Analysis Of Global Data Research Articles

Comprehensive analysis of geographic and breed-purpose influences on genetic diversity and inherited disease risk in the Doberman dog breed

BackgroundPublicly available phenotype data and genotyping array data from two citizen science projects: “Doberman Health Surveys” and “The Doberman Diversity Project” were analyzed to explore relative homozygosity, diversity, and disorder risk according to geographical locale and breeding purpose in the Doberman.ResultsFrom the phenotypic data cohort, life expectancy of a Doberman at birth is 9.1 years. The leading causes of death were heart disease (accounting for 28% of deaths) and cancers (collectively accounting for 14% of deaths).By genotyping, the world Doberman population exists as four major cohorts (European exhibition-bred, Americas exhibition-bred, European work, Americas pet/informal). Considering the entire Doberman population, four genomic regions longer than 500 Kb are fixed in 90% or more of 3,226 dogs included in this study. The four fixed regions reside on two autosomal chromosomes: CFA3:0.8–2.3 Mb (1.55 Mb); CFA3: 57.9–59.8 Mb (1.8 Mb); CFA31:0–1.2 Mb (1.2 Mb); and CFA31:4.80–6.47 Mb (1.67 Mb). Using public variant call files including variants for eight Doberman pinschers, we observed 30 potentially functional alternate variants that were evolutionarily diverged relative to the wider sequenced dog population within the four strongly homozygous chromosomal regions.Effective population size (Ne) is a statistical measure of breed diversity at the time of sampling that approximates the number of unique individuals. The major identified sub-populations of Dobermans demonstrated Ne in the range 70–236. The mean level of inbreeding in the Doberman breed is 40% as calculated by the number of array variants in runs of homozygosity divided by the assayed genome size (excluding the X chromosome). The lowest observed level of inbreeding in the Dobermans assayed was 15% in animals that were first generation mixes of European and USA bred Dobermans. Array variant analysis shows that inter-crossing between European and USA-bred Dobermans has capacity to re-introduce variation at many loci that are strongly homozygous.ConclusionsWe conclude that efforts to improve breed diversity first should focus on regions with the highest fixation levels, but managers must ensure that mutation loads are not worsened by increasing the frequencies of rarer haplotypes in the identified regions. The analysis of global data identified regions of strong fixation that might impact known disorder risks in the breed. Plausible gene candidates for future analysis of the genetic basis of cardiac disease and cancer were identified in the analysis.

A new global coupled atmosphere-ocean wavenumber-4 pattern in Southern mid–latitudes during austral summer and its climate linkage

A new pattern referred to as the coupled ocean-atmosphere wavenumber-4 (COAW4) pattern has been identified in the Southern mid-latitudes during austral summer. This pattern consists of a wavenumber-4 pattern in the anomalous 200-hPa meridional wind and a wavenumber-4 pattern of the anomalous sea surface temperature (SST). The SST component of the COAW4 pattern, which includes the Indian Ocean Subtropical Dipole (IOSD), the South Atlantic Subtropical Dipole (SASD) and the South Pacific Subtropical Dipole (SPSD), develops through air-sea interactions involving surface turbulent heat flux, surface wind, and ocean mixed-layer depth. The atmospheric component displays a barotropic structure. The sources for COAW4 pattern include not only the wavenumber-4 pattern of the anomalous SST over Southern oceans, but also the anomalous convective activities over Southern land areas. The COAW4 pattern is associated with increased precipitation over land in southern mid-latitudes, particularly in central Australia. Furthermore, the COAW4 pattern is linked to Antarctic sea ice cover in the Weddell, Amundsen, and northern Ross Seas. Plain language summary In the southern mid-latitudes, there exists a wavenumber 4 pattern in the anomalous 200-hPa meridional wind and a wavenumber-4 pattern of the anomalous sea surface temperature (SST). Previous studies have examined the two wavenumber-4 patterns separately, but their potential linkage remains largely unknown. Through statistical analyses of SST and atmospheric global data, we demonstrated that the two wavenumber 4 patterns could be integrated into a coupled ocean-atmosphere wavenumber-4 (COAW4) pattern in Southern mid-latitudes in austral summer. Additionally, we have investigated the sources of this pattern as well as its effect on precipitation over southern lands and on Antarctic sea ice.

