Clinical and preclinical studies have shown that reduction in parathyroid hormone (PTH) and fibroblast growth factor 23 (FGF23) can ameliorate anemia associated with chronic kidney disease (CKD). Additionally, clinical studies have demonstrated that salmon calcitonin (sCT) effectively reduces secondary hyperparathyroidism (SHPT) and FGF23. Thus, this study aimed to investigate the potential of sCT to improve renal anemia in a rat model. Male Wistar rats (N=24) were orally administered with adenine (100 mg/kg/day) for 28 days to induce renal anemia. Subsequently, subcutaneous administration of sCT (20 IU/kg/day) or recombinant human erythropoietin (rhEPO) (30 IU/kg/day) was carried out for 21 days. Hematological, biochemical parameters, and histopathological analysis were measured at the end of study (Day 50) with primary objective of investigating the effect of sCT on serum EPO levels. Adenine exposure resulted in reduced (EPO) serum levels, decreased total red blood cell (RBC) counts, hemoglobin (Hb), and hematocrit (Hct), accompanied by elevated serum levels of blood urea nitrogen (BUN), creatinine, PTH, and FGF23. In adenine-treated wistar rats, both sCT and rhEPO administrations successfully increased EPO serum levels, total RBC counts, Hb, and Hct, while decreasing serum BUN, creatinine, FGF23, and PTH levels. Histopathological analysis revealed characteristic kidney damage indicative of CKD in adenine-treated rats, which was notably absent in rats treated with sCT or rhEPO. The study concludes that sCT successfully mitigated renal anemia in rats suggesting its potential as a promising therapeutic strategy for CKD-related anemia. These findings support the translational potential of sCT for improving anemia in CKD patients.

The automotive industry is characterized by rapid technological advancements and increasing market competition, necessitating effective product development strategies. This paper presents an AI-based expert system designed to enhance decision-making at each stage of the product development process, utilizing a stage-gate framework. By integrating machine learning algorithms and data analytics, the expert system aids in evaluating project feasibility, risk assessment, and prioritization of product features. The system's effectiveness is demonstrated through a case study involving multiple automotive projects, showcasing its potential to optimize decision-making and improve project outcomes.

With the growth of cloud computing and the popularity of electronic health records (EHR), more and more patients and hospitals are uploading EHR to the cloud for storage, retrieval and organization. Due to the privacy of EHR, cloud-based EHR systems need to protect data security and provide access control, and attribute-based encryption (ABE) is the appropriate technology. Nevertheless, traditional single-center ABE schemes do not conform to the collaborative scenario of electronic health care, and some of them do not support real-time attribute update. Consequently, this paper proposes a lightweight CP-ABE scheme for EHR over cloud based on blockchain and secure multi-party computation (LCBS). Firstly, we introduce the model of multi-authority and innovatively apply secure multi-party computation to initialize the system, which maintains normal system operation while the power is decentralized. Secondly, we designed a blockchain suitable for EHR systems to record the users’ key information, assisting multiple entities to verify the key at different stages and protecting the EHR from illegal acquisition. In addition, our scheme supports lightweight attribute update, which requires small amount of computational overhead to achieve instant attribute update. Finally, through formal security analysis and simulation experiments of the LCBS system, it is shown that our scheme guarantees data security and improves computing efficiency.

Numerous developments and applications have been made possible by the quick development of the Internet of Things (IoT) in various fields, including banking, healthcare, smart homes, and smart cities. Smart security systems are gaining popularity due to their adaptability, decreased need for human intervention, increased reliability, time efficiency, and improved threat detection. Although different solutions have been developed as smart systems, limitations include limited coverage, false alarms, flaws in authentication procedures, privacy problems, reaction time, and external dependency. The mentioned issues must be addressed for an efficient smart security system. This paper proposes an IoT-based smart security system to detect threats using machine learning to recognise human faces and objects. This system uses a Convolutional Neural Network (CNN) for face recognition to identify intruders and black-listed objects using the Single Shot Detector (SSD) method. When an unknown person is found, the system notifies the admin through push notification to take additional action. In conclusion, the smart security system yielded promising results, with CNN achieving an accuracy of 94%, precision of 90.91%, recall of 100%, specificity of 85%, F1-score of 95.24%, and SSD achieving accuracy of 90%, precision of 90%, recall of 100%, specificity of 0%, and F1-score of 94.7% for face and object detection, respectively. The potential uses of the smart security system go beyond the purview of this research and can be put into practice in various industries, including finance, healthcare, smart homes, and smart cities. This system may significantly improve security measures and offer a safer environment by utilising cutting-edge technology and machine learning approaches.

