New decoding scheme for LDPC codes based on simple product code structure

In this paper, a new decoding scheme for low-density parity-check (LDPC) codes using the concept of simple product code structure is proposed based on combining two independently received soft-decision data for the same codeword. LDPC codes act as horizontal codes of the product codes and simple algebraic codes are used as vertical codes to help decoding of the LDPC codes. The decoding capability of the proposed decoding scheme is defined and analyzed using the paritycheck matrices of vertical codes and especially the combined-decodability is derived for the case of single parity-check (SPC) and Hamming codes being used as vertical codes. It is also shown that the proposed decoding scheme achieves much better error-correcting capability in high signal to noise ratio (SNR) region with low additional decoding complexity, compared with a conventional decoding scheme.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Iterative DNA Coding Scheme With GC Balance and Run-Length Constraints Using a Greedy Algorithm

In this paper, we propose a novel iterative encoding algorithm for DNA storage to satisfy both the GC balance and run-length constraints using a greedy algorithm. DNA strands with run-length more than three and the GC balance ratio far from 50\% are known to be prone to errors. The proposed encoding algorithm stores data at high information density with high flexibility of run-length at most $m$ and GC balance between $0.5\pm\alpha$ for arbitrary $m$ and $\alpha$. More importantly, we propose a novel mapping method to reduce the average bit error compared to the randomly generated mapping method, using a greedy algorithm. The proposed algorithm is implemented through iterative encoding, consisting of three main steps: randomization, M-ary mapping, and verification. It has an information density of 1.8616 bits/nt in the case of $m=3$, which approaches the theoretical upper bound of 1.98 bits/nt, while satisfying two constraints. Also, the average bit error caused by the one nt error is 2.3455 bits, which is reduced by $20.5\%$, compared to the randomized mapping.Comment: 19 page

Benign metastasizing leiomyoma of the lung

Benign leiomyomas of the uterus are uncommonly found in association with benign smooth muscle tumors beyond the confines of the uterus. Benign metastasizing leiomyoma (BML) is a rare disease in which the lung is described to be the most afflicted extrauterine organ. We present a brief review of the literature, along with case reports for four patients who were followed up after resection of a pulmonary lesion or after pathological confirmation by biopsy. The clinical course of BML varies from chronic asymptomatic appearance to rapid progression, leading to respiratory failure and death. Our BML patients did not complain of pulmonary symptoms, such as cough, dyspnea, or chest tightness. Pathology revealed benign leiomyomas with no atypia and mitotic activity <5 per 10 high-power field. Immunohistochemical staining was positive for actin and desmin. A standard treatment for BML has not yet been established. Because of the hormone-sensitive characteristics of BML, treatments are based on hormonal manipulation along with either surgical or medical oophorectomy. Benign metastasizing leiomyoma can be observed in postmenopausal women. We observed four patients who did not receive adjuvant hormonal therapy because they were postmenopausal or perimenopausal. All patients are still healthy and show no evidence of recurrence or progression of the disease

Non-negligible Occurrence of Errors in Gender Description in Public Data Sets

Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public datasets, we observed that errors in gender information occur quite often in public datasets. When we analyzed the gender description and the methylation patterns of gender-specific probes (glucose-6-phosphate dehydrogenase [G6PD], ephrin-B1 [EFNB1], and testis specific protein, Y-linked 2 [TSPY2]) in 5,611 samples produced using Infinium 450K HumanMethylation arrays, we found that 19 samples from 7 datasets were erroneously described. We also analyzed 1,819 samples produced using the Affymetrix U133Plus2 array using several gender-specific genes (X (inactive)-specific transcript [XIST], eukaryotic translation initiation factor 1A, Y-linked [EIF1AY], and DEAD [Asp-Glu-Ala-Asp] box polypeptide 3, Y-linked [DDDX3Y]) and found that 40 samples from 3 datasets were erroneously described. We suggest that the users of public datasets should not expect that the data are error-free and, whenever possible, that they should check the consistency of the data