PGT-M for spinocerebellar ataxia type 1: development of a STR panel and a report of two clinical cases.

PURPOSE: To present the developed preimplantation genetic testing (PGT) for spinocerebellar ataxia type 1 (SCA1) and the outcomes of IVF with PGT. METHODS: PGT was performed for two unrelated couples from the Republic of Sakha (Yakutia) with the risk of SCA1 in one spouse. We have developed a system for PGT of a monogenic disease (PGT-M) for SCA1, which includes the analysis of a panel of 11 polymorphic STR markers linked to the ATXN1 gene and a pathogenic variant of the ATXN1 gene using nested PCR and fragment analysis. IVF/ICSI programs were performed according to standard protocols. Multiple displacement amplification (MDA) was used for whole genome amplification (WGA) and array comparative genomic hybridization (aCGH) for aneuploidy testing (PGT-A). RESULTS: Eight STRs were informative for the first couple and ten for the second. Similarity of the haplotypes carrying pathogenic variants of the ATXN1 gene was noted. In the first case, during IVF/ICSI-PGT, three embryos reached the blastocyst stage and were biopsied. One embryo was diagnosed as normal by maternal STR haplotype and the ATXN1 allele. PGT-A revealed euploidy. The embryo transfer resulted in a singleton pregnancy, and a healthy boy was born. Postnatal diagnosis confirmed normal ATXN1. In the second case, two blastocysts were biopsied. Both were diagnosed as normal by PGT-M, but PGT-A revealed aneuploidy. CONCLUSION: Birth of a healthy child after PGT for SCA1 was the first case of successful preimplantation prevention of SCA1 for the Yakut couple and the first case of successful PGT for SCA1 in Russia.

Universal Approach to Integrating Reduced Graphene Oxide into Polymer Electronics.

Flexible electronics have sparked significant interest in the development of electrically conductive polymer-based composite materials. While efforts are being made to fabricate these composites through laser integration techniques, a versatile methodology applicable to a broad range of thermoplastic polymers remains elusive. Moreover, the underlying mechanisms driving the formation of such composites are not thoroughly understood. Addressing this knowledge gap, our research focuses on the core processes determining the integration of reduced graphene oxide (rGO) with polymers to engineer coatings that are not only flexible and robust but also exhibit electrical conductivity. Notably, we have identified a particular range of laser power densities (between 0.8 and 1.83 kW/cm2), which enables obtaining graphene polymer composite coatings for a large set of thermoplastic polymers. These laser parameters are primarily defined by the thermal properties of the polymers as confirmed by thermal analysis as well as numerical simulations. Scanning electron microscopy with elemental analysis and X-ray photoelectron spectroscopy showed that conductivity can be achieved by two mechanisms-rGO integration and polymer carbonization. Additionally, high-speed videos allowed us to capture the graphene oxide (GO) modification and melt pool formation during laser processing. The cross-sectional analysis of the laser-processed samples showed that the convective flows are present in the polymer substrate explaining the observed behavior. Moreover, the practical application of our research is exemplified through the successful assembly of a conductive wristband for wearable devices. Our study not only fills a critical knowledge gap but also offers a tangible illustration of the potential impact of laser-induced rGO-polymer integration in materials science and engineering applications.

Quantitative Prediction of Inorganic Nanomaterial Cellular Toxicity via Machine Learning.

Organic chemistry has seen colossal progress due to machine learning (ML). However, the translation of artificial intelligence (AI) into materials science is challenging, where biological behavior prediction becomes even more complicated. Nanotoxicity is a critical parameter that describes their interaction with the living organisms screened in every bio-related research. To prevent excessive experiments, such properties have to be pre-evaluated. Several existing ML models partially fulfill the gap by predicting whether a nanomaterial is toxic or not. Yet, this binary categorization neglects the concentration dependencies crucial for experimental scientists. Here, an ML-based approach is proposed to the quantitative prediction of inorganic nanomaterial cytotoxicity achieving the precision expressed by 10-fold cross-validation (CV) Q2  = 0.86 with the root mean squared error (RMSE) of 12.2% obtained by the correlation-based feature selection and grid search-based model hyperparameters optimization. To provide further model flexibility, quantitative atom property-based nanomaterial descriptors are introduced allowing the model to extrapolate on unseen samples. Feature importance is calculated to find an interpretable model with optimal decision-making. These findings allow experimental scientists to perform primary in silico candidate screening and minimize the number of excessive, labor-intensive experiments enabling the rapid development of nanomaterials for medicinal purposes.

Climate-induced mortality of Siberian pine and fir in the Lake Baikal Watershed, Siberia.

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called "dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Tree Wave Migration Across an Elevation Gradient in the Altai Mountains, Siberia.

The phenomenon of "tree waves" (hedges and ribbons) formation within the alpine ecotone in Altai Mountains and its response to observed air temperature increase was considered. At the upper limit of tree growth Siberian pine (Pinus sibirica) forms hedges on windward slopes and ribbons on the leeward ones. Hedges were formed by prevailing winds and oriented along winds direction. Ribbons were formed by snow blowing and accumulating on the leeward slope and perpendicular to the prevailing winds, as well as to the elevation gradient. Hedges were always linked with microtopography features, whereas ribbons were not. Trees are migrating upward by waves and new ribbons and hedges are forming at or near tree line, whereas at lower elevations ribbons and hedges are being transformed into closed forests. Time series of high-resolution satellite scenes (from 1968 to 2010) indicated an upslope shift in the position ribbons averaged 155±26 m (or 3.7 m yr-1) and crown closure increased (about 35-90%). The hedges advance was limited by poor regeneration establishment and was negligible. Regeneration within the "ribbon zone" was approximately 2.5 times (5060 vs 2120 ha-1) higher then within the "hedges zone". During the last four decades, Siberian pine in both hedges and ribbons strongly increased its growth increment and recent tree growth rate for 50 year old trees was about twice higher than recorded for similarly aged trees at the beginning of the 20th century. Hedges and ribbons are phenomena that are widespread within the southern and northern Siberian Mountains.

Larch Forests of Middle Siberia: Long-Term Trends in Fire Return Intervals.

Fire history within the northern larch forests of Central Siberia was studied (65+°N). Fires within this area are predominantly caused by lightning strikes rather than human activity. Mean fire return intervals (FRI) were found to be 112 ± 49 years (based on fire scars) and 106 ± 36 years (based on fire scars and tree natality dates). FRI were increased with latitude increase, and observed to be about 80 years at 64°N, about 200 years near the Arctic Circle, and about 300 years nearby the northern range limit of larch stands (~71°+N). Northward FRI increase correlated with incoming solar radiation (r = - 0.95). Post Little Ice Age (LIA) warming (after 1850) caused approximately a doubling of fire events (in comparison with a similar period during LIA). The data obtained support a hypothesis of climate-induced fire frequency increase.