We present a statistical model of the ionospheric electric field derived from line-of-sight plasma velocity measurements from the Super Dual Auroral Radar Network (SuperDARN). Electric potential patterns are produced using an established technique that models the electric field as a spherical harmonic expansion of the ionospheric electric field. Improvements over existing models are achieved by the use of novel parameterisations that capture three major sources of time-variability of the coupled solar wind-magnetosphere-ionosphere system. The first source of variability relates directly to the time-dependence of the system to the upstream solar wind conditions, specifically the strength and orientation of the interplanetary magnetic field. The magnetosphere-ionosphere system is not static under continuous driving by the solar wind but evolves with time, even if the solar wind conditions themselves remain steady. We account for this by defining a solar wind steadiness timescale with which we parameterise the electric field. The second source of variability relates to the storage and release of energy in the magnetosphere that is associated with magnetospheric substorms. The electric field evolves throughout the substorms cycle, and its morphology is strongly influenced by the location of substorm onset. We therefore parameterise by substorm onset location and the time relative to substorm onset. Lastly we account for the variability introduced by geomagnetic storms. The ionospheric electric field evolves differently through each phase of a storm, so we parameterise by storm phase. We discuss the details of the model, and assess its performance by comparison to other models and to observations.

Migration is an energy-intensive phase of birds’ life cycle, often including the crossing of large ecological barriers on non-stop flights. The release of corticosterone (CORT), an adrenocortical hormone (also known as the stress hormone), generally rises at the onset of migration to facilitate and sustain high-energy metabolism. However, during prolonged flights, unfavourable meteorological events may affect the ability of migrants to cope with other stressors. In this study, we evaluated the effects of weather along the Mediterranean Sea on the physiological conditions of birds that reached a stopover island. We assessed fuel stores and CORT variations during pre-breeding migration in two trans-Saharan species, the Common Whitethroat (Curruca communis) and the Garden Warbler (Sylvia borin), upon arrival after the Mediterranean Sea crossing. By examining tailwinds and air temperature at different altitudes in the period preceding the arrival, we found that even with unfavourable weather conditions birds arrived at the stopover site with residual energy reserves. Also, adverse weather conditions did not influence baseline CORT levels. Interestingly, while both species exhibited a normal stress response to additional stressors, Garden Warblers showed peak CORT levels correlated with higher temperatures. These results suggest that migrants are generally well-equipped to handle variable weather conditions and may avoid migrating during extreme weather. As only birds surviving the sea crossing were studied, we suspect that most birds in poor condition did not reach the stopover site. Species-specific adaptations and diverse pre-migration ecological contexts may lead to different migration strategies to face this long-distance journey. Future research should explore to what extent physiological adjustments may aid migrants in dealing with the current increase in extreme meteorological events.

