12 research outputs found

    First Report of Insect Endophytic Oviposition from the Upper Permian of the Pechora Basin, on a Leaf of Phylladoderma (Peltaspermopsida: Cardiolepidaceae)

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    Β© 2020, Pleiades Publishing, Ltd. Abstract: The first endophytic oviposition from the Upper Permian of the Pechora Basin (Talbeyskaya Formation, Severodvinian–Vyatkian) is described in a formal system. Paleoovoidus krassilovi sp. nov. is a linear oviposition arranged in two oppositely directed rows on a leaf of Phylladoderma arberi Zalessky, 1913; it was probably produced by an odonatan insect. Cuticle punctures that probably represent traces of feeding by small and/or young palaeodictyopteroid nymphs were previously described from Phylladoderma leaves found in the same deposits. Fossil insects remain unknown from the Talbeyskaya Formation, but fossil records of plant–insect interactions enable the reconstruction of a well-balanced insect community that included sucking phytophages (palaeodictyopteroids) and predators (odonatans)

    ΠΠ΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΡŒΠ½Ρ‹Π΅ Π²Π½Π΅ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹Π΅ Π»ΠΎΠ²ΡƒΡˆΠΊΠΈ: Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ для диагностики ΠΈ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π° COVID-19

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    Rationale: An important element of antiviral defense in the pathophysiology of COVID-19 is the innate cell immunity including polymorphonuclear neutrophils prone to netotic transformation. Neutrophils can be not only a marker of acute infection, but, being a source of neutrophil extracellular traps (NET), can play a key role in the development of thrombotic complications leading to acute respiratory insufficiency in COVID-19.Aim: To determine the diagnostic and prognostic value of NET levels in patients with COVID-19.Materials and methods: We monitored NET levels in peripheral blood of 34 patients with COVID-19 (mean age, 67 Β± 15.8 years), admitted to MONIKI hospital. The control group consisted of 54 healthy volunteers (mean age, 52 Β± 11.5 years). Whole blood samples of 2 pL each were used for the preparation of monolayer smears (Giemsa stain) and calculation of at least 200 cell structures including native intact and transformed neutrophils (MECOS-C2 microscope, Medical computer systems).Results: Patients with COVID-19 had higher NET levels, compared to those in healthy controls: 14.5% (2.9-28.6%) vs. 5.0% (1.8-11.9%, p 0.0001). The patients who were on non-invasive respiratory support (23.5%) had a NET level of 12% (8.122.3%), whereas those on invasive mechanical ventilation (17.6%) had a 1.5-fold higher NET level of 17.9% (12.3-28.2%) (p 0.05). In the patients who died (11.8% of the cases), the NET level amounted to 19% (16.5-26%, p 0.05). Monitoring of blood NET levels was performed in 9 patients from the day of admittance to the day of their transfer to the intensive care unit / discharge / death. It was shown that a decrease of NET levels mirrors an improvement of the patient's clinical condition and efficacy of his/hers treatment. On the opposite, an increase of NET levels can indicate a deterioration