Miracle-dz/UniFAR-FTUs huggingface dataset:
Turnover of Newborn Olfactory Bulb Neurons Optimizes Olfaction

Postdevelopmental neurogenesis occurs in the olfactory bulb (OB), to which new interneurons are continuously recruited. However, only a subset of the adult-generated interneurons survives, as many undergo programmed cell death. As part of homeostatic processes, the removal of new neurons is required alongside the addition of new ones, to ensure a stable neuron number. In addition to a critical role in tissue maintenance, it is still unclear whether this neuronal elimination affects the functioning of adult circuits. Using focal drug delivery restricted to the OB, we investigated the significance of programmed cell death in the adult OB circuits. Cell death was effectively blocked by the broad-spectrum caspase inhibitor benzyloxycarbonyl-Val-Ala-Asp(OMe)-fluoromethylketone (zVAD). The zVAD effect differed with newborn interneuron location, either in the superficial (periglomerular cells) or in the deep (granule cells) OB layers. Furthermore, whereas sensory experience potentiated the effect of zVAD on the survival of new granule cells, it had no additional effect on the survival of new periglomerular cells. Thus, distinct mechanisms control the survival/elimination decision of newborn interneuron subtypes. However, zVAD had no effect on the olfactory sensory neurons projecting to the bulb. Remarkably, psychophysical analyzes revealed that a normal rate of new neuron elimination was essential for optimal odorant exploration and discrimination. This study highlights the importance of cell elimination for adjusting olfactory performance. We conclude that adult-generated OB interneurons are continually turned over, rather than simply added, and the precise balance between new and mature interneurons, set through active selection/elimination processes, is essential for optimizing olfaction.
Simultaneous Determination of Cobalt, Copper and Zinc by Energy Dispersive X-ray Fluorescence Spectrometry after Preconcentration on PAR-loaded Ion-Exchange Resin

A sensitive method for the preconcentration and determination of trace amounts of Co, Cu and Zn by energy-dispersive X-ray fluorescence spectrometry (EDXRF) has been developed. The method is based on the fact that 4-(2-pyridylazo)-resorcinol (PAR) loaded Dowex anion-exchange resin (PAR-resin) can effectively adsorb Co, Cu and Zn at pH 9.0 to form PAR-metal complexes. The detection limits for Co, Cu and Zn were 1.53, 0.31 and 0.21 ppb, respectively. The precisions for five replicate measurements of the three metals were 3.4, 2.7 and 2.1% RSD, and the calibration curves were linear up to 75 μg with correlation coefficients of 0.9975, 0.9980 and 0.9985, respectively. The method was successfully applied for the simultaneous determination of Co, Cu and Zn in seawater samples at ppb levels.
Antimicrobial Resistance in Neisseria gonorrhoeae in the 21st Century: Past, Evolution, and Future

SUMMARY Neisseria gonorrhoeae is evolving into a superbug with resistance to previously and currently recommended antimicrobials for treatment of gonorrhea, which is a major public health concern globally. Given the global nature of gonorrhea, the high rate of usage of antimicrobials, suboptimal control and monitoring of antimicrobial resistance (AMR) and treatment failures, slow update of treatment guidelines in most geographical settings, and the extraordinary capacity of the gonococci to develop and retain AMR, it is likely that the global problem of gonococcal AMR will worsen in the foreseeable future and that the severe complications of gonorrhea will emerge as a silent epidemic. By understanding the evolution, emergence, and spread of AMR in N. gonorrhoeae, including its molecular and phenotypic mechanisms, resistance to antimicrobials used clinically can be anticipated, future methods for genetic testing for AMR might permit region-specific and tailor-made antimicrobial therapy, and the design of novel antimicrobials to circumvent the resistance problems can be undertaken more rationally. This review focuses on the history and evolution of gonorrhea treatment regimens and emerging resistance to them, on genetic and phenotypic determinants of gonococcal resistance to previously and currently recommended antimicrobials, including biological costs or benefits; and on crucial actions and future advances necessary to detect and treat resistant gonococcal strains and, ultimately, retain gonorrhea as a treatable infection.
Irinotecan plus cisplatin for therapy of small-cell carcinoma of the esophagus: report of 12 cases from single institution experience.

