Quantum spin nematic phase in a square-lattice iridate.

Spin nematic is a magnetic analogue of classical liquid crystals, a fourth state of matter exhibiting characteristics of both liquid and solid1,2. Particularly intriguing is a valence-bond spin nematic3-5, in which spins are quantum entangled to form a multipolar order without breaking time-reversal symmetry, but its unambiguous experimental realization remains elusive. Here we establish a spin nematic phase in the square-lattice iridate Sr2IrO4, which approximately realizes a pseudospin one-half Heisenberg antiferromagnet in the strong spin-orbit coupling limit6-9. Upon cooling, the transition into the spin nematic phase at TC ≈ 263 K is marked by a divergence in the static spin quadrupole susceptibility extracted from our Raman spectra and concomitant emergence of a collective mode associated with the spontaneous breaking of rotational symmetries. The quadrupolar order persists in the antiferromagnetic phase below TN ≈ 230 K and becomes directly observable through its interference with the antiferromagnetic order in resonant X-ray diffraction, which allows us to uniquely determine its spatial structure. Further, we find using resonant inelastic X-ray scattering a complete breakdown of coherent magnon excitations at short-wavelength scales, suggesting a many-body quantum entanglement in the antiferromagnetic state10,11. Taken together, our results reveal a quantum order underlying the Néel antiferromagnet that is widely believed to be intimately connected to the mechanism of high-temperature superconductivity12,13.

Structures of Vac8-containing protein complexes reveal the underlying mechanism by which Vac8 regulates multiple cellular processes.

Vac8, a yeast vacuolar protein with armadillo repeats, mediates various cellular processes by changing its binding partners; however, the mechanism by which Vac8 differentially regulates these processes remains poorly understood. Vac8 interacts with Nvj1 to form the nuclear-vacuole junction (NVJ) and with Atg13 to mediate cytoplasm-to-vacuole targeting (Cvt), a selective autophagy-like pathway that delivers cytoplasmic aminopeptidase I directly to the vacuole. In addition, Vac8 associates with Myo2, a yeast class V myosin, through its interaction with Vac17 for vacuolar inheritance from the mother cell to the emerging daughter cell during cell divisions. Here, we determined the X-ray crystal structure of the Vac8-Vac17 complex and found that its interaction interfaces are bipartite, unlike those of the Vac8-Nvj1 and Vac8-Atg13 complexes. When the key amino acids present in the interface between Vac8 and Vac17 were mutated, vacuole inheritance was severely impaired in vivo. Furthermore, binding of Vac17 to Vac8 prevented dimerization of Vac8, which is required for its interactions with Nvj1 and Atg13, by clamping the H1 helix to the ARM1 domain of Vac8 and thereby preventing exposure of the binding interface for Vac8 dimerization. Consistently, the binding affinity of Vac17-bound Vac8 for Nvj1 or Atg13 was markedly lower than that of free Vac8. Likewise, free Vac17 had no affinity for the Vac8-Nvj1 and Vac8-Atg13 complexes. These results provide insights into how vacuole inheritance and other Vac8-mediated processes, such as NVJ formation and Cvt, occur independently of one another.

Bidirectional de novo peptide sequencing using a transformer model.

In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely employed to identify peptide sequences, and numerous tools have been proposed over the past two decades. Recently, deep learning approaches have been introduced for de novo sequencing. Previous methods focused on encoding tandem mass spectra and predicting peptide sequences from the first amino acid onwards. However, when predicting peptides using tandem mass spectra, the peptide sequence can be predicted not only from the first amino acid but also from the last amino acid due to the coexistence of b-ion (or a- or c-ion) and y-ion (or x- or z-ion) fragments in the tandem mass spectra. Therefore, it is essential to predict peptide sequences bidirectionally. Our approach, called NovoB, utilizes a Transformer model to predict peptide sequences bidirectionally, starting with both the first and last amino acids. In comparison to Casanovo, our method achieved an improvement of the average peptide-level accuracy rate of approximately 9.8% across all species.

Bioinspired Fluorine Labeling for 19F NMR-Based Plasma Amine Profiling.

Metabolite profiling serves as a powerful tool that advances our understanding of biological systems, disease mechanisms, and environmental interactions. In this study, we present an approach employing 19F-nuclear magnetic resonance (19F NMR) spectroscopy for plasma amine profiling. This method utilizes a highly efficient and reliable fluorine-labeling reagent, 3,5-difluorosalicylaldehyde, which effectively emulates pyridoxal phosphate, facilitating the formation of Schiff base compounds with primary amines. The fluorine labeling allows for distinct resolution of 19F NMR signals from amine mixtures, leading to precise identification and quantification of amine metabolites in human plasma. This advancement offers valuable tools for furthering metabolomics research.