Jet Quenching for Heavy Flavors in AA and pp Collisions

We perform a global analysis of experimental data on jet quenching for heavy flavors for scenarios with and without quark-gluon plasma formation in pp collisions. We find that the theoretical predictions for the nuclear modification factor RAA for heavy flavors at the LHC energies are very similar for these scenarios, and the results for RAA and v2 agree reasonably with the LHC data. The agreement with data at the RHIC top energy becomes somewhat better for the intermediate scenario, in which the quark-gluon plasma formation in pp collisions occurs only at the LHC energies. Our fits to heavy flavor RAA show that description of jet quenching for heavy flavors requires somewhat bigger αs than data on jet quenching for light hadrons.

SMEFiT: a flexible toolbox for global interpretations of particle physics data with effective field theories

The Standard Model Effective Field Theory (SMEFT) provides a robust framework to interpret experimental measurements in the context of new physics scenarios while minimising assumptions on the nature of the underlying UV-complete theory. We present the Python open source SMEFiT framework, designed to carry out parameter inference in the SMEFT within a global analysis of particle physics data. SMEFiT is suitable for inference problems involving a large number of EFT degrees of freedom, without restrictions on their functional dependence in the fitted observables, can include UV-inspired restrictions in the parameter space, and implements arbitrary rotations between operator bases. Posterior distributions are determined from two complementary approaches, Nested Sampling and Monte Carlo optimisation. SMEFiT is released together with documentation, tutorials, and post-analysis reporting tools, and can be used to carry out state-of-the-art EFT fits of Higgs, top quark, and electroweak production data. To illustrate its functionalities, we reproduce the results of the recent ATLAS EFT interpretation of Higgs and electroweak data from Run II and demonstrate how equivalent results are obtained in two different operator bases.

Several Topics on Transverse Momentum-Dependent Fragmentation Functions

The hadronization of a high-energy parton is described by fragmentation functions which are introduced through QCD factorizations. While the hadronization mechanism per se remains uknown, fragmentation functions can still be investigated qualitatively and quantitatively. The qualitative study mainly concentrates on extracting genuine features based on the operator definition in quantum field theory. The quantitative research focuses on describing a variety of experimental data employing the fragmentation function given by the parameterizations or model calculations. With the foundation of the transverse-momentum-dependent factorization, the QCD evolution of leading twist transverse-momentum-dependent fragmentation functions has also been established. In addition, the universality of fragmentation functions has been proven, albeit model-dependently, so that it is possible to perform a global analysis of experimental data in different high-energy reactions. The collective efforts may eventually reveal important information hidden in the shadow of nonperturbative physics. This review covers the following topics: transverse-momentum-dependent factorization and the corresponding QCD evolution, spin-dependent fragmentation functions at leading and higher twists, several experimental measurements and corresponding phenomenological studies, and some model calculations.

Asymmetric inter-layer interactions induce a double transition of information spreading

In recent years, a unique double transition phenomenon was observed under an asymmetric interaction in the epidemic model, where there are two transitions in the phase diagram of the spreading range versus the transmission probability. However, whether the asymmetric interactions exist and induce the double transition of information spreading is not very clear. Based on the global Twitter network communication data analysis, we found that besides the symmetric effects, there are also asymmetric interactions between different continents, indicated by the asymmetric weights of information exchange. To understand how the asymmetry affects the spreading behaviors, we proposed an information spreading model on a synthetic two-layered network and quantified the asymmetric interactions between regions by asymmetric inter-layer transmission probabilities. Interestingly, our results reveal a double transition under a strong inter-layer asymmetry in the phase diagram, which is derived from an asynchronous outbreak within the two layers. In addition, we discovered that depending on the strength of asymmetry, the second transition could alter from continuous to discontinuous. Finally, we developed a theory with asymmetric interactions to explain the numerical results thoroughly. The findings of this work may shed some light on comprehending the information’s secondary outbreaks in the real world.