The recent era of Industry 4.0 extensively utilizes manipulators for various critical automation tasks. Handling a manipulator robot is a complex task. This research employs a 3-R (revolute) manipulator robot to achieve optimal joint trajectories for drawing different alphabets and shapes. The solution to inverse kinematics (IK) is essential; therefore, an artificial neural network (ANN) based model is used. The forward and backward reaching inverse kinematics (FABRIK) technique provides stability, though it is computationally intensive and time-consuming. To design a low-cost hybrid model, ANN combined with FABRIK is proposed to compute IK. Using the proposed model, coordinates for different alphabets and shapes within the confined workspace were calculated. We have developed a 3R (revolute) manipulator that utilizes deep learning (DL) and IK. The ANN automatically obtains specific end-effector coordinates. Due to the non-linear characteristics of IK’s mathematical model, inverse kinematics is a time-consuming procedure, making it difficult to provide a mathematical solution. Our primary goal is to reduce processing costs by using ANN and FABRIK with the IK model to solve IK problems and obtain coordinates for any form or alphabet within a given workspace. To ensure a safe region is selected, this model combines the control barrier function (CBF) with the Lyapunov function. The accuracy of the model exceeds 99.5 percent. We have calculated the mean square error (MSE) as 1.66, the root mean square error (RMSE) as 1.25, and the mean absolute error (MAE) as 0.96 for our model. The error between the model’s predicted and actual coordinates also demonstrates letter coordinates and shapes drawn using a physical 3R manipulator model. As a result, this approach can be used to accurately estimate the angles in complex 3DoF inverse kinematics models.

This article presents an analytical model to estimate wind velocity uncertainties in ground-based (dual) Doppler lidar measurements. The model follows the principles of uncertainty propagation as recommended by the Guide to the Expression of Uncertainty in Measurements. Key-input quantities of the measuring model considered uncertain include elevation and azimuth angles and focus distance, or range. The uncertainty model also accounts for bias and random errors originating from hardware components and data processing techniques. Uncertainty correlations within a single lidar and between instruments in a dual-lidar system are addressed. The measurement model assumes perfect spatio-temporal synchronisation between the lidar instruments while probing a non-turbulent wind inflow described by a vertical shear model. Results from the analytical solution are verified using Monte Carlo simulations, obtaining very good agreement from the comparison. The pattern of the uncertainty distributions is predominantly influenced by the relative positioning of the measuring system(s) and the intended measurement point(s). The magnitude of the uncertainty distributions is principally determined by the intrinsic uncertainty of the lidar, modulated by the set of relevant uncertainty correlations.

Mathematical abilities and (pre)skills are based on non-symbolic and symbolic systems of numerical processing. The aim of this study was to investigate quantity processing in preschool children in Croatia. A total of 122 typically developing preschool children (two equal groups; four- and five-year-olds) were solving two types of tasks: non-symbolic and symbolic quantity estimations. Contrary to our expectations, the children’s performances on non-symbolic and symbolic tasks were not statistically significantly connected. As we had assumed, both groups performed better on the non-symbolic tasks, and the older group outperformed the younger group on both types of tasks. We found distance effect on the non-symbolic task and size effect on the symbolic task for both groups. The results are consistent with the findings of previous research supporting the developmental perspective of two systems and the role of formal educational in their progression.

not-yet-known not-yet-known not-yet-known unknown Socioeconomic status (SES) is a complex and multidimensional construct that includes objective characteristics (e.g., income, education, occupation) and people’s subjective assessments of their position on the socioeconomic spectrum. Both types of indicators have been associated with impacts on different aspects of child development and parenting practices. However, studies that analyze children’s developmental needs from different perspectives of objective and subjective disadvantage are rare. In this study, we proposed to extend previous research on SES by comparing two approaches to measuring SES and analyzing their contribution to childhood experiences during the preschool year. For that, participants were recruited from schools and a public cultural center in Buenos Aires (N= 162; Mage= 5.77, SD= 0.36; 45.1% girls). Our results showed that both SES approaches (measured through maternal education level and parental perception of access to resources) partially overlap. Both are predictors of considerable variance in many childhood experiences. Nevertheless, subjective SES is the unique predictor for specific childhood experiences, whereas objective SES presents a greater influence (larger probabilities) on most childhood experiences analyzed. Although preliminary, these results highlight the need to consider the joint assessment of objective and subjective SES measurement strategies to understand the associations between SES and childhood experiences fully.