Exploring the Smoking-Epilepsy Nexus: a systematic review and meta-analysis of observational studies : Smoking and epilepsy.

BACKGROUND: Epilepsy, characterized by recurrent unprovoked seizures, poses significant challenges to affected individuals globally. While several established risk factors for epilepsy exist, the association with cigarette smoking remains debated. This study aims to conduct systematic review and meta-analysis to elucidate the potential association between smoking and the likelihood of epilepsy. METHODS: The search was performed on March 31st, 2023, using the Medline, Embase, Web of Science, Scopus, and ScienceDirect. We included cohort, cross-sectional, and case-control studies in our meta-analysis, conducting subgroup analyses based on smoking history, sex, and epilepsy type to yield specific insights. RESULTS: We identified 2550 studies, of which 17 studies were finally included in this study. The pooled odds ratio of epilepsy was 1.14 (0.96-1.36) in smokers compared to non-smokers. In current smokers compared to non-smokers, the odds ratio was 1.46 (1.13-1.89), while, in former smokers compared to non-smokers, the odds ratio was 1.14 (0.83-1.56). CONCLUSIONS: While the overall association between smoking and epilepsy did not reach statistical significance, a notable association was found among current smokers. The study emphasizes the importance of smoking cessation as a potential preventive measure against epilepsy, especially given the proconvulsive effects of nicotine. Future research should address limitations and explore specific clinical scenarios to enhance our understanding of the complex relationship between cigarette use and epilepsy. SYSTEMATIC REVIEW REGISTRATION: CRD42022342510.

Differences in factors associated with insomnia symptoms between patients with epilepsy with and without depressive symptoms.

OBJECTIVE: To determine if insomnia-related factors differ depending on the presence of depression in patients with epilepsy. METHODS: This cross-sectional multicenter study collected data on depressive symptoms, insomnia symptoms, and excessive daytime sleepiness, which were defined as a Patient Health Questionnaire-9 (PHQ-9) score of ≥ 10, an Insomnia Severity Index (ISI) score of ≥ 15, and an Epworth Sleepiness Scale (ESS) of ≥ 11, respectively. Further, uncontrolled seizures were defined as one or more seizures per month during antiseizure medications treatment. A stepwise logistic regression analysis was conducted, with a logistic regression with interaction terms performed to identify differences in insomnia-related factors depending on depressive symptoms. RESULTS: Of 282 adults with epilepsy (men, 58 %; mean age, 40.4 ± 13.9 years), a PHQ-9 score ≥ 10, an ISI score ≥ 15, an ESS score ≥ 11 were noted in 23.4 % (n = 66), 20.2 % (n = 57), and 12.8 % (n = 36), respectively. More patients with depressive symptoms had an ISI score ≥ 15 (56.1 % vs. 9.3 %; p < 0.001) than those without. In multiple logistic regression, uncontrolled seizures (odds ratio [OR], 4.896; p < 0.01), daytime sleepiness (OR, 5.369; p < 0.05), and a history of psychiatric disorders (OR, 3.971; p < 0.05) were identified as significant factors that were more likely to be associated with an ISI score ≥ 15; however, this was only true in patients without depressive symptoms. In contrast, use of perampanel (OR, 0.282; p < 0.05) was less likely associated, while female sex (OR, 3.178; p < 0.05) was more likely associated with an ISI score ≥ 15 only in patients with depressive symptoms. CONCLUSIONS: Insomnia-related factors in patients with epilepsy may differ between patients with and without depression. Our findings of different insomnia-related factors based on the presence of depression may facilitate the management of patients with epilepsy.

Three-Dimensional Image Visualization under Photon-Starved Conditions Using N Observations and Statistical Estimation.

In this paper, we propose a method for the three-dimensional (3D) image visualization of objects under photon-starved conditions using multiple observations and statistical estimation. To visualize 3D objects under these conditions, photon counting integral imaging was used, which can extract photons from 3D objects using the Poisson random process. However, this process may not reconstruct 3D images under severely photon-starved conditions due to a lack of photons. Therefore, to solve this problem, in this paper, we propose N-observation photon-counting integral imaging with statistical estimation. Since photons are extracted randomly using the Poisson distribution, increasing the samples of photons can improve the accuracy of photon extraction. In addition, by using a statistical estimation method, such as maximum likelihood estimation, 3D images can be reconstructed. To prove our proposed method, we implemented the optical experiment and calculated its performance metrics, which included the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), peak-to-correlation energy (PCE), and the peak sidelobe ratio (PSR).