Primary charge separation in native and plant pheophytin a-modified reaction centers of Chloroflexus aurantiacus: Ultrafast transient absorption measurements at low temperature

Ultrafast transient absorption (TA) spectroscopy was used to study electron transfer (ET) at 100 K in native (as isolated) reaction centers (RCs) of the green filamentous photosynthetic bacterium Chloroflexus (Cfl.) aurantiacus. The rise and decay of the 1028 nm anion absorption band of the monomeric bacteriochlorophyll a molecule at the BA binding site were monitored as indicators of the formation and decay of the P+BA− state, respectively (P is the primary electron donor, a dimer of bacteriochlorophyll a molecules). Global analysis of the TA data indicated the presence of at least two populations of the P⁎ excited state, which decay by distinct means, forming the state P+HA− (HA is a photochemically active bacteriopheophytin a molecule). In one population (~65 %), P⁎ decays in ~2 ps with the formation of P+HA− via a short-lived P+BA− intermediate in a two-step ET process P⁎ → P+BA−→ P+HA−. In another population (~35 %), P⁎ decays in ~20 ps to form P+HA− via a superexchange mechanism without producing measurable amounts of P+BA−. Similar TA measurements performed on chemically modified RCs of Cfl. aurantiacus containing plant pheophytin a at the HA binding site also showed the presence of two P⁎ populations (~2 and ~20 ps), with P⁎ decaying through P+BA− only in the ~2 ps population. At 100 K, the quantum yield of primary charge separation in native RCs is determined to be close to unity. The results are discussed in terms of involving a one-step P⁎ → P+HA− superexchange process as an alternative highly efficient ET pathway in Cfl. aurantiacus RCs.

Anaerobic thiosulfate oxidation by the Roseobacter group is prevalent in marine biofilms

Thiosulfate oxidation by microbes has a major impact on global sulfur cycling. Here, we provide evidence that bacteria within various Roseobacter lineages are important for thiosulfate oxidation in marine biofilms. We isolate and sequence the genomes of 54 biofilm-associated Roseobacter strains, finding conserved sox gene clusters for thiosulfate oxidation and plasmids, pointing to a niche-specific lifestyle. Analysis of global ocean metagenomic data suggests that Roseobacter strains are abundant in biofilms and mats on various substrates, including stones, artificial surfaces, plant roots, and hydrothermal vent chimneys. Metatranscriptomic analysis indicates that the majority of active sox genes in biofilms belong to Roseobacter strains. Furthermore, we show that Roseobacter strains can grow and oxidize thiosulfate to sulfate under both aerobic and anaerobic conditions. Transcriptomic and membrane proteomic analyses of biofilms formed by a representative strain indicate that thiosulfate induces sox gene expression and alterations in cell membrane protein composition, and promotes biofilm formation and anaerobic respiration. We propose that bacteria of the Roseobacter group are major thiosulfate-oxidizers in marine biofilms, where anaerobic thiosulfate metabolism is preferred.

Non-communicable disease policy implementation from 2014 to 2021: a repeated cross-sectional analysis of global policy data for 194 countries

Non-communicable diseases (NCDs) are the world's leading cause of death and disability. Global implementation of WHO-recommended NCD policies has been increasing with time, but in 2019 fewer than half of these policies had been implemented globally. In 2022, WHO released updated data on NCD policy implementation, on the basis of surveys conducted in 2021 during the COVID-19 pandemic. We sought to examine whether the trajectory of global policy implementation changed during this period. In this repeated cross-sectional analysis, we used data from the 2015, 2017, 2020, and 2022 WHO progress monitors to calculate NCD policy implementation scores for all 194 WHO member states. We used Welch's ANOVA and Games-Howell post-hoc pairwise testing to examine changes in mean implementation scores for 19 WHO-recommended NCD policies, with assessment at the global, geographical, geopolitical, and country-income levels. We collated sales data on tobacco, alcohol, and junk foods to examine the association between changes in sales and the predicted probability of implementation of policies targeting these products. We also calculated the Corporate Financial Influence Index (CFII) for each country, which was used to assess the association between corporate influence and policy implementation. We used logistic regression to assess the relationship between product sales and the probability of implementing related policies. The relationship between CFII and policy implementation was assessed with Pearson's correlation analysis and random-effects multivariate regression. Across the 194 countries, in the years preceding publication of each progress monitor, mean total policy implementation score (out of a potential 18·0) was 7·0 (SD 3·5) in 2014, 8·2 (3·5) in 2016, 8·6 (3·6) in 2019, and 8·6 (3·6) in 2021. Only the differences in mean implementation score between 2014 and the other three report years were deemed statistically significant (pairwise p<0·05). Thus the steady improvement in mean global NCD policy implementation stalled in 2021 at 47·8%. However, from 2019 to 2021, we identified shifts in individual policies: global mean implementation scores increased for policies on tobacco, clinical guidelines, salt, and child food marketing, and decreased for policies on alcohol, breastmilk substitute marketing, physical activity mass media campaigns, risk factor surveys, and national NCD plans and targets. Six of the seven policies with the lowest levels of implementation (global mean score <0·4 out of a potential 1·0) in both 2019 and 2021 were related to tobacco, alcohol, and unhealthy food. From 2020 onwards, we identified weak or no associations between sales of tobacco, alcohol, and junk foods and the predicted probability of implementing policies related to each commodity. Country-level CFII was significantly associated with total policy implementation score (Pearson's r -0·49, 95% CI -0·59 to -0·36), and this finding was supported in multivariate modelling for all policies combined and for all commercial policies except alcohol policies. NCD policy implementation has stagnated. Progress in the implementation of some policies is matched by decreased implementation of others, particularly those related to unhealthy commodities. To prevent NCDs and their consequences, and attain the Sustainable Development Goals, the rate of NCD policy adoption must be substantially and urgently increased before the next NCD progress monitor and UN high-level meeting on NCDs in 2024. None.