This paper presents Point Cloud Map Fitting (PCMF), a SLAM-based method for robust global positioning of autonomous surface vehicles in harbor environments. To address the challenge of precise positioning in unstructured and dynamic environments, a LiDAR sensor provides accurate measurements of the surroundings, which are fitted to a prior map using rotational initial alignment and G-ICP detail registration. The initial alignment process improves the accuracy of subsequent registration by leveraging corner features of the environment to address the limitations associated with large transformations in ICP registration. The resulting position estimates enable redundant positioning estimated by an Unscented Kalman Filter sensor fusion algorithm together with GNSS. The pipeline is tested in the field with multiple locations, tides, and weather conditions to demonstrate efficient position estimation in real time. The multimodal positioning system is stress-tested through the manipulation of GNSS signals in a simulated cyber-attack, which serves to demonstrate the edge case robustness of the system.

Background/Rationale Weekly cholecalciferol can be an alternative to daily supplementation to reduce pill burden in patients with complex medication regimens and hypovitaminosis D, but evidence supporting this switch is unclear. Objective We aimed to determine whether weekly cholecalciferol was superior to daily cholecalciferol to replete patients with hypovitaminosis D. Methods We conducted a systematic review of randomized controlled trials involving participants with baseline hypovitaminosis D (<30ng/ml) comparing weekly versus daily cholecalciferol dosing and where serum cholecalciferol was measured within 90 days of starting treatment. We searched MEDLINE, CINAHL and EMBASE from inception to May 7 th, 2024. A random-effects meta-analysis evaluated the odds ratio for repletion of serum Vitamin D levels. Findings Eight trials involving 542 patients were included in the analysis. Weekly D3 and daily cholecalciferol were not significantly different in correcting hypovitaminosis D (OR=1.5, 95% CI = 0.3-6.9, p=0.6, favoring weekly dosing, I 2=85.3%). A sensitivity analysis excluding otherwise healthy patients had similar findings (OR=0.8, 95% CI=0.3–2.1, p=0.6). Most studies were judged to be at risk of bias, the different doses being compared increased the heterogeneity (I 2=85.3%). Conclusions There is limited direct evidence supporting a switch from daily to weekly cholecalciferol dosing; however, weekly supplementation was not demonstrably worse at repleting levels and decreases a patient’s daily pill burden.

Metal dichalcogenide based 2D materials, gained considerable attention recently as a hydrogen evolution reaction (HER) electrocatalyst. In this work, we synthesized MoSe2 based electrocatalyst via hydrothermal route with varying phase contents (1T/2H) and respective HER performances were evaluated under the acidic media (0.5M H2SO4), where best HER performance was obtained from the sample consisting of mixed 1T/2H phases, which was directly grown on a carbon paper (167mV at 10mA/cm2) Furthermore, HER performance of electrocatalyst was further improved by in-situ electrodeposition of Pt nanoparticles (0.15 wt%) on the MoSe2 surface, which lead to significant enhancement in the HER performances (133mV at 10mA/cm2). Finally, we conducted DFT calculations to reveal the origin of such enhanced performances when the mixed 1T/2H phases were present, where phase boundary region (1T/2H heterojunction) act as a low energy pathway for H2 adsorption and desorption via electron accumulation effect. Moreover, presence of the Pt nanoparticles tunes the electronic states of the MoSe2 based catalyst, resulting in the enhanced HER activity at heterointerface of 1T/2H MoSe2 while facilitating the hydrogen adsorption and desorption process providing a low energy pathway for HER. These results provide new insight on atomic level understanding of the MoSe2 based catalyst for HER application.

Methods: This study established a home care routing and scheduling model and determined the corresponding spatial optimization problems. The problems were reduced to a multi-depot vehicle path optimization problem, and the nondeterministic polynomial time difficulty of this problem was demonstrated. Results: The results show that the algorithms developed in this study were significantly more effective than the benchmark and random algorithms. Considering the total operating costs of home healthcare institutions, the service-time first greedy algorithm, customized genetic algorithm, and customized tabu search algorithm reduced costs by 45.8%, 53.0%, and 57.7%, respectively, compared with the benchmark algorithm. In addition, the greedy algorithm and customized genetic algorithm, which prioritize service time, improved the service quality of family medical institutions by 31.7% and 65.7%, respectively, compared to the benchmark algorithm, and by 65.7% and 126.3%, respectively, compared to the random algorithm. Conclusions: By unveiling effective resource allocation and spatial optimization strategies for home healthcare in rural China, this study offers valuable insights for policymakers. The findings contribute to informed decision-making, facilitate cost minimization, and maximize service quality in healthcare policy formulation and implementation. Keywords: home care, path planning, resource scheduling, society population