Image Processing Techniques for Improving Quality of 3D Profile in Digital Holographic Microscopy Using Deep Learning Algorithm.

Digital Holographic Microscopy (DHM) is a 3D imaging technology widely applied in biology, microelectronics, and medical research. However, the noise generated during the 3D imaging process can affect the accuracy of medical diagnoses. To solve this problem, we proposed several frequency domain filtering algorithms. However, the filtering algorithms we proposed have a limitation in that they can only be applied when the distance between the direct current (DC) spectrum and sidebands are sufficiently far. To address these limitations, among the proposed filtering algorithms, the HiVA algorithm and deep learning algorithm, which effectively filter by distinguishing between noise and detailed information of the object, are used to enable filtering regardless of the distance between the DC spectrum and sidebands. In this paper, a combination of deep learning technology and traditional image processing methods is proposed, aiming to reduce noise in 3D profile imaging using the Improved Denoising Diffusion Probabilistic Models (IDDPM) algorithm.

Wafer-Scale Epitaxial Growth of an Atomically Thin Single-Crystal Insulator as a Substrate of Two-Dimensional Material Field-Effect Transistors.

As the electron mobility of two-dimensional (2D) materials is dependent on an insulating substrate, the nonuniform surface charge and morphology of silicon dioxide (SiO2) layers degrade the electron mobility of 2D materials. Here, we demonstrate that an atomically thin single-crystal insulating layer of silicon oxynitride (SiON) can be grown epitaxially on a SiC wafer at a wafer scale and find that the electron mobility of graphene field-effect transistors on the SiON layer is 1.5 times higher than that of graphene field-effect transistors on typical SiO2 films. Microscale and nanoscale void defects caused by heterostructure growth were eliminated for the wafer-scale growth of the single-crystal SiON layer. The single-crystal SiON layer can be grown on a SiC wafer with a single thermal process. This simple fabrication process, compatible with commercial semiconductor fabrication processes, makes the layer an excellent replacement for the SiO2/Si wafer.

Mitogenomic Characterization and Phylogenetic Placement of African Hind, Cephalopholis taeniops: Shedding Light on the Evolution of Groupers (Serranidae: Epinephelinae).

The global exploration of evolutionary trends in groupers, based on mitogenomes, is currently underway. This research extensively investigates the structure of and variations in Cephalopholis species mitogenomes, along with their phylogenetic relationships, focusing specifically on Cephalopholis taeniops from the Eastern Atlantic Ocean. The generated mitogenome spans 16,572 base pairs and exhibits a gene order analogous to that of the ancestral teleost's, featuring 13 protein-coding genes (PCGs), two ribosomal RNA genes (rRNAs), 22 transfer RNA genes (tRNAs), and an AT-rich control region. The mitogenome of C. taeniops displays an AT bias (54.99%), aligning with related species. The majority of PCGs in the mitogenome initiate with the start codon ATG, with the exceptions being COI (GTG) and atp6 (TTG). The relative synonymous codon usage analysis revealed the maximum abundance of leucine, proline, serine, and threonine. The nonsynonymous/synonymous ratios were <1, which indicates a strong negative selection among all PCGs of the Cephalopholis species. In C. taeniops, the prevalent transfer RNAs display conventional cloverleaf secondary structures, except for tRNA-serine (GCT), which lacks a dihydrouracil (DHU) stem. A comparative examination of conserved domains and sequence blocks across various Cephalopholis species indicates noteworthy variations in length and nucleotide diversity. Maximum likelihood, neighbor-joining, and Bayesian phylogenetic analyses, employing the concatenated PCGs and a combination of PCGs + rRNAs, distinctly separate all Cephalopholis species, including C. taeniops. Overall, these findings deepen our understanding of evolutionary relationships among serranid groupers, emphasizing the significance of structural considerations in mitogenomic analyses.

Progressive search in tandem mass spectrometry.