BACKGROUND Esophageal small-cell cancer is a rare disease, and standard therapy has not yet been established. METHODS A total of 12 esophageal small-cell carcinoma patients were treated with CPT-11 (70 mg/m(2)) on Days 1 and 15 and CPT-11 plus CDDP (80 mg/m(2)) on Day 1 with each cycle repeated every 4 weeks at our institution. RESULTS A total of 46 chemotherapy courses were given (median, 3.5). There were two complete responses and eight partial responses. The median survival time was 417 (97-1626) days, and three patients were still alive for >40 months. Grade 4 neutropenia was observed in two patients, Grade 4 anemia in one patient, Grade 3-4 diarrhea in three patients and Grade 3-4 hyponatremia in three patients. Other adverse reactions seen were mild with no treatment-related deaths observed. CONCLUSIONS To our knowledge, this is the first report of the series of more than 10 patients with small-cell carcinoma of the esophagus treated with the same chemotherapy regimen. The combination of CPT-11 and CDDP appears to be effective therapy of this disease with acceptable toxicity profile. We believe that this regimen is one of the options to be considered for treatment of esophageal small-cell carcinoma.
Where are you heading? Flexible integration of retinal and extra‐retinal cues during self‐motion perception

As we move forward in the environment, we experience a radial expansion of the retinal image, wherein the center corresponds to the instantaneous direction of self-motion. Humans can precisely perceive their heading direction even when the retinal motion is distorted by gaze shifts due to eye/body rotations. Previous studies have suggested that both retinal and extra-retinal strategies can compensate for the retinal image distortion. However, the relative contributions of each strategy remain unclear. To address this issue, we devised a two-alternative-headings discrimination task, in which participants had either real or simulated pursuit eye movements. The two conditions had the same retinal input but either with or without extra-retinal eye movement signals. Thus, the behavioral difference between conditions served as a metric of extra-retinal contribution. We systematically and independently manipulated pursuit speed, heading speed, and the reliability of retinal signals. We found that the levels of extra-retinal contributions increased with increasing pursuit speed (stronger extra-retinal signal), and with decreasing heading speed (weaker retinal signal). In addition, extra-retinal contributions also increased as we corrupted retinal signals with noise. Our results revealed that the relative magnitude of retinal and extra-retinal contributions was not fixed but rather flexibly adjusted to each specific task condition. This task-dependent, flexible integration appears to take the form of a reliability-based weighting scheme that maximizes heading performance.
Bayesian Parametric and Nonparametric Inference for Multiple Record Linkage

Record linkage is an historically important statistical problem arising when data about some population of individuals is spread over several files. As kids, we grew up with the game “Where in the world is Carmen San Diego”? Nowadays, the name of the game for the U.S. Census Bureau and other organizations is who’s the real Steve Fienberg, where they are dealing with deciding if someone named Steve Fienberg is the same person across multiple lists. This problem has been looked at in the past in the two-file setting and more recently for multiple files. We propose Bayesian parametric and nonparametric methodology for multiples files in which the fields are regarded as independent. A linkage structure represents whether or not individuals i and j in particular lists are matches. We estimate the posterior distribution of this linkage structure via a hybrid Markov chain Monte Carlo (MCMC) algorithm. We then compute associated matching probabilities that individuals are captured using the National Long-Term Care Survey (NLTCS) dataset, where the truth is known since patients are tracked by a unique patient identifier.
Air Pollution and Mortality in the Medicare Population

