Understanding nitrogen recovery from wastewater with a high nitrogen concentration using microbial electrolysis cells.

This study was aimed at understanding the effect of applied voltage, catholyte and reactor scale on nitrogen recovery from two different organic wastes (digestate and pig slurry) by means of microbial electrolysis cell (MEC) technology. For this purpose, MEC sizes of 100, 500 and 1000 mL were tested at applied voltages of 0.6, 1 and 1.4 V using either a phosphate-buffered solution or NaCl solution as the catholyte. By increasing the reactor size from 500 to 1000 mL, a decrease in the ammonia recovery efficiency from 47 to 42% was observed. The results also showed that the phosphate-buffered solution is preferable as the catholyte and that the voltage applied does not have a noticeable effect on current production and ammonia recovery. Low biodegradability of the wastes was identified as the main bottleneck.

Efficient Implementation of a Symbol Timing Estimator for Broadband PLC.

Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA.

Targeting PDGF signaling of cancer-associated fibroblasts blocks feedback activation of HIF-1α and tumor progression of clear cell ovarian cancer.

Ovarian clear cell carcinoma (OCCC) is a gynecological cancer with a dismal prognosis; however, the mechanism underlying OCCC chemoresistance is not well understood. To explore the intracellular networks associated with the chemoresistance, we analyze surgical specimens by performing integrative analyses that combine single-cell analyses and spatial transcriptomics. We find that a chemoresistant OCCC subpopulation with elevated HIF activity localizes mainly in areas populated by cancer-associated fibroblasts (CAFs) with a myofibroblastic phenotype, which is corroborated by quantitative immunostaining. CAF-enhanced chemoresistance and HIF-1α induction are recapitulated in co-culture assays, which show that cancer-derived platelet-derived growth factor (PDGF) contributes to the chemoresistance and HIF-1α induction via PDGF receptor signaling in CAFs. Ripretinib is identified as an effective receptor tyrosine kinase inhibitor against CAF survival. In the co-culture system and xenograft tumors, ripretinib prevents CAF survival and suppresses OCCC proliferation in the presence of carboplatin, indicating that combination of conventional chemotherapy and CAF-targeted agents is effective against OCCC.

Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes.

Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data.

Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we develop a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After evaluating its sensitivity and precision, we apply it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,049 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extract 3,000 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The in-silico screening framework demonstrates the possibility of near-automatically acquiring medical knowledge, making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB ( https://iravdb.io/ ).

Whole genome sequencing analysis identifies recurrent structural alterations in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is the predominant type of esophageal cancer in the Asian region, including Japan. A previous study reported mutational landscape of Japanese ESCCs by using exome sequencing. However, somatic structural alterations were yet to be explored. To provide a comprehensive mutational landscape, we performed whole genome sequencing (WGS) analysis of biopsy specimens from 20 ESCC patients in a Japanese population. WGS analysis identified non-silent coding mutations of TP53, ZNF750 and FAT1 in ESCC. We detected six mutational signatures in ESCC, one of which showed significant association with smoking status. Recurrent structural variations, many of which were chromosomal deletions, affected genes such as LRP1B, TTC28, CSMD1, PDE4D, SDK1 and WWOX in 25%-30% of tumors. Somatic copy number amplifications at 11q13.3 (CCND1), 3q26.33 (TP63/SOX2), and 8p11.23 (FGFR1) and deletions at 9p21.3 (CDKN2A) were identified. Overall, these multi-dimensional view of genomic alterations improve the understanding of the ESCC development at molecular level and provides future prognosis and therapeutic implications for ESCC in Japan.

A new beamforming method and hardware architecture for real time two way dynamic depth focusing.

The Total Focusing Method (TFM) yields a focused image in emission and in reception while Phased Array (PA) imaging provides Dynamic Depth Focusing (DDF) in reception only. Besides, most NDE applications have two propagation media, where refraction at the interface complicates time-of-flight (TOF) and focal law computations. This affects especially TFM, which must compute the TOFs from all elements to image pixels and use them to select the data for imaging. A new method with real-time Dynamic Depth Full Focusing (DDFF), in emission and reception, is proposed in this work. It is called Total Focusing Phased Array (TFPA) because it uses concepts of TFM and PA. Omnidirectional emissions are used to create a synthetic aperture as in TFM, while beamforming is carried out along scan lines as in PA, simplifying the delay calculation in the presence of interfaces and providing an efficient hardware implementation. Refraction at the interface between two media is eliminated by a Virtual Array (VA) that converts such scenario into a simple homogeneous medium. Propagation can be considered along scan lines from the virtual array at constant speed, as in homogeneous media. Strict dynamic focusing is performed in real-time, an important difference with other approaches that require iterative Fermat search to get the focal laws for every imaged point. With TFPA only 3 parameters per element and scan line are required to perform this task. Experiments are carried out to compare the three techniques, PA, TFM and TFPA. TFM and TFPA yield similar image quality, offering improved depth of field and resolution over PA. On the other hand, TFPA avoids most of the burden for computing TOFs and operates in real time with one or two media propagation.

Genomic analysis of pancreatic juice DNA assesses malignant risk of intraductal papillary mucinous neoplasm of pancreas.