BACKGROUND: High-throughput Proteomics has been accelerated by (tandem) mass spectrometry. However, the slow speed of mass spectra analysis prevents the analysis results from being up-to-date. Tandem mass spectrometry database search requires O(|S||D|) time where S is the set of spectra and D is the set of peptides in a database. With usual values of |S| and |D|, database search is quite time consuming. Meanwhile, the database for search is usually updated every month, with 0.5-2% changes. Although the change in the database is usually very small, it may cause extensive changes in the overall analysis results because individual PSM scores such as deltaCn and E-value depend on the entire search results. Therefore, to keep the search results up-to-date, one needs to perform database search from scratch every time the database is updated, which is very inefficient. RESULTS: Thus, we present a very efficient method to keep the search results up-to-date where the results are the same as those achieved by the normal search from scratch. This method, called progressive search, runs in O(|S||ΔD|) time on average where ΔD is the difference between the old and the new databases. The experimental results show that the progressive search is up to 53.9 times faster for PSM update only and up to 16.5 times faster for both PSM and E-value update. CONCLUSIONS: Progressive search is a novel approach to efficiently obtain analysis results for updated database in tandem mass spectrometry. Compared to performing a normal search from scratch, progressive search achieves the same results much faster. Progressive search is freely available at: https://isa.hanyang.ac.kr/ProgSearch.html .

Electrocatalytic Access to Azetidines via Intramolecular Allylic Hydroamination: Scrutinizing Key Oxidation Steps through Electrochemical Kinetic Analysis.

Azetidines are prominent structural scaffolds in bioactive molecules, medicinal chemistry, and ligand design for transition metals. However, state-of-the-art methods cannot be applied to intramolecular hydroamination of allylic amine derivatives despite their underlying potential as one of the most prevalent synthetic precursors to azetidines. Herein, we report an electrocatalytic method for intramolecular hydroamination of allylic sulfonamides to access azetidines for the first time. The merger of cobalt catalysis and electricity enables the regioselective generation of key carbocationic intermediates, which could directly undergo intramolecular C-N bond formation. The mechanistic investigations including electrochemical kinetic analysis suggest that either the catalyst regeneration by nucleophilic cyclization or the second electrochemical oxidation to access the carbocationic intermediate is involved in the rate-determining step (RDS) of our electrochemical protocol and highlight the ability of electrochemistry in providing ideal means to mediate catalyst oxidation.

Chiral Discrimination of Monosaccharides Derivatized with 2-Fluorophenyl Hydrazine Using 19F NMR Spectroscopy.

Chiral discrimination of monosaccharides holds significant importance, especially given the growing interest of the pharmaceutical industry in their utilization. However, the majority of existing methods has predominantly centered around chromatographic techniques. In this study, we introduce a 19F NMR-based comprehensive approach for chiral analysis specifically tailored for 15 pairs of aldoses. This technique involves employing sugar hydrazones containing fluorine in combination with chiral octahedral gallium and scandium complexes. By utilizing highly sensitive 19F NMR spectroscopy, the fluorine label in the sugar hydrazone enables accurate differentiation between d and l enantiomers. The efficiency of the newly developed method was demonstrated through its successful application in both quantitative and qualitative analyses of mixtures containing various monosaccharides.

Extreme UV Resist Exhibiting Synergism between Chemical and Physical Crosslinking Mechanisms.

Carbon-fluorine bonds in fluorinated molecules can undergo homolytic cleavage reactions when electrons are injected, and the resulting radicals combine to form network structures characterized by reduced solubility. This crosslinking chemistry suggests a new category of patterning materials that function under electron beam (e-beam) and extreme ultraviolet (EUV) lithographic conditions. Although this chemistry enables the production of 50 nm or smaller-sized features of simple fluoroalkylated polymers, it is limited by the need for relatively large amounts of irradiation energy to achieve required solubility changes. Therefore, this study was undertaken to devise a sensitivity-enhancing strategy based on a synergistic combination of radical crosslinking and hydrogen-bonding interactions between highly fluoroalkylated copolymers. An alternating copolymer was synthesized using tert-butoxystyrene and a fluoroalkylated maleimide, the former of which produces active hydrogens through catalytic acidolysis reactions. When the polymer was blended with a catalytic amount of a photoacid generator and subjected to lithographic patterning tests under e-beam and EUV irradiation, the deprotection reactions of tert-butoxy moieties proceeded at room temperature and led to a solubility decrease. We presume the small number of hydroxyl moieties produced formed an intermolecular hydrogen-bonding network, which acted synergistically with the covalent crosslinks generated by C-F bonds. When 30 nm features of copolymer thin films were fabricated by EUV lithography, sensitivity was improved by 25-34% without significant deterioration of pattern quality, especially line-edge roughness. These results demonstrate that EUV resists with improved patterning capabilities can be achieved by combining catalytic acidolysis reactions and noncatalytic crosslinking chemistry.

