The Cultural-Historical Development of Mental Processes and the Theory of Stepwise Formation of Mental Actions and Concepts

The article examines the problem of the relationship between universal and specific forms of cultural–historical development of mental processes. From different methodological approaches, the author prefers an activity approach which emphasizes genetic primacy of external practical activity. This approach allows, according to the author, universality of internalization and at the same time ethnic uniqueness of mental processes. The article clarifies the problem of internalization through two practical examples: 1) the development of mental counting actions and 2) the process of human goal setting.     

Improved two‐stage group sequential procedures for testing a secondary endpoint after the primary endpoint achieves significance

In two‐stage group sequential trials with a primary and a secondary endpoint, the overall type I error rate for the primary endpoint is often controlled by an α‐level boundary, such as an O'Brien‐Fleming or Pocock boundary. Following a hierarchical testing sequence, the secondary endpoint is tested only if the primary endpoint achieves statistical significance either at an interim analysis or at the final analysis. To control the type I error rate for the secondary endpoint, this is tested using a Bonferroni procedure or any α‐level group sequential method. In comparison with marginal testing, there is an overall power loss for the test of the secondary endpoint since a claim of a positive result depends on the significance of the primary endpoint in the hierarchical testing sequence. We propose two group sequential testing procedures with improved secondary power: the improved Bonferroni procedure and the improved Pocock procedure. The proposed procedures use the correlation between the interim and final statistics for the secondary endpoint while applying graphical approaches to transfer the significance level from the primary endpoint to the secondary endpoint. The procedures control the familywise error rate (FWER) strongly by construction and this is confirmed via simulation. We also compare the proposed procedures with other commonly used group sequential procedures in terms of control of the FWER and the power of rejecting the secondary hypothesis. An example is provided to illustrate the procedures.     

The dynamics of experimental arable weed communities under different management practices

Abstract. Weed communities, comprising 12 introduced species at constant starting densities and three species already present in the seed bank, were followed through three years of continuous winter wheat. The wheat and weeds were subjected to two treatments in a split-plot factorial design, organic contrasting with conventional fertilizer, and ploughing plus hand-roguing contrasting with minimum tillage plus herbicide. The minimum tilled plots developed in a uniform manner, and became dominated by very high densities of Anisantha sterilis. Agrostemma githago and Galium aparine also persisted in these plots at lower densities. The ploughed plots had a lower total density but a greater range of species. Stellaria media, Veronica persica and Avena fatua were the most common; other species occurred at lower densities. The major effect of fertilizer treatment was a greater initial increase by G. aparine on the organic, minimum tilled plots compared with the conventionally fertilized, minimum tilled plots. Species associated with minimum tillage were annuals with either no or a short term seed bank and autumn germination and rather predictable dynamics, whereas species that did well under ploughing were either spring germinating or had a persistent seed bank, implying greater annual variation in population size associated with weather conditions. There seemed no clear way to distinguish between those species which were abundant on the ploughed plots and those which were scarce under all conditions using readily accessible data.     

The need and means to characterize sediment structure and behaviour prior to the selection and implementation of remediation plans

Remediation of contaminated sediments requires detailed characterizations of the speciation of the toxic substances and their transformations with regard to time and spatial distribution. While many approaches exist to address dissolved species of toxicants, there is a need to characterize sediments per se in terms of materials or particles which bind toxicants and modulate their bioavailability and rate of burial. Such specific information can be achieved through the correlative use of analytical microscopies, applied directly to native aquatic materials and used in conjunction with novel particle isolation methods and standard techniques of analytical chemistry. Such sedimentary `materials' are dominated by clays and other colloidal minerals, microorganisms, humic substances, organic debris, iron and manganese oxide coatings and extracellular polymeric substances. By using new technology to (1) identify particles and their relative abundances, (2) examine specific toxicant/particle associations at the scale of individual abundant particles, and (3) follow transformations over time, we produce information more insightful than was obtainable previously. Such knowledge will assist in determining which remediation technologies would be best for a given contaminated sediment (i.e. `intrinsic remediation' or dredging/disposal).     

Protistan microbial observatory in the Cariaco Basin,Caribbean. I. Pyrosequencing vs Sanger insights into species richness

Microbial diversity and distribution are topics of intensive research. In two companion papers in this issue, we describe the results of the Cariaco Microbial Observatory (Caribbean Sea, Venezuela). The Basin contains the largest body of marine anoxic water, and presents an opportunity to study protistan communities across biogeochemical gradients. In the first paper, we survey 18S ribosomal RNA (rRNA) gene sequence diversity using both Sanger- and pyrosequencing-based approaches, employing multiple PCR primers, and state-of-the-art statistical analyses to estimate microbial richness missed by the survey. Sampling the Basin at three stations, in two seasons, and at four depths with distinct biogeochemical regimes, we obtained the largest, and arguably the least biased collection of over 6000 nearly full-length protistan rRNA gene sequences from a given oceanographic regime to date, and over 80 000 pyrosequencing tags. These represent all major and many minor protistan taxa, at frequencies globally similar between the two sequence collections. This large data set provided, via the recently developed parametric modeling, the first statistically sound prediction of the total size of protistan richness in a large and varied environment, such as the Cariaco Basin: over 36 000 species, defined as almost full-length 18S rRNA gene sequence clusters sharing over 99% sequence homology. This richness is a small fraction of the grand total of known protists (over 100 000–500 000 species), suggesting a degree of protistan endemism.     

