Basic statistics in cell biology.

The physicist Ernest Rutherford said, "If your experiment needs statistics, you ought to have done a better experiment." Although this aphorism remains true for much of today's research in cell biology, a basic understanding of statistics can be useful to cell biologists to help in monitoring the conduct of their experiments, in interpreting the results, in presenting them in publications, and when critically evaluating research by others. However, training in statistics is often focused on the sophisticated needs of clinical researchers, psychologists, and epidemiologists, whose conclusions depend wholly on statistics, rather than the practical needs of cell biologists, whose experiments often provide evidence that is not statistical in nature. This review describes some of the basic statistical principles that may be of use to experimental biologists, but it does not cover the sophisticated statistics needed for papers that contain evidence of no other kind.

Compensation effect of mortality is a challenge to substantial lifespan extension of humans.

Despite frequent claims regarding radical extensions of human lifespan in the near future, many pragmatic scientists caution against excessive and baseless optimism on this front. In this study, we examine the compensation effect of mortality (CEM) as a potential challenge to substantial lifespan extension. The CEM is an empirical mortality regularity, often depicted as relative mortality convergence at advanced ages. Analysis of mortality data from 44 human populations, available in the Human Mortality Database, demonstrated that CEM can be represented as a continuous decline in relative mortality variation (assessed through the coefficient of variation and the standard deviation of the logarithm of mortality) with age, reaching a minimum corresponding to the species-specific lifespan. Through this method, the species-specific lifespan is determined to be 96-97 years, closely aligning with estimates derived from correlations between Gompertz parameters (95-98 years). Importantly, this representation of CEM can be achieved non-parametrically, eliminating the need for estimating Gompertz parameters. CEM is a challenge to lifespan extension, because it suggests that the true aging rate in humans (based on loss of vital elements, e.g., functional cells) remains stable at approximately 1% per year in the majority of human populations and is not affected by environmental or familial longevity factors. Given this rate of functional cell loss, one might anticipate that the total pool of functional cells could be entirely depleted by the age of 115-120 years creating physiological limit to human lifespan. Mortality pattern of supercentenarians (110 + years) aligns with this prediction.

Association of total sleep duration variability with risk of new stroke in the middle-aged and elderly Chinese population.

OBJECTIVE: To investigate the association between total sleep duration variability and stroke in the middle-aged and elderly population in China. METHODS: Data were collected from the 2011, 2013, 2015, and 2018 surveys of the China Health and Retirement Longitudinal Study (CHARLS). A total of 3485 participants, who had not experienced a stroke until 2015 and completed the follow-up in 2018, were enrolled to analyze the relationship between total sleep duration variability and new stroke. Total sleep duration was calculated by summing self-reported nocturnal sleep duration and daytime napping. The variability was determined by calculating the standard deviation (SD) of total sleep duration across the first three waves. A binary logistic regression model was utilized to analyze this association. RESULTS: Of the 3485 participants, 183 (5.25%) sustained a stroke event. A dose-response relationship was observed, indicating an increased stroke risk of 0.2 per unit (hours) increase in total sleep duration variability [OR (95% CI): 1.20 (1.01-1.42)]. Upon stratification by sex groups, this increased risk was significant only in men [OR (95% CI): 1.44 (1.12-1.83)]. CONCLUSION: Increased total sleep duration variability was associated with an increased risk of stroke in the middle-aged and elderly, independent of factors such as age, nocturnal sleep duration, napping habits, region of residence, hypertension, diabetes mellitus, dyslipidemia, BMI, smoking, drinking habits, and marital status. However, a more notable correlation was observed in males.

Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years.