and risk of unfavorable course.Conclusion: We have identified some pathophysiological mechanisms in COVID-19, related to the neutrophil compartment. Patients with coronavirus infection are characterized by high NET levels which is at least 3-fold higher than that in healthy volunteers. This indicates an abnormality in immune host defense and development of an inadequate inflammatory response. An increase of NET in whole blood smears of more than 16% can be a criterion of an unfavorable prognosis of the disease course and the risk of death.ΠΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ. Π’ ΠΏΠ°Ρ‚ΠΎΠ³Π΅Π½Π΅Π·Π΅ COVID-19 Π²Π°ΠΆΠ½Ρ‹ΠΌ элСмСнтом противовирусной Π·Π°Ρ‰ΠΈΡ‚Ρ‹ выступаСт Π²Ρ€ΠΎΠΆΠ΄Π΅Π½Π½Ρ‹ΠΉ ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹ΠΉ ΠΈΠΌΠΌΡƒΠ½ΠΈΡ‚Π΅Ρ‚, Π²ΠΊΠ»ΡŽΡ‡Π°ΡŽΡ‰ΠΈΠΉ Π² Ρ‚ΠΎΠΌ числС полиморфноядСрныС Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»Ρ‹, склонныС ΠΊ Π½Π΅Ρ‚ΠΎΠ·Π½ΠΎΠΉ трансформации. ΠŸΡ€ΠΈ этом Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»Ρ‹ Π½Π΅ Ρ‚ΠΎΠ»ΡŒΠΊΠΎ слуТат ΠΌΠ°Ρ€ΠΊΠ΅Ρ€ΠΎΠΌ острой ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ, Π½ΠΎ ΠΈ, Π±ΡƒΠ΄ΡƒΡ‡ΠΈ источником Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Π²Π½Π΅ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹Ρ… Π»ΠΎΠ²ΡƒΡˆΠ΅ΠΊ (НВЛ), ΠΈΠ³Ρ€Π°ΡŽΡ‚ ΠΊΠ»ΡŽΡ‡Π΅Π²ΡƒΡŽ Ρ€ΠΎΠ»ΡŒ Π² Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠΈ тромботичСских ослоТнСний, приводящих ΠΊ острой Π΄Ρ‹Ρ…Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠΉ нСдостаточности ΠΏΡ€ΠΈ COVID-19.ЦСль - ΡƒΡΡ‚Π°Π½ΠΎΠ²ΠΈΡ‚ΡŒ диагностичСскоС ΠΈ прогностичСскоС Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ уровня Π²Π½Π΅ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹Ρ… Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Π»ΠΎΠ²ΡƒΡˆΠ΅ΠΊ Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с COVID-19.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π» ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. ΠŸΡ€ΠΎΠ²Π΅Π΄Π΅Π½ ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³ уровня НВЛ пСрифСричСской ΠΊΡ€ΠΎΠ²ΠΈ Ρƒ 34 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с COVID-19 (срСдний возраст 67 Β± 15,8 Π³ΠΎΠ΄Π°), госпитализированных Π² Π“Π‘Π£Π— МО МОНИКИ ΠΈΠΌ. М.Π€. Владимирского. ΠšΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½ΡƒΡŽ Π³Ρ€ΡƒΠΏΠΏΡƒ составили 54 практичСски Π·Π΄ΠΎΡ€ΠΎΠ²Ρ‹Ρ… Π΄ΠΎΠ±Ρ€ΠΎΠ²ΠΎΠ»ΡŒΡ†Π° (срСдний возраст 52 Β± 11,5 Π³ΠΎΠ΄Π°). Из 2 ΠΌΠΊΠ» Ρ†Π΅Π»ΡŒΠ½ΠΎΠΉ ΠΊΡ€ΠΎΠ²ΠΈ Π³ΠΎΡ‚ΠΎΠ²ΠΈΠ»ΠΈ ΠΌΠ°Π·ΠΊΠΈ ΠΏΠΎ Ρ‚ΠΈΠΏΡƒ «монослой», ΠΎΠΊΡ€Π°ΡˆΠΈΠ²Π°Π»ΠΈ ΠΏΠΎ Романовскому - Π“ΠΈΠΌΠ·Π΅ ΠΈ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ систСмы автоматичСского микроскопа ΠœΠ•ΠšΠžΠ‘-Π¦2 (ООО Β«ΠœΠ΅Π΄ΠΈΡ†ΠΈΠ½ΡΠΊΠΈΠ΅ ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½Ρ‹Π΅ систСмы (ΠœΠ•ΠšΠžΠ‘)Β») подсчитывали массив Π½Π΅ ΠΌΠ΅Π½Π΅Π΅ 200 ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹Ρ… структур, Π²ΠΊΠ»ΡŽΡ‡Π°ΡŽΡ‰ΠΈΠΉ Π½Π°Ρ‚ΠΈΠ²Π½Ρ‹Π΅ Π½Π΅Ρ€Π°Π·Ρ€ΡƒΡˆΠ΅Π½Π½Ρ‹Π΅ ΠΈ трансформированныС Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»Ρ‹.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π£ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с COVID-19 зарСгистрирован высокий ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ НВЛ - 14,5% (2,9-28,6%) ΠΏΡ€ΠΎΡ‚ΠΈΠ² 5,0% (1,8-11,9%) Π² ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½ΠΎΠΉ Π³Ρ€ΡƒΠΏΠΏΠ΅ (p 0,0001). 