BACKGROUND Studies have shown that long‐term exposure to air pollution increases mortality. However, evidence is limited for air‐pollution levels below the most recent National Ambient Air Quality Standards. Previous studies involved predominantly urban populations and did not have the statistical power to estimate the health effects in underrepresented groups. METHODS We constructed an open cohort of all Medicare beneficiaries (60,925,443 persons) in the continental United States from the years 2000 through 2012, with 460,310,521 person‐years of follow‐up. Annual averages of fine particulate matter (particles with a mass median aerodynamic diameter of less than 2.5 μm [PM2.5]) and ozone were estimated according to the ZIP Code of residence for each enrollee with the use of previously validated prediction models. We estimated the risk of death associated with exposure to increases of 10 μg per cubic meter for PM2.5 and 10 parts per billion (ppb) for ozone using a two‐pollutant Cox proportional‐hazards model that controlled for demographic characteristics, Medicaid eligibility, and area‐level covariates. RESULTS Increases of 10 μg per cubic meter in PM2.5 and of 10 ppb in ozone were associated with increases in all‐cause mortality of 7.3% (95% confidence interval [CI], 7.1 to 7.5) and 1.1% (95% CI, 1.0 to 1.2), respectively. When the analysis was restricted to person‐years with exposure to PM2.5 of less than 12 μg per cubic meter and ozone of less than 50 ppb, the same increases in PM2.5 and ozone were associated with increases in the risk of death of 13.6% (95% CI, 13.1 to 14.1) and 1.0% (95% CI, 0.9 to 1.1), respectively. For PM2.5, the risk of death among men, blacks, and people with Medicaid eligibility was higher than that in the rest of the population. CONCLUSIONS In the entire Medicare population, there was significant evidence of adverse effects related to exposure to PM2.5 and ozone at concentrations below current national standards. This effect was most pronounced among self‐identified racial minorities and people with low income. (Supported by the Health Effects Institute and others.)
Enhancing Writing Ability through Multiple-Intelligence Strategies

This quasi-experimental research investigates how multiple-intelligence strategies and instructions can be used to improve the writing ability of students. The experimental group was taught the five multiple intelligences related to writing: verbal-linguistic, logical-mathematical, visual-spatial, interpersonal and intrapersonal. Students were also taught the five multiple-intelligence strategies related to writing which were brainstorming, topic-word association, rank ordering, mind-mapping, and metacognition. Both the experimental and the control groups were given two compositions: a narrative and an expository. After two months of training they were given a posttest to find out whether there was any significant difference in the writing ability of students. Writing ability was measured based on the Six-Trait Analytic Writing Rubric. Paired Sample T-Test, ANOVA, and MANOVA were used to analyze the data collected. Significant improvement is seen in the overall writing ability of students and also in the six traits analyzed after two months of training.
Application of support vector machine to predict fault prone classes

Empirical validation of software metrics to predict quality using machine learning methods is important to ensure their practical relevance in the software organizations. It would also be interesting to know the relationship between object-oriented metrics and fault proneness. In this paper, we build a Support Vector Machine (SVM) model to find the relation-ship between object-oriented metrics given by Chidamber and Kemerer and fault proneness. The proposed model is empirically evaluated using open source software. The performance of the SVM method was evaluated by Receiver Operating Characteristic (ROC) analysis. Based on these results, it is reasonable to claim that such models could help for planning and performing testing by focusing resources on fault- prone parts of the design and code. Thus, the study shows that SVM method may also be used in constructing software quality models. However, similar types of studies are required to be carried out in order to establish the acceptability of the model.
Indapamide Lowers Blood Pressure by Increasing Production of Epoxyeicosatrienoic Acids in the Kidney