OBJECTIVES: This article defines analytical performance specifications (APS) for evaluating laboratory proficiency through an external quality assessment scheme. METHODS: Standard deviations for proficiency assessment were derived from Thompson's characteristic function applied to robust data calculated from participants' submissions in the Occupational and Environmental Laboratory Medicine (OELM) external quality assurance scheme for trace elements in serum, whole blood and urine. Characteristic function was based on two parameters: (1) ß - the average coefficient of variation (CV) at high sample concentrations; (2) α - the average standard deviation (SD) at low sample concentrations. APSs were defined as 1.65 standard deviations calculated by Thompson's approach. Comparison between OELM robust data and characteristic function were used to validate the model. RESULTS: Application of the characteristic function allowed calculated APS for 18 elements across three matrices. Some limitations were noted, particularly for elements (1) with no sample concentrations near analytical technique limit of detection; (2) exhibiting high robust CV at high concentration; (3) exhibiting high analytical variability such as whole blood Tl and urine Pb; (4) with an unbalanced number of robust SD above and under the characteristic function such as whole blood Mn and serum Al and Zn. CONCLUSIONS: The characteristic function was a useful means of deriving APS for trace elements in biological fluids where biological variation data or outcome studies were not available. However, OELM external quality assurance scheme data suggests that the characteristic functions are not appropriate for all elements.

Association between short-term blood pressure variability and target organ damage in non-dialysis patients with chronic kidney disease.

BACKGROUND: It is unclear whether short-term blood pressure variability (BPV) is associated with target organ damage in patients with non-dialysis chronic kidney disease (CKD). METHODS: A cross-sectional, single-center study was conducted among 3442 non-dialysis CKD patients hospitalized in the department of Nephrology of the Fifth Affiliated Hospital of Sun Yat-sen University from November 2017 to July 2022 and collected the demographic, laboratory, clinic blood pressure, ambulatory blood pressure data, and short-term BPV assessed by the weighted standard deviation (wSD) derived from ambulatory blood pressure monitoring (ABPM). Multivariate logistic analyses were used to evaluate the independent effects between short-term BPV and subclinical target organ damage, including left ventricular hypertrophy (LVH), abnormal carotid intima-media thickness (CIMT), low estimated glomerular filtration rate (eGFR), and albuminuria. RESULTS: The average age of the participants was 47.53 ± 14.06 years and 56% of participants were male. The baseline eGFR was 69 mL/min/1.73 m2. Based on the tertile distribution of wSD according to equal numbers, patients were divided into three categories with T1(< 9.66 mmHg), T2(9.66-12.23 mmHg), and T3(> 12.23 mmHg) of SBPV; T1(< 8.17 mmHg), T2(8.17-9.93 mmHg), and T3(> 9.93 mmHg) of DBPV. The participants with the higher wSD group had a higher prevalence of target organ damage than their counterparts (P-trend < 0.05). An increasing trend in short-term variability was present with advancing CKD stages (P-trend < 0.001). Multivariate logistic analyses results showed that the odds ratio (OR) of SBP wSD was (1.07 [1.03,1.11], P < 0.001) for LVH, (1.04 [1.01,1.07, P = 0.029) for abnormal CIMT, (1.05 [1.02,1.08], P = 0.002) for low eGFR, and (1.06 [1.02,1.09], P = 0.002) for albuminuria; The OR of DBP wSD was (1.07 [1.02,1.12], P = 0.005) for LVH, (1.05 [1.01,1.09], P = 0.028) for abnormal CIMT, (1.05 [1.01,1.09], P = 0.022) for low eGFR, and (1.05 [1.01,1.10], P = 0.025) for albuminuria when adjusted for confounding factors and mean BP. CONCLUSIONS: In conclusion, short-term BPV is associated with target organ damage, and irresponsible of average blood pressure levels, in Chinese non-dialysis CKD participants.

Body weight and eating attitudes influence improvement of depressive symptoms in children and pre-adolescents with eating disorders: a prospective multicenter cohort study.

BACKGROUND: Pediatric patients with eating disorders in a multicenter joint study on 11 facilities were enrolled and prospectively investigated to determine whether improvement in body weight, eating attitudes, and psychosocial factors in children with eating disorders would also improve depressive symptoms. METHODS: In this study, 91 patients were enrolled between April 2014 and March 2016. The severity of underweight was assessed using the body mass index-standard deviation score (BMI-SDS), eating behavior was assessed using the children's eating attitude test (ChEAT26), the outcome of childhood eating disorders was assessed using the childhood eating disorder outcome scale, and depressive symptoms were assessed using the Children's Depression Inventory (CDI) score. RESULTS: After 12 months of treatment, depressive symptoms were evaluated in 62 of the 91 cases where it was evaluated at the initial phase. There was no difference in background characteristics between the included patients and the 29 patients who dropped out. A paired-sample t-test revealed a significant decrease in CDI scores after 12 months of treatment (p < 0.001, 95% CI: 2.401-7.373) and a significant increase in the BMI-SDS (p < 0.001, 95% CI: - 2.41973-1.45321). Multiple regression analysis revealed that BMI-SDS and ChEAT26 scores at the initial phase were beneficial in CDI recovery. In addition, BMI-SDS at the initial phase was useful for predicting BMI-SDS recovery after 12 months of treatment. CONCLUSIONS: Depressive symptoms in children with eating disorders improved with therapeutic intervention on body weight and eating attitudes. TRIAL REGISTRATION: The Clinical Trial Number for this study is UMIN000055004.