23,5% Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ…, ΠΏΠΎΠ»ΡƒΡ‡Π°Π²ΡˆΠΈΡ… ΠΏΡ€ΠΎΡΡ‚ΡƒΡŽ Ρ€Π΅ΡΠΏΠΈΡ€Π°Ρ‚ΠΎΡ€Π½ΡƒΡŽ ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ, продСмонстрировали ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ НВЛ 12% (8,1-22,3%), Ρ‚ΠΎΠ³Π΄Π° ΠΊΠ°ΠΊ Ρƒ 17,6% ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ΄ΠΊΠ»ΡŽΡ‡Π΅Π½Ρ‹ ΠΊ искусствСнной вСнтиляции Π»Π΅Π³ΠΊΠΈΡ…, ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ НВЛ оказался Π² 1,5 Ρ€Π°Π·Π° Π²Ρ‹ΡˆΠ΅ - 17,9% (12,3-28,2%) (p 0,05). Π’ 11,8% случаСв с Π»Π΅Ρ‚Π°Π»ΡŒΠ½Ρ‹ΠΌ исходом ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ НВЛ достигал 19% (16,5-26%) (p 0,05). ΠœΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³ уровня НВЛ Π² ΠΊΡ€ΠΎΠ²ΠΈ 9 Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… ΠΎΡ‚ ΠΌΠΎΠΌΠ΅Π½Ρ‚Π° поступлСния Π΄ΠΎ ΠΌΠΎΠΌΠ΅Π½Ρ‚Π° ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ΄Π° Π² ΠΎΡ‚Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Ρ€Π΅Π°Π½ΠΈΠΌΠ°Ρ†ΠΈΠΈ ΠΈ интСнсивной Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ/выписки ΠΈΠ»ΠΈ смСрти ΠΏΠΎΠΊΠ°Π·Π°Π», Ρ‡Ρ‚ΠΎ сниТСниС уровня ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½Π½Ρ‹Ρ… НВЛ ΠΎΡ‚Ρ€Π°ΠΆΠ°Π΅Ρ‚ ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½ΠΈΠ΅ клиничСского состояния ΠΈ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠΉ Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ. Рост уровня НВЛ, Π½Π°ΠΏΡ€ΠΎΡ‚ΠΈΠ², ΠΌΠΎΠΆΠ΅Ρ‚ ΡΠ²ΠΈΠ΄Π΅Ρ‚Π΅Π»ΡŒΡΡ‚Π²ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΠ± ΡƒΡ…ΡƒΠ΄ΡˆΠ΅Π½ΠΈΠΈ ΠΈ рискС Π½Π΅Π³Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ развития событий.Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. ВыявлСны Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ патофизиологичСскиС ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΡ‹ развития COVID-19, связанныС с ΠΊΠΎΠΌΠΏΠ°Ρ€Ρ‚ΠΌΠ΅Π½Ρ‚ΠΎΠΌ Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΠΎΠ². УстановлСно, Ρ‡Ρ‚ΠΎ для Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… с коронавирусной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠ΅ΠΉ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π½ΠΎ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ высокого уровня НВЛ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ Π² 3 Ρ€Π°Π·Π° ΠΈ Π±ΠΎΠ»Π΅Π΅ ΠΏΡ€Π΅Π²Ρ‹ΡˆΠ°Π΅Ρ‚ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ практичСски Π·Π΄ΠΎΡ€ΠΎΠ²Ρ‹Ρ… Π΄ΠΎΠ±Ρ€ΠΎΠ²ΠΎΠ»ΡŒΡ†Π΅Π² ΠΈ ΡΠ²ΠΈΠ΄Π΅Ρ‚Π΅Π»ΡŒΡΡ‚Π²ΡƒΠ΅Ρ‚ ΠΎ сбоС ΠΈΠΌΠΌΡƒΠ½Π½Ρ‹Ρ… ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΠΎΠ² Π·Π°Ρ‰ΠΈΡ‚Ρ‹ ΠΈ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠΈ Π½Π΅Π°Π΄Π΅ΠΊΠ²Π°Ρ‚Π½ΠΎΠ³ΠΎ Π²ΠΎΡΠΏΠ°Π»ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π°. ΠŸΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΠ΅ Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Π²Π½Π΅ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹Ρ… Π»ΠΎΠ²ΡƒΡˆΠ΅ΠΊ Π² ΠΌΠ°Π·ΠΊΠ°Ρ… Ρ†Π΅Π»ΡŒΠ½ΠΎΠΉ ΠΊΡ€ΠΎΠ²ΠΈ Π±ΠΎΠ»Π΅Π΅ 16% ΠΌΠΎΠΆΠ΅Ρ‚ ΡΠ»ΡƒΠΆΠΈΡ‚ΡŒ ΠΊΡ€ΠΈΡ‚Π΅Ρ€ΠΈΠ΅ΠΌ Π½Π΅Π³Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π° тСчСния заболСвания ΠΈ риска Π»Π΅Ρ‚Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ исхода

