On the number of epi-, mono-, and homomorphisms of groups

It is known that the number of homomorphisms from a group $F$ to a group $G$ is divisible by the greatest common divisor of the order of $G$ and the exponent of $F/[F,F]$. We investigate the number of homomorphisms satisfying some natural conditions such as injectivity or surjectivity. The simplest nontrivial corollary of our results is the following fact: {\it in any finite group, the number of generating pairs $(x,y)$ such that $x^3=1=y^5$, is a multiple of the greatest common divisor of 15 and the order of the group $[G,G]\cdot\{g^{15}\;|\;g\in G\}$.Comment: 5 pages. A Russian version of this paper is at http://halgebra.math.msu.su/staff/klyachko/papers.htm . V2: minor corrections. arXiv admin note: text overlap with arXiv:1806.0887

Трудоустройство молодежи с высшим образованием и уроки пандемии: научный доклад

The scientific report presents the results of a monitoring study on the employment of youth with higher education, conducted in 2020 and capturing the first wave of the coronavirus pandemic

Development of exosome-encapsulated paclitaxel to overcome MDR in cancer cells

AbstractExosomes have recently come into focus as "natural nanoparticles" for use as drug delivery vehicles. Our objective was to assess the feasibility of an exosome-based drug delivery platform for a potent chemotherapeutic agent, paclitaxel (PTX), to treat MDR cancer. Herein, we developed different methods of loading exosomes released by macrophages with PTX (exoPTX), and characterized their size, stability, drug release, and in vitro antitumor efficacy. Reformation of the exosomal membrane upon sonication resulted in high loading efficiency and sustained drug release. Importantly, incorporation of PTX into exosomes increased cytotoxicity more than 50 times in drug resistant MDCKMDR1 (Pgp+) cells. Next, our studies demonstrated a nearly complete co-localization of airway-delivered exosomes with cancer cells in a model of murine Lewis lung carcinoma pulmonary metastases, and a potent anticancer effect in this mouse model. We conclude that exoPTX holds significant potential for the delivery of various chemotherapeutics to treat drug resistant cancers.From the Clinical EditorExosomes are membrane-derived natural vesicles of ~40 - 200 nm size. They have been under extensive research as novel drug delivery vehicles. In this article, the authors developed exosome-based system to carry formulation of PTX and showed efficacy in the treatment of multi-drug resistant cancer cells. This novel system may be further developed to carry other chemotherapeutic agents in the future

Macrophages offer a paradigm switch for CNS delivery of therapeutic proteins

Active targeted transport of the nanoformulated redox enzyme, catalase, in macrophages attenuates oxidative stress and as such increases survival of dopaminergic neurons in animal models of Parkinson’s disease. Optimization of the drug formulation is crucial for the successful delivery in living cells. We demonstrated earlier that packaging of catalase into a polyion complex micelle (‘nanozyme’) with a synthetic polyelectrolyte block copolymer protected the enzyme against degradation in macrophages and improved therapeutic outcomes. We now report the manufacture of nanozymes with superior structure and therapeutic indices

SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages

This year's iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features. In terms of the task, we enrich UniMorph with new data for 32 languages from 13 language families, with most of them being under-resourced: Kunwinjku, Classical Syriac, Arabic (Modern Standard, Egyptian, Gulf), Hebrew, Amharic, Aymara, Magahi, Braj, Kurdish (Central, Northern, Southern), Polish, Karelian, Livvi, Ludic, Veps, Võro, Evenki, Xibe, Tuvan, Sakha, Turkish, Indonesian, Kodi, Seneca, Asháninka, Yanesha, Chukchi, Itelmen, Eibela. We evaluate six systems on the new data and conduct an extensive error analysis of the systems' predictions. Transformer-based models generally demonstrate superior performance on the majority of languages, achieving >90% accuracy on 65% of them. The languages on which systems yielded low accuracy are mainly under-resourced, with a limited amount of data. Most errors made by the systems are due to allomorphy, honorificity, and form variation. In addition, we observe that systems especially struggle to inflect multiword lemmas. The systems also produce misspelled forms or end up in repetitive loops (e.g., RNN-based models). Finally, we report a large drop in systems' performance on previously unseen lemmas.Peer reviewe