Dynamic evolution and spatial difference of public health service supply in economically developed provinces of China: typical evidence from Guangdong Province.

OBJECTIVE: The outbreak of the COVID-19 pandemic has drawn attention from all sectors of society to the level of public health services. This study aims to investigate the level of public health service supply in the four major regions of Guangdong Province, providing a basis for optimizing health resource allocation. METHODS: This article uses the entropy method and panel data of 21 prefecture-level cities in Guangdong Province from 2005 to 2021 to construct the evaluation index system of public health service supply and calculate its supply index. On this basis, the standard deviation ellipse method, kernel density estimation, and Markov chain are used to analyze the spatiotemporal evolution trend of the public health service supply level in Guangdong Province. The Dagum Gini coefficient and panel regression model are further used to analyze the relative differences and the key influencing factors of difference formation. Finally, the threshold effect model is used to explore the action mechanism of the key factors. RESULTS: Overall, the level of public health service supply in Guangdong Province is on an upward trend. Among them, polarization and gradient effects are observed in the Pearl River Delta and Eastern Guangdong regions; the balance of public health service supply in Western Guangdong and Northern Mountainous areas has improved. During the observation period, the level of public health services in Guangdong Province shifted towards a higher level with a smaller probability of leapfrogging transition, and regions with a high level of supply demonstrated a positive spillover effect. The overall difference, intra-regional difference and inter-regional difference in the level of public health service supply in Guangdong Province during the observation period showed different evolutionary trends, and spatial differences still exist. These differences are more significantly positively affected by factors such as the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate. Under different economic development threshold values, the degree of fiscal decentralization and urbanization rate both have a double threshold effect on the role of public health service supply level. CONCLUSION: The overall level of public health service supply in Guangdong Province has improved, but spatial differences still exist. Key factors influencing these differences include the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate, all of which exhibit threshold effects. It is suggested that, in view of the actual situation of each region, efforts should be made to build and maintain their own advantages, enhance the spatial linkage of public health service supply, and consider the threshold effects of key factors in order to optimize the allocation of health resources.

Research on the Application of Dynamic Process Correlation Based on Radar Data in Mine Slope Sliding Early Warning.

With the gradual expansion of mining scale in open-pit coal mines, slope safety problems are increasingly diversified and complicated. In order to reduce the potential loss caused by slope sliding and reduce the major threat to the safety of life and property of residents in the mining area, this study selected two mining areas in Xinjiang as cases and focused on the relationship between phase noise and deformation. The study predicts the specific time point of slope sliding by analyzing the dynamic history correlation tangent angle between the two. Firstly, the time series data of the micro-variation monitoring radar are used to obtain the small deformation of the study area by differential InSAR (D-InSAR), and the phase noise is extracted from the radar echo in the sequence data. Then, the volume of the deformation body is calculated by analyzing the small deformation at each time point, and the standard deviation of the phase noise is calculated accordingly. Finally, the sliding time of the deformation body is predicted by combining the tangent angle of the ratio of the volume of the deformation body to the standard deviation of the phase noise. The results show that the maximum deformation rates of the deformation bodies in the studied mining areas reach 10.1 mm/h and 6.65 mm/h, respectively, and the maximum deformation volumes are 2,619,521.74 mm3 and 2,503,794.206 mm3, respectively. The predicted landslide time is earlier than the actual landslide time, which verifies the effectiveness of the proposed method. This prediction method can effectively identify the upcoming sliding events and the characteristics of the slope, provide more accurate and reliable prediction results for the slope monitoring staff, and significantly improve the efficiency of slope monitoring and early warning.