Sex differences in the relationship between aggression and symptoms of depression and anxiety in adults with refractory focal epilepsy.

PURPOSE: To determine whether sex affects the relationship between aggression and symptoms of depression and anxiety in adults with refractory focal epilepsy. METHODS: This cross-sectional study was conducted in 85 adults with refractory focal seizures, which are defined as one or more seizures recurring per month even when the patient is treated with two or more antiseizure medications. We used the Buss-Perry Aggression Questionnaire (AQ) and the Hospital Anxiety and Depression Scale (HADS) to evaluate aggression and symptoms of depression and anxiety, respectively. We performed multivariate linear regression and analysis of covariance with interaction terms. HADS-depression and HADS-anxiety scores were separately evaluated to avoid multicollinearity between both of them. RESULTS: The HADS-depression and HADS-anxiety scores, male sex, an antiseizure medication load of ≥3, and the use of pregabalin were independently correlated with at least one of the AQ total and subscale scores. These models for depressive and anxiety symptoms explained 34.2% and 32.5%, respectively, of the variance of the AQ total score. Although the AQ total scores did not differ between the sexes, sex significantly affected the relationships between aggression and symptoms of depression and anxiety. Specifically, HADS-depression and HADS-anxiety scores were positively associated with the AQ total scores, especially scores of verbal aggression and anger subtypes, in men but not in women. CONCLUSIONS: These findings support the importance of including anger management and other strategies targeted toward aggression in the development of psychological interventions to reduce anxiety and depression in adults with refractory focal epilepsy. Tailoring those interventions to the needs of males and females will be important to consider. .

Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter.

In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the problem that results are random because Poisson random numbers are temporally and spatially independent. Therefore, in this paper, we apply a technique called Kalman filter to photon-counting integral imaging, which corrects data groups with errors, to improve the visual quality of results. The purpose of this paper is to reduce randomness and improve the accuracy of visualization for results by incorporating the Kalman filter into 3D reconstruction images under extremely low light conditions. Since the proposed method has better structure similarity (SSIM), peak signal-to-noise ratio (PSNR) and cross-correlation values than the conventional method, it can be said that the visualization of low illuminated images can be accurate. In addition, the proposed method is expected to accelerate the development of autonomous driving technology and security camera technology.

Palladium-Catalyzed Hydrosilylation of Unactivated Alkenes and Conjugated Dienes with Tertiary Silanes Controlled by Hemilabile Hybrid P,O Ligand.

Novel P,O-type ligands, N-disulfonyl bicyclic bridgehead phosphorus triamides, were synthesized and utilized in Pd-catalyzed hydrosilylation involving tertiary silanes, unactivated alkenes, and conjugated dienes. The ligand displayed a remarkable level of reactivity for alkene hydrosilylation with tertiary silanes and its use resulted in a significant improvement in the regioselectivity of diene hydrosilylation towards 1,2-hydrosilylation. X-ray crystallographic analysis confirmed the bidentate nature of the ligand, with coordination of phosphorus and oxygen. Control experiments provided evidence for the formation of Pd0 species and the reversibility of Pd-H insertion in the reaction mechanism. Density functional theory (DFT) computations supported the importance of the hemilabile P,O ligand in stabilizing both the rate-determining transition state of Pd-H insertion and the transition state of reductive elimination that determines the regioselectivity.

High Salt Intake Recruits Tonic Activation of NR2D Subunit-Containing Extrasynaptic NMDARs in Vasopressin Neurons.

