Fixation Region Overlap: A quantitative method for the analysis of fixational eye movement patterns

This article presents a new method for the quantitative analyses of fixation patterns in eye tracking data. The Fixation Region Overlap Analysis (FROA) uses thresholded spatial distributions of fixation frequency or duration to determine regions-of-interest (ROIs). The locations of these ROIs are contrasted with fixation regions of other empirically-derived, or modelled, data patterns by comparing region pixel overlap. A Monte Carlo procedure is used to assess the statistical significance of fixation region overlap based on 95% confi-dence intervals (C.I.) of the distribution of random overlap for each set of thresholded ROIs. The value of the FROA method is demonstrated by applying it to data acquired in an object recognition task to determine which of two potential models best account for the observed fixation patterns

Efficient Hamiltonian programming in qubit arrays with nearest-neighbour couplings

We consider the problem of selectively controlling couplings in a practical quantum processor with always-on interactions that are diagonal in the computational basis, using sequences of local NOT gates. This methodology is well-known in NMR implementations, but previous approaches do not scale efficiently for the general fully-connected Hamiltonian, where the complexity of finding time-optimal solutions makes them only practical up to a few tens of qubits. Given the rapid growth in the number of qubits in cutting-edge quantum processors, it is of interest to investigate the applicability of this control scheme to much larger scale systems with realistic restrictions on connectivity. Here we present an efficient scheme to find near time-optimal solutions that can be applied to engineered qubit arrays with local connectivity for any number of qubits, indicating the potential for practical quantum computing in such systems.Comment: 5 pages, 5 figures. Shortened and clarified from previous versio

Do We Really Even Need Data?

As artificial intelligence and machine learning tools become more accessible, and scientists face new obstacles to data collection (e.g. rising costs, declining survey response rates), researchers increasingly use predictions from pre-trained algorithms as outcome variables. Though appealing for financial and logistical reasons, using standard tools for inference can misrepresent the association between independent variables and the outcome of interest when the true, unobserved outcome is replaced by a predicted value. In this paper, we characterize the statistical challenges inherent to this so-called ``inference with predicted data'' problem and elucidate three potential sources of error: (i) the relationship between predicted outcomes and their true, unobserved counterparts, (ii) robustness of the machine learning model to resampling or uncertainty about the training data, and (iii) appropriately propagating not just bias but also uncertainty from predictions into the ultimate inference procedure

From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives

In settings where most deaths occur outside the healthcare system, verbal autopsies (VAs) are a common tool to monitor trends in causes of death (COD). VAs are interviews with a surviving caregiver or relative that are used to predict the decedent's COD. Turning VAs into actionable insights for researchers and policymakers requires two steps (i) predicting likely COD using the VA interview and (ii) performing inference with predicted CODs (e.g. modeling the breakdown of causes by demographic factors using a sample of deaths). In this paper, we develop a method for valid inference using outcomes (in our case COD) predicted from free-form text using state-of-the-art NLP techniques. This method, which we call multiPPI++, extends recent work in "prediction-powered inference" to multinomial classification. We leverage a suite of NLP techniques for COD prediction and, through empirical analysis of VA data, demonstrate the effectiveness of our approach in handling transportability issues. multiPPI++ recovers ground truth estimates, regardless of which NLP model produced predictions and regardless of whether they were produced by a more accurate predictor like GPT-4-32k or a less accurate predictor like KNN. Our findings demonstrate the practical importance of inference correction for public health decision-making and suggests that if inference tasks are the end goal, having a small amount of contextually relevant, high quality labeled data is essential regardless of the NLP algorithm.Comment: 12 pages, 7 figure

The G-protein-coupled receptor CLR is upregulated in an autocrine loop with adrenomedullin in clear cell renal cell carcinoma and associated with poor prognosis

Purpose: The G-protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) and its ligand peptide adrenomedullin (encoded by ADM gene) are implicated in tumor angiogenesis in mouse models but poorly defined in human cancers. We therefore investigated the diagnostic/prognostic use for CLR in human tumor types that may rely on adrenomedullin signaling and in clear cell renal cell carcinoma (RCC), a highly vascular tumor, in particular. Experimental Design: In silico gene expression mRNA profiling microarray study (n = 168 tumors) and cancer profiling cDNA array hybridization (n=241 pairs of patient-matched tumor/normal tissue samples) were carried out to analyze ADM mRNA expression in 13 tumor types. Immunohistochemistry on tissue microarrays containing patient-matched renal tumor/normal tissues (n = 87 pairs) was conducted to study CLR expression and its association with clinicopathologic parameters and disease outcome. Results: ADM expression was significantly upregulated only in RCC and endometrial adenocarcinoma compared with normal tissue counterparts (P < 0.01). CLR was localized in tumor cells and vessels in RCC and upregulated as compared with patient-matched normal control kidney (P < 0.001). Higher CLR expression was found in advanced stages (P < 0.05), correlated with high tumor grade (P < 0.01) and conferred shorter overall survival (P < 0.01). Conclusions: In human tissues ADM expression is upregulated in cancer type-specific manner, implicating potential role for adrenomedullin signaling in particular in RCC, where CLR localization suggests autocrine/paracrine mode for adrenomedullin action within the tumor microenvironment. Our findings reveal previously unrecognized CLR upregulation in an autocrine loop with adrenomedullin in RCCwith potential application for this GPCR as a target for future functional studies and drug development. © 2013 AACR