Stair-Fall Risk Parameters in a Controlled Gait Laboratory Environment and Real (Domestic) Houses: A Prospective Study in Faller and Non-Faller Groups.

BACKGROUND: Falling on stairs is a major health hazard for older people. Risk factors for stair falls have been identified, but these are mostly examined in controlled biomechanics/gait laboratory environments, on experimental stairs with a given set of step dimensions. It remains unknown whether the conclusions drawn from these controlled environments would apply to the negotiation of other domestic staircases with different dimensions in real houses where people live. OBJECTIVES: The aim of this paper is to investigate whether selected biomechanical stepping behavior determined through stair gait parameters such as foot clearance, foot contact length and cadence are maintained when the staircase dimensions are different in real houses. METHODS: Twenty-five older adults (>65 years) walked on a custom-made seven-step laboratory staircase. Older adults were classified into two groups (fallers and non-fallers) based on recent fall history. Among the 25 participants, 13 people had at least one fall, trip, or slip in the last six months and they were assigned to the fallers group; 12 people did not experience any fall in the last six months, so they were assigned to the non-fallers group. In addition, these participants walked on the stairs in three different real exemplar houses wearing a novel instrumented shoe sensor system that could measure the above stair gait parameters. MATLAB was used to extract fall risk parameters from the collected data. One-way ANOVA was used to compare fall risk parameters on the different staircases. In addition, the laboratory-based fall risk parameters were compared to those derived from the real house stairs. RESULTS: There was a significant difference in selected stair-fall biomechanical risk factors among the house and laboratory staircases. The fall risk group comparisons suggest that high-risk fallers implemented a biomechanically riskier strategy that could increase overall falling risk. CONCLUSIONS: The significant differences due to the main effects of the fallers and non-fallers groups were obtained. For example, when ascending, the fallers group had less foot clearance on the entry (p = 0.016) and middle steps (p = 0.003); in addition, they had more foot clearance variability on the entry steps (p = 0.003). This suggests that the fallers group in this present study did not adopt more conservative stepping strategies during stair ascent compared to low-risk older adults. By showing less foot clearance and more variability in foot clearance, the risk for a trip would be increased.

Wall Shear Stress (WSS) Analysis in Atherosclerosis in Partial Ligated Apolipoprotein E Knockout Mouse Model through Computational Fluid Dynamics (CFD).

Atherosclerosis involves an inflammatory response due to plaque formation within the arteries, which can lead to ischemic stroke and heart disease. It is one of the leading causes of death worldwide, with various contributing factors such as hyperlipidemia, hypertension, obesity, diabetes, and smoking. Wall shear stress (WSS) is also known as a contributing factor of the formation of atherosclerotic plaques. Since the causes of atherosclerosis cannot be attributed to a single factor, clearly understanding the mechanisms and causes of its occurrence is crucial for preventing the disease and developing effective treatment strategies. To better understand atherosclerosis and define the correlation between various contributing factors, computational fluid dynamics (CFD) analysis is primarily used. CFD simulates WSS, the frictional force caused by blood flow on the vessel wall with various hemodynamic changes. Using apolipoprotein E knockout (ApoE-KO) mice subjected to partial ligation and a high-fat diet at 1-week, 2-week, and 4-week intervals as an atherosclerosis model, CFD analysis was conducted along with the reconstruction of carotid artery blood flow via magnetic resonance imaging (MRI) and compared to the inflammatory factors and pathological staining. In this experiment, a comparative analysis of the effects of high WSS and low WSS was conducted by comparing the standard deviation of time-averaged wall shear stress (TAWSS) at each point within the vessel wall. As a novel approach, the standard deviation of TAWSS within the vessel was analyzed with the staining results and pathological features. Since the onset of atherosclerosis cannot be explained by a single factor, the aim was to find the correlation between the thickness of atherosclerotic plaques and inflammatory factors through standard deviation analysis. As a result, the gap between low WSS and high WSS widened as the interval between weeks in the atherosclerosis mouse model increased. This finding not only linked the occurrence of atherosclerosis to WSS differences but also provided a connection to the causes of vulnerable plaques.