Remission is the desired outcome following OIT as it allows individuals to discontinue treatment and eat the allergen freely. Early initiation of OIT in infants and toddlers has been embraced as an approach to increase the likelihood of remission. However, there is no high-quality evidence supporting younger age as an independent factor driving remission; available studies are limited by small samples of younger subjects and lack of adjustment for confounding covariates, particularly peanut-specific IgE (sIgE) levels which is closely correlated with age. This study examined relationships between peanut sIgE and age at baseline and remission, in children aged 1-10 who completed 18 months of OIT in the PPOIT-003 RCT (n=162). Remission was defined as absence of clinical reactivity to peanut after 8 weeks of allergen avoidance/treatment discontinuation. Age and sIgE were examined as continuous variables in univariate and multivariate regression models. Baseline peanut sIgE levels were significantly associated with remission, independent of age (OR 0.1 [0.05-0.22], p<0.001). Higher peanut sIgE was consistently predictive of lower likelihood of remission, independent of age. In contrast, there was no independent association between age and remission after adjusting for baseline sIgE (OR 0.94 [0.79-1.12], p=0.5). Findings do not support age as an independent predictor of remission following OIT. Additional studies examining safety and efficacy of OIT in infants and younger children are urgently needed, ahead of widespread adoption of early intervention.

not-yet-known not-yet-known not-yet-known unknown The honeybee Apis mellifera Linnaeus, 1758 is an economically and ecologically important insect. In Burkina Faso, knowledge of the morphometric characteristics of honeybees is limited, although this information is important and reflects their ability to adapt to the environment. The aim of this study is to morphometrically characterize A. mellifera and to determine the variability of its traits according to climatic zones. A sample of 800 worker bees from 80 colonies was collected from 16 apiaries in the Sudanian and Sudano-Sahelian climatic zones. 20 morphometric characteristics were measured according to their biological significance. The results reveal that the individuals had an average body length of 13.22 ± 1.25 mm and a proboscis length of 4.31±0.57 mm. A positive correlation (p < 0.05) was established between forewing length and hind leg length (r 2= 0.82). In the Soudano-Sahelian climatic zone, the mean body length was 13.75 ± 1.14 mm, whereas it was shorter in the Soudanian zone, with a mean of 12.54 ± 1.04 mm (p < 0.001). Similarly, the mean proboscis length is 4.47 ± 0.54 mm in the Sudano-Sahelian zone, while it is lower (4.09 ± 0.53mm) in the Sudanian zone (p< 0.001). Through multivariate analysis, we detected three morphometrically separable groups of bees: one group belonging to each climatic zone and a third group made up of bees from both climatic zones. These results could have implications for biodiversity conservation and sustainable beekeeping in Burkina Faso.

This paper discusses the impacts of human habitation on the natural ecosystem of a wetland, Pallikaranai, Chennai, India. We have adopted a social-ecological systems approach to define the problem and examine the aspects surrounding it. Through this research we address sociological aspects and gauge community perception, knowledge, attitude and behaviour of the urban society interacting with the marsh and with water bodies in general. Our findings show that, although 88% (178 out of 203) of those who were surveyed were concerned about the environment, such concern – and their knowledge and awareness – were not always reflected in their actions, mainly because of external factors including the increasing population density and such aspects of urban lifestyle as water consumption. The dynamics of this social-ecological system is further explored by examining trends in social, ecological and climate-related parameters and observing the timeline of events which have resulted in the present state of the marsh. International recognition by Ramsar is a landmark event and how the administration and stakeholders will collaborate to promote biodiversity conservation is currently a question. Our research attempts to provide a framework and throw light upon details and issues which, when considered, will ameliorate the existing social-ecological system, with respect to this case as well as many other wetlands in similar circumstances.