    Causes of Juvenile Delinquency in the Republic of Kazakhstan

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    Goal: The goal of this paper is to identify the causes of juvenile delinquency in the Republic of Kazakhstan. Methodology: Application of interviewing and expert estimation methods, as well as sociological method helped to study crime among minors as a periodically changing social and legal phenomenon caused by a set of social, political, economic, legal and psychological-pedagogical reasons and conditions. Results: The primary causes of juvenile delinquency in the Republic of Kazakhstan have been identified. These include: impact of the mass media, Internet etc., which resulted in a weakening of the previously existing family and social traditions; low social level of the family; asocial lifestyle of parents; lack of control by adults; negative environment in which a juvenile lives and resides; inoccupation and lack of leisure during non-study time. Β© 2020, Springer Nature Switzerland AG

    Climate and biotic evolution during the Permian-Triassic transition in the temperate Northern Hemisphere, Kuznetsk Basin, Siberia, Russia

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    The Siberian Traps volcanism is widely considered the main cause of the end-Permian mass extinction, the greatest biological crisis in the Earth history. While the extinction is interpreted as catastrophic and sudden with estimates of duration of approximately 35–40 thousand years from marine strata in South China, various lines of evidence have emerged for a more complex, prolonged, and diachronous extinction pattern. We present here the results of a multidisciplinary study of the Permian-Triassic continental transition in the Kuznetsk Basin, Russia. The region is proximal to the Siberian Traps LIP and the detrimental effects of the flood basalt volcanism in the Kuznetsk Basin may have been of similar scale as in the main area of the Siberian Traps distribution (Tunguska and Taymyr regions). Whereas earlier work has placed the Permian-Triassic boundary position between the coal-bearing Tailugan Formation and the volcanoclastic Maltsev Formation, here we revised the traditional model using three independent methods: radioisotopic CA-IDTIMS U-Pb zircon ages, Ξ΄13Corg isotope values and paleomagnetic proxies. The regional extinction of the humid-dominated forest flora (cordaites) and the aridity-induced biotic turnover in the Kuznetsk Basin occurred 820 kyr earlier than the end-Permian extinction event recorded in South China at 251.94 Ma. The biota in Kuznetsk Basin at the turnover subsequently diversified (with some exceptions) across the Permian-Triassic transition. By compiling a large taxonomic database, we find that marine and terrestrial biotic diversity in Siberia progressively increased from the beginning of the Permian up to the middle Roadian (early Guadalupian global glacial event). After that time, the diversity at the species and generic level progressively and slowly declined towards the aforementioned latest Changhsingian (252.76 Ma) biotic turnover. Starting from this time, the biota rapidly diversified in the latest Changhsingian and Early-Middle Triassic. We suggest that the Permian-Triassic mass extinction mostly occurred in the tropics and subtropics due to the strong climatic warming, which was relatively low in late Changhsingian and gradually but quickly extends in the latest Changhsingian to an abnormally high temperature and extremely low oxygenated water in the oceans that was deadly for most marine animals. The warm climate shift poleward during Permian-Triassic transition in the middle-high latitudes caused the replacement (turnover) of the humid-related biotas by the dry climate-related and more diverse communities, which continued to expand throughout the Triassic in both marine and terrestrial habitats. The pattern of the Permian-Triassic event in both marine and terrestrial habitats was more intricate in terms of extinction, turnover, and diversity of biota within the different climatic zones and environmental habitats than has been generally considered
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