Structural characterization of a cytosine-rich potential quadruplex forming sequence in the EGFR promoter

I-motifs are tetra-helixes that may form in cytosine-rich strands. They are based on cytosine–cytosine+ base pairs that require the N3 hemi-protonation of the nucleobases, and therefore, the stability of these non-canonical DNA arrangements depends on pH. These structures are promising targets for the development of new cancer therapies since they are enriched in the promoters of oncogenes where they can play a role in the regulation of transcription. The proximal promoter of the EGFR oncogene has multiple regions with a significant potential to form such a tetra-helix arrangement. Here, we present the thermodynamic characterization of a C-rich sequence located 37 nucleotides upstream of the transcription starting site of EGFR. We confirmed the ability of this sequence to fold into an I-motif. By applying a global analysis of calorimetric and spectroscopic data, we derived the dependency of the apparent standard Gibbs free energy change associated with the I-motif folding upon temperature and pH. The results showed that, in contrast to in silico prediction, only 4 CC+ base pairs formed while additional GC and TT base pairings were detected in the I-motif. Noteworthy, a single residue mutation at G14 largely shifts the equilibrium toward the formation of multimeric species.

Prototype global analysis of LISA data with multiple source types

The novel data analysis challenges posed by the Laser Interferometer Space Antenna (LISA) arise from the overwhelmingly large number of astrophysical sources in the measurement band and the density with which they are found in the data. Robust detection and characterization of the numerous gravitational wave sources in LISA data can not be done sequentially, but rather through a simultaneous global fit of a data model containing the full suite of astrophysical and instrumental features present in the data. While previous analyses have focused on individual source types in isolation, here we present the first demonstration of a LISA global fit analysis containing combined astrophysical populations. The prototype pipeline uses a blocked Metropolis Hastings algorithm to alternatingly fit to a population of ultracompact galactic binaries, known “verification binaries” already identified by electromagnetic observations, a population of massive black hole mergers, and an instrument noise model. The global LISA analysis software suite (GLASS) is assembled from independently developed samplers for the different model components. The modular design enables flexibility to future development by defining standard interfaces for adding new, or updating additional, components to the global fit without being overly prescriptive for how those modules must be internally designed. The GLASS pipeline is demonstrated on data simulated for the LISA Data Challenge 2b. Results of the analysis and a road-map for continued development are described in detail.14 MoreReceived 11 January 2023Accepted 27 January 2023DOI:https://doi.org/10.1103/PhysRevD.107.063004© 2023 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasGravitational wavesGravitation, Cosmology & Astrophysics

Evaluating and Measuring Exactly the Distances between Aggregate Health Performances: A Global Health Data and Welfare Regime Analysis

This paper presents the results of a global data analysis that for the first time ever looks at the exact performance distances when combining groups of quantitative health and health care indicators that stand for performance differences between the health care system performances of different countries in every corner of the world. Thus, by using Aspalter’s new Standardized Relative Performance Index, we can now not just rank all health care systems and health policy outcomes (as before) but can also, which is entirely new, measure them exactly and compare them exactly with one to another and/or different groups of indicators (dimensions) thereof. The World Health Organization, the Organization of Economic Corporation and Development, and the World Bank have yet to use such an indicator (Aspalter’s Index) that is able to add up and directly compare different variables, groups of variables among each other, and, of course, for example, different groups of countries among each other, while adding to the quality and quantity of overall information and knowledge gathered on the research subject(s) in the case of quantitative data analysis. For a more in-depth analytical purpose, the “Ten Worlds of Welfare Regime Theory” (or “ten worlds theory” in short) has been used to arrive at further conclusions and extra valuable information and knowledge on top of the rich comparative data analysis conducted in this study.

