Tag: statistics

Int Urol Nephrol. 2022 Aug 25. doi: 10.1007/s11255-022-03346-7. Online ahead of print.

ABSTRACT

PURPOSE: We aim to evaluate the impact of preoperative thrombocytosis on oncological outcomes in patients with bladder cancer (BC) who undergo radical cystectomy (RC).

METHODS: Retrospective data collection of 1092 patients managed by RC for BC from 2 tertiary-care centers was performed. Elevated platelet count (PLT) was defined as > 450 × 10⁹/L. Univariable and multivariable logistic regression analyses were used to investigate the impact of thrombocytosis on oncological outcomes. These outcomes were also compared using Kaplan-Meier survival analysis.

RESULTS: The median follow-up was 50 months (32-64 months). Thrombocytosis was detected in 18.6% of the patients. The 3-year cancer-specific survival (CSS) for patients with normal PLT count was 92% which was higher than those with elevated PLT count (55%, P < 0.001). Similar results were found for the 6-year CSS with 82% for the no thrombocytosis group and 27% for the thrombocytosis group. Thrombocytosis was still significantly associated with poor prognosis for overall survival and recurrence-free survival (P < 0.001). In the multivariate analysis, CSS was significantly lower in patients with thrombocytosis (HR = 1.71, 95% CI = 1.22-2.39, P = 0.002). Patients with elevated PLT counts were also significantly more likely to receive adjuvant chemotherapy, to have a T stage > pT2b (P = 0.024), to have a positive lymph node, to have variant histology and positive resection margins, and to have concomitant carcinoma in situ (CIS) on final pathology (all P < 0.001).

CONCLUSIONS: Preoperative thrombocytosis was valuable for predicting the oncological outcomes of patients undergoing RC for BC.

PMID:36008697 | DOI:10.1007/s11255-022-03346-7

Environ Monit Assess. 2022 Aug 25;194(10):709. doi: 10.1007/s10661-022-10342-y.

ABSTRACT

The growth of the world population has led to the expansion of agricultural areas to produce food that meets world demand, making it necessary to increase productivity and maintain environmental sustainability in these areas. Seeking sustainable food production, the agricultural use of soil must be assessed in view of optimal use or land as natural resource, as well as minimize the effects of global warming related to land use and land cover (LULC). We hypothesize that different LULC affects Amazonian soil attributes. In this study, the effect of different LULC in the southern Brazilian Amazon, namely, native forest, pasture, and rice and soybean crops, on the spatial variability of soil fertility and texture was assessed, seeking to obtain information that will guide farmers in the near future to better exploit their areas and contribute to a more sustainable agriculture. Descriptive statistical analysis was performed for the pH, H + Al, Al, Ca, Mg, P, K, Cu, Fe, Mn, Zn, V, m, organic matter, clay, silt, and sand values from soil samples under different LULC. To verify the data normality, the Shapiro-Wilk test at 5% significance was performed. Outlier analysis using boxplot graphics, principal component analysis (PCA), and cluster analysis was performed. Data were submitted to geostatistical analysis to verify the spatial dependence degree of the variables through semivariograms for interpolated kriging maps. Except for silt, all variables were well represented in the factor map. PCA revealed that the data variability can be explained mainly by pH, V, Ca, K, and Zn values, which are inversely proportional to m, P, and sand. Through geostatistical analysis, spatial dependence ranging from moderate to strong was observed, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Yet, a spatial dependence ranging from moderate to strong was found, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Our findings reveal a lower fertility and higher acidity in forest areas, whereas crop areas presented the opposite result.

PMID:36008644 | DOI:10.1007/s10661-022-10342-y

Bull Math Biol. 2022 Aug 25;84(10):107. doi: 10.1007/s11538-022-01066-8.

ABSTRACT

The spiking activity of mitral cells (MC) in the olfactory bulb is a key attribute in olfactory sensory information processing to downstream cortical areas. A more detailed understanding of the modulation of MC spike statistics could shed light on mechanistic studies of olfactory bulb circuits and olfactory coding. We study the spike response of a recently developed single-compartment biophysical MC model containing seven known ionic currents and calcium dynamics subject to constant current input with background white noise. We observe rich spiking dynamics even with constant current input, including multimodal peaks in the interspike interval distribution (ISI). Although weak-to-moderate background noise for a fixed current input does not change the firing rate much, the spike dynamics can change dramatically, exhibiting non-monotonic spike variability not commonly observed in standard neuron models. We explain these dynamics with a phenomenological model of the ISI probability density function. Our study clarifies some of the complexities of MC spiking dynamics.

