Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life, and limits their performance in activities of daily life. The realization of natural control for prosthetic hands is crucial to improving the quality of life of amputees. Surface electromyography (sEMG) signal is one of the most widely used biological signals for the prediction of upper limb motor intention, which is an essential element of the control systems of prosthetic hands. The conversion of sEMG signals into effective control signals often requires a lot of computational power and complex process. Existing commercial prosthetic hands can only provide natural control for very few active degrees of freedom. Deep learning (DL) has performed surprisingly well in the development of intelligent systems in recent years. The significant improvement of hardware equipment and the continuous emergence of large data sets of sEMG have also boosted the DL research in sEMG signal processing. DL can effectively improve the accuracy of sEMG pattern recognition and reduce the influence of interference factors. This paper analyzes the applicability and efficiency of DL in sEMG-based gesture recognition and reviews the key techniques of DL-based sEMG pattern recognition for the prosthetic hand, including signal acquisition, signal preprocessing, feature extraction, classification of patterns, post-processing, and performance evaluation. Finally, the current challenges and future prospects in clinical application of these techniques are outlined and discussed. For human, the worth of hand is indisputable. The hand is the most diverse and dexterous part of the human body, which can execute various activities to interact with the environment by adopting a variety of different motion strategies  and deep learning (DL). ML, which is the method based on feature engineering, could learn and perform tasks from the data input of automatic modeling. For conventional machine learning algorithms, there are limitations in processing raw data, because they could not effectively train on inconsistent, noisy, abstract, and high-dimensional data  we comprehensively analyze the overall structure of DL in sEMG-based gesture recognition; (2) we comprehensively review the latest methods and technologies of sEMG based gesture recognition; (3) we raise the existing challenges and promising research prospects of sEMG based on motion intention recognition in prosthetic hand field.The approaches of gesture recognition model are very similar, but the method of each stage is different; in addition, not all studies use all stages of standard structure. Considering this, we propose a standard approach composed of six parts, which are data acquisition, data preprocessing, feature extraction, classification of patterns, post-processing, and performance evaluation. The sEMG signals are collected from sEMG sensors, which could adopt two different acquisition criteria, sparse multi-channel sEMG and high-density sEMG (HD-sEMG), in the density of the employed electrodes of view  traditional manual feature extraction method is used to increase the data density of sparse multi-channel sEMG; (2) the raw sEMG signal is directly input into the network to realize end-to-end learning.For the traditional feature extraction methods, many researchers are devoted to propose new features based on professional knowledge , mean absolute values (MAV), integrated EMG (iEMG), histogram (HIST), root mean square (RMS), zero crossings (ZC), standard deviation (SD), slope sign change (SSC), Willison amplitude (WAMP), variance (VAR), V-order (V), simple square integral (SSI), and so on, which are often used in combination. The detailed information is shown in Frequency domain features: The FD features are calculated by Fourier transform of the autocorrelation function of sEMG signal and estimated by periodogram or parameter method. The common frequency domain characteristic of sEMG signal is frequency ratio (FR), total power (TP), mean power (MP), median frequency (MDF), mean frequency (MNF), power spectrum (PS), and so on. The detailed information is shown in Time-frequency domain features: The TFD features are expressed as locating the energy of sEMG signal both in time and frequency, which is usually an important approach in feature extraction. The typical representative of time-frequency analysis is wavelet transform  is the mother wavelet, and τ is the translation parameter. ni is the length of the ith level decomposition coefficient ci ; μ is the mean of ci , average power of the coefficient ci (APOCi), standard deviation of the coefficient ci (STDOCi), ratio between MOACi+1 and MOACi.where Parameter model: The basic principle of the parameter model is to regard it as a time series based on sequence information in the raw sEMG. Because sEMG signal is steady on short notice, the coefficients and intercept of the fourth-order autoregressive model are often selected as the characteristic values  is the most extensive applications for DL architecture based on sEMG gesture recognition. Park and Lee  proposedOne of the most important advantages of CNN is that it can automatically learn spatial features from input data or extract unlabeled features. However, the sEMG is the form of time series signal essentially, which is more suitable for recurrent neural network (RNN) that has dominant position in processing temporal or otherwise sequential information , whose goal is to recover the original data as lossless as possible from the abstract data; the other is probabilistic restricted Boltzmann machine (RBM) and its improved algorithm deep belief network (DBN), whose goal is to maximize the probability of the original data appearing when the RBM reaches a stable state. AE are data compression algorithm, which use efficient data encodings to map noisy input data into clean output Le, . VujakliApart from the above methods, there are many other DL methods applied to sEMG pattern recognition. Because of the simplicity of the structure, fully connected neural networks , skin conditions  , what amputee can do after training (which is a reflection of behavior in life and working environment) (de Vet et al., This review paper briefly introduces the advances of DL-based sEMG pattern recognition techniques for the prosthetic hand in recent years. Through the literature survey of DL application in sEMG recognition, some of the core techniques are highlighted, some of the most common challenges to be solved are analyzed, and some of the most possible development prospects are discussed. It could be found that gesture recognition techniques based on DL has great potential in using sEMG signal to accurately interpret amputee's motion intention, which is of great significance to the development of intelligent prosthetic hand. However, their individual difference, real-time usability, and long-term stability are still being highly limited by many complex factors in these approaches. The high variability of sEMG, the lack of existing data, the limitation of hardware resources, and the lack of clinical evaluation conditions seriously affect the progress of pattern recognition techniques based on DL. In addition, the natural movements of the upper limbs are independent, continuous, and proportional activations of multiple DOFs, while the existing techniques can only use a limited number of patterns for discrete classification. These should be well-improved in the future real-time application of prosthetic hands.WL and PS wrote this paper. PS and HY suggested the methodology. PS supervised the entire project. All authors reviewed the manuscript, read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: Transition metals play a crucial role in brain metabolism: since they exist in different oxidation states they are involved in ROS generation, but they are also co-factors of enzymes in cellular energy metabolism or oxidative defense. Methods: Paired serum and cerebrospinal fluid (CSF) samples were analyzed for iron, zinc, copper and manganese as well as for speciation using SEC-ICP-DRC-MS. Brain extracts from Mn-exposed rats were additionally analyzed with SEC-ICP-DRC-MS. Results: The concentration patterns of transition metal size fractions were correlated between serum and CSF: Total element concentrations were significantly lower in CSF. Fe-ferritin was decreased in CSF whereas a LMW Fe fraction was relatively increased. The 400–600 kDa Zn fraction and the Cu-ceruloplasmin fraction were decreased in CSF, by contrast the 40–80 kDa fraction, containing Cu- and Zn-albumin, relatively increased. For manganese, the α-2-macroglobulin fraction showed significantly lower concentration in CSF, whereas the citrate Mn fraction was enriched. Results from the rat brain extracts supported the findings from human paired serum and CSF samples. Conclusions: Transition metals are strictly controlled at neural barriers (NB) of neurologic healthy patients. High molecular weight species are down-concentrated along NB, however, the Mn-citrate fraction seems to be less controlled, which may be problematic under environmental load. The first-row transition metals iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu) can exist in multiple oxidation states and participate in electron transfer reactions that are fundamental to sustain life for all organisms that undertake oxidative metabolism. Approximately one-third of the human proteome is bound to metals ,2. UnlikEspecially the central nervous system (CNS) is sensitive to disturbances in trace element concentrations due to their extensive utilization in order to satisfy the high neuronal energy demand. Given the relatively narrow range between deficiency and toxicity, trace elements need to be tightly regulated to ensure optimal neuronal development and maintenance of healthy brain functions . Regulat2+ into redox-inactive Fe3+), selenoproteins  and redox-buffering metalloenzymes  and selenium-containing glutathione peroxidase (GPX) that break down superoxide anions and lipid peroxides [Importantly, small amounts of free and “labile” redox-active elements, such as chemically reduced Fe and Cu, are able to catalyze reactive oxygen species (ROS) via Fenton chemistry, generating hydrogen peroxides, hydroxyl radicals, and superoxide anions. At physiological relevant scales, ROS act as pleiotropic signaling molecules . Howeveeroxides ,17). Moreroxides ,19, whileroxides ,21, thusMn is also a redox-active element, but due to a higher reduction potential it is less prone to such redox chemistry compared to Fe and Cu. Importantly, Mn plays a key role in cellular adaption to OS, either through activating Mn-containing SOD enzymes and forming unbound free Mn-based antioxidants . Moreove2+ in biological systems. In total, 90% of the total brain Zn is protein-bound, associated with sulfur in cysteine residues allowing its rapid dissociation dependent on the cellular redox status. Protein-bound Zn essentially contributes to maintain redox balance by limiting OS by protecting thiol groups from oxidation and regulating glutathione metabolism [In sharp contrast to these redox-cycling trace elements, the highly abundant Zn metal has no direct redox capacity and always exists as bi-valent Zntabolism ,29. Onlytabolism ,29,30. Dtabolism ,32. (CSF/Serum) ratio reflecting the metal homeostasis across NB. Employing speciation analysis techniques to characterize element-carrying proteins and low molecular mass (LMM)-element species provide novel insights into metal neurochemistry and transport from blood to the CSF compartment and vice versa [Several studies have already investigated total element concentrations in CSF ,34, seruce versa ,41,42,43ce versa , mouse ace versa ,46, seruce versa ,48, as wce versa , thyroidce versa , CSF [51ce versa ,53 and pce versa ,41,42,54In this study, we utilize a SEC-ICP-DRC-MS approach to gain a deeper knowledge of Fe, Zn, Cu, and Mn and their relative abundancies in size fractions from 24 paired human serum/CSF samples and in previously published brain samples of Mn exposed rats ,56.