In addition to producing a classical excitatory postsynaptic current via activation of synaptic NMDA receptors (NMDARs), glutamate in the brain also induces a tonic NMDAR current (INMDA) via activation of extrasynaptic NMDARs (eNMDARs). However, since Mg2+ blocks NMDARs in nondepolarized neurons, the potential contribution of eNMDARs to the overall neuronal excitatory/inhibitory (E/I) balance remains unknown. Here, we demonstrate that chronic (7 d) salt loading (SL) recruited NR2D subunit-containing NMDARs to generate an Mg2+-resistant tonic INMDA in nondepolarized [Vh (holding potential) -70 mV] vasopressin (VP; but not oxytocin) supraoptic nucleus (SON) neurons in male rodents. Conversely, in euhydrated (EU) and 3 d SL mice, Mg2+-resistant tonic INMDA was not observed. Pharmacological and genetic intervention of NR2D subunits blocked the Mg2+-resistant tonic INMDA in VP neurons under SL conditions, while an NR2B antagonist unveiled Mg2+-sensitive tonic INMDA but not Mg2+-resistant tonic INMDA In the EU group VP neurons, an Mg2+-resistant tonic INMDA was not generated by increased ambient glutamate or treatment with coagonists (e.g., d-serine and glycine). Chronic SL significantly increased NR2D expression but not NR2B expression in the SON relative to the EU group or after 3 d under SL conditions. Finally, Mg2+-resistant tonic INMDA selectively upregulated neuronal excitability in VP neurons under SL conditions, independent of ionotropic GABAergic input. Our results indicate that the activation of NR2D-containing NMDARs constitutes a novel mechanism that generates an Mg2+-resistant tonic INMDA in nondepolarized VP neurons, thus causing an E/I balance shift in VP neurons to compensate for the hormonal demands imposed by a chronic osmotic challenge.SIGNIFICANCE STATEMENT The hypothalamic supraoptic nucleus (SON) consists of two different types of magnocellular neurosecretory cells (MNCs) that synthesize and release the following two peptide hormones: vasopressin (VP), which is necessary for regulation of fluid homeostasis; and oxytocin (OT), which plays a major role in lactation and parturition. NMDA receptors (NMDARs) play important roles in shaping neuronal firing patterns and hormone release from the SON MNCs in response to various physiological challenges. Our results show that prolonged (7 d) salt loading generated a Mg2+-resistant tonic NMDA current mediated by NR2D subunit-containing receptors, which efficiently activated nondepolarized VP (but not OT) neurons. Our findings support the hypothesis that NR2D subunit-containing NMDARs play an important adaptive role in adult brain in response to a sustained osmotic challenge.

False discovery rate estimation using candidate peptides for each spectrum.

BACKGROUND: False discovery rate (FDR) estimation is very important in proteomics. The target-decoy strategy (TDS), which is often used for FDR estimation, estimates the FDR under the assumption that when spectra are identified incorrectly, the probabilities of the spectra matching the target or decoy peptides are identical. However, no spectra matching target or decoy peptide probabilities are identical. We propose cTDS (target-decoy strategy with candidate peptides) for accurate estimation of the FDR using the probability that the spectrum is identified incorrectly as a target or decoy peptide. RESULTS: Most spectrum cases result in a probability of having the spectrum identified incorrectly as a target or decoy peptide of close to 0.5, but only about 1.14-4.85% of the total spectra have an exact probability of 0.5. We used an entrapment sequence method to demonstrate the accuracy of cTDS. For fixed FDR thresholds (1-10%), the false match rate (FMR) in cTDS is closer than the FMR in TDS. We compared the number of peptide-spectrum matches (PSMs) obtained with TDS and cTDS at a 1% FDR threshold with the HEK293 dataset. In the first and third replications, the number of PSMs obtained with cTDS for the reverse, pseudo-reverse, shuffle, and de Bruijn databases exceeded those obtained with TDS (about 0.001-0.132%), with the pseudo-shuffle database containing less compared to TDS (about 0.05-0.126%). In the second replication, the number of PSMs obtained with cTDS for all databases exceeds that obtained with TDS (about 0.013-0.274%). CONCLUSIONS: When spectra are actually identified incorrectly, most probabilities of the spectra matching a target or decoy peptide are not identical. Therefore, we propose cTDS, which estimates the FDR more accurately using the probability of the spectrum being identified incorrectly as a target or decoy peptide.

Single cell lineage reconstruction using distance-based algorithms and the R package, DCLEAR.

BACKGROUND: DCLEAR is an R package used for single cell lineage reconstruction. The advances of CRISPR-based gene editing technologies have enabled the prediction of cell lineage trees based on observed edited barcodes from each cell. However, the performance of existing reconstruction methods of cell lineage trees was not accessed until recently. In response to this problem, the Allen Institute hosted the Cell Lineage Reconstruction Dream Challenge in 2020 to crowdsource relevant knowledge from across the world. Our team won sub-challenges 2 and 3 in the challenge competition. RESULTS: The DCLEAR package contained the R codes, which was submitted in response to sub-challenges 2 and 3. Our method consists of two steps: (1) distance matrix estimation and (2) the tree reconstruction from the distance matrix. We proposed two novel methods for distance matrix estimation as outlined in the DCLEAR package. Using our method, we find that two of the more sophisticated distance methods display a substantially improved level of performance compared to the traditional Hamming distance method. DCLEAR is open source and freely available from R CRAN and from under the GNU General Public License, version 3. CONCLUSIONS: DCLEAR is a powerful resource for single cell lineage reconstruction.