Imperfectly coordinated water molecules pave the way for homogeneous ice nucleation

Water freezing is ubiquitous on Earth, affecting many areas from biology to climate science and aviation technology. Probing the atomic structure in the homogeneous ice nucleation process from scratch is of great value but still experimentally unachievable. Theoretical simulations have found that ice originates from the low-mobile region with increasing abundance and persistence of tetrahedrally coordinated water molecules. However, a detailed microscopic picture of how the disordered hydrogen-bond network rearranges itself into an ordered network is still unclear. In this work, we use a deep neural network (DNN) model to "learn" the interatomic potential energy from quantum mechanical data, thereby allowing for large-scale and long molecular dynamics (MD) simulations with ab initio accuracy. The nucleation mechanism and dynamics at atomic resolution, represented by a total of 36 $\mu$s-long MD trajectories, are deeply affected by the structural and dynamical heterogeneity in supercooled water. We find that imperfectly coordinated (IC) water molecules with high mobility pave the way for hydrogen-bond network rearrangement, leading to the growth or shrinkage of the ice nucleus. The hydrogen-bond network formed by perfectly coordinated (PC) molecules stabilizes the nucleus, thus preventing it from vanishing and growing. Consequently, ice is born through competition and cooperation between IC and PC molecules. We anticipate that our picture of the microscopic mechanism of ice nucleation will provide new insights into many properties of water and other relevant materials.Comment: 20 pages, 4 figures, under peer revie

Leczenie oksytocyną zapobiega stłuszczeniu szpiku kostnego obserwowanemu u królików z cukrzycą wywołaną alloksanem — badanie przy użyciu protonowej spektroskopii rezonansu magnetycznego

Introduction: Oxytocin might be used therapeutically as an ally to rescue osteopathy resulting from diabetes. However, the in vivo effects of oxytocin on marrow adipogenesis in diabetes remain unknown. In this longitudinal study, we aimed to investigate the protective ef­fects of oxytocin on diabetes-induced marrow adiposity in rabbits using proton MR spectroscopy. Material and methods: Forty-five female New Zealand rabbits were randomly divided into controls, diabetes, and diabetes treated with oxytocin (ip, 0.78 mg/kg) for six months. Marrow fat fraction (FF) was determined by proton MR spectroscopy at baseline, and at three and six months. Bone mineral density was measured by dual-energy X-ray absorptiometry. Serum biomarkers, glycolipid metabolism, and histological analysis of marrow adipocytes were determined. Results: Oxytocin treatment had positive metabolic effects in diabetic rabbits, which was based on the changes in glucose metabolism, insulin sensitivity, and lipid profiles. The diabetic rabbits demonstrated dramatic marrow adiposity in a time-dependent manner; at three and six months the FF percentage changes from baseline were 10.1% and 25.8%, respectively (all P < 0.001). Moreover, oxytocin treatment significantly reversed FF values and quantitative parameters of marrow adipocyte in diabetic rabbits to levels of naive control rabbits. Oxytocin improved bone formation marker in diabetic rabbits compared to the saline group. Also, treatment of diabetic rabbits with oxytocin significantly mitigated bone deterioration when compared with the saline-treated diabetic group (all P < 0.05). Conclusions: Oxytocin appears to alleviate harmful effects of hyperglycaemia on marrow adiposity. Proton MR spectroscopy may be a valuable tool, providing complementary information on efficacy assessments.Wstęp: Oksytocyna może być stosowana terapeutycznie w osteopatii wynikającej z cukrzycy, jednakże jej wpływ in vivo na stłuszczenie szpiku kostnego w przebiegu cukrzycy pozostaje niezbadany. Niniejsze badanie przekrojowe ma na celu zbadać ochronne działanie oksy­tocyny na wywołane cukrzycą stłuszczenie szpiku kostnego u królików przy użyciu protonowej spektroskopii rezonansu magnetycznego. Materiał i metody: Czterdzieści pięć samic królików nowozelandzkich podzielono losowo na grupę kontrolną, grupę z cukrzycą oraz grupę z cukrzycą leczoną oksytocyną (0.78 mg/kg, i.p.) przez sześć miesięcy. Frakcja tłuszczu (ang. fat fraction; FF) szpiku kostnego została określona za pomocą protonowej spektroskopii rezonansu magnetycznego na początku badania oraz po trzech i sześciu miesiącach. Gęstość mineralną kości zmierzono za pomocą absorpcjometrii promieniowania rentgenowskiego o podwójnej energii. Określono również biomarkery surowicy krwi, metabolizm glikolipidów oraz sporządzono analizę histologiczną adipocytów szpiku kostnego. Wyniki: Leczenie oksytocyną przyniosło pozytywne efekty metaboliczne u królików z cukrzycą, co stwierdzono na podstawie zmian w me­tabolizmie glukozy, wrażliwości na insulinę oraz profili lipidowych. Zauważono drastyczny wzrost stłuszczenia szpiku kostnego u królików z cukrzycą w sposób zależny od czasu; po trzech i sześciu miesiącach, procentowe zmiany frakcji tłuszczu w stosunku do wartości wyjściowej wynosiły odpowiednio 10,1% i 25,8% (wszystkie P &lt; 0.001). Co więcej, leczenie oksytocyną znacząco odwracało wartości frakcji tłuszczu oraz ilościowe parametry adipocytów szpiku kostnego u królików z cukrzycą do poziomu królików z grupy kontrolnej. Oksytocyna poprawiała marker tworzenia kości u królików z cukrzycą w porównaniu do grupy, której podawano sól fizjologiczną. Ponadto, leczenie oksytocyną królików z cukrzycą znacząco łagodziło niszczenie kości w porównaniu do grupy z cukrzycą, której podawano sól fizjologiczną (wszystkie P &lt; 0.05). Wnioski: Oksytocyna wydaje się zmniejszać szkodliwy wpływ hiperglikemii na stłuszczenie szpiku kostnego. Protonowa spektroskopia rezonansu magnetycznego może być cennym narzędziem, dostarczającym uzupełniających informacji na temat oceny skuteczności leczenia

