Introduction We aimed to establish a standardized, routine‐use pre‐analytical protocol for measuring Alzheimer's disease (AD) biomarkers in cerebrospinal fluid (CSF). Methods The effect of pre‐analytical factors (sample collection/handling/storage/transportation) on biomarker levels was assessed using freshly collected CSF. Tube type/sterilization was assessed using previously frozen samples. A low‐bind false‐bottom tube (FBT, Sarstedt) was used for all experiments, except tube types/sterilization experiments. Biomarkers were measured using Elecsys CSF assays. Results Amyloid beta (Aβ) 1‐42 levels varied by tube type, using a low‐bind FBT reduced variation. Aβ 1‐42 levels were higher with no mixing versus roller/inversion mixing. Aβ 1‐42 levels were lower with horizontal versus upright transportation; this was resolved by maximal tube filling and storage at 2°C to 8°C. Aβ 1‐40 levels were less strongly affected. Phospho‐tau and total‐tau levels were largely unaffected. Discussion We propose an easy‐to‐use, standardized, routine‐use pre‐analytical protocol, using low‐bind FBTs, for measuring AD CSF biomarkers in clinical practice.

Compositional data analysis refers to analyzing relative information, based on ratios between the variables in a data set. Data from epidemiology are usually treated as absolute information in an analysis. We outline the differences in both approaches for univariate and multivariate statistical analyses, using illustrative data sets from Austrian districts. Not only the results of the analyses can differ, but in particular the interpretation differs. It is demonstrated that the compositional data analysis approach leads to new and interesting insights.

Compositional data analysis deals with situations where the relevant information is contained only in the ratios between the measured variables, and not in the reported values. This article focuses on high-dimensional compositional data (in the sense of hundreds or even thousands of variables), as they appear in chemometrics (e.g., mass spectral data), proteomics or genomics. The goal of this contribution is to perform a dimension reduction of such data, where the new directions should allow for interpretability. An approach named principal balances turned out to be successful for low dimensions. Here, the concept of sparse principal component analysis is proposed for constructing principal directions, the so-called sparse principal balances. They are sparse (contain many zeros), build an orthonormal basis in the sample space of the compositional data, are efficient for dimension reduction and are applicable to high-dimensional data.

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Rhabdomyomatous mesenchymal hamartoma is a rare dermal lesion which was first described in 1986 as "striated muscle hamartoma". It usually develops in the head and neck region of newborns. We report a 38-day-old girl with a congenital skin tag in the perianal region. Physical examination did not reveal any congenital abnormalities or other dermal lesions. Histopathological examination showed a hamartoma with disorganized skeletal muscle fibers. The differential diagnosis includes skin tag, accessory tragus and soft fibroma. Rhabdomyomatous mesenchymal hamartoma differs from the listed lesions with its striated muscle component. Since it does not carry the risk of recurrence and malignant transformation, it is not very important to distinguish it from these lesions. However, a correct diagnosis is important because approximately one third of the cases are associated with congenital anomalies. Also, histopathological diagnosis should be made in children with perianal localization due to similar clinical manifestation of rhabdomyosarcoma.

The previously proposed bitwise retransmission schemes which retransmit only selected bits to accumulate their reliability are designed and evaluated. Unlike conventional automatic repeat request (ARQ) schemes, the bitwise retransmission schemes do not require a checksum for error detection. The bitwise retransmission decisions and combining can be performed either after demodulation of the received symbols or after channel decoding. The design and analysis assume error-free feedback, however, the impact of feedback errors is also considered. The bit-error rate (BER) expressions are derived and verified by computer simulations in order to optimize the parameters of the retransmission schemes. The BER performance of coded and uncoded bitwise retransmissions is compared with a hybrid ARQ (HARQ) scheme over additive white Gaussian noise (AWGN), slow fading, and fast fading channels. It is shown that bitwise retransmissions outperform block repetition coding (BRC) over AWGN channels. In addition, the selection diversity created by the bitwise retransmissions can outperform the HARQ at large signal-to-noise ratio (SNR) over fast fading channels. Finally, the practical design of a bitwise retransmission protocol for data fusion in wireless sensor networks is presented assuming Zigbee, WiFi and Bluetooth system parameters.

Compositional data, as they typically appear in geochemistry in terms of concentrations of chemical elements in soil samples, need to be expressed in log-ratio coordinates before applying the traditional statistical tools if the relative structure of the data is of primary interest. There are different possibilities for this purpose, like centered log-ratio coefficients, or isometric log-ratio coordinates. In both the approaches, geometric means of the compositional parts are involved, and it is unclear how measurement errors or detection limit problems affect their presentation in coordinates. This problem is investigated theoretically by making use of the theory of error propagation. Due to certain limitations of this approach, the effect of error propagation is also studied by means of simulations. This allows to provide recommendations for practitioners on the amount of error and on the expected distortion of the results, depending on the purpose of the analysis.

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