Bacille Calmette Guerin (BCG) and prevention of types 1 and 2 diabetes: Results of two observational studies.

Diabetes is a common disease marked by high blood sugars. An earlier clinical trial in type 1 diabetic subjects (T1Ds) found that repeat BCG vaccinations succeeded in lowering HbA1c values over a multi-year course. Here we seek to determine whether BCG therapy for bladder cancer may improve blood sugar levels in patients with comorbid T1D and type 2 diabetes (T2D). We also investigate whether BCG exposure may reduce onset of T1D and T2D by examining country-by-country impact of BCG childhood vaccination policies in relation to disease incidence. We first analyzed three large US patient datasets (Optum Labs data [N = 45 million], Massachusetts General Brigham [N = 6.5 million], and Quest Diagnostics [N = 263 million adults]), by sorting out subjects with documented T1D (N = 19) or T2D (N = 106) undergoing BCG therapy for bladder cancer, and then by retrospectively assessing BCG's subsequent year-by-year impact on blood sugar trends. Additionally, we performed an ecological analysis of global data to assess the country-by-country associations between mandatory neonatal BCG vaccination programs and T1D and T2D incidence. Multi-dose BCG therapy in adults with comorbid diabetes and bladder cancer was associated with multi-year and stable lowering of HbA1c in T1Ds, but not in T2Ds. The lack of a similar benefit in T2D may be due to concurrent administration of the diabetes drug metformin, which inhibits BCG's beneficial effect on glycolysis pathways. Countries with mandatory neonatal BCG vaccination policies had a lower incidence of T1D in two international databases and a lower incidence of T2D in one of the databases. The epidemiological evidence analyzed here suggests that BCG may play a role in the prevention of T1D. It does not support prevention of T2D, most likely because of interference by metformin. Our ecological analysis of global data suggests a role for neonatal BCG in the prevention of T1D and, to a lesser extent, T2D. Randomized clinical trials are needed to confirm these findings.

Precision and systematic errors in global helioseismology mode fitting and inversions: Leveraging some 25 years of nearly uninterrupted observations

We have on hand some 25 years of nearly uninterrupted high-quality and high-cadence global helioseismic data. The Global Oscillations Network Group (GONG) project has been producing science quality data since 1995, the Michelson Doppler Imager (MDI) started in 1996, and the Helioseismic and Magnetic Imager (HMI) took over in 2010. Fundamental new constraints have been imposed by helioseismic inferences, yet global helioseismology data processing seems somewhat frozen in time for some of its methodologies. I review and discuss some specific aspects of global helioseismology data analysis, with an emphasis on the issues and challenges presented by mode fitting and inversion techniques. I compare and contrast results derived by different fitting methods, whether using different techniques, different lengths of time series, or different fitting parameters, like leakage matrices or the inclusion or omission of the mode profile asymmetry, leading to our current best handle on the residual systematic errors.

Effective Shear and Bulk Viscosities of the Quark–Gluon Plasma: QCD Versus Heavy-ion Data

In recent years, there has been a significant effort to extract the temperature-dependent shear ($\eta/s$) and bulk ($\zeta/s$) viscosity over entropy ratios of the quark-gluon plasma from a global comparison of heavy-ion data with results of hydrodynamic simulations. However, anisotropic flow, which is arguably the most sensitive probe of viscosity, is only sensitive to an {\it effective\/} viscosity over entropy ratio, which is obtained by taking a weighted average over the temperature, and summing the contributions of shear and bulk. We estimate this effective viscosity using existing first-principles calculations, which give $0.17<(\eta/s)_{\rm eff}<0.21$, and $(\zeta/s)_{\rm eff}<0.08$, implying that the damping of anisotropic flow at the LHC is mostly due to shear viscosity. The values extracted from global data analyses are compatible with these theory predictions.

