A twisted tale of the transverse-mass tail

We propose a tantalizing possibility that misinterpretation of the reconstructed missing momentum may have yielded the observed discrepancies among measurements of the $W$-mass in different collider experiments. We introduce a proof-of-principle scenario characterized by a new physics particle, which can be produced associated with the $W$-boson in hadron collisions and contributes to the net missing momentum observed in a detector. We show that these exotic events pass the selection criteria imposed by various collaborations at reasonably high rates. Consequently, in the presence of even a handful of these events, a fit based on the ansatz that the missing momentum is primarily due to neutrinos (as it happens in the Standard Model), yields a $W$-boson mass that differs from its true value. Moreover, the best fit mass depends on the nature of the collider and the center-of-mass energy of collisions. We construct a barebones model that demonstrates this possibility quantitatively while satisfying current constraints. Interestingly, we find that the nature of the new physics particle and its interactions appear as a variation of the physics of Axion-like particles after a field redefinition.Comment: 24 pages, 7 figures, a new appendix added, version published in JHE

Phenethyl Isothiocyanate Exhibits Antileukemic Activity \u3cem\u3eIn Vitro\u3c/em\u3e and \u3cem\u3eIn Vivo\u3c/em\u3e by Inactivation of Akt and Activation of JNK Pathways

Effects of phenethyl isothiocyanate (PEITC) have been investigated in human leukemia cells (U937, Jurkat, and HL-60) as well as in primary human acute myeloid leukemia (AML) cells in relation to apoptosis and cell signaling events. Exposure of cells to PEITC resulted in pronounced increase in the activation of caspase-3, -8, -9, cleavage/degradation of PARP, and apoptosis in dose- and time-dependent manners. These events were accompanied by the caspase-independent downregulation of Mcl-1, inactivation of Akt, as well as activation of Jun N-terminal kinase (JNK). Inhibition of PI3K/Akt by LY294002 significantly enhanced PEITC-induced apoptosis. Conversely, enforced activation of Akt by a constitutively active Akt construct markedly abrogated PEITC-mediated JNK activation, Mcl-1 downregulation, caspase activation, and apoptosis, and also interruption of the JNK pathway by pharmacological or genetically (e.g., siRNA) attenuated PEITC-induced apoptosis. Finally, administration of PEITC markedly inhibited tumor growth and induced apoptosis in U937 xenograft model in association with inactivation of Akt, activation of JNK, as well as downregulation of Mcl-1. Taken together, these findings represent a novel mechanism by which agents targeting Akt/JNK/Mcl-1 pathway potentiate PEITC lethality in transformed and primary human leukemia cells and inhibitory activity of tumor growth of U937 xenograft model

Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data

Interpretable machine learning models for gene expression datasets are important for understanding the decision-making process of a classifier and gaining insights on the underlying molecular processes of genetic conditions. Interpretable models can potentially support early diagnosis before full disease manifestation. This is particularly important yet, challenging for mental health. We hypothesise this is due to extreme heterogeneity issues which may be overcome and explained by personalised modelling techniques. Thus far, most machine learning methods applied to gene expression datasets, including deep neural networks, lack personalised interpretability. This paper proposes a new methodology named personalised constrained neuro fuzzy inference (PCNFI) for learning personalised rules from high dimensional datasets which are structurally and semantically interpretable. Case studies on two mental health related datasets (schizophrenia and bipolar disorders) have shown that the relatively short and simple personalised fuzzy rules provided enhanced interpretability as well as better classification performance compared to other commonly used machine learning methods. Performance test on a cancer dataset also showed that PCNFI matches previous benchmarks. Insights from our approach also indicated the importance of two genes (ATRX and TSPAN2) as possible biomarkers for early differentiation of ultra-high risk, bipolar and healthy individuals. These genes are linked to cognitive ability and impulsive behaviour. Our findings suggest a significant starting point for further research into the biological role of cognitive and impulsivity-related differences. With potential applications across bio-medical research, the proposed PCNFI method is promising for diagnosis, prognosis, and the design of personalised treatment plans for better outcomes in the future

Investigation of social and cognitive predictors in non-transition ultra-high-risk’ individuals for psychosis using spiking neural networks

