights iron-rich tailings from the Fundão dam failure can be in detail characterized via pXRF ex situ, providing a secure basis for complementary studies in situ aiming at identify contaminated hot spots, digital mapping of soil and properties variability, and embasing pedological, agricultural and environmental purposes.

Determinants of the composition of ectoparasitic flies of bats (Diptera: Streblidae, Nycteribiidae) in the Amazon and Cerrado landscape scales and ecotonal areas.

The high diversity of bats in the Neotropics is primarily associated with various ectoparasite species on their bodies. Interactions between these animals need to be comprehensively investigated at landscape scales, focusing on understanding the patterns of diversity of species. We sought to evaluate, througt bat captures and ectoparasite sampling, the determinants of the composition of ectoparasitic flies species present in bats in in the Amazon and Cerrado biomes and ecotone areas. We used a generalized dissimilarity model (GDM) to verify what factors explained the composition of ectoparasitic flies of bats using landscape metrics, geographic distance, biome, and host composition. Twenty-four bat species haboured a total of 33 species of ectoparasitic flies. Host composition was the best predictor of fly composition, followed by the environmental variables and by biome. Geographical distance presented negligible effects. Studies on large scales tend to reveal a wide diversity of ectoparasitic flies. Host composition, as the best predictor of fly composition, may be associated with interspecific characteristics among species. We recommend studies focusing on the landscape to understand better the parasitic associations of bats and their distribution across environments.

Spawning, egg and larval description of the brazilian basslet Gramma brasiliensis Sazima, Gasparini & Moura, 1998 in captivity.

Brazilian basslet Gramma brasiliensis is a fish highly appreciated by the marine ornamental industry. There is an increasing interest in the development of a breeding protocol for this species. However, descriptions of the reproductive biology, eggs and larval development are scarce. This study was the first to describe the spawning, eggs and larvae of G. brasiliensis in captivity, including mouth size information. Six spawning events produced egg masses with 27, 127, 600, 750, 850, and 950 eggs. Larger egg masses showed embryos with at least two different developmental stages. Eggs are spherical (∼1.0 mm diameter), held together by filaments entangling chorionic projections. Larvae with fewer than 12 hph (hours post-hatch) presented 3.55 mm standard-length, well developed eyes, fully absorbed yolk sac, an inflated swim bladder and mouth opened. Exogenous feeding on rotifers began within 12 hph. The average mouth width at first feeding was 0.38 mm. The first settled larva was noted by day 21. This information should help to determine appropriate diets and prey-shift time during the larviculture of the species.

RS3PE syndrome: Autoinflammatory features of a rare disorder.

Remitting seronegative symmetrical synovitis with pitting oedema (RS3PE) syndrome was first described by McCarty in 1985 and is characterized by pitting oedema and an acute symmetrical synovitis of small joints. Self-directed inflammation in autoimmune disorders is caused by an abnormal activation of the adaptive immune system, while in autoinflammatory disorders, it is due to aberrant activation of the innate immune system without autoantibodies or autoreactive T cells. The role of autoimmunity in the pathogenesis of RS3PE syndrome is suggested by possible associations with some autoimmune diseases and human leukocyte antigen (HLA) haplotypes. However, several other features point to a possible role of autoinflammation in RS3PE syndrome. In this review, the relative contributions of both innate and adaptive immune systems to the pathogenesis of RS3PE syndrome are discussed.

A Graph-Space Optimal Transport Approach Based on Kaniadakis κ-Gaussian Distribution for Inverse Problems Related to Wave Propagation.

Data-centric inverse problems are a process of inferring physical attributes from indirect measurements. Full-waveform inversion (FWI) is a non-linear inverse problem that attempts to obtain a quantitative physical model by comparing the wave equation solution with observed data, optimizing an objective function. However, the FWI is strenuously dependent on a robust objective function, especially for dealing with cycle-skipping issues and non-Gaussian noises in the dataset. In this work, we present an objective function based on the Kaniadakis κ-Gaussian distribution and the optimal transport (OT) theory to mitigate non-Gaussian noise effects and phase ambiguity concerns that cause cycle skipping. We construct the κ-objective function using the probabilistic maximum likelihood procedure and include it within a well-posed version of the original OT formulation, known as the Kantorovich-Rubinstein metric. We represent the data in the graph space to satisfy the probability axioms required by the Kantorovich-Rubinstein framework. We call our proposal the κ-Graph-Space Optimal Transport FWI (κ-GSOT-FWI). The results suggest that the κ-GSOT-FWI is an effective procedure to circumvent the effects of non-Gaussian noise and cycle-skipping problems. They also show that the Kaniadakis κ-statistics significantly improve the FWI objective function convergence, resulting in higher-resolution models than classical techniques, especially when κ=0.6.

Improved Spatial Memory And Neuroinflammatory Profile Changes in Aged Rats Submitted to Photobiomodulation Therapy.

Recent evidences have shown the therapeutic potential of transcranial photobiomodulation on traumatic brain injury and Alzheimer's disease. Despite the promising benefits in the brain, little is known about the laser's effects in the absence of pathological conditions. We submitted young (4 months old) and aged (20 months old) rats to transcranial low-level laser and evaluated their exploratory activity and habituation in open field, anxiety in elevated plus maze, spatial memory in Barnes maze, and aversive memory in a step-down inhibitory avoidance task. Additionally, the levels of a panel of inflammatory cytokines and chemokines were quantified in two different brain regions: the cerebral cortex and the hippocampus. Young and aged rats submitted to transcranial laser exhibited better cognitive performance in Barnes maze than did control rats. Transcranial laser therapy decreased cortical levels of GM-CSF, IL-10, MCP-1, LIX, and TNFα in young rats and IL-5 in aged rats. High levels of IL-6, IL-10, and TNF-alpha were found in the cerebral cortex of aged rats submitted to transcranial laser. In the hippocampus, a decrease in IP-10 and fractalkine levels was observed in the aged rats from the laser group when compared to the aged rats from the control group. Our data indicate that transcranial photobiomodulation improves spatial learning and memory and alters the neuroinflammatory profile of young and aged rats' brains.