Epidemiological characterization of lonomism in South America

Lonomism is the envenomation caused by accidental contact with Lonomia caterpillars, and this is a public health priority in South America since it is relatively common but remains underestimated. This study presents an updated and integrative analysis of reliable global data from 1960 to 2020 on the epidemiology of this envenomation in the whole continent. A total of 13,186 notifications were recorded for South America: 13,056 (99.01%) in Brazil, 49 (0.37%) in Argentina, 43 (0.33%) in Colombia, 29 (0.22%) in Venezuela, 6 (0.05%) in Peru and 3 (0.02%) in French Guiana. The number of new locations reporting accidents has increased since the first formally notifications at the middle of the last century. Most of these locations are situated in Brazil, the pioneer in deeply researching the Lonomia genus and its impacts in public health. Most victims were males, in the economically productive age group, and accidental contact occurred more frequently in the upper limbs while doing activities outdoors in urban/rural areas. Regarding the determinants of clinical outcome, countries where patients received delayed medical care were associated with a higher number of moderate and/or severe cases, as well as a higher chance of progressing to death. Additionally, the longer the delay for accessing medical care, the higher the risk of developing systemic complications, thereby increasing the need for specific treatment. Our study also shows that accidents globally occurred more frequently in the summer months and in the beginning of autumn. Although having identified several shortcomings in the documents selected and verified that notifications are strongly biased by public policies adopted by each South American country, this study provides the first comprehensive assessment of lonomism in South America, demonstrating the increase in the number of accidents, and their expansion to other areas of the continent over time. Our findings will undoubtedly help guide the appropriate allocation of resources and implementation of prevention strategies and define priority criteria for epidemiological surveillance of this neglected tropical disease.

Population fluctuations and synanthropy explain transmission risk in rodent-borne zoonoses

Population fluctuations are widespread across the animal kingdom, especially in the order Rodentia, which includes many globally important reservoir species for zoonotic pathogens. The implications of these fluctuations for zoonotic spillover remain poorly understood. Here, we report a global empirical analysis of data describing the linkages between habitat use, population fluctuations and zoonotic reservoir status in rodents. Our quantitative synthesis is based on data collated from papers and databases. We show that the magnitude of population fluctuations combined with species’ synanthropy and degree of human exploitation together distinguish most rodent reservoirs at a global scale, a result that was consistent across all pathogen types and pathogen transmission modes. Our spatial analyses identified hotspots of high transmission risk, including regions where reservoir species dominate the rodent community. Beyond rodents, these generalities inform our understanding of how natural and anthropogenic factors interact to increase the risk of zoonotic spillover in a rapidly changing world.

Autologous Versus Haploidentical Stem Cell Transplantation in Adult Patients with Intermediate Risk Actue Myelogenous Leukemia in First Complete Remission and Undetectable Minimal Residual Disease: A Global Preliminary Analysis of Chinese Data

Background: Stem cell transplantation (SCT) is a potentially curative post-remission therapy for intermediate-risk acute myeloid leukemia (AML) patients. For patients in first remission (CR1) with negative measurable residual disease (MRD) and without a HLA-matched donor, both autologous SCT (ASCT) and haploidentical donor SCT (haplo-SCT) were acceptable options, but it is controversial that which one is preferred. Methods: A retrospective study was conducted in 8 Chinese centers. The inclusion criteria were: 1) adult patients >18 years old; 2) diagnosis as AML with intermediate-risk according to ELN 2017; 3) ASCT or haplo-SCT underwent between 2010-2019; 4) in CR1 and MRD negative before transplant. The Primary endpoint was overall survival (OS). Secondary endpoints were progression-free survival (PFS), cumulative incidence of relapse (CIR), treatment-related mortality (TRM), and graft-versus-host disease-free and relapse-free survival (GRFS). Results: Totally 299 patients were enrolled in this study, including 97 recepients after ASCT and 202 recipients after haplo-SCT (Table 1). The median follow-up was 28 months in ASCT group versus 35 months in haplo-SCT group. Compared to haplo-SCT, patients after ASCT had increased 3-year CIR (27.0% ± 0.2% versus 13.5% ± 0.1%, p = 0.004) but reduced 3-year TRM (3.5% ± 0.0% versus 12.0% ± 0.0%, p = 0.013), which led to similar 3-year OS (80.8% ± 4.3% versus 79.2% ± 3.1%, p = 0.796) and PFS (69.5% ± 5.0% versus 73.7% ± 3.3%, p = 0.504). Moreover, the 3-year GRFS was remarkable better in ASCT group (69.5% ± 5.0% versus 55.9% ± 3.6%, p = 0.009) (Figure 1), which implied a survival with superior quality of life (QoL). In multivariate analysis, haplo-SCT independently related to an improved CIR, while increased TRM and reduced GRFS. Additionally, age more than 50 was associated with the worse OS, CIR and GRFS. Conclusions: We concluded that both ASCT and haplo-SCT were applicable for patients with intermediate-risk AML in MRD-negative CR1, but the absence of GVHD might potentially favor the QoL for patients receiving ASCT. Randomized trials are needed to confirm our conclusion. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Link Prediction in Co-authorship Networks

