Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.

ObjectiveThe purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software.Materials and methodsMR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic.ResultsOur study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant.ConclusionThe use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics

A physical mechanism for North Atlantic SST influence on the Indian summer monsoon

A link between the Atlantic Multidecadal Oscillation (AMO) and multidecadal variability of the Indian summer monsoon rainfall is unraveled and a long sought physical mechanism linking Atlantic climate and monsoon has been identified. The AMO produces persistent weakening (strengthening) of the meridional gradient of tropospheric temperature (TT) by setting up negative (positive) TT anomaly over Eurasia during northern late summer/autumn resulting in early (late) withdrawal of the south west monsoon and persistent decrease (increase) of seasonal monsoon rainfall. On inter-annual time scales, strong North Atlantic Oscillation (NAO) or North Annular mode (NAM) influences the monsoon by producing similar TT anomaly over Eurasia. The AMO achieves the interdecadal modulation of the monsoon by modulating the frequency of occurrence of strong NAO/NAM events. This mechanism also provides a basis for explaining the observed teleconnection between North Atlantic temperature and the Asian monsoon in paleoclimatic proxies

Decolonising the curriculum

Social science courses are increasingly coming under fire for the over-representation of white male authors and theorists. Campaigns such as ‘Why Is My Curriculum White?’ call into question the ‘Dead White Men’ approach to teaching political theory, where few female and theorists of colour are included on reading lists. The ways in which knowledge is produced, propagated and perpetuated through White, Western perspectives also spawned the related campaign ‘Why Is My Professor White?’ These campaigns are taking place against a backdrop of immense changes in the higher education sector, which earlier this year saw thousands of university academic staff go on strike over pensions, and a spate of anti-casualisation campaigns crop up at universities across the country. Changes such as these disproportionately affect women and ethnic minorities because of the extent to which we are subject to structural inequalities. Ethnic and gender penalties are present at every academic pay grade. Women are more likely to be on casual, part-time contracts. And ethnic minorities still constitute a minor proportion of senior academic and management staff in most universities. As women of colour (WOC) in the academy – emerging scholars of race who have yet to begin permanent academic roles – the decolonisation campaigns hold personal as well as professional resonance for us. They fuel our desire to impart real change in the way politics is taught in the United Kingdom and to help make a space for scholars like us. However, this desire must sit alongside the realities of our future in the academy. We both started out PhDs in the mid-2010s with the hope of becoming critical and radical but essentially fully fledged and secure academic employees. The structural changes the academy is undergoing not only undermines the work we do to represent the work of subaltern scholars in the field of politics but makes us question our ability as well as our desire to survive and thrive as academics

Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving

Generative large language models (LLMs) with instruct training such as GPT-4 can follow human-provided instruction prompts and generate human-like responses to these prompts. Apart from natural language responses, they have also been found to be effective at generating formal artifacts such as code, plans, and logical specifications from natural language prompts. Despite their remarkably improved accuracy, these models are still known to produce factually incorrect or contextually inappropriate results despite their syntactic coherence - a phenomenon often referred to as hallucination. This limitation makes it difficult to use these models to synthesize formal artifacts that are used in safety-critical applications. Unlike tasks such as text summarization and question-answering, bugs in code, plan, and other formal artifacts produced by LLMs can be catastrophic. We posit that we can use the satisfiability modulo theory (SMT) solvers as deductive reasoning engines to analyze the generated solutions from the LLMs, produce counterexamples when the solutions are incorrect, and provide that feedback to the LLMs exploiting the dialog capability of instruct-trained LLMs. This interaction between inductive LLMs and deductive SMT solvers can iteratively steer the LLM to generate the correct response. In our experiments, we use planning over the domain of blocks as our synthesis task for evaluating our approach. We use GPT-4, GPT3.5 Turbo, Davinci, Curie, Babbage, and Ada as the LLMs and Z3 as the SMT solver. Our method allows the user to communicate the planning problem in natural language; even the formulation of queries to SMT solvers is automatically generated from natural language. Thus, the proposed technique can enable non-expert users to describe their problems in natural language, and the combination of LLMs and SMT solvers can produce provably correct solutions.Comment: 25 pages, 7 figure

Purification and biochemical characterization of a novel secretory dipeptidyl peptidase IV from porcine serum

Purification of DPP-IV enzyme from porcine serum, is presented in this study for the first time. The high molecular weight DPP-IV from porcine serum was fractioned using Sephadex G-75 gel filtration followed by DEAE Sephadex anion exchange and Sephadex G-100 gel filtration chromatography columns with a final yield of 11.25%. The SDS-PAGE of the purified sample showed a single band of molecular mass nearing 160 kDa. Distinct single band was observed after PAS staining confirmed it to be a glycoprotein. The purified enzyme showed an optimum pH and temperature of 8 and 37 degrees C, respectively. The enzyme effectively cleaved fluorogenic substrate Gly-Pro-AMC with Km and Vmax of 4.578 mu M and 90.84 nmoles/min, respectively. Purified DPP-IV activity was inhibited by Diprotin A with an IC(50)value of 8.473 mu M. Among the three plant extracts used to study DPP-IV inhibition, the aqueous hot extract ofTerminalia chebulashowed the highest inhibition of 87.19%, followed by the aqueous cold extract ofMomordica carantia, ( 31.6%) andAzadirachta indica(34.16%) at the concentration of 25 mu g

Hnrnph1 Is A Quantitative Trait Gene for Methamphetamine Sensitivity.