(CSF/Serum) < 1, highlighting a selective and controlled permeation by NB to avoid excessive exposure to neuronal tissue [CSF is rigidly regulated by NB to ensure a stable environment for neuronal function. Furthermore, it provides a sink for the elimination of solutes from the brain interstitium . To charl tissue ,40 /C(serum))” ratio, where the target value for patients with age range applicable to our samples is < 6.5 × 10−3 [−3). Iron (Fe), the most enriched CSF metal, was drastically decreased across NB from 1220 ± 293 (serum) to 19 ± 6.7 µg/L (CSF) . Relativ3+ ions ,65. Para5 × 10−3 ,67, and Zinc (Zn), the second most abundant element in the CSF, was also decreased across NB from 704 ± 159 (serum) to 18 ± 6.9 µg/L (CSF) . RelativCopper (Cu) was significantly decreased across NB from 1380 ± 560 (serum) to 17 ± 2 µg/L (CSF) . Relativ3+ is known to use free binding sites at transferrin, competing with Fe3+ [Lastly, Manganese (Mn) was markedly depleted across NB from 1350 ± 311 (serum) to 500 ± 200 ng/L (CSF) . Relativith Fe3+ ,73,74. Lith Fe3+ , we idenith Fe3+ ,76.p = 0.0096; p = 0.0069; Next, we further determined the interdependency between all four elements in serum and CSF samples using Pearson’s correlation analysis. We demonstrated a positive correlation between “Fe vs. Mn”  . Althoug2+/Fe3+ towards Fe2+ in Mn-exposed rat and mouse brains compared to control animals [3+ and more free redox-active Fe2+ amount which generates neurotoxic ROS [Despite the low statistical power, the positive correlations of “Fe vs. Mn” and “Zn vs. Mn” in human CSF samples inspired us to re-analyze brain extracts from our previously published rat model of Mn exposure ,61. In b animals ,56. Nume animals ). IndeedIn contrast to Fe, we did not observe any significant changes in the distribution of Zn-containing protein fractions in Mn-exposed rat brains C. This c(CSF/Serum) ratios similar to those reported elsewhere [In this study, we analyzed 24 matched and paired CSF/serum samples for total concentrations and for speciation of four essential trance elements . We revealed that all metals were significantly down-concentrated in CSF compared to corresponding serum samples and demonstrated Qlsewhere . Using olsewhere ,80) and lsewhere . Our datThe study was performed in agreement with the ethical standards set in the Helsinki’s Declaration and its later amendments and was approved by the Ethics committee of the Technische Universität Munich (TUM) under ethics file number AZ 9/15 S. Study participants gave informed consent to the use of samples for scientific purpose. Serum and CSF sample pairs were drawn from 24 patients with unspecific neurological complaints, such as headache, dizziness and various sensory symptoms. CSF and serum samples were collected initially for our previous study  : 612 Da; glutathione  308 Da; Mn(II) (55 Da) = as inorganic MnCl2. TRIS, HNO3, HCl (suprapure), NH4-acetate (NH4Ac) and acetic acid (HAc), MnCl2 * 5 H2O and citrate were ordered from Merck, Darmstadt, Germany. HNO3 was purified by subboiling distillation. Argon (Ar)liqu and NH3 were purchased from Air-Liquide, Gröbenzell, Germany. An Ar vaporizer at the tank provided Ar gas. The TSKgel (230–450 mesh) for SEC separation was purchased from Merck, Darmstadt, Germany.Proteins, peptides, amino acids and elemental standards with different molecular masses were purchased from Merck-Sigma-Aldrich, Deisenhofen, Germany for mass calibration of the SEC column by retention time determination. These compounds were Blue dextran: 2000 kDa; iron-loaded ferritin: 900 kD; α-2-macroglobuline: 620 kD; α-globuline: 150 kD; ceruloplasmin 151 kDa; arginase: 107 kD; transferrin: 78 kD; albumin: 68.5 kDa; α-lactalbumin: 18 kDa; 2, FeCl2, CuCl2 and ZnCl2 were prepared by dissolving 100 mg/L . Mn-citrate stock solution was prepared by mixing a solution of 1 g/L citrate with a MnCl2 solution (5 mg/L) using a ratio of 4 + 1 (v + v), resulting in a Mn-citrate stock concentration of 1 mg Mn/L. Mn-albumin and Mn-transferrin stock solutions were prepared in analogy by mixing 1 g/L protein solution with 5 mg/L MnCl2 solution , resulting in 1 mg Mn/L for each compound. Stock solutions were aliquoted and stored in the dark at −20 °C. No destabilization of standard compounds was observed using these conditions. Working solutions were prepared daily by appropriate dilution with TRIS-HCl, 10 mM, pH 7.4. Single standards and the analysis of standard mixtures were used to achieve information on SEC retention times or migration times in CE separations. Stock solutions of MnCl4Ac was used as the eluent at a flow rate of 0.75 mL/min. In [TM software was applied.Size exclusion chromatography for species fractionation was chosen to avoid or minimize species changes during HPLC separation. SEC of Cu, Fe, Mn and Zn species from paired serum and CSF samples were performed by a hyphenated system consisting of a Knauer 1100 Smartline inert Series gradient HPLC system with an electronic sample injection valve with a 100 µL injection loop . Two serially installed SEC columns, a Biobasic 300 mesh column  was connected in front to a 550 × 10 mm ID Kronlab column filled with TSK-HW40S (separation range < 100–2000 Da). This column combination provided the necessary wide separation range, enabling the separation of various metalloprotein fractions from each other and from low-molecular weight metallo-compound fractions. Tris-HAc  + 250 mM NH/min. In , the elu/min. In . The mas4-Ac was used. The retention times (RT) were determined by peak maxima in UV and for metalloproteins additionally by ICP-MS detection. Retention times followed two calibration curves for the two columns: from 27  to 47 min (~5 kDa) according to the equation “ln(kDa) = −0.0716 * RT + 5.0939 (r2 = 0.9992) and from 48 (>2 kDa) to 60 min  according to the equation “ln(kDa) = −0.2387 * RT +12.59 (r2 = 0.9993). Peak fractions from samples were assigned to molecular masses calculated due to the above equations.The mass calibration in the serially connected columns was performed using proteins and LMM standards with known molecular weight. As mobile phase TRIS-HCl 10 mM, pH 7.4 + 250 mM NH55Mn, 57Fe, 63Cu and 66Zn in the time-resolved mode. For SEC coupling the column effluent was passing the UV detector and then was directed to a Meinhard nebulizer (which was mounted to a cyclone spray chamber) using a PEEK transfer tube (ID 100 µm). The RF power was set to 1250 W, the plasma gas was 15 L Ar/min. The nebulizer gas was optimized and finally set to 0.98 (Meinhard) or 1.02 (Micromist) mL Ar/min. The dwell time was 500 ms. The dynamic reaction cell (DRC) was operated using NH3 as DRC gas, finally at a flow rate of 0.58 mL/min. The DRC bandpass (q) was set to 0.45. These parameters were the optimal conditions for this instrument. LOQ for metal species in SEC-ICP-DRC-MS were calculated as 10 σ-criterion. They were 20 ng/L for Mn species, 25 ng/L for Fe species, 65 ng/L for Cu species and 60 ng/L for Zn species.A NexIon ICP-MS, Perkin Elmer  with dynamic reaction cell capability was employed for online determination of For quality control total element concentrations were additionally measured with an ICP-OES “Optima 7300” (Perkin Elmer) in parallel to ICP-DRC-MS. Sample introduction was performed by the instruments peristaltic pump at 1.0 mL/min and a Meinhard nebulizer which was mounted to a cyclon spray chamber. The measured spectral element lines were Cu: 324.754 nm; Fe: 259.941; Mn: 257.610 nm; Zn: 213.856 nm. The RF power was set to 1000 W, the plasma gas was 15 L Ar/min, whereas the nebulizer gas was 600 mL Ar/min. Regularly after 10 measurements three blank determinations and a control determination of certified element standards (SPEX) were performed. Comparability between the ICP-OES and -MS was checked by analyzing identical rat brain extracts (n = 10) and serum with both detectors in analogy to . Resultst-test and for multiple comparisons, two-way ANOVA followed by Bonferroni post hoc analysis was applied [p < 0.05 and values are reported as mean ± SEM. Further details of statistical tests are provided in the figure legends.The relative percentage changes of element species fractions were calculated in relation to the total element concentration changes using Microsoft Excel. The relationships between indicated trace elements in serum and CSF were determined using Pearson’s correlation coefficient, simple comparisons were analyzed using unpaired  applied . Statist


