MRI spectrum of cerebral palsy in correlation with clinical profile

OBJECTIVES: To describe MRI brain spectrum in a group of Cerebral Palsy children and correlate with perinatal history, clinical subgroups. To correlate callosal thinning with topographies and periventricular leukomalacia grades. METHODS: IRB approved observational study (cross sectional study) on CP children in between the period March 2012-October 2013 in Christian Medical College, Vellore. The important MRI features described are periventricular leukomalacia (PVL), deep gray nuclei involvement, cystic encephalomalacia, arterial territory infarcts, corpus callosal thinning, perirolandic cortical gliosis and malformations. These were correlated with the relevant perinatal history and clinical subgroups by cross tabulation and Chi square tests. RESULTS: A set of specific MRI features can be seen in different clinical pictures and a particular clinical picture can have varied MRI findings. Higher grades of PVL are associated with higher degree of neurological deficit and higher grades of thinning of corpus callosum. Deep gray nucleus signal abnormalities are seen significantly with combination of neonatal hyperbilirubinemia and birth asphyxia. Dystonic cerebral palsy is strongly associated with the deep gray nuclei involvement. Callosal thinning may be an isolated finding in CP; hence an important pick up

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Measurement of hepatic venous pressure gradient revisited: Catheter wedge vs balloon wedge techniques

Aims: To evaluate the accuracy of measurement of hepatic venous pressure gradient by catheter wedge as compared to balloon wedge (the gold standard). Materials and Methods: Forty-five patients having a clinical diagnosis of intrahepatic portal hypertension were subjected to the two different types of pressure measurements (catheter wedge and balloon wedge) during transjugular liver biopsy under fluoroscopic guidance. Statistical Analysis: Spearman′s rank correlation coefficient, Bland-Altman plot for agreement, and single measure intraclass correlation were used for analysis of data. Results: There was a close correlation between the results obtained by both the techniques, with highly significant concordance (P < 0.0001). Hepatic venous pressure gradients as measured by the catheter wedge technique were either equal to or less than those obtained by the balloon wedge technique. Conclusions: The difference in hepatic venous pressure gradients measured by the two techniques is insignificant

Novel endolithic bacteria of phylum Chloroflexota reveal a myriad of potential survival strategies in the Antarctic desert

The ice-free McMurdo Dry Valleys of Antarctica are dominated by nutrient-poor mineral soil and rocky outcrops. The principal habitat for microorganisms is within rocks (endolithic). In this environment, microorganisms are provided with protection against sub-zero temperatures, rapid thermal fluctuations, extreme dryness, and ultraviolet and solar radiation. Endolithic communities include lichen, algae, fungi, and a diverse array of bacteria. Chloroflexota is among the most abundant bacterial phyla present in these communities. Among the Chloroflexota are four novel classes of bacteria, here named Candidatus Spiritibacteria class. nov. (=UBA5177), Candidatus Martimicrobia class. nov. (=UBA4733), Candidatus Tarhunnaeia class. nov. (=UBA6077), and Candidatus Uliximicrobia class. nov. (=UBA2235). We retrieved 17 high-quality metagenome-assembled genomes (MAGs) that represent these four classes. Based on genome predictions, all these bacteria are inferred to be aerobic heterotrophs that encode enzymes for the catabolism of diverse sugars. These and other organic substrates are likely derived from lichen, algae, and fungi, as metabolites (including photosynthate), cell wall components, and extracellular matrix components. The majority of MAGs encode the capacity for trace gas oxidation using high-affinity uptake hydrogenases, which could provide energy and metabolic water required for survival and persistence. Furthermore, some MAGs encode the capacity to couple the energy generated from H2 and CO oxidation to support carbon fixation (atmospheric chemosynthesis). All encode mechanisms for the detoxification and efflux of heavy metals. Certain MAGs encode features that indicate possible interactions with other organisms, such as Tc-type toxin complexes, hemolysins, and macroglobulins.IMPORTANCEThe ice-free McMurdo Dry Valleys of Antarctica are the coldest and most hyperarid desert on Earth. It is, therefore, the closest analog to the surface of the planet Mars. Bacteria and other microorganisms survive by inhabiting airspaces within rocks (endolithic). We identify four novel classes of phylum Chloroflexota, and, based on interrogation of 17 metagenome-assembled genomes, we predict specific metabolic and physiological adaptations that facilitate the survival of these bacteria in this harsh environment-including oxidation of trace gases and the utilization of nutrients (including sugars) derived from lichen, algae, and fungi. We propose that such adaptations allow these endolithic bacteria to eke out an existence in this cold and extremely dry habita

Atmospheric chemosynthesis is phylogenetically and geographically widespread and contributes significantly to carbon fixation throughout cold deserts

DATA AVAILABILITY : Next generation sequencing data that supports the findings of this study have been deposited in GenBank with the accession code PRJNA664610. All other data supporting the findings of this study are available in the article/Supplementary Information.Cold desert soil microbiomes thrive despite severe moisture and nutrient limitations. In Eastern Antarctic soils, bacterial primary production is supported by trace gas oxidation and the light-independent RuBisCO form IE. This study aims to determine if atmospheric chemosynthesis is widespread within Antarctic, Arctic and Tibetan cold deserts, to identify the breadth of trace gas chemosynthetic taxa and to further characterize the genetic determinants of this process. H2 oxidation was ubiquitous, far exceeding rates reported to fulfill the maintenance needs of similarly structured edaphic microbiomes. Atmospheric chemosynthesis occurred globally, contributing significantly (p < 0.05) to carbon fixation in Antarctica and the high Arctic. Taxonomic and functional analyses were performed upon 18 cold desert metagenomes, 230 dereplicated medium-to-high-quality derived metagenome-assembled genomes (MAGs) and an additional 24,080 publicly available genomes. Hydrogenotrophic and carboxydotrophic growth markers were widespread. RuBisCO IE was discovered to co-occur alongside trace gas oxidation enzymes in representative Chloroflexota, Firmicutes, Deinococcota and Verrucomicrobiota genomes. We identify a novel group of high-affinity [NiFe]-hydrogenases, group 1m, through phylogenetics, gene structure analysis and homology modeling, and reveal substantial genetic diversity within RuBisCO form IE (rbcL1E), and high-affinity 1h and 1l [NiFe]-hydrogenase groups. We conclude that atmospheric chemosynthesis is a globally-distributed phenomenon, extending throughout cold deserts, with significant implications for the global carbon cycle and bacterial survival within environmental reservoirs.The Australian Government Research Training Program (RTP) Scholarship, the Australian Research Council Future Fellowship, the Australian Antarctic Program Project 5097, the Australian Antarctic Science project grant, an ARC DECRA Fellowship, and a NHMRC New Investigator Grant. Open Access funding enabled and organized by CAUL and its Member Institutions.www.nature.com/ismejam2023BiochemistryGeneticsMicrobiology and Plant PathologySDG-15:Life on lan

Political Determinants of Population Dynamics

The article suggests that the massive transformation of the political system often referred to as “political development” is responsible for the movement from high to low birth-and death rates in national populations. The effect of the changing political system is independent of (and in addition to) the effects of socioeconomic changes previously presented in the theory of demographic demographic transition. The article reports first the nature of the systematic connection between change in the political system on the one hand and change in vital rates on the other. Second, it presents a new empirical measure of the capacity and effectiveness of whole political systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67298/2/10.1177_0010414083016001001.pd