Besides social network analysis, the Link-Prediction (LP) problem has useful applications in information retrieval, bioinformatics, telecommunications, microbiology, and e-commerce as a forecast of future links in a given context to find what possible connections are based on a local and global statistical analysis of the given graph data. However, in Academic Social Networks (ASNs), the LP issue has recently attracted a lot of attention in academia and called for a variety of link prediction techniques to predict co-authorship among researchers and to examine the rich structural and associated data. As a result, this study investigates the problem of LP in ASNs to forecast the upcoming co-authorships among researchers. In a systematic approach, this review presents, analyses, and compares the primary taxonomies of topological-based, content-based, and hybrid-based approaches, which are used for computing similar scores for each pair of unconnected nodes. Then, this study ends with findings on challenges and open problems for the community to work on for further development of the LP problem of scholarly social networks.

Advanced database mining of efficient haloalkane dehalogenases by sequence and structure bioinformatics and microfluidics

Next-generation sequencing doubles genomic databases every 2.5 years. The accumulation of sequence data provides a unique opportunity to identify interesting biocatalysts directly in the databases without tedious and time-consuming engineering. Herein, we present a pipeline integrating sequence and structural bioinformatics with microfluidic enzymology for bioprospecting of efficient and robust haloalkane dehalogenases. The bioinformatic part identified 2,905 putative dehalogenases and prioritized a “small-but-smart” set of 45 genes, yielding 40 active enzymes, 24 of which were biochemically characterized by microfluidic enzymology techniques. Combining microfluidics with modern global data analysis provided precious mechanistic insights related to the high catalytic efficiency of selected enzymes. Overall, we have doubled the dehalogenation “toolbox” characterized over three decades, yielding biocatalysts that surpass the efficiency of currently available wild-type and engineered enzymes. This pipeline is generally applicable to other enzyme families and can accelerate the identification of efficient biocatalysts for industrial use. • A pipeline integrating bioinformatics and microfluidic enzymology is introduced • A small-but-smart set of selected genes yielded a 90% success rate of active enzymes • Microfluidics and global data analysis provided mechanistic insight into biocatalysis • The obtained dehalogenases outperform previously discovered or engineered variants For decades, scientists have asked themselves how to obtain better enzymes: should they discover new enzymes from nature or improve known enzymes by protein engineering? The success of many protein engineering studies might lead to underestimating the potential of natural diversity represented by genomic databases. We present a pipeline integrating sequence and structural bioinformatics with microfluidic enzymology to discover efficient and robust biocatalysts. Bioinformatic analysis prioritizes promising candidates, while microfluidic enzymology facilitates efficient characterization of these enzymes, leading to mechanistic insights. The obtained enzymes catalytically outperformed previously known variants, independently of whether these had been newly discovered or engineered. This study represents an interesting conceptual view of current approaches used in biocatalyst development, which should explore the great potential of structural and functional diversity found in nature. We present a pipeline integrating sequence and structural bioinformatics with microfluidic enzymology to discover efficient and robust haloalkane dehalogenases. Our smart bioinformatic identification of promising candidates in genomic databases is followed by efficient microfluidic characterization, in terms of activity, specificity, stability, and mechanistic insights. The obtained biocatalysts outperform the previously known wild-type and engineered dehalogenases. This strategy is applicable to other enzyme families, paving the way toward accelerating the identification of novel biocatalysts for industrial applications.