This paper presents a novel method to assess the pathogenicity of Pyrin protein mutations by using mutual information (MI) as a measure to quantify the correlation between residue motions or fluctuations and associated changes affecting the phenotype. The concept of MI profile shift is presented to quantify changes in MI upon mutation, revealing insights into residue-residue interactions at critical positions. We apply this method to the Pyrin protein variants, which are associated with an autosomal recessively inherited disease called familial Mediterranean fever (FMF) since the available tools do not help predict the pathogenicity of the most penetrant variants. We demonstrate the utility of MI profile shifts in assessing the effects of mutations on protein stability, function, and disease phenotype. The importance of MI shifts, for the pyrin example the negative shifts, as indicators of severe functional effects is emphasized, along with exploring potential compensatory mechanisms indicated by positive MI shifts, which are otherwise random and inconsequential. The paper also discusses challenges in relating MI profile changes to disease severity and advocates for comprehensive analysis considering genetic, environmental, and stochastic factors. Overall, this study provides insights into the molecular mechanisms underlying the pathogenesis of FMF and offers a framework for identifying potential therapeutic targets based on MI profile changes induced by mutations.

Dear Thioguanine,David S. Dickens MD11Division of Pediatric Hematology/Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa

The bioaugmentation performance is severely reduced in the treatment of high saline pesticide wastewater because the growth and degradation activity of pesticide degraders are significantly inhibited by high salt concentrations. In this study, an artificial halotolerant degrader J9U-MP capable of mineralizing p-nitrophenol (PNP) substituted organophosphorus pesticides (OPs) [e.g., methyl parathion (MP)] was created by integrating a MP-mineralizing pathway into the genome of a salt-tolerant chassis Halomonas cupida J9. MP degradation coupled with stable isotope analysis indicated that J9U-MP was able to metabolize MP as a sole carbon source to finally produce CO 2 and H 2O in high-salt media (up to 120 g/L NaCl). J9U-MP was genetically stable during passage culture and exogenous gene integration did not negatively influence growth and metabolism of J9U-MP. A real-time monitoring system was established with enhanced green fluorescent protein (EGFP) to track the movement and activity of J9U-MP in environmental remediation. A low-oxygen tolerant system was developed by enhancing oxygen utilization, which makes J9U-MP maintain the MP-mineralizing activity under oxygen-limited conditions. More importantly, efficient mineralization of MP by J9U-MP in high saline wastewater was demonstrated. This study highlights that synthetic biology has opened up new avenues for creating stress-resistant pollutants-mineralizing microbes. Competitive advantages of J9U-MP in high-salinity and low-oxygen environments make this degrader suitable for bioaugmentation of pesticide wastewater.

Background: Cancer therapy– related cardiac dysfunction (CTRCD) is nowadays a frequently encountered clinical presentation, and transthoracic echocardiography (TTE) is usually the routine imaging modality of its screening and detection. The aim is to early detect subclinical CTRCD using non invasive imaging techniques & cardiac biomarkers. Methods: Eighty-eight patients with cancer, planned to receive Anthracyclines(AC) or Trastuzumab (TZB) were enrolled, baseline screening included 2D TTE, GLS and cardiac troponin I and NtProBNP measurments before receiving any treatment, follow up at three and six months were done using the same variables to early detect CTRCD and start CPT even in cases of mild dysfunction. Results: Twenty six patients developed CTRCD, 18 had mild and 8 had moderate asymptomatic CTRCD defined by relative decline in GLS & LVEF following the latest ESC cardio-oncology guidelines. The percentage of change in GLS from baseline and at 3 and 6 months was able to detect CTRCD in both groups in our population which was >16.6% at 3 months with P value of <0.001*and CI 0.783 – 0.934 and >10.10% at 6 months with P value of of <0.001*and CI 0.765 – 0.935 .At three months GLS values ≤-18.6 was able to detect CTRCD with P value of of <0.001*and CI 0.673 0.885.Compared to patients who did not develop CRTD, patients with mild asymptomatic CTRCD had double levels of NT-Pro BNP with a median of (99.5 ) ( IQR: 44.0 – 154.0) at 3 months follow up with P value 0.037 which was normalized at 6 months. Conclusion: The relative decline of GLS and elevation of NT-proBNP were able to diagnose patients with subclinical CTRCD in patients receiving AC with early start of Cardioprotective Treatments (CPT) which enabled the patients to continue their chemotherapeutic treatment uninterrupted without developing serious grades of LV dysfunction and even some patients showed improvement after CPT.