Diuretics are widely used in the treatment of hypertension, although the precise mechanisms remain unknown. Epoxyeicosatrienoic acids (EETs), cytochrome P450 (P450) epoxygenase metabolites of arachidonic acid, play critical roles in regulation of blood pressure. The present study was carried out to investigate whether EETs participate in the antihypertensive effect of thiazide diuretics [hydrochlorothiazide (HCTZ)] and thiazide-like diuretics (indapamide). Male spontaneously hypertensive rats (SHRs) were treated with indapamide or HCTZ for 8 weeks. Systolic blood pressure, measured via tail-cuff plethysmography and confirmed via intra-arterial measurements, was significantly decreased in indapamide- and HCTZ-treated SHRs compared with saline-treated SHRs. Indapamide increased kidney CYP2C23 expression, decreased soluble epoxide hydrolase expression, increased urinary and renovascular 11,12- and 14,15-EETs, and decreased production of 11,12- and 14,15-dihydroxyeicosatrienoic acids in SHRs. No effect on expression of CYP4A1 or CYP2J3, or on 20-hydroxyeicosatetraenoic acid production, was observed, suggesting indapamide specifically targets CYP2C23-derived EETs. Treatment of SHRs with HCTZ did not affect the levels of P450s or their metabolites. Increased cAMP activity and protein kinase A expression were observed in the renal microvessels of indapamide-treated SHRs. Indapamide ameliorated oxidative stress and inflammation in renal cortices by down-regulating the expression of p47phox, nuclear factor-κB, transforming growth factor-β1, and phosphorylated mitogen-activated protein kinase. Furthermore, the p47phox-lowering effect of indapamide in angiotensin II–treated rat mesangial cells was partially blocked by the presence of N-(methylsulfonyl)-2-(2-propynyloxy)-benzenehexanamide (MS-PPOH) or CYP2C23 small interfering RNA. Together, these results indicate that the hypotensive effects of indapamide are mediated, at least in part, by the P450 epoxygenase system in SHRs, and provide novel insights into the blood pressure–lowering mechanisms of diuretics.
Color Image Segmentation: From the View of Projective Clustering

An intuitive way of color image segmentation is through clustering in which each pixel in an image is treated as a data point in the feature space. A feature space is effective if it can provide high distinguishability among objects in images. Typically, in the preprocessing phase, various modalities or feature spaces are considered, such as color, texture, intensity, and spatial information. Feature selection or reduction can also be understood as transforming the original feature space into a more distinguishable space (or subspaces) for distinguishing different content in an image. Most clustering-based image segmentation algorithms work in the full feature space while considering the tradeoff between efficiency and effectiveness. The authors’ observation indicates that often time objects in images can be simply detected by applying clustering algorithms in subspaces. In this paper, they propose an image segmentation framework, named Hill-Climbing based Projective Clustering (HCPC), which utilizes EPCH (an efficient projective clustering technique by histogram construction) as the core framework and Hill-Climbing K-means (HC) for dense region detection, and thereby being able to distinguish image contents within subspaces of a given feature space. Moreover, a new feature space, named HSV r V g V b , is also explored which is derived from Hue, Saturation, and Value (HSV) color space. The scalability of the proposed algorithm is linear to the dimensionality of the feature space, and our segmentation results outperform that of HC and other projective clustering-based algorithms.
The Othering of Palestinians in Film: Munich (2006) and Waltz with Bashir (2009)

This paper is a critical textual analysis of two of the most popular and critically acclaimed non-documentary films on the Arab-Israeli conflict. The wide array of popular films on Israel and Palestine released in the past two decades, and the myriad perspectives they present, call for a more current critical textual analysis, as some of these films have been very well-received by audiences worldwide and have garnered numerous international film awards. These films include Divine Intervention (2002), Munich (2006), Miral (2010), Ajami (2010), and Waltz with Bashir (2009), to name a few. Film provides a popular medium through which we find an active Othering of Palestinians, sometimes even in films that have set out to upend dominant narratives. By undertaking a textual analysis of two of these films, Munich and Waltz with Bashir , and utilising works on collective memory along with elements of critical race theory, this paper discusses some problematic aspects of modern film representations of Arabs in relation to the Arab-Israeli conflict. This study carries implications for both historical and political studies of this conflict, and for communications theory by delving more deeply into media depictions of race, ethnicity, and nationality amidst the Arab-Israeli conflict. It also raises questions as to the dominance of Orientalism and neo-Orientalism in media depictions of Palestine and Palestinians and how that may be changing due to an emerging ‘Palestinian narrative’ in recent films. Furthermore, by lending a critical eye towards these films, we can take a more accurate look at the larger historiography and media landscape surrounding the Arab-Israeli conflict and observe how recent political developments ‘on the ground’ have, or have not, influenced depictions of the conflict and the region.
Muddy Waters 1 Running Head : MUDDY WATERS Welcome Clarity for Muddy Waters