PMID:36008641 | DOI:10.1007/s11538-022-01066-8

Psychon Bull Rev. 2022 Aug 25. doi: 10.3758/s13423-022-02161-6. Online ahead of print.

ABSTRACT

Dyadic interactions require dynamic correspondence between one’s own movements and those of the other agent. This mapping is largely viewed as imitative, with the behavioural hallmark being a reaction-time cost for mismatched actions. Yet the complex motor patterns humans enact together extend beyond direct-matching, varying adaptively between imitation, complementary movements, and counter-imitation. Optimal behaviour requires an agent to predict not only what is likely to be observed but also how that observed action will relate to their own motor planning. In 28 healthy adults, we examined imitation and counter-imitation in a task that varied the likelihood of stimulus-response congruence from highly predictable, to moderately predictable, to unpredictable. To gain mechanistic insights into the statistical learning of stimulus-response compatibility, we compared two computational models of behaviour: (1) a classic fixed learning-rate model (Rescorla-Wagner reinforcement [RW]) and (2) a hierarchical model of perceptual-behavioural processes in which the learning rate adapts to the inferred environmental volatility (hierarchical Gaussian filter [HGF]). Though more complex and hence penalized by model selection, the HGF provided a more likely model of the participants’ behaviour. Matching motor responses were only primed (faster) in the most experimentally volatile context. This bias was reversed so that mismatched actions were primed when beliefs about volatility were lower. Inferential statistics indicated that matching responses were only primed in unpredictable contexts when stimuli-response congruence was at 50:50 chance. Outside of these unpredictable blocks the classic stimulus-response compatibility effect was reversed: Incongruent responses were faster than congruent ones. We show that hierarchical Bayesian learning of environmental statistics may underlie response priming during dyadic interactions.

PMID:36008626 | DOI:10.3758/s13423-022-02161-6

Ophthalmol Ther. 2022 Aug 25. doi: 10.1007/s40123-022-00560-5. Online ahead of print.

ABSTRACT

INTRODUCTION: Recent studies indicate that short-term monocular deprivation increases the deprived eye’s contribution to binocular fusion in both adults with normal vision and amblyopia. In this study, we investigated whether the changes in visual plasticity depended on the duration of deprivation in normal and amblyopic adults.

METHODS: Twelve anisometropia amblyopic observers (aged 24.8 ± 2.3 years) and 12 age-matched normal observers (aged 23.9 ± 1.2 years) participated in the study. The non-dominant eye of normal observers or amblyopic eye of amblyopic observers was deprived for 30, 120, and 300 min in a randomized order. Their eye balance was measured with a phase combination task, which is a psychophysical test, before and after the deprivation. This design enabled us to measure changes induced in binocular balance as an index visual plasticity due to monocular deprivations.

RESULTS: By comparing the ocular dominance changes as a result of monocular deprivation with different deprivation durations, we found evidence that the ocular dominance changes are slightly larger after longer deprivations in both normal and amblyopic observers, albeit with a statistical significance. The changes from 120-min were significantly greater than those from 30-min deprivation in both groups. The magnitude of changes in sensory eye balance was significantly larger in normal observers than that in the amblyopic observers; however, the longevity of changes in visual plasticity was found to be more long-lasting in amblyopic observers than the normal counterparts.

CONCLUSIONS: The duration of deprivation matters in both normal and amblyopic observers. Ocular dominance imbalance that is typically observed in amblyopia can be more ameliorated with a longer duration of deprivation.

PMID:36008603 | DOI:10.1007/s40123-022-00560-5

Pediatr Res. 2022 Aug 25. doi: 10.1038/s41390-022-02270-x. Online ahead of print.

ABSTRACT

BACKGROUND: Maintaining of remission early in the disease course of Crohn’s disease (CD) is essential and has major impact on the future prognosis. This study aimed to identify baseline predictors to develop model allowing stratification of patients who will not benefit from long-term azathioprine (AZA) treatment and will require more intensive therapy.

METHODS: This study was designed to develop clinical prediction rule using retrospective data analysis of pediatric CD patients included in prospective inception cohort. Clinical relapse was defined as necessity of re-induction of remission. Sequence of Cox models was fitted to predict risk of relapse.

RESULTS: Out of 1190 CD patients from 13 European centers, 441 were included, 50.3% patients did not experience clinical relapse within 2 years of AZA treatment initiation. Median time to relapse was 2.11 (CI 1.59-2.46) years. Of all the tested parameters available at diagnosis, six were significant in multivariate analyses: C-reactive protein (p = 0.038), body mass index Z-score >0.8 SD (p = 0.002), abnormal sigmoid imaging (p = 0.039), abnormal esophageal endoscopy (p = 0.005), ileocolonic localization (p = 0.023), AZA dose in specific age category (p = 0.031).