Psychostimulant addiction is a heritable substance use disorder; however its genetic basis is almost entirely unknown. Quantitative trait locus (QTL) mapping in mice offers a complementary approach to human genome-wide association studies and can facilitate environment control, statistical power, novel gene discovery, and neurobiological mechanisms. We used interval-specific congenic mouse lines carrying various segments of chromosome 11 from the DBA/2J strain on an isogenic C57BL/6J background to positionally clone a 206 kb QTL (50,185,512-50,391,845 bp) that was causally associated with a reduction in the locomotor stimulant response to methamphetamine (2 mg/kg, i.p.; DBA/2J < C57BL/6J)-a non-contingent, drug-induced behavior that is associated with stimulation of the dopaminergic reward circuitry. This chromosomal region contained only two protein coding genes-heterogeneous nuclear ribonucleoprotein, H1 (Hnrnph1) and RUN and FYVE domain-containing 1 (Rufy1). Transcriptome analysis via mRNA sequencing in the striatum implicated a neurobiological mechanism involving a reduction in mesolimbic innervation and striatal neurotransmission. For instance, Nr4a2 (nuclear receptor subfamily 4, group A, member 2), a transcription factor crucial for midbrain dopaminergic neuron development, exhibited a 2.1-fold decrease in expression (DBA/2J < C57BL/6J; p 4.2 x 10-15). Transcription activator-like effector nucleases (TALENs)-mediated introduction of frameshift deletions in the first coding exon of Hnrnph1, but not Rufy1, recapitulated the reduced methamphetamine behavioral response, thus identifying Hnrnph1 as a quantitative trait gene for methamphetamine sensitivity. These results define a novel contribution of Hnrnph1 to neurobehavioral dysfunction associated with dopaminergic neurotransmission. These findings could have implications for understanding the genetic basis of methamphetamine addiction in humans and the development of novel therapeutics for prevention and treatment of substance abuse and possibly other psychiatric disorders

Effect of Education on Myopia: Evidence from the United Kingdom ROSLA 1972 Reform

YesCross-sectional and longitudinal studies have consistently reported an association between education and myopia. However, conventional observational studies are at risk of bias due to confounding by factors such as socioeconomic position and parental educational attainment. The current study aimed to estimate the causal effect of education on refractive error using regression discontinuity analysis. Methods: Regression discontinuity analysis was applied to assess the influence on refractive error of the raising of the school leaving age (ROSLA) from 15 to 16 years introduced in England and Wales in 1972. For comparison, a conventional ordinary least squares (OLS) analysis was performed. The analysis sample comprised 21,548 UK Biobank participants born in a nine-year interval centered on September 1957, the date of birth of those first affected by ROSLA. Results: In OLS analysis, the ROSLA 1972 reform was associated with a −0.29 D (95% confidence interval [CI]: −0.36 to −0.21, P < 0.001) more negative refractive error. In other words, the refractive error of the study sample became more negative by −0.29 D during the transition from a minimum school leaving age of 15 to 16 years of age. Regression discontinuity analysis estimated the causal effect of the ROSLA 1972 reform on refractive error as −0.77 D (95% CI: −1.53 to −0.02, P = 0.04). Conclusions: Additional compulsory schooling due to the ROSLA 1972 reform was associated with a more negative refractive error, providing additional support for a causal relationship between education and myopia.Global Education program of the Russian Federation government (DP) and an NIHR Senior Research Fellowship award SRF-2015-08-005 (CW), The Department for Health through an award made by the NIHR to the Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust, and UCL Institute of Ophthalmology, London, United Kingdom (grant no. BRC2_009). Additional support was provided by The Special Trustees of Moorfields Eye Hospital, London, United Kingdom (grant no. ST 12 09

Early diagnosis of pseudopregnancy in goats by ultrasonography and response to treatment using cloprostenol sodium

Pseudopregnancy is a state of temporary infertility in goats characterised by the accumulation of sterile fluid in the uterus in the absence of a foetus with persistent corpus luteum. B-mode ultrasonographic examination of goats on day 60 post-breeding was conducted for differential diagnosis of pregnancy, non-pregnancy and pseudopregnancy. Pseudopregnant does diagnosed on day 60 (day 0) post-breeding (Group I, n=8) were treated with three doses of 125μg of cloprostenol sodium (i/m) 10 days apart and were bred by natural service on induced oestrus after the third dose of treatment. The response to treatment was evaluated and compared with normal cycling does (Group II, n=8) which were mated on spontaneous oestrus. The uterine wall thickness measured ultrasonographically on day 0 in group I and on day 60 post-breeding in pregnant does of group II were 0.63 ± 0.02 and 0.66±0.03 cm, respectively (P >0.05). Serum progesterone concentration estimated on day 0, day of the evacuation of uterine fluid, days 10 and 20 in group I and on day 60 post-breeding in group II were 2.73 ± 0.19, 0.78± 0.19, 1.67 ± 0.10, 1.72 ± 0.19 and 3.64± 0.16 ng/mL, respectively. A statistically significant difference was observed between day 0 in group I and day 60 in group II; within group I, between day 0 and the day of evacuation and between the day of evacuation and day 10. Pregnancy diagnosis on day 60 post-breeding revealed a conception rate of 50 and 75 per cent in groups I and II, respectively (P>0.05)