In his article Lee advocates using directed acyclic graphs (DAGs) to test causal theory in differential psychology. We applaud Lee’s efforts to introduce graph theory and causal hypotheses to differential psychology. We agree that these methods lead to better understanding of the mechanisms underlying behavior. We thus join in advocating the use of these methods that, while they require more creative effort, honestly confront and overcome the problems of assigning causality which plague differential psychology and public policy.
A Framework to Evaluate the Effectiveness of Different Load Testing Analysis Techniques

Large-scale software systems like Amazon and eBay must be load tested to ensure they can handle hundreds and millions of current requests in the field. Load testing usually lasts for a few hours or even days and generates large volumes of system behavior data (execution logs and counters). This data must be properly analyzed to check whether there are any performance problems in a load test. However, the sheer size of the data prevents effective manual analysis. In addition, unlike functional tests, there is usually no test oracle associated with a load test. To cope with these challenges, there have been many analysis techniques proposed to automatically detect problems in a load test by comparing the behavior of the current test against previous test(s). Unfortunately, none of these techniques compare their performance against each other. In this paper, we have proposed a framework, which evaluates and compares the effectiveness of different test analysis techniques. We have evaluated a total of 23 test analysis techniques using load testing data from three open source systems. Based on our experiments, we have found that all the test analysis techniques can effectively build performance models using data from both buggy or non-buggy tests and flag the performance deviations between them. It is more cost-effective to compare the current test against two recent previous test(s), while using testing data collected under longer sampling intervals (≥180 seconds). Among all the test analysis techniques, Control Chart, Descriptive Statistics and Regression Tree yield the best performance. Our evaluation framework and findings can be very useful for load testing practitioners and researchers. To encourage further research on this topic, we have made our testing data publicity available to download.
Defining a Gene Promoter Methylation Signature in Sputum for Lung Cancer Risk Assessment

Purpose: To evaluate the methylation state of 31 genes in sputum as biomarkers in an expanded nested, case–control study from the Colorado cohort, and to assess the replication of results from the most promising genes in an independent case–control study of asymptomatic patients with stage I lung cancer from New Mexico. Experimental Design: Cases and controls from Colorado and New Mexico were interrogated for methylation of up to 31 genes using nested, methylation-specific PCR. Individual genes and methylation indices were used to assess the association between methylation and lung cancer with logistic regression modeling. Results: Seventeen genes with ORs of 1.4 to 3.6 were identified and selected for replication in the New Mexico study. Overall, the direction of effects seen in New Mexico was similar to Colorado with the largest increase in case discrimination (ORs, 3.2–4.2) seen for the PAX5α, GATA5, and SULF2 genes. Receiver operating characteristic (ROC) curves generated from seven-gene panels from Colorado and New Mexico studies showed prediction accuracy of 71% and 77%, respectively. A 22-fold increase in lung cancer risk was seen for a subset of New Mexico cases with five or more genes methylated. Sequence variants associated with lung cancer did not improve the accuracy of this gene methylation panel. Conclusions: These studies have identified and replicated a panel of methylated genes whose integration with other promising biomarkers could initially identify the highest risk smokers for computed tomographic screening for early detection of lung cancer. Clin Cancer Res; 18(12); 3387–95. ©2012 AACR.