A new entry into the portfolio of α-glucosidase inhibitors as potent therapeutics for type 2 diabetes: Design,bioevaluation and one-pot multi-component synthesis of diamine-bridged coumarinyl oxadiazole conjugates

Diabetes mellitus (DM), a chronic multifarious metabolic disorder resulting from impaired glucose homeostasis has become one of the most challenging diseases with severe life threat to public health. The inhibition of α-glucosidase, a key carbohydrate hydrolyzing enzyme, could serve as one of the effective methodology in both preventing and treating diabetes through controlling the postprandial glucose levels and suppressing postprandial hyperglycemia. In this context, three series of diamine-bridged bis-coumarinyl oxadiazole conjugates were designed and synthesized by one-pot multi-component methodology. The synthesized conjugates (4a–j, 5a–j, 6a–j) were evaluated as potential inhibitors of glucosidases. Compound 6f containing 4,4′-oxydianiline linker was identified as the lead and selective inhibitor of α-glucosidase enzyme with an IC₅₀ value of 0.07 ± 0.001 μM (acarbose: IC₅₀ = 38.2 ± 0.12 μM). This inhibition efficacy was ∼545-fold higher compared to the standard drug. Compound 6f was also emerged as the lead molecule against intestinal maltase-glucoamylase with good inhibition strength (IC₅₀ = 0.04 ± 0.02 μM) compared to acarbose (IC₅₀ = 0.06 ± 0.01 μM). Against β-glucosidase enzyme, compound 6 g was noted as the lead inhibitor with IC₅₀ value of 0.08 ± 0.002 μM. Michaelis–Menten kinetic experiments were performed to explore the mechanism of inhibition. Molecular docking studies of the synthesized library of hybrid structures against glucosidase enzyme were performed to describe ligand-protein interactions at molecular level that provided an insight into the biological properties of the analyzed compounds. The results suggested that the inhibitors could be stabilized in the active site through the formation of multiple interactions with catalytic residues in a cooperative fashion. In addition, strong binding interactions of the compounds with the amino acid residues were effective for the successful identification of α-glucosidase inhibitors.     

“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.     

Polyphasic characterization of Delftia acidovorans ESM-1, a facultative methylotrophic bacterium isolated from rhizosphere of Eruca sativa

In this study, one bacterial strain, ESM-1, was isolated from rhizosphere of Eruca sativa, growing in Al Hofouf, Saudia Arabia, after enrichment with methanol as a sole carbon and energy source in a batch culture. ESM-1 was characterized by a polyphasic approach. The strain was identified as Delftia acidovorans at similarity level of 99.9% of the 16S rRNA gene sequences. Results of the Biolog Gen III MicroPlate test system showed that strain ESM-1 reacted positively to 47 (50%) including the one-carbon compound formic acid, and partially positive to 6 (∼6.4%) out of the 94 different the traits examined. The total cellular fatty acids composition of the strain ESM-1 was (C_16:1ω7c/C_16:1ω6c) and C_16:0) and matched that of Delftia acidovorans at a similarity index of 0.9, providing a robustness to the ESM-1 identification. Furthermore, ESM-1 displayed a complex polar lipid profile consisting of phosphatidylethanolamine, phosphatidylglycerol, glycolipid, aminolipid, in addition to uncharacterized lipids. The DNA G+C content of the strain was 66.6 mol%. Phylogenetic analyses based on 16S rRNA gene sequences showed that the strain ESM1-1 was clearly clustered within the Delftia clade and constructed a monophyletic subcluster with Delftia acidovorans NBRC14950. The results addressed that ESM-1 is a facultative methylotrophic bacterium indigenous to Al Hofouf region and opens the door for potential biotechnological applications (e.g., bioremediation) of this strain, in future. Additionally, these findings assure that the total cellular fatty acid analysis and 16S rRNA gene are reliable tool for bacterial characterization and identification.     

Quality control of Utermöhl-based phytoplankton counting and biovolume estimates—an easy task or a Gordian knot?

The most suitable way for standardizing biovolume based assemblage analysis using the Utermöhl technique for counting combined with biomass conversion has not yet been found even though this method has been successfully used in plankton studies for many years. Due to the complexity of the approach easily applicable steps to initially meet primary standard end point or target counts for intra-laboratory standardization tested here seem promising. Examples from count validation and biometric data from the large datasets of three laboratories are given. The first two examples initially intended to quantify the taxon specific scatter of counts by (A) using identical replica of field samples combined with a half-chamber count (scan of every second transect) and the 30 random field approach, respectively, and (B) the replication of transect counts in one sample. Both examples identified relatively low minimum count thresholds to delimit counting errors for single cell counts. The third example identifies shape variability and allometric relationships of the main axes and shows a way to improve taxon specific biomass estimates with special reference to cell thickness. However improved precision of quantitative phytoplankton analysis requires optimization of combined counting strategy and biovolume assessment methods.