Staphylococcus epidermidis genome, denoted CLIMB1, which we characterized in terms of its MLST profile, gene complement , and similarity to other annotated S. epidermidis genomes. Our results demonstrate that WGA directly applied to CSF is a valuable tool for the identification and genomic characterization of dominant microorganisms in CSF shunt infections, which can facilitate molecular approaches for the development of better diagnostic and treatment methods.Understanding the etiology of cerebrospinal fluid (CSF) shunt infections and reinfections requires detailed characterization of associated microorganisms. Traditionally, identification of bacteria present in the CSF has relied on culture methods, but recent studies have used high throughput sequencing of 16S rRNA genes. Here we evaluated the method of shotgun DNA sequencing for its potential to provide additional genomic information. CSF samples were collected from 3 patients near the beginning and end of each of 2 infection episodes. Extracted total DNA was sequenced by: (1) whole genome amplification followed by shotgun sequencing (WGA) and (2) high-throughput sequencing of the 16S rRNA V4 region (16S). Taxonomic assignments of sequences from WGA and 16S were compared with one another and with conventional microbiological cultures. While classification of bacteria was consistent among the 3 approaches, WGA provided additional insights into sample microbiological composition, such as showing relative abundances of microbial versus human DNA, identifying samples of questionable quality, and detecting significant viral load in some samples. One sample yielded sufficient non-human reads to allow assembly of a high-quality  Hydrocephalus is a common cause of neurological disability in children . CerebroAmong the 20 to 25% of patients with treated CSF shunt infection who develop reinfection, it is unclear whether reinfections are caused by an organism that persists from one infection to the next, or are independent infection events. In the majority of reinfections (70%), the organism(s) recovered by culture differ between the first and second infection . DetaileSeveral methods exist for characterizing microorganisms in CSF and other clinical specimens. Microbiological culture methods, typically bacterial cultures, are standard in the routine clinical laboratory practice . While sHere we describe a proof of concept study to assess the usefulness of WGA for characterizing the microbiota of CSF shunt infections, comparing results of WGA with those of conventional microbiological culture and 16S rRNA high throughput sequencing (16S).The cohort considered in this study was previously described . EligiblCollection and storage of CSF was done under standard sterile conditions. The initial CSF sample for diagnosis of infection was obtained by needle aspiration of the shunt reservoir outside the operating room in a bedside “shunt tap”. The CSF sample near the beginning of the infection, which was analyzed in this study, was either left over from the initial diagnostic sample or was obtained in the operating room under sterile conditions from the system being removed during the first surgery to treat infection. Samples near the end of the infection were generally obtained under sterile bedside conditions through a sampling port within sterile extension tubing attached to the external ventricular drain.CSF samples were stored at 4°C upon collection, aliquoted into vials of ~100 µl, and stored at -70°C. PCH samples were shipped overnight to Seattle on dry ice for analysis.https://clsi.org).All samples were tested by routine CSF aerobic culture in hospital-certified laboratories at both SCH and PCH. The methodology followed guidelines of the Clinical and Laboratory Standards Institute guidelines  and CSF microbiota amplicon library construction was carried out using a one-step PCR amplification targeting the V4 region of the bacterial 16S rRNA gene as described .Sequencing of the pooled libraries was carried out for 600 cycles on an Illumina MiSeq desktop sequencer using the Miseq Reagent Kit v3.Whole genome amplification of DNA purified from CSF samples and two mock community samples was carried out using the REPLI-g Mini Kit  in accordance with the manufacturer’s recommendations. For each sample, including mock communities and no-template controls, a random-fragment library was constructed using the Nextera DNA Sample Preparation Kit (Illumina) with dual indexing and sequenced on the HiSeq 2500 platform to produce 96-bp paired-end reads.Sequencing data were analyzed using the denoising program DADA2  version, and aliShotgun sequence data were analyzed using the program Kraken  against Non-human DNA reads were assembled and annotated with the Comprehensive Genome Analysis service on the PATRIC website . This anS. epidermidis (http://bigsdb.pasteur.fr) for K. pneumoniae (Multilocus sequence typing (MLST) analysis was performed on the PubMLST.org website  for S. edermidis  and on Ieumoniae .S. epidermidis CLIMB1 genome, and the closest 100 matching genomes were identified. A rooted phylogenetic tree was built using the Codon Tree method, with Staphylococcus caprae C87 as an outgroup.The PATRIC Similar Genome Finder was searched with the assembled e.g. Delftia spp., Bradyrhizobium spp.), indicated potential quality issues with the latter 2 samples. These samples were therefore excluded from further analysis. The proportion of sequencing reads contributed by bacteria in the remaining 10 samples ranged from 0.1 to 22.8% . In 2 samples collected near the beginning of an infection episode, the proportion of bacterial reads was particularly high: Sample P1 I1 B – 15.7% and 22.8%, and P2 I2 B – 6.4% and 7.1%. Viral sequences were observed in 2 samples at low frequency (< 0.2%). No archaeal sequences were detected in any of the CSF samples.CSF samples were expected to contain substantial amounts of human DNA, along with DNA from other types of organisms, both pathogenic and opportunistic. We estimated the relative DNA abundance of organisms from the major domains of life in CSF samples by the distribution of reads in WGA (S. epidermidis in 2 samples (P1 I1 B and P2 I1 B), and K. pneumoniae (P2 I2 B) and S. pyogenes (P3 I1 B) in one sample each. S. aureus sequences were present in all samples, including the no template negative controls.Taxonomic assignment of WGA DNA reads identified 16 bacterial species that comprised 5% or more of bacterial reads in at least 1 CSF sample , it is dStaphylococcus epidermis in sample P1 I1 B and Klebsiella pneumoniae in P2 I2 B). These were also 2 of the 3 clinical samples yielding 16S rRNA above the level of detection by qPCR  reads assigned to a Staphylococcus phage StB20-like genome. StB20 was previously described as a lysogenic bacteriophage isolated from a coagulase-negative Staphylococcus capitis . Assembly of the non-human reads from sample P2 I2 B yielded 55 contigs spanning 610 Kbp of DNA. 410 Kbp (68%) of this sequence showed over 99% identity to multiple K. pneumoniae chromosomal sequences from GenBank. 136 Kbp (22%) of the assembled sequence had a 100% match to an unnamed plasmid of 239 Kbp total length from K. pneumoniae KP14003. None of the 7 K. pneumoniae MLST genes were present in the assembled sequence. A possible explanation is that the contigs represent only a partial assembly of a putative K. pneumoniae genome, which missed the MLST genes by chance due to low coverage (< 10%) of the chromosomal sequence.A set of contigs of sufficient quality was assembled S. epidermidis CLIMB1 assembly consisted of 76 contigs comprising a total of 2.42 Mbp . MLST sequences of CLIMB1 assign this strain to profile 16-2-1-2-2-15-1-1 or ST-16. The PubMLST database contains 3 other previously described isolates with profile ST-16, 2 from human(s) in the USA in 2001 and Russia in 2010 and 1 from an environmental source in Poland in 2007.The S. epidermidis CLIMB1 genome and the 100 most similar genomes from the PATRIC database , antimicrobial resistance gene content, and phylogenetic relationships to previously identified strains. These results were achieved without physical removal of the highly abundant human DNA from CSF shunt infection specimens before processing for sequencing. However, this analysis was only possible for a sample with one predominant bacterial species, which yielded a sufficient number of sequencing reads. Therefore, the utility of WGA may be optimal at the beginning of CSF shunt infection, before the bacterial infection is cleared by antibiotic treatment.WGA holds the promise of detailed molecular characterization of genomic DNA, which implies precise strain identification, evaluation of putative antibiotic resistance genes, and characterization of metabolic capacity. For example, the This work builds on an earlier report of the application of WGA to a cohort of hospitalized patients with infectious meningitis and encephalitis . In contBecause reinfection occurs at high rates among patients with CSF shunt infection, detailed genomic characterization of microorganisms in CSF can help answer questions about the etiology of infection and reinfection. We previously explored the relationship between infection and reinfection using 16S . In thatWe therefore suggest a more targeted approach to address the question of microorganism persistence from one infection to another, which relies on the high resolution information provided by WGA and the enhanced sensitivity and specificity of PCR. The approach would apply WGA to CSF samples at the beginning of a reinfection to obtain the genomic sequence of the principal infecting organism. The sequence information would be used to develop strain-specific PCR primers, which would be used to detect the strain in late samples of the previous infection. A positive result would provide strong evidence for the hypothesis that microorganisms present at low levels in CSF during treatment of an infection can lead to reinfection. Such an approach would be based on existing methodology. For example, methods for designing specific primers based on bacterial genomic sequence have been described in the literature . Nested We acknowledge several limitations for this proof of concept study. Extraction and sequencing of DNA from CSF samples is challenging due to low DNA abundance. In addition, analysis of microbial sequences is limited by the high proportion of human DNA, even during an active infection. As a result, the sensitivity of WGA is not better than that of 16S and worse than culture. Only a small fraction of the CSF samples we analyzed produced a sufficient number of bacterial reads to allow partial genomic assembly of predominant species. An expanded study would be needed to better understand the applicability of the approach. WGA may only be useful for CSF infections where one or a small number of microorganisms dominate. Alternately, as has been shown in aseptic meningitis , WGA mayDespite these limitations, our findings demonstrate the promise of WGA for research of CSF shunt infection. WGA results: (1) were consistent with culture-based methods, (2) identified all bacteria detected in culture to the species level, while taxa were classified by 16S rRNA to only genus or family level, and (3) provided additional insights regarding viruses present and strain identity of predominant bacteria. Further work is needed to better understand the utility of WGA in the setting of CSF shunts and CSF shunt infection, including a comparison between the