Pyo-ovarium during pregnancy. Case report

The issue of postpartum inflammatory diseases of the uterus and appendages remains relevant for modern obstetrics due to their high percentage (5–26%) in the structure of morbidity and mortality among postpartum women. A rare clinical case of purulent oophoritis that occurred in a woman at the end of pregnancy and was detected on day 22 after childbirth, which was due to diagnostic difficulties, is presented, and the management approach in this clinical situation is shown

Transboundary Cooperation Improves Endangered Species Monitoring and Conservation Actions: A Case Study of the Global Population of Amur Leopards

Political borders and natural boundaries of wildlife populations seldom coincide, often to the detriment of conservation objectives. Transnational monitoring of endangered carnivores is rare, but is necessary for accurate population monitoring and coordinated conservation policies. We investigate the benefits of collaboratively monitoring the abundance and survival of the critically endangered Amur leopard, which occurs as a single transboundary population across China and Russia. Country‐specific results overestimated abundance and were generally less precise compared to integrated monitoring estimates; the global population was similar in both years: 84 (70–108, 95% confidence interval). Uncertainty in country‐specific annual survival estimates were approximately twice the integrated estimates of 0.82 (0.69–0.91, 95% confidence limits). This collaborative effort provided a better understanding of Amur leopard population dynamics, represented a first step in building trust, and lead to cooperative agreements to coordinate conservation policies

Modern Pollen Assemblages From Lake Sediments and Soil in East Siberia and Relative Pollen Productivity Estimates for Major Taxa

Modern pollen–vegetation–climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen–vegetation–climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.</jats:p

Epidemiology of Brucellosis and Genetic Diversity of Brucella abortus in Kazakhstan

Brucellosis is a major zoonotic infection in Kazakhstan. However, there is limited data on its incidence in humans and animals, and the genetic diversity of prevalent strains is virtually unstudied. Additionally, there is no detailed overview of Kazakhstan brucellosis control and eradication programs. Here, we analyzed brucellosis epidemiological data, and assessed the effectiveness of eradication strategies employed over the past 70 years to counteract this infection. We also conducted multiple loci variable-number tandem repeat analysis (MLVA) of Brucella abortus strains found in Kazakhstan. We analyzed official data on the incidence of animal brucellosis in Kazakhstan. The records span more than 70 years of antibrucellosis campaigns, and contain a brief description of the applied control strategies, their effectiveness, and their impact on the incidence in humans. The MLVA-16 method was used to type 94 strains of B. abortus and serial passages of B. abortus 82, a strain used in vaccines. MLVA-8 and MLVA-11 analyses clustered strains into a total of four and sevengenotypes, respectively; it is the first time that four of these genotypes have been described. MLVA-16 analysis divided strains into 28 distinct genotypes having genetic similarity coefficient that varies from 60 to100% and a Hunter & Gaston diversity index of 0.871. MST analysis reconstruction revealed clustering into "Kazakhstani-Chinese (Central Asian)", "European" and "American" lines. Detection of multiple genotypes in a single outbreak confirms that poorly controlled trade of livestock plays a crucial role in the spread of infection. Notably, the MLVA-16 profile of the B. abortus 82 strain was unique and did not change during 33 serial passages. MLVA genotyping may thus be useful for epidemiological monitoring of brucellosis, and for tracking the source(s) of infection. We suggest that countrywide application of MLVA genotyping would improve the control of brucellosis in Kazakhstan

Pharmacological sequestration of mitochondrial calcium uptake protects against dementia and β-amyloid neurotoxicity

All forms of dementia including Alzheimer's disease are currently incurable. Mitochondrial dysfunction and calcium alterations are shown to be involved in the mechanism of neurodegeneration in Alzheimer's disease. Previously we have described the ability of compound Tg-2112x to protect neurons via sequestration of mitochondrial calcium uptake and we suggest that it can also be protective against neurodegeneration and development of dementia. Using primary co-culture neurons and astrocytes we studied the effect of Tg-2112x and its derivative Tg-2113x on β-amyloid-induced changes in calcium signal, mitochondrial membrane potential, mitochondrial calcium, and cell death. We have found that both compounds had no effect on β-amyloid or acetylcholine-induced calcium changes in the cytosol although Tg2113x, but not Tg2112x reduced glutamate-induced calcium signal. Both compounds were able to reduce mitochondrial calcium uptake and protected cells against β-amyloid-induced mitochondrial depolarization and cell death. Behavioral effects of Tg-2113x on learning and memory in fear conditioning were also studied in 3 mouse models of neurodegeneration: aged (16-month-old) C57Bl/6j mice, scopolamine-induced amnesia (3-month-old mice), and 9-month-old 5xFAD mice. It was found that Tg-2113x prevented age-, scopolamine- and cerebral amyloidosis-induced decrease in fear conditioning. In addition, Tg-2113x restored fear extinction of aged mice. Thus, reduction of the mitochondrial calcium uptake protects neurons and astrocytes against β-amyloid-induced cell death and contributes to protection against dementia of different ethology. These compounds could be used as background for the developing of a novel generation of disease-modifying neuroprotective agents