[Development of a carbamazepine determination method based on high-performance liquid chromatography with diode array]. / Razrabotka metodiki opredeleniya karbamazepina na osnove vysokoeffektivnoi zhidkostnoi khromatografii s diodno-matrichnym detektirovaniem.

Carbamazepine is used in the treatment of convulsive disorders, trigeminal neuralgia and mental illnesses such as bipolar disorder and pain syndromes. It has been found in clinical applications that carbamazepine causes many serious adverse drug reactions, which are associated with drug concentration in blood and dosage in clinical use. Due to its pharmacological properties, carbamazepine can be life-threatening in an overdosage, making the therapeutic drug control of carbamazepine important in any clinical settings. Creation of a method for carbamazepine quantification in biological objects during forensic chemical examinations is an urgent problem. A method of high-performance liquid chromatography with diode array detection is proposed for carbamazepine quantitation. The stability of proposed conditions for carbamazepine analysis has been proved in the modifying study conditions (flow rate of eluent, its composition, pH of buffer, column oven temperature). The relative standard deviation of retention time and areas of chromatographic peaks of carbamazepine did not exceed 0.5%.

Versatile recognition of graphene layers from optical images under controlled illumination through green channel correlation method.

In this study, a simple yet versatile method is proposed for identifying the number of exfoliated graphene layers transferred on an oxide substrate from optical images, utilizing a limited number of input images for training, paired with a more traditional number of a few thousand well-published Github images for testing and predicting. Two thresholding approaches, namely the standard deviation-based approach and the linear regression-based approach, were employed in this study. The method specifically leverages the red, green, and blue color channels of image pixels and creates a correlation between the green channel of the background and the green channel of the various layers of graphene. This method proves to be a feasible alternative to deep learning-based graphene recognition and traditional microscopic analysis. The proposed methodology performs well under conditions where the effect of surrounding light on the graphene-on-oxide sample is minimum and allows rapid identification of the various graphene layers. The study additionally addresses the functionality of the proposed methodology with nonhomogeneous lighting conditions, showcasing successful prediction of graphene layers from images that are lower in quality compared to typically published in literature. In all, the proposed methodology opens up the possibility for the non-destructive identification of graphene layers from optical images by utilizing a new and versatile method that is quick, inexpensive, and works well with fewer images that are not necessarily of high quality.

A Simple Approach to Determine Single-Receiver Differential Code Bias Using Precise Point Positioning.

In this study, a precise single-receiver differential code bias (DCB) estimation method using the precise point positioning (PPP) model is presented. The first step is to extract the high-precision ionospheric observations, including DCBs, based on the PPP model. Then, the satellite DCBs are corrected using International GNSS Service (IGS) products. Lastly, the algorithm for the minimization of the standard deviation of vertical total electron content (VTECmstd) is employed to determine the value of receiver DCB. To check the method, GNSS data from more than 200 IGS stations around the globe on four days with various geomagnetic and solar activity circumstances are processed. The receiver DCBs are compared to those obtained using previous carried-to-code level (CCL) models. The experimental results show that, compared to the CCL model, the values of VTECmstd for most stations are significantly reduced, the mean number of stations with negative ionospheric measurements is reduced by 40% after correcting the receiver DCBs, and the mean error of estimated receiver DCBs is reduced by approximately 0.6 ns using the PPP model. These results suggest that this method can provide more high-precision receiver DCB estimation.

Exploring the spatiotemporal pattern evolution of carbon emissions and air pollution in Chinese cities.

Based on data from 335 cities in China, this study employs the standard deviation ellipse method to portray unbalanced and differential spatiotemporal evolution patterns of environmental emissions and socioeconomic elements. A logarithmic mean Divisia index analysis and in-depth discussion are carried out to disclose the main driving factors and underlying reasons for the differences. Decoupling trends exist among carbon emissions, gross domestic product (GDP) and population in terms of their gravity center migrations. The standard deviation ellipse direction of carbon emissions gradually changed from 'northeast‒southwest' to 'northwest‒southeast', and the standard deviation ellipse areas of carbon emissions and air pollution continuously expanded over time; at the same time, that of GDP contracted. Economic growth has always been the main driver of carbon emissions and air pollution nationally, but its role has weakened. Moreover, decreases in the energy intensity and carbon and pollution intensities are the main factors contributing to emissions reductions. Differentiated spatiotemporal economic structure evolution, regional heterogeneities in the energy intensity and efficiency, and cross-region power energy transmissions are identified as the underlying reasons for the unbalanced spatiotemporal patterns of the environmental emissions and socioeconomic elements. Based on these findings, policy suggestions can be made to address the imbalances and promote carbon mitigation, air quality improvement and high-quality social-economic development at the city level.