Biogeographic knowledge of Amazonian amphibians presents significant challenges in spatial and temporal coverage, as well as in the taxonomic refinement of their diversity. Despite recent advances, the spatial distribution of sampling and detailed taxonomic knowledge remain limited, potentially causing biases in our understanding of their diversity and distribution. In this study, we conducted a large-scale analysis using an extensive database with 951 species and 213,072 georeferenced occurrence records, distributed across 24,319 sampling points in the Amazon. This analysis aimed to elucidate potential drivers of sampling biases for Amazonian amphibians in the presence of infrastructure factors (cities, hydroelectric dams, and transmission lines) and accessibility (navigable rivers and roads). Among accessibility factors, we found that rivers were the main facilitators in amphibian sampling. On the other hand, roads did not exert a strong influence as expected, due to the late and limited development of land transportation in the region, which has historically been dominated by river transportation. Among the infrastructure factors, both cities and hydroelectric plants had a moderate influence on sampling. The reason for this is that most cities in the Amazon region were established a few decades ago and have limited infrastructure, especially considering the presence of consolidated research centers. Hydroelectric plants have generated extensive databases due to environmental legislation requirements for their installation, but restricted access to information from these reports limited their use in this study. We conclude that Amazonian amphibian sampling exhibits significant geographic bias, attributable to the uneven distribution of research efforts caused by logistical challenges, including accessibility and infrastructure limitations. Overcoming these obstacles requires coordinated efforts between researchers and decision-makers, as well as investment in research infrastructure and data dissemination initiatives, not only for amphibians, but for all biodiversity in the face of increasing deforestation and climate change.

Polymyxin-B induced skin hyperpigmentation is an adverse event which can be easily missed by physician or dermatologists due to its rarity or not knowing about the fact. Here, I'm reporting a case in an adult patient admitted for pneumonia due to multidrug resistant klebsiella, received polymyxin-B for 4 days which led to development of skin hyperpigmentation, rapid in onset, confined to face and didn't resolve in 2 months of follow up, after stoppage of the culprit drug.

The report discusses the implications of using different volumes of flushing media during embryo flushing (EF) procedures in a single donor mare that experienced multiple unintended pregnancies following negative EF outcomes. The study involved two sets of EF experiments over two years on a non-lactating Spanish purebred mare with a single functioning ovary. The initial experiments (group, n=6) used 1L of flushing medium (Ringer´s Lactate), and subsequent tests (group 2, n=5) increased the volume to 2L, to assess whether a larger volume could enhance embryo recovery rates. No luteolytic agent was administered after any of the EF procedures. Data collection included the number of double and single ovulations (OV), embryos recovered and subsequent pregnancies. The overall incidence of double OV was 36.3%, and did not vary (p>0.05) between group 1 and 2 (33.3% and 40%). The results indicated a significant improvement (p<0.05) in embryo recovery rates with the increased medium volume in group 1 and 2, (25% and 85.7%, respectively). A tendency was noted (p=0.06) for more positive EF outcomes in group 2 (100% positive outcome). The number of pregnancies found based on the number of OV recorded was significant (4/8 and 0/7, p<0.05). The study concluded that a higher volume of flushing medium yields a higher embryo recovery rate and minimizes unintended pregnancies in the subject mare.