effectiveness of the WGA with other approaches to characterizing the microbiota such as strain-specific PCR primers.https://www.ncbi.nlm.nih.gov) under BioProject PRJNA707514.DNA sequence data presented in this study can be found online at the National Center for Biotechnology Information (The study received initial Institutional Review Board approvals from the Seattle Children’s Research Institute on Febryary 8, 2011 and the University of Utah, as well as approval from the Primary Children’s Hospital Privacy Board on January 14, 2009. For all study subjects, except those from Primary Children’s Hospital prior to March 18, 2010, consent was obtained for additional CSF to be collected on each occasion that regular CSF samples were obtained during treatment for CSF shunt infection. Prior to March 18, 2010 at Primary Children’s Hospital, we used CSF remaining for after routine processing and testing in the Primary Children’s Hospital Microbiology Laboratory.Current membership of the CLIMB group includes: Alexander Cheong, Gabriel Haller, Julie McGalliard, Diego Morales, Amanda Morgan, Alexander Rangel-Humphrey, and Lisa Wick. Past membership includes: Dan Berger, Whitney Bond, Haley Botteron, Courtney Dethlefs, Jessica Foster, Mohammed Gabir, Robert Johnson, Deanna Mercer, and Linda Shih.TS, PH, CP, KW, and LH conceived and designed the study. DL, PM, JH, JO, and TS provided oversight over study enrollment and material collection. CP performed the experiments. PH, CP, and KW analyzed the data. PH, TS, and CP wrote sections of the manuscript. All authors contributed to the article and approved the submitted version.via K24 HL141669.This study was supported by R01 NS095979. DL receives research funding and equipment for unrelated projects through Microbot Medical, Inc. and Medtronic, Inc. LH receives additional support from the National Institutes of Health Author KW was employed by company New Harmony Statistical Consulting LLC.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Cerebrospinal fluid (CSF) analysis supports diagnosis of neurodegenerative diseases (NDs), however a number of issues limits its potentialities in clinical practice. Here, a newly developed technique for fluid voltammetry, relying on a simple sensor , was used to test the applicability for CSF analysis. BIONOTE was initially calibrated on an artificial CSF-like solution and then applied on human CSF, either immediately after collection or after refrigerated storage. Following optimization, it was used to evaluate 11 CSF samples correlating the electrochemical dataset with CSF routine parameters and biomarkers of neurodegeneration. Multivariate data analysis was performed for model elaboration and calibration using principal component analysis and partial least squares discriminant analysis. BIONOTE presented a high capacity to predict both physiological and pathological constituents of artificial CSF. It differentiated distinct fresh human CSF samples well but lost accuracy after refrigerated storage. The electrochemical analysis-derived data correlated with either CSF routine cytochemical indexes or a biomarker of neurodegeneration. BIONOTE resulted as being a reliable system for electrochemical analysis of CSF. The CSF fingerprint provided by the sensor has shown itself to be sensitive to CSF modification, thus it is potentially representative of CSF alteration. This result opens the way to its testing in further study addressed at assessing the clinical relevance of the methodology. Because of its advantages due to the ease and rapidity of the methodology, a validation study is now required to translate the technique into clinical practice and improve diagnostic workup of NDs. Neurodegenerative diseases (NDs) are a heterogeneous group of progressive and disabling conditions whose worldwide incidence and prevalence are increasing following global aging and longer life expectancy.Neuropathology and pathophysiology differ among NDs; conversely, clinical disturbances, including both motor and cognitive disturbances, may overlap. Indeed, while Alzheimer’s disease (AD) and Parkinson’s disease (PD), the two most common NDs, basically present with typical syndromes, there are many other cases in which the diagnosis is more challenging because of the clinical complexity and variety .Nowadays NDs remain incurable disorders. However, the therapeutic scenario is rapidly changing and potential disease-modifying treatments are upcoming. Therefore, the diagnostic certainty now represents an urgent need in the field of NDs, since the therapeutic success may depend on a timely and precise diagnosis ,3.To date, the diagnosis of different NDs mostly relies on clinical criteria, whereas instrumental findings  offer support. Actually, fluid biomarkers are constantly gaining more relevance, such that cerebrospinal fluid (CSF) biomarkers are crucial in diagnosis and stratification of patients with suspected AD, as well as allowing prognostic evaluations in patients with PD ,4,5,6.CSF, indeed, reflects pathological changes occurring at the central nervous system (CNS) level, thus representing a valuable source for reliable biomarkers informing on the biological events underlying clinical conditions. Despite these theoretical advantages, development and use of CSF biomarkers are still limited by several factors, which include either the scarcity of molecular targets or issues related to the validation and spread of assay methodologies. In this perspective, the application of novel technologies in CSF analysis aimed at overcoming current barriers would be fundamental .In this direction, here we present a newly developed technique based on voltammetry oriented towards a detailed chemical description of fluids’ characteristics ,9.This technique is based on a sensor system able to analyze many different biological fluids ,9, alreaThe method of the analysis of CSF is not new, and this analyte has been also measured with non-conventional sensors  ,15,16,17In particular, we preliminarily applied the technique to artificial CSF in order to assess applicability and performance in terms of sensitivity and resolution.Then we tested this technique on samples of human-derived CSF, in order to evaluate its potentialities and to understand its relevance for future use in clinical frames.Considering the simplicity of the instrument, the low costs of each measurement and the fingerprinting approach , the goal of this work consists in demonstrating the feasibility of the application via a proof of concept experiment. The voltammetric sensor consists of a sensing platform, named BIONOTE , inclThis instrument has been already used with human fluids, namely for etiological diagnosis of pleural effusion , ascitesSince BIONOTE has never been tested on CSF, here we set an experimental plane aiming to: (1) estimate BIONOTE sensitivity and resolution in the assessment of CSF samples such to be used for the content analysis and between-samples discrimination; (2) assess the reliability and effectiveness of BIONOTE-based analysis after CSF sample storage; (3) evaluate the capability of BIONOTE to differentiate CSF samples from different clinical conditions.Aim 1 has been addressed by an experiment of calibration of the BIONOTE to the artificial CSF constituents; aim 2 has been addressed by the optimization of the experimental setup for human CSF analysis; aim 3 has been addressed by applying the BIONOTE analysis protocol on a small number of patient-derived CSF samples as a pilot experience.All standard solutions used for calibration purposes were prepared dissolving the chemical compound in bi-distilled water at the higher concentration and by following dilutions. All chemical standards were purchased at Sigma Aldrich : potassium chloride (P3911), sodium chloride (S7653), sodium bicarbonate (S5761), calcium chloride (C5670), magnesium chloride (M8266), Sodium hydrosulfide hydrate (161527), dopamine hydrochloride (H8502). All these samples were prepared and measured in glass test-tubes.The BIONOTE was initially challenged against these CSF constituents individually as described in . Seven cTo find further evidence supporting the employability of the BIONOTE system for CSF analysis, an artificial CSF was prepared.The artificial CSF was freshly prepared before each experimental session dissolving in bi-distilled water the compounds reported in Next, dopamine and NaHS were added at different concentrations, mimicking some alterations occurring in NDs  Table 3Table 3.To prevent undesirable oxidation phenomena of dopamine, which may potentially affect the voltammetric analysis, each solution was bubbled with nitrogen before dopamine addition .CSF samples were obtained from a total of 11 subjects  undergoing lumbar puncture (LP) for diagnostic purpose at the Neurology Unit of Tor Vergata University Hospital . None of them was diagnosed with NDs . LP was performed at the bedside, in the morning, after an overnight fast, with the subject lying in lateral decubitus position. CSF samples were collected and processed according to standard procedures. Analysis was carried at the local laboratory and included routine quantitative assessment of glucose, lactate, total proteins, albumin, white blood cells, Immunoglobulin G (IgG), and the evaluation of neurodegeneration-related biomarkers amyloid-β-42 peptide, total tau protein, 181-phosphorylated tau protein ,21 Tabl.Five of these 11 samples were further used for a repeatability evaluation by being measured multiple times immediately after the lumbar puncture, and a reproducibility estimation over time by being re-analysed after 30 and 120 days of stocking at −80 °C.The electrochemical pattern registered by the voltammetric sensor holds a multidimensional (500 points) and enriched informative content. The complex nature of this dataset required the application of multivariate data analysis techniques to provide a simplified representation of the multidimensional space acquired and to highlight the most informative features.Principal components analysis (PCA) allowed the representation of the multidimensional dataset onto a simplified scatter chart by defining the most important variables that characterized the specific phenomenon of interest .Each measurement of the data set is represented by a point on the PCA plane . When the points are close one to each other, they form a cluster of samples with similar characteristics. The points far from this cluster have different characteristics.Calibration was performed via partial least squares discriminant analysis (PLS-DA) coupled with the leave-one-out criterion as a cross-validation method in order to obtain all the predictive