Intraductal papillary mucinous neoplasm (IPMN) of pancreas has a high risk to develop into invasive cancer or co-occur with malignant lesion. Therefore, it is important to assess its malignant risk by less-invasive approach. Pancreatic juice cell-free DNA (PJD) would be an ideal material in this purpose, but genetic biomarkers for predicting malignant risk from PJD are not yet established. We here performed deep exome sequencing analysis of PJD from 39 IPMN patients with or without malignant lesion. Somatic alterations and copy number alterations (CNAs) detected in PJD were compared with the histologic grade of IPMN to evaluate their potential as a malignancy marker. Somatic mutations of KRAS, GNAS, TP53, and RNF43 were commonly detected in PJD of IPMNs, but no association with the histologic grades of IPMN was found. Instead, mutation burden was positively correlated with the histologic grade (r = 0.427, P = 0.015). We also observed frequent copy number deletions in 17p13 (TP53) and amplifications in 7q21 and 8q24 (MYC) in PJDs. The amplifications in 7q21 and 8q24 were positively correlated with the histologic grade and most prevalent in the cases of invasive carcinoma (P = 0.002 and 7/11; P = 0.011 and 6/11, respectively). We concluded that mutation burden and CNAs detected in PJD may have potential to assess the malignant progression risk of IPMNs.

Pilot-scale bioelectrochemical system for simultaneous nitrogen and carbon removal in urban wastewater treatment plants.

This study aims to characterize the performance of a 150 L bioelectrochemical system-based plant, during the simultaneous carbon and nitrogen removal from several waste streams of wastewater treatment plants. The bioelectrochemical system (BES) contained five electrode pairs (operated hydraulically and electrically in parallel) and was fed with either wastewater, centrate (nutrient-rich liquid stream produced during the dewatering of digested biomass), or a mixture of both over 63 days, with a hydraulic retention time of one day. Total organic carbon and total nitrogen removal rates averaged 80% and 70%, respectively, with a specific energy consumption of 0.18 kWh·m-3 (BES + ancillary equipment). This work also underlines the challenges of using BES for nitrogen removal, highlighting the limitations of the current design, and suggesting some strategies for improvement.

Impact of the start-up process on the microbial communities in biocathodes for electrosynthesis.

This study seeks to understand how the bacterial communities that develop on biocathodes are influenced by inocula diversity and electrode potential during start-up. Two different inocula are used: one from a highly diverse environment (river mud) and the other from a low diverse milieu (anaerobic digestion). In addition, both inocula were subjected to two different polarising voltages: oxidative (+0.2 V vs. Ag/AgCl) and reductive (-0.8 V vs. Ag/AgCl). Bacterial communities were analysed by means of high throughput sequencing. Possible syntrophic interactions and competitions between archaea and eubacteria were described together with a discussion of their potential role in product formation and current production. The results confirmed that reductive potentials lead to an inconsistent start-up procedure regardless of the inoculum used. However, imposing oxidative potentials help to quickly develop an electroactive biofilm ready to withstand reductive potentials (i.e. biocathodic operation). The microbial structure that finally developed on them was highly dependent on the raw community present in the inoculum. Using a non-specialised inoculum resulted in a highly specialised biofilm, which was accompanied by an improved performance in terms of consumed current and product generation. Interestingly, a much more specialised inoculum promoted a rediversification in the biofilm, with a lower general cell performance.

Genomic landscape of colitis-associated cancer indicates the impact of chronic inflammation and its stratification by mutations in the Wnt signaling.

Inflammatory bowel disease (IBD) increases the risk of colorectal cancer, known as colitis-associated cancer (CAC). It is still unclear what driver mutations are caused by chronic inflammation and lead to CAC development. To get insight into this issue, we investigated somatic alterations in CAC. We performed exome sequencing of 22 fresh CACs and targeted sequencing of 43 genes on 90 archive specimens from Japanese CAC patients, of which 58 were ulcerative colitis (UC) and 32 were Crohn's disease (CD). Consistently with the previous reports, TP53 was commonly mutated (66%) whereas APC, KRAS and SMAD4 were mutated less frequently (16%, 11% and 11%, respectively). Mucinous CD-CACs in the anus, an Asian-specific subtype of CD-CAC, had less somatic mutations in our target genes. We also found that RNF43, a negative regulator of the Wnt signaling, was somatically mutated in a significant fraction of CACs (10 of 90; 11%). Two lines of evidence indicated that somatic mutations of RNF43 were related to chronic inflammation. First, somatic mutations of RNF43 were significantly associated with longer duration of IBD. Second, clinico-pathological features suggested many of the APC-mutated CACs were actually sporadic colorectal cancer whereas RNF43-mutated CACs did not have this tendency. RNA-Seq analysis showed that RNF43-mutated CACs had elevated expression of c-Myc and its target genes, suggesting that RNF43 is a bona fide driver of CAC development. This study provides evidence that somatic mutation of RNF43 is the driver genetic alteration that links chronic inflammation and cancer development in about 10% of CACs.

Methodology for Fast and Facile Characterisation of Carbon-Based Electrodes Focused on Bioelectrochemical Systems Development and Scale Up.

The development and practical implementation of bioelectrochemical systems (BES) requires an in-depth characterisation of their components. The electrodes, which are critical elements, are usually built from carbon-based materials due to their high specific surface area, biocompatibility and chemical stability. In this study, a simple methodology to electrochemically characterise carbon-based electrodes has been developed, derived from conventional electrochemical analyses. Combined with classical electrochemical theory and the more innovative fractal geometry approach, our method is aimed at comparing and characterising the performance of carbon electrodes through the determination of the electroactive surface and its fractal dimension. Overall, this methodology provides a quick and easy method for the screening of suitable electrode materials to be implemented in BES.