CONCLUSIONS: Although the possibility of predicting relapse on AZA treatment appears limited, we developed predictive model based on six baseline parameters potentially helpful in clinical decision.

IMPACT: The possibility of predicting relapse on AZA treatment appears to be possible but limited. We identified six independent predictors available at diagnosis of early AZA/6-MP treatment failure in pediatric CD patients. Using combination of these factors, a model applicable to clinical practice was created. A web-based tool, allowing estimation of individual relapse risk in pediatric CD patients on a particular therapeutic regimen, has been developed.

PMID:36008595 | DOI:10.1038/s41390-022-02270-x

Commun Biol. 2022 Aug 25;5(1):874. doi: 10.1038/s42003-022-03817-8.

ABSTRACT

To advance understanding of biodiversity and ecosystem function, ecologists seek widely applicable relationships among species diversity and other ecosystem characteristics such as species productivity, biomass, and abundance. These metrics vary widely across ecosystems and no relationship among any combination of them that is valid across habitats, taxa, and spatial scales, has heretofore been found. Here we derive such a relationship, an equation of state, among species richness, energy flow, biomass, and abundance by combining results from the Maximum Entropy Theory of Ecology and the Metabolic Theory of Ecology. It accurately captures the relationship among these state variables in 42 data sets, including vegetation and arthropod communities, that span a wide variety of spatial scales and habitats. The success of our ecological equation of state opens opportunities for estimating difficult-to-measure state variables from measurements of others, adds support for two current theories in ecology, and is a step toward unification in ecology.

PMID:36008589 | DOI:10.1038/s42003-022-03817-8

Environ Sci Pollut Res Int. 2022 Aug 26. doi: 10.1007/s11356-022-22685-7. Online ahead of print.

ABSTRACT

The Pearl River Basin (PRB) is a significant area for economic development (ED) and ecological protection in China. Studying the relationship between carbon emission (CE) and ED is crucial for China and the world to cope with climate change and achieve CO₂ reduction. For 48 cities in the PRB, we used the coupling coordination model and geographically weighted regression model to analyze the coupling coordination degree (CCD) between CE and ED and investigate the main influencing factors. The results suggested that (1) the CCD presents spatial heterogeneity, with the Pearl River Delta having the highest value and the middle reaches having the lowest value; (2) the coupling coordination type between CE and ED changes from incoordination to coordination in general; and (3) the resident income and population size have a positive influence on the CCD of the cities in the lower reaches, while the secondary industry scale has a beneficial impact on the upstream. Finally, we put forward corresponding policy suggestions to achieve sustainable development in terms of reducing economic inequities, enhancing public expenditure and innovation capability, and streamlining the industrial structure.

PMID:36008585 | DOI:10.1007/s11356-022-22685-7

Environ Sci Pollut Res Int. 2022 Aug 26. doi: 10.1007/s11356-022-22662-0. Online ahead of print.

ABSTRACT

Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM_2.5, PM₁₀, O₃, SO₂, and NO₂), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients’ average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m³ increase in O₃, PM_2.5 and PM₁₀ exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O₃ and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O₃ and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.

PMID:36008583 | DOI:10.1007/s11356-022-22662-0

Sci Rep. 2022 Aug 25;12(1):14490. doi: 10.1038/s41598-022-18773-w.

ABSTRACT

The global agri-food system relies on synthetic nitrogen (N) fertilisation to increase crop yields, yet the use of synthetic N fertiliser is unsustainable. In this study we estimate global greenhouse (GHG) emissions due to synthetic N fertiliser manufacture, transportation, and field use in agricultural systems. By developing the largest field-level dataset available on N₂O soil emissions we estimate national, regional and global N₂O direct emission factors (EFs), while we retrieve from the literature the EFs for indirect N₂O soil emissions, and for N fertiliser manufacturing and transportation. We find that the synthetic N fertiliser supply chain was responsible for estimated emissions of 1.13 GtCO₂e in 2018, representing 10.6% of agricultural emissions and 2.1% of global GHG emissions. Synthetic N fertiliser production accounted for 38.8% of total synthetic N fertiliser-associated emissions, while field emissions accounted for 58.6% and transportation accounted for the remaining 2.6%. The top four emitters together, China, India, USA and EU28 accounted for 62% of the total. Historical trends reveal the great disparity in total and per capita N use in regional food production. Reducing overall production and use of synthetic N fertilisers offers large mitigation potential and in many cases realisable potential to reduce emissions.

PMID:36008570 | DOI:10.1038/s41598-022-18773-w