Low-power infrared laser modulates mRNA levels from genes of base excision repair and genomic stabilization in heart tissue from an experimental model of acute lung injury.

The aim of this study was to evaluate photobiomodulation effects on mRNA relative levels from genes of base excision repair and genomic stabilization in heart tissue from an experimental model of acute lung injury by sepsis. For experimental procedure, animals were randomly assigned to six main groups: (1) control group was animals treated with intraperitoneal saline solution; (2) LASER-10 was animals treated with intraperitoneal saline solution and exposed to an infrared laser at 10 J cm-2; (3) LASER-20 was animals treated with intraperitoneal saline solution and exposed to an infrared laser at 20 J cm-2; (4) acute lung injury (ALI) was animals treated with intraperitoneal LPS (10 mg kg-1); (5) ALI-LASER10 was animals treated with intraperitoneal LPS (10 mg kg-1) and, after 4 h, exposed to an infrared laser at 10 J cm-2 and (6) ALI-LASER20 was animals treated with intraperitoneal LPS (10 mg kg-1) and, after 4 h, exposed to an infrared laser at 20 J cm-2. Irradiation was performed only once and animal euthanasias for analysis of mRNA relative levels by RT-qPCR. Our results showed that there was a reduction of mRNA relative levels from ATM gene and an increase of mRNA relative levels from P53 gene in the heart of animals with ALI when compared to the control group. In addition, there was an increase of mRNA relative levels from OGG1 and APE1 gene in hearts from animals with ALI when compared to the control group. After irradiation, an increase of mRNA relative levels from ATM and OGG1 gene was observed at 20 J cm-2. In conclusion, low-power laser modulates the mRNA relative levels from genes of base excision repair and genomic stabilization in the experimental model of acute lung injury evaluated.

Telemedicine to Timor-Leste: implementing an international cardiac telehealth service during population dislocation, floods and COVID-19.

BACKGROUND: The East Timor Hearts Fund has provided cardiac services in Timor-Leste since 2010, conducting three clinics yearly. AIM: To develop collaborative telehealth services between Australia and Timor-Leste in the context of international border closures due to the COVID-19 pandemic. METHODS: Scoping discussions identified major challenges (structural, patient related and medical system related). At two pilot clinics, patient history, investigation and management were collated. Clinic metrics were compared with an index face-to-face clinic in February 2019. Post-clinic discussions identified areas of success and shortfall in the conduct of the telehealth clinics. RESULTS: Twenty-three patients were reviewed at the online telehealth clinics held onsite at Timorese medical facilities. Compared with an index 2019 clinic, there were markedly lower numbers of new referrals (2 vs 190 patients; 8.7% vs 59.4%). Patients seen at the online clinic were predominantly female (17/23; 73.9%) and Dili based (18/23; 78.3%), with a mean age of 25.9 ± 7.2 years. The majority (12/23; 52.2%) had isolated rheumatic mitral valve disease. Investigations including electrocardiography, pathology, echocardiography and 6-min walk tests were conducted in select patients. Medication advice was provided for 10 (43.5%) patients. Eleven (47.8%) patients were deemed to require urgent intervention. Post-clinic discussions indicated general satisfaction with telehealth clinics, although frustration at the current inability to provide interventional services was highlighted. CONCLUSION: Our pilot telehealth clinics indicate that capacity-building telemedicine can be rapidly implemented in an emergency setting internationally. Clinic design benefits from careful identification and resolution of challenges to optimise flow. Cardiac patients in Timor-Leste have a significant burden of disease amenable to intervention.

Quantitative Optical Coherence Tomography Angiography Biomarkers for Alport Syndrome.

PURPOSE: The aim of this study was to evaluate microvascular abnormalities of patients with Alport syndrome (AS) using optical coherence tomography angiography (OCT-A) quantitative biomarkers. METHODS: This was cross sectional, prospective evaluation of consecutive patients with AS and healthy subjects. AS diagnosis was performed by the genetic test. All participants underwent a retinal vasculature evaluation by spectral-domain optical coherence tomography (SD-OCT) and OCT-A of the macula. Quantitative analysis included whole vascular density, foveal avascular zone area, fractal dimension (FD), and lacunarity (LAC). RESULTS: Ninety-four eyes were included in this study, 45 eyes from patients with AS and 49 eyes from healthy subjects. The pathogenic mutation in the COL4A5 gene on the chromosome X was found in 14 patients; the pathogenic autosomal recessive mutations in the COL4A3 gene were found in 9 patients. Quantitative evaluation demonstrated a significant difference between AS and healthy subjects on LAC of the superficial capillary plexus and deep capillary plexus (DCP) (p < 0.001 and p < 0.001, respectively) and on FD in the DCP (p < 0.001). CONCLUSION: The DCP Alport patients have a higher vessel nonuniformity than DCP of healthy subjects. We hypothesize that endothelial cell lesion in the setting of low resistance at the DCP circuit could lead to long-term structural disorganization.