Timing of Spheno-Occipital Synchondrosis Closure in Cleft Lip and Palate Patients in Iranian Population.

This study aimed to evaluate the chronological age range associated with each stage of spheno-occipital synchondrosis (SOS) fusion in patients with cleft lip and palate compared to the noncleft group, using cone-beam computed tomography (CBCT) images.In this study, the degree of SOS fusion was assessed using a 4-stage scoring system on CBCT images of 190 individuals (92 patients with cleft lip and palate, 98 noncleft individuals). A χ2 test was performed to assess the correlation between age and fusion stage. The independent sample t tests were used to evaluate the differences in the mean values of the samples of each group and each sex, as well as the mean value of each stage (P < .05).The results showed that there was no significant difference in the timing of the SOS fusion stages between the patients with cleft palate and the noncleft group. Although the fusion process of SOS begins about one year earlier in females, the complete ossification occurs at the mean age of 18.5 for both sexes in the experimental group and the mean age of 19.0 in the noncleft group.The present study found no differences in the fusion stages of the spheno-occipital synchondrosis between patients with cleft lip and palate and healthy individuals.

Variance in the macular sublayers' volume as a diagnostic tool for primary open-angle glaucoma.

PURPOSE: To assess the variance of macular sublayers' volume in glaucoma patients compared with normal individuals. METHODS: This case-control observational study included 63 cases of primary open-angle glaucoma and 57 healthy controls. Macular volumetric scans were captured at the 6 mm ETDRS circle for each retinal sublayer using Spectralis OCT2. The studied macular sublayers included the retinal nerve fiber layer, ganglion cell layer, inner plexiform layer, inner nuclear layer, outer plexiform layer, outer nuclear layer, and outer retinal layers (external limiting membrane to the retinal pigment epithelium). Standard deviation (SD) and coefficient of variation (CoV) of macular sublayers' volume were calculated. An unpaired Student t test (or its nonparametric equivalent) was used to compare each variable between groups. The receiver operating characteristic curve (ROC) was used to investigate the discriminative ability of each parameter. RESULTS: There was no significant difference for age or sex between the groups. The SD (of all sublayers' volume) was greater in the glaucomatous eyes compared with controls (0.620 ± 0.073vs.0.524 ± 0.056  mm3, respectively; P < 0.001). The same pattern was observed for CoV (7.890 ± 0.979vs.6.128 ± 0.583; P < 0.001). The area under curves (AUCs) for SD and CoV were 0.855and0.930, respectively (P = 0.05). The best cutoff value for the CoV was 6.712. The CoV and ganglion cell layer (GCL) volume revealed similar sensitivity (80.75) at 95% specificity for diagnosing glaucoma. The CoV detected 5 patients with glaucoma who had normal GCC volume. CONCLUSION: This study showed that the macular sublayers' volume variance parameters could be viable OCT biomarkers for detecting glaucomatous changes.

Transformation of Sequential Hospital and Outpatient Laboratory Data into Between-Day Reference Change Values.