models on the calibration data.All the multivariate data analyses were performed using PLSToolbox  in Matlab Environment .The fingerprints obtained by the sensor reflected the chemical composition of the measured samples. Thus, a multidimensional model was elaborated via PLS-DA using the leave-one-out criterion; this model received as input the multidimensional fingerprint and is able to predict with a reasonable error  the concentration of the different compounds in the sample solution.2, NaCl, NaHCO3, CaCl2, NaHS and dopamine dissolved in bi-distilled water.In Important confirmations can be inferred from the curves shown in Indeed, it is evident that each compound generates a voltammogram with a peculiar profile; each of these voltammograms is different, in shape, from the others; these profiles preserve their shape for each constituent when varying the concentration level, but this shapes increase their area and the height of each peak as the concentration increases.All these data have been used for calibration purposes. To this scope each single curve has been treated as a multidimensional data source (the 500 points acquired to form the voltammogram).PLS-DA was used for the calibration model. The ability of the sensor inferred by the qualitative observation of the curves (above introduced) is confirmed by the encouraging values calculated for the root mean square errors in calibration (RMSEC) and in cross validation (RMSECV), for each of the constituents the artificial CSF. All these parameters are reported in In order to understand the influence of these RMSECV when assessing the concentration of the different compounds in bi-distilled water, the percentage error can be calculated taking into account the span of the all range of concentrations considered in the calibration measurements.3, 6% for CaCl2, 5% for MgCl2, 9% for NaHS, 18% for dopamine. These percentage errors should not be affordable when the sensor is used as an analytical method for constituent quantification. In this case the goal is not quantification. The important result coming from these limited percentage errors is that the sensor is able to distinguish the modification of the artificial CSF when its composition is modified. Aiming at discriminating alteration of CSF due to a diseased condition, this is a promising result, encouraging the next step of verification, consisting in measuring artificial CSF as a whole.The percentage errors are the following: 6% for KCl, 1% for NaCl, 5% for NaHCOArtificial CSF was measured as a whole in different altered conditions, simulated by varying the concentration levels of NaHS and of dopamine. The consequent modifications of the sensor response can be observed in The data obtained by BIONOTE-based analysis of the artificial CSF solutions modified with dopamine and NaHS addition were elaborated through multivariate data analysis techniques (PLS) in order to mathematically confirm this ability of the sensor in discriminating altered conditions of artificial CSF. PLS regression model on NaHS modified solutions confirmed the BIONOTE’s ability to predict NaHS concentration with a RMSECV of about 0.07 mM, even in a complex mixture and with better performance with respect to NaHS as sole compound in bi-distilled water (which was 0.09 mM).This result corroborates what arose in the comparison between the electrochemical fingerprint of the native artificial CSF and the modified one .−3 mM. The optimized experimental setup allowed us to achieve better performance by decreasing the error of the PLS regression model with respect to the 1.80 × 10−3 mM error obtained for dopamine as sole compound in bi-distilled water.Similarly, the BIONOTE showed a satisfactory and promising performance in the analysis of dopamine-modified artificial CSF with a RMSECV of about 0.67 × 10Once the ability to detect relevant markers in an artificial complex mixture was confirmed, the voltammetric sensor was challenged with human CSF.The first test on human CSF samples was oriented to the optimization of the measurement protocol. Indeed, in the application of this new methodology in the field, some practical problems  were encountered.The first problem was relative to the clinical practicability of the method. Indeed, it is useful to understand whether the CSF extracted from an individual must be measured immediately after extraction or can be stored and measured later. This is a problem of repeatability.Five CSF samples, extracted from five patients, were used for a repeatability evaluation. These samples were measured multiple times immediately after the LP, and a reproducibility estimation over the time were performed via successive re-analyses of the same samples after 30 and 120 days of stocking at −80 °C. The overall dataset was elaborated through PCA, an unsupervised multivariate data analysis technique, and the result is reported in As can be seen from the score plot of the PCA, the three experimental sessions shaped distinct clusters in the three-dimensional space defined by PC1, PC2 and PC3 accounting for about 86% of the explained variance.This result highlighted the evolution of the biological sample over time, even if properly stocked at −80 °C. Particularly, applying PCA analysis over the three experimental session independently, it becomes clear that most of the information pertained to the fresh CSF tends to disappear during the storage as a result of a progressive modification.Indeed, looking at While the fresh samples were clearly distinguishable over the plane along both the PC1 and PC2, these were less divergent already after 30 days of storage and became overlapped in the last time step evaluated a–c. FurtEleven CSF samples from non-ND patients were analyzed with the BIONOTE voltammetric sensor immediately after LP. Each CSF was measured five times, and the mean electrochemical fingerprints over the five cycles have been calculated and represented in two figures: all the voltammograms together, overlapped in the same graph ; and a gIn Moreover, each voltammogram is characterized by peculiar peaks, probably associated with the expected interindividual variability. This behavior is put in evidence more clearly by the 11 panels of The BIONOTE is proposed here as a fast, easy and cheap instrument to discriminate altered CSFs against controls and, hopefully, also to discriminate CSFs referring to different diseases. This is an ambitious end-point, which can be achieved through sensor response characterization (as described above) but also comparing BIONOTE outputs against the clinical standard data. A list of biochemical parameters was selected for this test: glucose, lactate, total proteins, albumin, white blood cells, immunoglobulin-G, amyloid-β-42, total-tau, phosphorylated-181-tau.To train the BIONOTE system to predict biochemical parameters usually retrieved by standard analytical techniques, the whole dataset was elaborated several times through multivariate data analysis against each marker. The results obtained from the PLS regression models built on the related clinical data are reported in Thus far, the BIONOTE showed a quite different performance ranging from optimal , to sub-optimal (immunoglobulin-G and phosphorylated-181-tau protein) and also inadequate (lactate and amyloid-β-42 protein).BIONOTE is a sensor for voltammetric analysis of fluids which has been used already for clinical applications with promising results. Indeed, it has been tested to analyze pleural, ascitic, lower-limb ulcers liquids, and urine ,12,13. HIn this study, we initially assessed the BIONOTE performances on an artificial CSF sample to establish its capability to recognize main different physiological and pathological CSF constituents coherently with their concentration.After such a calibration, the BIONOTE was used with human CSF obtained from five patients receiving LP for diagnostic purposes. The test was conducted in three conditions reflecting what commonly occurs in clinical practice, where CSF could be analyzed either immediately after the LP or after refrigerated storage (−80 °C). Namely, the BIONOTE-based analysis was performed repeatedly on fresh samples and after two periods of freezing, for 30 and 120 days, respectively, showing that the accuracy to differentiate distinct samples was better in fresh conditions, while it decreased progressively with −80 °C storage, probably because of CSF’s electrochemical modifications due to prolonged refrigeration.Finally, the BIONOTE-based analysis was applied to fresh CSF samples from 11 human subjects to predict different biochemical markers. Of interest, the strongest associations resulted with routine parameters such as glucose, total proteins, white blood cells, albumin, and especially with total-tau protein, a marker of neuronal injury whose CSF levels proportionally increase with axonal degeneration in neurons, as occurs in AD , prion dDespite the limitation of this pilot study, such as the sample size and enrolment of a so-called “control population” (patients not diagnosed with NDs), BIONOTE emerges as a reliable device for voltammetric analysis applicable for clinical purposes even in neurology. Actually, the sensor was able to detect differences in fresh CSF due to various concentrations of both physiological and pathological constituents, which may reflect different clinical conditions. The main quality of BIONOTE is the ease and the rapidity of electrochemical analysis, which applied on fresh CSF samples may inform immediately on relevant clinical events. Indeed, electrochemical analysis relies on a simple and manageable device whose outcome is provided in a short time.These strengths seem to be fundamental to fill current gaps of CSF-assisted diagnosis in the field of NDs. Accordingly, is now necessary to proceed with confirmatory studies involving patients on larger scale.The endpoint of this work is the proof of concept of the BIONOTE as a relevant sensor for the characterization of CSF, oriented to its utilization as a fast pre-screening instrument to address further analysis and therapies. This clinical use is beyond the scope of the work, while the proof of concept has been shown by the pilot study presented. BIONOTE output is characteristic and reproducible for artificial CSF and for the human CSF. Thus, the methodology developed and tested is effective and its application shown a good reproducibility. Moreover, the CSF fingerprint provided by the sensor has been shown to be sensitive to CSF modification, and thus it is potentially representative of CSF alteration. This result opens the way to its testing in a further study addressed to assess the clinical relevance of the methodology.