Neuronal Activity Regulates Hippocampal miRNA Expression

Neuronal activity regulates a broad range of processes in the hippocampus, including the precise regulation of translation. Disruptions in proper translational control in the nervous system are associated with a variety of disorders that fall in the autistic spectrum. MicroRNA (miRNA) represent a relatively recently discovered player in the regulation of translation in the nervous system. We have conducted an in depth analysis of how neuronal activity regulates miRNA expression in the hippocampus. Using deep sequencing we exhaustively identify all miRNAs, including 15 novel miRNAs, expressed in hippocampus of the adult mouse. We identified 119 miRNAs documented in miRBase but less than half of these miRNA were expressed at a level greater than 0.1% of total miRNA. Expression profiling following induction of neuronal activity by electroconvulsive shock demonstrates that most miRNA show a biphasic pattern of expression: rapid induction of specific mature miRNA expression followed by a decline in expression. These results have important implications into how miRNAs influence activity-dependent translational control

Ricin Toxicokinetics and Its Sensitive Detection in Mouse Sera or Feces Using Immuno-PCR

Ricin (also called RCA-II or RCA(60)), one of the most potent toxins and documented bioweapons, is derived from castor beans of Ricinus communis. Several in vitro methods have been designed for ricin detection in complex food matrices in the event of intentional contamination. Recently, a novel Immuno-PCR (IPCR) assay was developed with a limit of detection of 10 fg/ml in a buffer matrix and about 10-1000-fold greater sensitivity than other methods in various food matrices.In order to devise a better diagnostic test for ricin, the IPCR assay was adapted for the detection of ricin in biological samples collected from mice after intoxication. The limit of detection in both mouse sera and feces was as low as 1 pg/ml. Using the mouse intravenous (iv) model for ricin intoxication, a biphasic half-life of ricin, with a rapid t(1/2)α of 4 min and a slower t(1/2)β of 86 min were observed. The molecular biodistribution time for ricin following oral ingestion was estimated using an antibody neutralization assay. Ricin was detected in the blood stream starting at approximately 6-7 h post- oral intoxication. Whole animal histopathological analysis was performed on mice treated orally or systemically with ricin. Severe lesions were observed in the pancreas, spleen and intestinal mesenteric lymph nodes, but no severe pathology in other major organs was observed.The determination of in vivo toxicokinetics and pathological effects of ricin following systemic and oral intoxication provide a better understanding of the etiology of intoxication and will help in the future design of more effective diagnostic and therapeutic methods

Mitochondrial genes are altered in blood early in Alzheimer's disease

Although mitochondrial dysfunction is a consistent feature of Alzheimer's disease in the brain and blood, the molecular mechanisms behind these phenomena are unknown. Here we have replicated our previous findings demonstrating reduced expression of nuclear-encoded oxidative phosphorylation (OXPHOS) subunits and subunits required for the translation of mitochondrial-encoded OXPHOS genes in blood from people with Alzheimer's disease and mild cognitive impairment. Interestingly this was accompanied by increased expression of some mitochondrial-encoded OXPHOS genes, namely those residing closest to the transcription start site of the polycistronic heavy chain mitochondrial transcript (MT-ND1, MT-ND2, MT-ATP6, MT-CO1, MT-CO2, MT-C03) and MT-ND6 transcribed from the light chain. Further we show that mitochondrial DNA copy number was unchanged suggesting no change in steady-state numbers of mitochondria. We suggest that an imbalance in nuclear and mitochondrial genome-encoded OXPHOS transcripts may drive a negative feedback loop reducing mitochondrial translation and compromising OXPHOS efficiency, which is likely to generate damaging reactive oxygen species

Interferon-driven alterations of the host’s amino acid metabolism in the pathogenesis of typhoid fever

Enteric fever, caused by Salmonella enterica serovar Typhi, is an important public health problem in resource-limited settings and, despite decades of research, human responses to the infection are poorly understood. In 41 healthy adults experimentally infected with wild-type S. Typhi, we detected significant cytokine responses within 12 h of bacterial ingestion. These early responses did not correlate with subsequent clinical disease outcomes and likely indicate initial host–pathogen interactions in the gut mucosa. In participants developing enteric fever after oral infection, marked transcriptional and cytokine responses during acute disease reflected dominant type I/II interferon signatures, which were significantly associated with bacteremia. Using a murine and macrophage infection model, we validated the pivotal role of this response in the expression of proteins of the host tryptophan metabolism during Salmonella infection. Corresponding alterations in tryptophan catabolites with immunomodulatory properties in serum of participants with typhoid fever confirmed the activity of this pathway, and implicate a central role of host tryptophan metabolism in the pathogenesis of typhoid fever

Breast tumour angiogenesis

The central importance of tumour neovascularization has been emphasized by clinical trials using antiangiogenic therapy in breast cancer. This review gives a background to breast tumour neovascularization in in situ and invasive breast cancer, outlines the mechanisms by which this is achieved and discusses the influence of the microenvironment, focusing on hypoxia. The regulation of angiogenesis and the antivascular agents that are used in an antiangiogenic dosing schedule, both novel and conventional, are also summarized