BACKGROUND: Serial differences between intrapatient consecutive measurements can be transformed into Taylor series of variation vs time with the intersection at time = 0 (y0) equal to the total variation (analytical + biological + preanalytical). With small preanalytical variation, y0, expressed as a percentage of the mean, is equal to the variable component of the reference change value (RCV) calculation: (CVA2 + CVI2)1/2. METHODS: We determined the between-day RCV of patient data for 17 analytes and compared them to healthy participants' RCVs. We analyzed 653 consecutive days of Dartmouth-Hitchcock Roche Modular general chemistry data (4.2 million results: 60% inpatient, 40% outpatient). The serial patient values of 17 analytes were transformed into 95% 2-sided RCV (RCVAlternate), and 3 sets of RCVhealthy were calculated from 3 Roche Modular analyzers' quality control summaries and CVI derived from biological variation (BV) studies using healthy participants. RESULTS: The RCVAlternate values are similar to RCVhealthy derived from known components of variation. For sodium, chloride, bicarbonate calcium, magnesium, phosphate, alanine aminotransferase, albumin, and total protein, the RCVs are equivalent. As expected, increased variation was found for glucose, aspartate aminotransferase, creatinine, and potassium. Direct bilirubin and urea demonstrated lower variation. CONCLUSIONS: Our RCVAlternate values integrate known and unknown components of analytic, biologic, and preanalytic variation, and depict the variations observed by clinical teams that make medical decisions based on the test values. The RCVAlternate values are similar to the RCVhealthy values derived from known components of variation and suggest further studies to better understand the results being generated on actual patients tested in typical laboratory environments.

Estimating the population variance, standard deviation, and coefficient of variation: Sample size and accuracy.

Small sample sizes are often used in human and primate evolutionary research to estimate population parameters such as the mean, variance, and standard deviation, as well as statistical measures such as the coefficient of variation. Determining how well sample estimates represent population parameters is essential for establishing confidence in the inferences made using those samples. We present methods for determining a priori the probability, based on Cochran's theorem, that the sample variance and sample standard deviation are within a specified fraction of the population parameters. We validate these methods using random resampling with replacement of a single variable from a commonly used large craniometric data set comprising modern human population samples from around the world. Results based on Cochran's theorem, which we validate, indicate that large random samples comprising hundreds of observations, rather than tens of observations, are needed to be confident that the sample estimate is a reasonably accurate approximation of the true population variance. Smaller sample sizes on the order of tens of observations, however, are sufficient for estimating the population standard deviation. We extend our method of validation to show that the coefficient of variation mirrors closely the results for the standard deviation.

Host diversity positively affects the temporal stability of foliar fungal diseases in a Tibetan alpine meadow.

BACKGROUND AND AIMS: Plant disease can dramatically affect population dynamics, community composition and ecosystem functions. However, most empirical studies focus on diseases at a certain time point and largely ignore their temporal stability, which directly affects our ability to predict when and where disease outbreaks will occur. METHODS: Using a removal experiment that manipulates plant diversity (i.e. a plant biodiversity and ecosystem function experiment) and a fertilization experiment in a Tibetan alpine meadow, we investigated how different plant biodiversity indices and nitrogen fertilization affect the temporal stability of foliar fungal diseases (measured as the mean value of community pathogen load divided by its standard deviation) over seven consecutive years. KEY RESULTS: We found that the temporal stability of foliar fungal diseases increased with plant diversity indices in the plant biodiversity and ecosystem function experiment. Meanwhile, we observed a weakly positive relationship between host diversity and temporal stability in the fertilization experiment. However, the nitrogen treatment did not affect temporal stability, given that fertilization increased both the mean and standard deviation of pathogen load by roughly the same magnitude. CONCLUSIONS: We conclude that host diversity regulates the temporal stability of pathogen load, but we note that this effect may be attenuated under rapid biodiversity loss in the Anthropocene.

Estimation of standard deviations and inverse-variance weights from an observed range.

A variety of methods have been proposed to estimate a standard deviation, when only a sample range has been observed or reported. This problem occurs in the interpretation of individual clinical studies that are incompletely reported, and also in their incorporation into meta-analyses. The methods differ with respect to their focus being either on the standard deviation in the underlying population or on the particular sample in hand, a distinction that has not been widely recognized. In this article, we contrast and compare various estimators of these two quantities with respect to bias and mean squared error, for normally distributed data. We show that unbiased estimators are available for either quantity, and recommend our preferred methods. We also propose a Taylor series method to obtain inverse-variance weights, for samples where only the sample range is available; this method yields very little bias, even for quite small samples. In contrast, the naïve approach of simply taking the inverse of an estimated variance is shown to be substantially biased, and can place unduly large weight on small samples, such as small clinical trials in a meta-analysis. Accordingly, this naïve (but commonly used) method is not recommended.