Proteomics studies are important for the discovery of new biomarkers as clinical tools for diagnosis and disease monitoring. However, preanalytical variations caused by differences in sample handling protocol pose challenges for assessing biomarker reliability and comparability between studies. The purpose of this study was to examine the effects of delayed centrifuging on measured protein levels in plasma and cerebrospinal fluid (CSF). Blood from healthy individuals and patients with multiple sclerosis along with CSF from patients with suspected neurological disorders were left at room temperature for different periods  prior to centrifuging. Ninety-one inflammation-related proteins were analyzed using a proximity extension assay, a high-sensitivity multiplex immunoassay. Additional metabolic and neurology-related markers were also investigated in CSF. In summary, many proteins, particularly in plasma, had increased levels with longer delays in processing likely due in part to intracellular leakage. Levels of caspase 8, interleukin 8, interleukin 18, sirtuin 2, and sulfotransferase 1A1 increased 2-fold to 10-fold in plasma after 24 h at room temperature. Similarly, levels of cathepsin H, ectonucleoside triphosphate diphosphohydrolase 5, and WW domain containing E3 ubiquitin protein ligase 2 differentiated in CSF with <6 h delay in processing. However, the rate of change for many proteins was relatively consistent; therefore, we were able to characterize biomarkers for detecting sample handling variability. Our findings highlight the importance of timely and consistent sample collection and the need for increased awareness of protein susceptibility to sample handling bias. In addition, suggested biomarkers may be used in certain situations to detect and correct for preanalytical variation in future studies.  •Several blood and cerebrospinal fluid proteins are affected by sample handling.•Plasma protein levels increased with longer centrifugation delay from hemolysis.•Certain proteins may assess sample handling variability and predict delay time. We assessed the effects of delayed sample handling on a panel of 92 inflammation-related proteins in the blood and cerebrospinal fluid. Plasma protein levels were measured at delayed centrifugation times of 1, 24, 48, and 72 h corresponding with common postal-transit delays, and changes in relative concentration were modeled and validated using an external dataset. Several proteins were selected as markers of assessing sample handling variability for application in future studies. Molecular biomarkers play an important role in the risk assessment, diagnosis, and monitoring of a wide range of diseases , 2, and Although blood remains ideal for clinical applications, the exclusivity of the central nervous system (CNS), as maintained by the blood–brain barrier, can compartmentalize potential markers of disease pathology. Therefore, many neurological diseases of the CNS utilize cerebrospinal fluid (CSF) as the primary source of biomarkers for diagnosing and disease monitoring. However, similar to blood, discrepancies in the handling of CSF samples may result in preanalytical variation of protein measures , 9. For In this study, we examine the preanalytical effects of handling time prior to sample processing on the levels of inflammation-related proteins in both plasma and CSF using high-sensitivity proximity extension technology , 13. Ourg at 15 min at RT, storage −80 °C). Similarly, CSF was also collected from three patients with other neurological diseases or suspected of MS using a 15 ml size polypropylene DNA-free, DNase-free, RNase-free tube, nonpyrogenic, and noncytotoxic (Sarstedt). Samples were left at RT for <1 (baseline) and 6 h. Two samples, one intact (“whole” CSF) and the other centrifuged , were compared for both time points. The whole CSF and recovered cell-free CSF were transferred into a 2 ml polypropylene tube (Sarstedt) and stored either at RT or at −80 °C. Both blood and CSF were processed on site within 1 h from collection and stored at −80 °C for less than 2 months before being thawed once, aliquoted, and shipped overnight on dry ice to Olink Proteomics AB for analysis.Blood was collected from three healthy individuals and three patients with MS in 10 ml Vacutainer tubes containing EDTA anticoagulant (Becton Dickinson) as part of the standard routine for the STOPMS-II cohort , locally collected at the Karolinska University Hospital (Protein concentrations were measured using a proximity extension assay (PEA) , a high-i.e., measurable concentration above the limit of detection) of 80% or above were analyzed. However, a few select proteins , and IL-10 receptor subunit alpha) with a call rate of 40 to 80% were also examined for changes in detectable presence with increasing processing delay.The inflammation panel was used for both plasma and CSF analyzing 91 proteins preselected with an emphasis on processes of inflammation and immune activation. Two additional panels (neuroexploratory and metabolism) were also analyzed for CSF to examine the effects of sample handling on metabolic and neurology-related markers in the CNS. Only measures with an overall call rate (r-project.org). Changes in protein measures between each time point and baseline were analyzed using a paired Student' t test. The change in plasma protein levels (P(t)) over time (t) in comparison to a reference sampling time (tR) and concentration (PR) was modeled using three standard functions: linear {P(t) = A(t − tR) + PR}, exp {P(t) = B(exp(A(t − tR))−1) + PR}, and Gompertz {P(t) = B ∗ exp(−ln(B/PR) ∗ exp(−A(t − tR)))−1}. As the baseline sample (<1 h from collection) was used as a reference, the reference time and value for both linear and exponential models were set at tR = 1 and PR = 0. For Gompertz models, protein changes were in reference to the proportion of baseline instead of change from baseline, therefore, tR = 1 and PR = 1. Parameters A and B that represent the rate of change and baseline level in the aforementioned formulae were then optimized, and models for each protein were examined for stability and fit. A recommended model was selected depending on whether the rate of change was stable (linear), increasing , or decreasing (Gompertz) over time. For CSF, only a linear model was used because of limited resolution.Data were processed and analyzed with R-3.2.3 . Three suggested markers of sample handling for each predetermined panel are listed in To a lesser degree, proteins in CSF were also affected by sample handling as shown in Our findings suggest that the levels of many proteins, particularly those in plasma, can be affected by delays in centrifugation, which is supported by previous studies , 7, 18. The relative consistency in protein level changes between samples of both healthy and diseased individuals indicates the value of biomarkers for detecting preanalytical variation. By selecting certain proteins as markers of delayed processing, one can detect preanalytical variability by examining sampling parameters such as sampling site, cohort, and periods; or measures of clinical characteristics such as exposures and disease status, which may unknowingly bias study comparisons. The usage of multiple markers can provide confirmation or may be necessary in cases where markers overlap with those of study interest. For each of the pre-established PEA assay panels, we have suggested several markers to aid in the detection of sample handling issues for future studies. As discussed previously, markers were selected based on their correlation to CD40L, a well-established marker of blood storage time and highly sensitive to sample handling variation , 15.e.g., AXIN-1, SIRT2) with the predicted rate of change  correcting other protein levels by predicting the deviation between the actual level and that expected from the determined time difference in step 1. However, this method only provides a rough approximation and does not factor in many other environmental and sample processing–related variables, which may influence protein measures  and upon request to the corresponding author, Ingrid Kockum, Department of Clinical Neuroscience, Karolinska Institutet, Ingrid.kockum@ki.se.Data are available at the Swedish National Data Service (This article contains T. O. has received lecture and/or advisory board honoraria and unrestricted MS research grants from Astrazeneca, Biogen, Novartis, Merck, Roche, Almirall, and Genzyme. F. P. has received research grants from Biogen, Genzyme, Merck KGaA, and Novartis and fees for serving as Chair of DMC in clinical trials with Parexel. Ö. L. is an employee of Olink Proteomics. J. H., M. K., G. J., and I. K. declare no competing interests.


The objective of the present study was to assess the putative value of the three IP3R subtypes as prognostic biomarkers in breast cancer. We found that IP3R3 is the most strongly expressed subtype in breast cancer tissue. Furthermore, IP3R3 and IP3R1 are significantly more expressed in invasive breast cancer tissue than in non-tumor tissue. In contrast to IP3R1 and IP3R2, the expression of IP3R3 was positively correlated with prognostic factors including tumor size, regional node invasion, histologic grade, proliferation index, and hormonal status. By analyzing public databases, we found that the expression of all IP3R subtypes is significantly correlated with the overall survival and disease-free survival of patients with breast cancer. We conclude that relative to the other two IP3R subtypes, IP3R3 expression is upregulated in breast cancer and is correlated with prognostic factors. We strongly believe that our results will open up new perspectives with regard to the link between IP3Rs and breast cancer aggressiveness.The inositol-trisphosphate receptor (IP2+ flux) is involved in many pathophysiology processes, including carcinogenesis. Inside the cell, the inositol-trisphosphate receptor (IP3R) is a major player in the regulation of the Ca2+ flux from the endoplasmic reticulum to the cytoplasm. The IP3Rs (and particularly the IP3R3 subtype) are known to be involved in proliferation, migration, and invasion processes in breast cancer cell lines. The objective of the present study was to evaluate the potential value of IP3Rs as prognostic biomarkers in breast cancer. We found that expression levels of IP3R3 and IP3R1 (but not IP3R2) were significantly higher in invasive breast cancer of no special type than in non-tumor tissue from the same patient. However, the IP3R3 subtype was expressed more strongly than the IP3R1 and IP3R2 subtypes. Furthermore, the expression of IP3R3 (but not of IP3R1 or IP3R2) was positively correlated with prognostic factors such as tumor size, regional node invasion, histologic grade, proliferation index, and hormone receptor