SiDroForest: a comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labeled trees, synthetically generated tree crowns, and Sentinel-2 labeled image patches

The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen–evergreen transition zone in Central Yakutia and the tundra–taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, https://doi.org/10.1594/PANGAEA.933263). The dataset includes structure-from-motion (SfM) point clouds and red–green–blue (RGB) and red–green–near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot.ii. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, https://doi.org/10.1594/PANGAEA.932821). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future.iii. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch (Larix gmelinii and Larix cajanderi) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, https://doi.org/10.1594/PANGAEA.932795). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species.iv. Dataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, https://doi.org/10.1594/PANGAEA.933268). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra–taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.</p

A clinical case of post-COVID-19 myoendocarditis and arrhythmic syndrome at the outpatient stage

Background: Infection with the SARS-CoV-2 virus entails the development of complications which affect the prognosis of the underlying disease. More than 40% of COVID-19 complications represent diseases of the cardiovascular system, most of which are the rhythm and conduction disturbances. In order to avoid these complications, it is necessary to detect cases of infection in a timely manner at the outpatient stage. Clinical case description: A 40-year-old patient came to the clinic with complaints of interruptions in the heart rhythm that appeared after the coronavirus infection. The laboratory examination (CBC) revealed signs of systemic inflammation (leukocytosis 12.6×109 U/l; erythrocyte sedimentation rate 18 mm/h, C-reactive protein 18 mg/l); the instrumental examination of the heart revealed the rhythm disturbances in the form of frequent ventricular ectopic activity and weakness of the SA node. The patient received propafenone (150 mg, 3 times a day) as a therapy with a positive effect. Against the background of improvement in the patient’s condition and despite the history of myocarditis and a positive result of enzyme immunoassay for antibodies to SARS-CoV-2 (IgG, 10 BAU/ml), the patient was prescribed immunization with the CoviVac vaccine. After the immunization, the condition worsening was observed in the form of an increase in the rhythm disturbances, which required an inpatient treatment. A clinical diagnosis of recurrent ventricular arrhythmia — ventricular extrasystole was established, and the therapy was corrected. The outcome was favorable. Conclusion: Myocarditis is one of the most common complications of SARS-CoV-2 and should be kept in mind at all stages of medical care. This clinical case demonstrates the importance of the correct diagnosis and treatment of post-COVID myocarditis, as well as the need to assess contraindications for SARS-CoV-2 vaccination in patients with cardiac complications

Distemper, extinction, and vaccination of the Amur tiger

Canine distemper virus (CDV) has recently emerged as an extinction threat for the endangered Amur tiger (Panthera tigris altaica). CDV is vaccine-preventable, and control strategies could require vaccination of domestic dogs and/or wildlife populations. However, vaccination of endangered wildlife remains controversial, which has led to a focus on interventions in domestic dogs, often assumed to be the source of infection. Effective decision making requires an understanding of the true reservoir dynamics, which poses substantial challenges in remote areas with diverse host communities. We carried out serological, demographic, and phylogenetic studies of dog and wildlife populations in the Russian Far East to show that a number of wildlife species are more important than dogs, both in maintaining CDV and as sources of infection for tigers. Critically, therefore, because CDV circulates among multiple wildlife sources, dog vaccination alone would not be effective at protecting tigers. We show, however, that low-coverage vaccination of tigers themselves is feasible and would produce substantive reductions in extinction risks. Vaccination of endangered wildlife provides a valuable component of conservation strategies for endangered species

Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass‐loss rate and stabilization

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large‐scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass‐loss rates and stabilization factors of plant‐derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy‐to‐degrade components accumulate during early‐stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass‐loss rates and stabilization, notably in colder locations. Using TBI improved mass‐loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early‐stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models

A complex approach to study the Amur leopard using camera traps in Protected Areas in the southwest of Primorsky krai (Russian Far East)

The paper describes the methodology and preliminary results of a complex camera trap study of the Amur leopard. The main studies were concentrated on protected areas: the Land of the Leopard National Park with its buffer zone and the Kedrovaya Pad' Biosphere Reserve, a total area of 3600 sq.km. The first results of the 2014–2015 survey period are presented. According to spatial capture-recapture analysis at least 57 adult Amur leopards occupied the Russian protected areas with the density of about 0.98 individuals/100 sq.km. The sex ratio (male : female) was 1:1.2. Five breeding females with 11 cubs were registered in 2014 and 9 females with 16 cubs in 2015. The basis was founded for long-term monitoring of and fundamental research on the Amur leopard in the protected areas in Primorsky Krai