Finding predictors of social and cognitive impairment in non-transition Ultra-High-Risk individuals (UHR) is critical in prognosis and planning of potential personalised intervention strategies. Social and cognitive functioning observed in youth at UHR for psychosis may be protective against transition to clinically relevant illness. The current study used a computational method known as Spiking Neural Network (SNN) to identify the cognitive and social predictors of transitioning outcome. Participants (90 UHR, 81 Healthy Control (HC)) completed batteries of neuropsychological tests in the domains of verbal memory, working memory, processing speed, attention, executive function along with social skills-based performance at baseline and 4 × 6-month follow-up intervals. The UHR status was recorded as Remitters, Converters or Maintained. SNN were used to model interactions between variables across groups over time and classify UHR status. The performance of SNN was examined relative to other machine learning methods. Higher interaction between social and cognitive variables was seen for the Maintained, than Remitter subgroup. Findings identified the most important cognitive and social variables (particularly verbal memory, processing speed, attention, affect and interpersonal social functioning) that showed discriminative patterns in the SNN models of HC vs UHR subgroups, with accuracies up to 80%; outperforming other machine learning models (56–64% based on 18 months data). This finding is indicative of a promising direction for early detection of social and cognitive impairment in UHR individuals that may not anticipate transition to psychosis and implicate early initiated interventions to stem the impact of clinical symptoms of psychosis

Involvement in surface antigen expression by a moonlighting FG-repeat nucleoporin in trypanosomes

Components of the nuclear periphery coordinate a multitude of activities, including macromolecular transport, cell-cycle progression, and chromatin organization. Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport, mRNA processing, and transcriptional regulation, and NPC components can define regions of high transcriptional activity in some organisms at the nuclear periphery and nucleoplasm. Lineage-specific features underpin several core nuclear functions and in trypanosomatids, which branched very early from other eukaryotes, unique protein components constitute the lamina, kinetochores, and parts of the NPCs. Here we describe a phenylalanine-glycine (FG)-repeat nucleoporin, TbNup53b, that has dual localizations within the nucleoplasm and NPC. In addition to association with nucleoporins, TbNup53b interacts with a known trans-splicing component, TSR1, and has a role in controlling expression of surface proteins including the nucleolar periphery-located, procyclin genes. Significantly, while several nucleoporins are implicated in intranuclear transcriptional regulation in metazoa, TbNup53b appears orthologous to components of the yeast/human Nup49/Nup58 complex, for which no transcriptional functions are known. These data suggest that FG-Nups are frequently co-opted to transcriptional functions during evolution and extend the presence of FG-repeat nucleoporin control of gene expression to trypanosomes, suggesting that this is a widespread and ancient eukaryotic feature, as well as underscoring once more flexibility within nucleoporin function

3, 3′-Diindolylmethane Exhibits Antileukemic Activity In Vitro and In Vivo through a Akt-Dependent Process

3,3′-diindolylmethane (DIM), one of the active products derived from Brassica plants, is a promising antitumor agent. The present study indicated that DIM significantly induced apoptosis in U937 human leukemia cells in dose- and time-dependent manners. These events were also noted in other human leukemia cells (Jurkat and HL-60) and primary human leukemia cells (AML) but not in normal bone marrow mononuclear cells. We also found that DIM-induced lethality is associated with caspases activation, myeloid cell leukemia-1 (Mcl-1) down-regulation, p21cip1/waf1 up-regulation, and Akt inactivation accompanied by c-jun NH2-terminal kinase (JNK) activation. Enforced activation of Akt by a constitutively active Akt construct prevented DIM-mediated caspase activation, Mcl-1 down-regulation, JNK activation, and apoptosis. Conversely, DIM lethality was potentiated by the PI3K inhibitor LY294002. Interruption of the JNK pathway by pharmacologic or genetic approaches attenuated DIM-induced caspases activation, Mcl-1 down-regulation, and apoptosis. Lastly, DIM inhibits tumor growth of mouse U937 xenograft, which was related to induction of apoptosis and inactivation of Akt, as well as activation of JNK. Collectively, these findings suggest that DIM induces apoptosis in human leukemia cell lines and primary human leukemia cells, and exhibits antileukemic activity in vivo through Akt inactivation and JNK activation

Geothermal Energy Market in Southern California Past, Present and Future

I'm pleased to be here as your keynote speaker from the utility industry. Today is fitting to discuss the role of an alternative/renewable energy resource such as geothermal. Three years ago today, the Exxon Valdez oil tanker spilled 11 million gallons of oil into Prince William Sound, Alaska. This ecological catastrophe was another of those periodic jolts that underscores the importance of lessening our nation's dependence on oil and increasing the use of cost-effective, environmentally benign alternative/renewable energy sources. Alternative/renewables have come a long way since the first oil crisis in 1973. Today, they provide 9 percent of electric power used in the United States. That's nearly double the figure of just two years ago. And since 1985, one-third of a new capacity has come from geothermal, solar, wind and biomass facilities. Nevertheless, geothermal supplies only about three-tenths of a percent of the country's electric power, or roughly 2,800 megawatts (MW). And most of that is in California. In fact, geothermal is California's second-largest source of renewable energy, supplying more than 5 percent of the power generated in the state. Today, I'd like to discuss the outlook for the geothermal industry, framing it within Southern California Edison's experience with geothermal and other alternative/renewable energy sources