status. In an analysis of public databases, we found that all IP3Rs types are significantly associated with overall survival and progression-free survival in patients with breast cancer. We conclude that relative to the other two IP3R subtypes, IP3R3 expression is upregulated in breast cancer and is correlated with prognostic factors.Breast cancer is the leading cause of cancer death among women in worldwide and France. The disease prognosis and treatment differ from one breast cancer subtype to another, and the disease outcome depends on many prognostic factors. Deregulation of ion flux (especially Ca In 2020, around 2.2 million new cases of breast cancer (BC) were diagnosed worldwide —making tAt BC diagnosis, 5% of patients have metastases . Ten to Despite the development of these new tools, some BCs will recur locally or will form metastases. It is therefore essential to find novel treatments and prognostic markers for even more effective patient care. The heterogeneity of BC is now taken into account when developing new therapies and prognostic factors, with a view to making treatment even more personalized.2+, from outside the cell or from within the endoplasmic reticulum (ER)) drive the development of metastases. When Ca2+ channels are open, the cytosolic Ca2+ concentration rises by a factor of 5 to 10 (from 100 nM to 500–1000 nM). Inside the cell, inositol -trisphosphate (IP3) generates part of this calcium signaling via the IP3 receptor (IP3R), which has three characterized subtypes: IP3R1, IP3R2, and IP3R3. The three subtypes show 60% to 80% homology and are expressed ubiquitously. Interestingly, it was found that each subtype has a specific calcium release signature: strong Ca2+ oscillations through IP3R2, weaker oscillations through IP3R1, and monophasic transients through IP3R3  was also evaluated. Five datasets were used: the “Breast cancer recurrence data, 9 datasets from 7 authors” (1561 patients), “Breast cancer Meta-base: 10 cohorts 22K gene” (1888 patients), “Breast Invasive Carcinoma TCGA” (502 patients), “Miller Bergh Breast GSE3494-GPL96” (236 patients) and “BRCA-TCGA Breast invasive carcinoma—July 2016” (962 patients).Survival analysis was conducted using the SurvExpress online tool (Available in bioinformatica.mty.itesm.mx/SurvExpress). Expression levels of the individual genes . Pairs of mean values were compared using a non-parametric Mann–Whitney test. A non-parametric Kruskal–Wallis test was used to compare means of more than two groups. The threshold for statistical significance was set to Between 1 November 2015 and 1 November 2018, 52 patients with IBC-NST treated at Amiens University Medical Center were included in the study. An additional 15 IBC-NST samples from patients at the Jean Godinot Institute cancer center  were included. Non-tumor tissue from the same patient was available for each BC tissue sample. The clinical and histologic characteristics are summarized in 3R subtype in IBC-NST samples and non-tumor tissue samples. We found that both IP3R1 and IP3R3 expression were significantly higher in BC tissue than in non-tumor tissue  vs. 1 ± 0.03 (N = 12), respectively; p = 0.02; IP3R3: 3.37 ± 0.14 (N = 29) vs. 1 ± 0.02 (N = 12), respectively; p < 0.0001)  vs. 1 ± 0.08 (N = 13), respectively; p = 0.8) (3R1 IH expression score was significantly higher in BC tissue than in non-tumor tissue (0.75 ± 0.14 (N = 40) vs. 0.39 ± 0.14 (N = 18), respectively; p = 0.05); the same was true for the IP3R3 IH expression score (1.48 ± 0.12 (N = 41) vs. 0.22 ± 0.08 (N = 17), respectively; p < 0.0001) (3R2 IH expression score between BC tissue and non-tumor tissue (1.64 ± 0.11 (N = 30) and 1.43 ± 0.19 (N = 18), respectively; p = 0.3)  A. IP3R3 p = 0.8) A. The sa 0.0001) B. In conp = 0.3) B. Taken 3R1 and IP3R3 were overexpressed in IBC-NST, we next sought to establish a link between IP3R expression on the one hand and predictive factors for survival and recurrence in BC patients on the other.After having found, in Western blot and in IH, that IP3R2, even though its expression levels were similar in the paired tumor and non-tumor samples.Tumor size is a major risk factor for local or remote BC recurrence; the larger the tumor, the greater the risk ,31,32,333R1, IP3R2, and IP3R3 IH expression scores (IH expression score in T1 BCs: 1.08 ± 0.22 (N = 10) for IP3R1; 1.67 ± 0.21 (N = 9) for IP3R2 and 1.36 ± 0.3; p = 0.33 (N = 10) for IP3R3) (3R2 and IP3R3 IH expression scores were significantly higher than the IP3R1 IH expression score (IH expression score in T2 BCs: 0.73 ± 0.18 (N = 24) for IP3R1 vs. 1.63 ± 0.14 (N = 19); p = 0.0001 for IP3R2 and 1.4 ± 0.14 (N = 25); p = 0.004 for IP3R3. IH expression score in T3 BCs: 0.18 ± 0.12 (N = 5) for IP3R1 vs. 1.8 ± 0.2 (N = 3); p = 0.04 for IP3R2 and 1.92 ± 0.32 (N = 5); p = 0.008 for IP3R3) , there were no statistically significant differences in the IPr IP3R3) A. In T2 r IP3R3) B,C. The Regional lymph node involvement is a risk factor for local and remote recurrence ,31. We c3R3 IH expression score was greater (by a factor of 1.3) in N+ BCs (1.72 ± 0.16 (N = 20)) than in N0 BCs (1.3 ± 0.16 (N = 21); p = 0.08)  for IP3R1 vs. 1.78 ± 0.17  for IP3R2, and 1.3 ± 0.16  for IP3R3. In N+ BCs, the IH expression score was 0.73 ± 0.21 (N = 20) for IP3R1, vs. 1.49 ± 0.13  for IP3R2, and 1.72 ± 0.16  for IP3R3.  A. The IPr IP3R3. B. Moreovd N+ BCs B. Thus, N = 16) for IP3R1 vs. 1.47 ± 0.26  for IP3R2 and 1.64 ± 0.19  for IP3R3. (B) The IH expression score in samples with a Ki67 index > 20% was 0.59 ± 0.2 (N = 20) for IP3R1 vs. 1.75 ± 0.15  for IP3R2 and 1.59 ± 0.18  for IP3R3 (The Ki67 proliferation index and the histologic (SBR) grade are risk factors for BC recurrence: the higher the index or grade, the greater the risk of recurrence ,31,32,33or IP3R3 A,B. In b−, luminal B HER2+, HER2, and TN) on the basis of histologic and molecular characteristics, which notably include expression of the estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67. Tumors that are ER+ and/or PR+ are referred to as HmR+. The prognosis, disease aggressiveness, and risk of remote metastasis and relapse vary from one subtype to another. In fact, the luminal A subtype has the best prognosis [At present, clinicians typically classify carcinomas into five subtypes  for IP3R1, vs. 1.61 ± 0.16 (N = 14) for IP3R2 and: 1.33 ± 0.17 (N = 17) for IP3R1; p = 0.2)  for IP3R1, vs. 1.54 ± 0.18  for IP3R2 and 1.54 ± 0.18  for IP3R3 and IP3R1 IH expression scores in TN BC: 0.51 ± 0.36 (N = 8) for IP3R1 vs. 1.97 ± 0.26  for IP3R2 and 1.48 ± 0.32  for IP3R3)  for IP3R1, vs. 1.67 ± 0.17  for IP3R2 and 1.3 ± 0.31 (N = 7) for IP3R3). In luminal B HER2+ samples, the IH expression score was significantly higher for IP3R3 than for IP3R1  for IP3R1, vs. 1.77 ± 0.23 (N = 6); p = 0.004) for IP3R3 and 1.38 ± 0.38 (N = 4) for IP3R2) (3R2 and IP3R3 IH expression scores in any of the subtypes. This finding suggests that IP3R3 is associated with a more aggressive disease profile for IBC-NST. We assessed the three IPp = 0.2) A. In lumr IP3R3) B,C. In lr IP3R2) D,E. Ther3Rs in the non-tumor tissue. Our results, obtained both by IH and Western blot, show that IP3R2 is strongly expressed in contrast to IP3R1 and IP3R3. IH expression score: IP3R2 = 1.43 ± 0.19 (N = 18) vs. 0.39 ± 0.14 (N = 18); p = 0.0001 for IP3R1 and 0.22 ± 0.08 (N = 17); p < 0.0001 for IP3R3. The IP3R2 relative expression score is 0.65 ± 0.08 (N = 13) vs. 0.24 ± 0.03 (N = 12); p < 0.0001 for IP3R1 and 0.25 ± 0.03 (N = 12); p < 0.0001) for IP3R3. Indeed, the relative expression and IH expression scores are significantly higher for IP3R2 than for IP3R1 or IP3R3  and splitting the patients into cohorts where the p-value was the lowest [We next sought to establish whether or not the expression of the three IPsubtypes . We usede lowest .BRCA-TCGA Breast invasive carcinoma—July 2016” database, IP3R1 and IP3R3 expression were significantly associated with poor overall survival  than IP3R3  or IP3R2   with the largest number of documented patients. In the “survival A,B. The nificant C. IP3R1 = 0.286) D. IP3R1 ectively , whereaspatients .3RS expression and disease-free survival  has not yet been demonstrated. Studying the tissue expression of the three IP3R subtypes is thus essential for understanding their mechanism of action. In that context, our results established for the first time a link between the level of expression of IP3R3 and the aggressiveness of IBC-NST. To the best of our knowledge, our study is the first to have established this link in BC—a link that is already known for cancers such as glioblastoma and gastric cancer. Although the prospective nature of our study consequently limited the number of samples eligible for this work, it enabled us to obtain precise data in terms of overall survival but also in terms of recurrence-free survival at 5 years. These data will be the subject of a future study.More specifically, IP stimuli  and an i stimuli . Moreoveignature . IP3R3 i pathway . However3R subtypes is negatively correlated with overall survival and disease-free survival. In BC, there are many clinical or histologic survival factors. All these criteria should be taken into account when selecting the primary treatment, neo-adjuvant or adjuvant chemotherapy, or a more targeted type of therapy such as hormone therapy. The negative correlation between IP3R subtype expression on the one hand, and overall survival and disease-free survival on the other, testifies to the receptor’s significant involvement in breast carcinogenesis in general and metastatic invasion in particular. It is known that the mortality rate in BC is linked to the occurrence of remote metastases [Based on a SurvExpress analysis of five databases, we showed that expression of the three IPtastases ,39. More3R1 and  IP3R3 are expressed significantly more in BC tissue than in non-tumor tissue  decreases with tumor size but is not correlated with other BC aggressiveness factors . IP3R3 can thus be considered as a marker of aggressiveness in BC as its expression is correlated to the severity of BC.We found that IPr tissue . IP3R3 e3R subtypes in breast carcinogenesis processes. Differences in expression between non-tumor tissue and tumor tissue are also observed in colorectal cancer. Indeed, IP3R3 is not detected in non-tumor tissue (in contrast to the other two subtypes) but is overexpressed in colorectal cancer tissue [3R subtypes are not expressed in all tissues and are expressed to differing degrees in given cell types. In rat hepatocytes, for example, IP3R3 is not expressed, IP3R1 is expressed diffusely in the cytoplasm, and IP3R2 is concentrated in the pericanalicular region [3R subtypes have distinct functions in the hepatocyte’s calcium signaling activity [3R1 and IP3R3 are involved in the epithelial–mesenchymal