Recipient Outcomes after ABO-Incompatible Liver Transplantation: A Systematic Review and Meta-Analysis

BACKGROUND: ABO-incompatible live transplantation (ILT) is not occasionally performed due to a relative high risk of graft failure. Knowledge of both graft and patient survival rate after ILT is essential for donor selection and therapeutic strategy. We systematically reviewed studies containing outcomes after ILT compared to that after ABO-compatible liver transplantation (CLT). METHODOLOGY/PRINCIPAL FINDINGS: We carried out a comprehensive search strategy on MEDLINE (1966-July 2010), EMBASE (1980-July 2010), Biosis Preview (1969-July 2010), Science Citation Index (1981-July 2010), Cochrane Database of Systematic Reviews (Cochrane Library, issue 7, 2010) and the National Institute of Health (July 2010). Two reviewers independently assessed the quality of each study and abstracted outcome data. Fourteen eligible studies were included which came from various medical centers all over the world. Meta-analysis results showed that no significantly statistical difference was found in pediatric graft survival rate, pediatric and adult patient survival rate between ILT and CLT group. In adult subgroup, the graft survival rate after ILT was significantly lower than that after CLT. The value of totally pooled OR was 0.64 (0.55, 0.74), 0.92 (0.62, 1.38) for graft survival rate and patient survival rate respectively. The whole complication incidence (including acute rejection and biliary complication) after ILT was higher than that after CLT, as the value of totally pooled OR was 3.02 (1.33, 6.85). Similarly, in acute rejection subgroup, the value of OR was 2.02 (1.01, 4.02). However, it was 4.08 (0.90, 18.51) in biliary complication subgroup. CONCLUSIONS/SIGNIFICANCE: In our view, pediatric ILT has not been a contraindication anymore due to a similar graft and patient survival rate between ILT and CLT group. Though adult graft survival rate is not so satisfactory, ILT is undoubtedly life-saving under exigent condition. Most studies included in our analysis are observational researches. Larger scale of researches and Randomized-Control Studies are still needed

A Comprehensive Survey on Distributed Training of Graph Neural Networks

Graph neural networks (GNNs) have been demonstrated to be a powerful algorithmic model in broad application fields for their effectiveness in learning over graphs. To scale GNN training up for large-scale and ever-growing graphs, the most promising solution is distributed training which distributes the workload of training across multiple computing nodes. At present, the volume of related research on distributed GNN training is exceptionally vast, accompanied by an extraordinarily rapid pace of publication. Moreover, the approaches reported in these studies exhibit significant divergence. This situation poses a considerable challenge for newcomers, hindering their ability to grasp a comprehensive understanding of the workflows, computational patterns, communication strategies, and optimization techniques employed in distributed GNN training. As a result, there is a pressing need for a survey to provide correct recognition, analysis, and comparisons in this field. In this paper, we provide a comprehensive survey of distributed GNN training by investigating various optimization techniques used in distributed GNN training. First, distributed GNN training is classified into several categories according to their workflows. In addition, their computational patterns and communication patterns, as well as the optimization techniques proposed by recent work are introduced. Second, the software frameworks and hardware platforms of distributed GNN training are also introduced for a deeper understanding. Third, distributed GNN training is compared with distributed training of deep neural networks, emphasizing the uniqueness of distributed GNN training. Finally, interesting issues and opportunities in this field are discussed.Comment: To Appear in Proceedings of the IEE