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Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the mechanism of disease development is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of AD's mechanism from machine learning (ML) is so far unrealized, majorly due to the lack of needed data density. To harness the AD mechanism's knowledge from the expression profiles of postmortem prefrontal cortex samples of 310 AD and 157 controls, we used seven predictive operators or combinations of RapidMiner Studio operators to establish predictive models from the input matrix and to assign a weight to each attribute. check details Besides, conventional fold-change methods were also applied as controls. The identified genes were further submitted to enrichment analysis for KEGG pathways. The average accuracy of ML models ranges from 86.30% to 91.22%. The overlap ratio of the identified genes between ML and conventional methods ranges from 19.7% to 21.3%. ML exclusively identified oxidative phosphorylation genes in the AD pathway. Our results highlighted the deficiency of oxidative phosphorylation in AD and suggest that ML should be considered as complementary to the conventional fold-change methods in transcriptome studies.If artificial intelligence (AI) is to help solve individual, societal and global problems, humans should neither underestimate nor overestimate its trustworthiness. Situated in-between these two extremes is an ideal 'Goldilocks' zone of credibility. But what will keep trust in this zone? We hypothesise that this role ultimately falls to the social cognition mechanisms which adaptively regulate conformity between humans. This novel hypothesis predicts that human-like functional biases in conformity should occur during interactions with AI. We examined multiple tests of this prediction using a collaborative remembering paradigm, where participants viewed household scenes for 30 s vs. 2 min, then saw 2-alternative forced-choice decisions about scene content originating either from AI- or human-sources. We manipulated the credibility of different sources (Experiment 1) and, from a single source, the estimated-likelihood (Experiment 2) and objective accuracy (Experiment 3) of specific decisions. As predicted, each manipulation produced functional biases for AI-sources mirroring those found for human-sources. Participants conformed more to higher credibility sources, and higher-likelihood or more objectively accurate decisions, becoming increasingly sensitive to source accuracy when their own capability was reduced. These findings support the hypothesised role of social cognition in regulating AI's influence, raising important implications and new directions for research on human-AI interaction.Microbial keratitis occurs from the infection of the cornea by fungi and or bacteria. It remains one of the most common global causes of irreversible blindness accounting for 3.5% (36 million) of blind people as of 2015. This paper looks at the use of a bacteria binding polymer designed to bind Staphylococcus aureus and remove it from the corneal surface. Mechanical unbinding measurements were used to probe the interactions of a thermo-active bacteria-binding polymer, highly-branched poly(N-isopropyl acrylamide), functionalised with modified vancomycin end groups (HB-PNIPAM-Van) to bacteria placed on rabbit corneal surfaces studied ex-vivo. This was conducted during sequential temperature phase transitions of HB-PNIPAM-Van-S. aureus below, above and below the lower critical solution temperature (LCST) in 3 stages, in-vitro, using a novel micro-bead force spectroscopy (MBFS) approach via atomic force microscopy (AFM). The effect of temperature on the functionality of HB-PNIPAM-Van-S. aureus showed that the polymer-bacteria complex reduced the work done in removing bacterial aggregates at T > LCST (p  2.5 µm) compared to S. aureus aggregates only. Here, we present the first study using AFM to assess the reversible mechanical impact of a thermo-active polymer-binding bacteria on a natural corneal surface.The relationships between the basic physical properties of seeds of selected spindle species were evaluated for the needs of seed sorting operations. Physical properties were measured in the seeds of five spindle species, and the presence of relationships between these attributes was determined in correlation and regression analyses. The average values of the evaluated parameters were determined in the following range terminal velocity-from 9.2 to 10.3 m s-1, thickness-from 2.57 to 3.26 mm, width-from 2.87 to 3.74 mm, length-from 3.94 to 5.52 mm, angle of external friction-from 20.7° to 24.6°, mass-from 16.5 to 33.8 mg. Spindle seeds were arranged in the following ascending order based on their geometric mean diameter winged spindle, Hamilton's spindle, large-winged spindle, broadleaf spindle and European spindle. Spindle seeds should be separated in a sieve equipped with at least two mesh screens with slotted apertures. Depending on the processed spindle species, aperture size should range from ≠ 2.7 to ≠ 3.5 mm in the top screen, and from ≠ 2.4 to ≠ 3.0 mm in the bottom screen.HLA-B*52 is an established genetic factor in Takayasu arteritis (TAK). Recently, single nucleotide polymorphisms (SNPs) in IL12B (rs6871626) and LILRA3 (rs103294) were newly identified as non-HLA susceptibility loci in TAK. Here, we examined how these SNPs contribute to clinical characteristics and vascular damage in TAK. We retrospectively reviewed the medical records of 99 TAK patients enrolled in our previous genome-wide association study, and whose genotypes for IL12B rs6871626, LILRA3 rs103294, and HLA-B*52 were available. Incidence of aortic regurgitation (AR) was significantly associated with the A allele (risk allele) of IL12B rs6871626 (CC 42%, AC 61%, AA 81%; p = 0.0052; odds ratio [OR] 2.45), as well as with the incidence of hypertension (p = 0.049; OR 1.82) and the proportion of patients who underwent aortic valve replacement (p = 0.023; OR 3.64). Regarding vascular damage, there was positive correlation between the Takayasu Arteritis Damage Score and the A allele of IL12B rs6871626 (CC 3.42 ± 2.71, AC 4.
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