transition in BC cells, whereas IP3R2 is not [Our data argue in favor of the involvement of all IPr tissue . The IP3r region . These sactivity . The dif2 is not .3R expression and other predictive factors of survival in BC. There were no significant differences in IP3R subtype expression in tissue from BCs smaller than 20 mm. However, the IH expression scores were significantly higher for IP3R2 and IP3R3 than for IP3R1 in tumors larger than 20 mm . IP3R3 expression appears to be correlated with tumor size. The IP3R3 subtype is therefore linked to disease aggressiveness with regard to tumor size—a major factor in the decision to prescribe adjuvant treatment. Based on other prognostic criteria, patients with a small tumor size might not receive chemotherapy. Wallgren et al. showed that tumor size >20 mm was a risk factor for local or remote recurrence [Next, we sought to establish a link between IPcurrence .3R3 is the most highly involved subtype since it (but not IP3R1 or IP3R2) is upregulated in N+ tissue. IP3R3 expression may therefore be linked to a more aggressive profile with regard to the lymph node invasion criterion.Regional lymph node invasion is a major risk factor for recurrence; the greater the number of invaded axillary lymph nodes, the greater the incidence of local or remote recurrence . IP3R3 i3R1 was expressed significantly less than the other two subtypes. These results suggest that IP3R3 expression is associated with the histologic prognosis and, again, more aggressive disease in patients with IBC-NST. Likewise, in tissue with a Ki67 proliferation index above 20%, IP3R1 was expressed significantly less than the other two subtypes. IP3R3, therefore, appears to be involved in IBC-NST with a high proliferation index and is linked to a more aggressive disease profile. The proliferation index and the histologic grade are predictive of a poor prognosis and are taken into account for certain treatment decisions.In SBR grade III IBC-NST, IP3R3 was expressed significantly more than IP3R1 in BCs overexpressing HmRs and HER2, whereas the expression of IP3R2 was significantly higher than that of IP3R1 in TN BC. Moreover, no differences between IP3R2 expression and IP3R3 expression were found in these two tumor subtypes. Overexpression of the HER2 receptor and the absence of HmR and HER2 expression are associated with a worse prognosis [3R3 is associated with more aggressive IBC-NST profiles, as defined by positivity or negativity for HmRs and HER2.Lastly, IPrognosis . Our res3R3 expression appears to be associated with more aggressive IBC-NST profiles. We established that the level of IP3R3 expression was significantly higher in BC tissue than in non-tumor tissue. IP3R2 was not overexpressed in BC tissue but is strongly expressed in all tissues—suggesting that it is essential for the mammary gland’s function. Therefore, our findings suggest that (i) IP3R3 is the subtype most significantly involved in breast carcinogenesis processes, and (ii) IP3R3 expression is linked to a more aggressive BC profile. Hence, IP3R3 might be a specific marker of BC aggressiveness. In contrast to the other two subtypes, IP3R3 is significantly involved in the proliferation and migration of human BC cells [3R3 influences the morphology of BC cells. When IP3R3 expression is low, human BC cells take on a round shape that is much less conducive to migration and invasion [3R3 might be involved in cell migration and invasion, with a role in the BC prognosis. IP3R3 is known to be involved in the carcinogenesis of other cancers. IP3R3 is thus overexpressed in cholangiocarcinoma, where it is involved in cell migration and proliferation [3R3 putative involvement as a prognostic factor in certain cancers.Based on our results, IPBC cells ,27. Furtinvasion . Prolifeferation . It alsoferation . These t3Rs (mainly IP3R3) have a role in apoptosis. In B and T lymphocytes, elevated IP3R3 expression induces more apoptosis [3R3 becomes anti-apoptotic; this is the case in clear cell kidney cancers, where IP3R3 has anti-apoptotic activity and IP3R1 has pro-apoptotic activity [3R expression in human BC cells induces an increase in apoptosis [IPpoptosis ; this ispoptosis  and hepapoptosis . In someactivity . This mipoptosis .3R3′s involvement in overall survival and disease-free survival in BC remains to be defined. If it is proven that a low IP3R3 threshold in an invasive breast tumor is correlated with greater survival, this receptor might eventually become a complementary tool in the decision to initiate (or not) adjuvant treatment. IP3R3 expression could therefore be integrated into genomic-based calculations of the recurrence risk.The current problem in BC management is the absolute necessity to not “over-treat” patients. The latest results from basic research and clinical studies argue in favor of therapeutic de-escalation and personalized medicine . For exa3R3 can be considered a prognostic marker in BC. In the longer term, it might be possible to predict tumor aggressiveness and perhaps select an appropriate adjuvant treatment if the primary tumor strongly expresses IP3R3.In conclusion, our results strongly suggest that IP


A 12-year-old Yorkshire terrier was referred for epileptic seizures and nasal discharge. The fluid was clear and serous. Cerebrospinal fluid (CSF) rhinorrhea was suspected, based on clinical signs and MRI findings. In humans, analysis of nasal secretions to determine the concentration of glucose and brain-type transferrin has been widely used clinically in order to confirm the presence of CSF rhinorrhea. The glucose concentration in the nasal discharge was 74 mg/dL. Serum-type and brain-type isoforms of transferrin were detectable in the nasal sample. The concentration of glucose and brain-type transferrin could be useful for diagnosing CSF rhinorrhea. Cerebrospinal fluid (CSF) rhinorrhea is a type of CSF leakage . CSF leaSuspected or confirmed CSF rhinorrhea has been reported only sporadically in dogs , 8. In cA 12-year-old 1.5 kg entire male Yorkshire terrier was referred with a history of acute onset of seizures 1 day before admission. Generalized seizures occurred seven or eight times a day. Loss of consciousness was noted during seizure, and subsided in less than 1 min. After generalized seizures, post-ictal signs including transient circling and mild ataxia was observed. Nasal discharge was noted. The fluid was clear and serous. Hematology and serum biochemistry results were unremarkable. Mental status was alert during the neurological examination. Mydriasis of the right eye due to adhesion of the iris and the lens was observed. No other abnormalities were found upon neurological examination. Based on these findings, the differential diagnoses were neoplasia, inflammation, idiopathic, anomaly, or vascular disease. The lesion was localized to the cerebrum or diencephalon.CT and MRI were undertaken to examine the cerebrum and diencephalon. Anesthesia was induced by propofol  at a dose of 5.0 mg/kg and was maintained by isoflurane . MRI was performed using a 0.4 T unit . The sequences included T2-weighted images  of transverse and sagittal views, fluid-attenuated inversion recovery  of transverse view, T1-weighted images  of transverse view, and postcontrast T1WI  of transverse view. Brain MRI revealed irregularities in the left cribriform plate compared to the right cribriform plate . Also obStreptococcus sp. was detected in the bacterial culture test. Based on the examination of nasal discharge and on imaging suggesting destruction of the cribriform plate, CSF leakage and meningoencephalitis were suspected.No epileptic fits were observed in the 2 months after phenobarbital was started. No neurological abnormalities were detected. The serous nasal discharge persisted. On the 68th day, CT and MRI were repeated to examine changes in the olfactory recess. No remarkable changes were noted in a CT/MRI scan in the lesion, relative to the previous scan. Cytologic examination of the nasal discharge found many degenerated neutrophils and phagocyted cocci, indicating pyogenic infectious inflammation. The glucose concentration in the nasal discharge of the dog was 74 mg/dL and CSF leakage was suspected, and further analysis was performed to check. Serum and CSF from a healthy dog  were used as controls. This procedure was conducted with the approval of Osaka Prefecture University Animal Care and Use Committee –30. The After antimicrobial treatment , the cytologic evaluation showed non-infectious inflammation. The owner declined surgical treatment to stop CSF leakage. Over the following 5 months, the dog remained normal in its general condition, and epileptic seizures did not worsen. On the 167th day a sudden worsening of its general condition was observed without seizures, and the dog died. No pathological autopsy was performed after death, and the precise cause of death was not identified.There have been only a few reports of diagnosis and treatment of CSF rhinorrhea in dogs and cats , 9. In tIn humans, commonly used modalities for confirming CSF rhinorrhea include CT, MRI, endoscopy, CT and MRI cisternography , 11, 12.Detection of glucose in nasal fluid is a classical method for testing CSF leakage in humans. The normal concentration of glucose in nasal fluid is less than 10 mg/dL, and, a concentration greater than 30 mg/dL glucose suggests severe rhinitis or CSF leakage into the nasal cavity in humans , 17. TheThe most common clinical signs in humans are a leak of clear and watery fluid from the nose and ear, with positional dependency . Most huThere are two main ways of treating CSF leakage into the nasal cavity. These are conservative management and surgical repair. The treatment of CSF rhinorrhea in humans depends on its cause, and surgery is not indicated only in the acute phase after traumatic brain injury . The sucCSF rhinorrhea should be included in the differential diagnosis when persistent nasal discharge and forebrain signs are observed. Detection of nasal glucose and brain-type transferrin would be useful for diagnosing CSF rhinorrhea in dogs.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.The animal study was reviewed and approved by Osaka Prefecture University Animal Care and Use Committee. Written informed consent was obtained from the owners for the participation of their animals in this study.KKi, HN, RK, YN, KKu, TT, and SS assisted with the diagnosis of this case and participated in clinical case management. HN and HA participated in the review and editing of the manuscript. All authors contributed to the article and approved the submitted version.Funding was provided in part by Grant-in-Aid for Scientific Research C (Grant No. 19K06405) from the Japan Society for the Promotion of Sciences.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.