PS2MS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PS2MS, an AI-powered predictive system designed specifically to address the limitations of identifying the emergence of unidentified novel illicit drugs. PS2MS builds a synthetic NPS database by enumerating feasible derivatives of known substances and uses deep learning to generate mass spectra and chemical fingerprints. When the mass spectrum of an analyte does not match any known reference, PS2MS simultaneously examines the chemical fingerprint and mass spectrum against the putative NPS database using integrated metrics to deduce possible identities. Experimental results affirm the effectiveness of PS2MS in identifying cathinone derivatives within real evidence specimens, signifying its potential for practical use in identifying emerging drugs of abuse for researchers and forensic experts.

Full-Privacy Secured Search Engine Empowered by Efficient Genome-Mapping Algorithms.

Since the 90s, keyword-based search engines have been the only option for people to locate relevant web content through a simple query comprising one to a few keywords. These engines, whether free or paid, retained users' search queries and preferences, often to deliver targeted ads. Additionally, user-uploaded articles for plagiarism detection can further be stored as part of service providers' expanding databases for profit. Essentially, users could not search without exposing their queries to these providers. We present a new solution here: a method for searching the internet using a full article as a query without disclosing the content. Our Sapiens Aperio Veritas Engine (S.A.V.E.) uses an encoding scheme and an FM-index search, borrowed from next-generation human genome sequencing. Each word in a user's query is transformed into one of 12 "amino acids" to create a pseudo-biological sequence (PBS) on the user's device. Plagiarism checks are done by users submitting their locally created PBSs to our cloud service. This detects identical content in our database, which includes all English and Chinese Wikipedia articles and Open Access journals up to April 2021. PBSs, longer than 12 "amino acids", show accurate results with less than 0.8% false positives. Performance-wise, S.A.V.E. runs at a similar genome-mapping speed as Bowtie and is >5 orders faster than BLAST. With both standard and private modes, S.A.V.E. offers a revolutionary, privacy-first search and plagiarism check system. We believe this sets an exciting precedent for future search engines prioritizing user confidentiality. S.A.V.E. can be accessed at https://dyn.life.nthu.edu.tw/SAVE/.

An FM-Index Based High-Throughput Memory-Efficient FPGA Accelerator for Paired-End Short-Read Mapping.

This article presents an Ferragina-Manzini index (FM-index) based paired-end short-read mapping hardware accelerator. Four techniques are proposed to significantly reduce the number of memory accesses and operations to improve the throughput. First, an interleaved data structure is proposed to reduce the processing time by 51.8% by leveraging the data locality. Second, the boundaries of possible mapping location candidates can be retrieved within only one memory access by constructing a lookup table along with the FM-index. This reduces the number of DRAM accesses by 60% with only a 64 MB memory overhead. Third, an additional step is added to skip the time-consuming repetitive location candidates filtering conditionally, avoiding unnecessary operations. Lastly, an early termination method is proposed to terminate the mapping process if any location candidate with a high enough alignment score is detected, greatly decreasing the execution time. Overall, the computation time is reduced by 92.6% with only a 2% memory overhead in DRAM. The proposed methods are realized on a Xilinx Alveo U250 FPGA. The proposed FPGA accelerator processes 1,085,812,766 short-reads from the U.S. Food and Drug Administration (FDA) dataset within 35.4 minutes at 200 MHz. It achieves a 1.7-to-18.6× higher throughput and the highest 99.3% accuracy by exploiting the paired-end short-read mapping, compared to state-of-the-art FPGA-based designs.

MiR34 contributes to spinal muscular atrophy and AAV9-mediated delivery of MiR34a ameliorates the motor deficits in SMA mice.

Spinal muscular atrophy (SMA) is a neurodegenerative disease characterized by the selective loss of spinal motor neurons (MNs) and concomitant muscle weakness. Mutation of SMN1 is known to cause SMA, and restoring SMN protein levels via antisense oligonucleotide treatment is effective for ameliorating symptoms. However, this approach is hindered by exorbitant costs, invasive procedures, and poor treatment responses of some patients. Here, we seek to circumvent these hurdles by identifying reliable biomarkers that could predict treatment efficacy. We uncovered that MiR34 exhibits consistent downregulation during SMA progression in both human and rodent contexts. Importantly, Mir34 family-knockout mice display axon swelling and reduced neuromuscular junction (NMJ) endplates, recapitulating SMA pathology. Introducing MiR34a via scAAV9 improved the motor ability of SMNΔ7 mice, possibly by restoring NMJ endplate size. Finally, we observed a consistent decreasing trend in MiR34 family expression in the cerebrospinal fluid (CSF) of type I SMA patients during the loading phase of nusinersen treatment. Baseline CSF MiR34 levels before nusinersen injection proved predictive of patient motor skills 1 year later. Thus, we propose that MiR34 may serve as a biomarker of SMA since it is associated with the pathology and can help evaluate the therapeutic effects of nusinersen.

Thermogravimetry combined with electrospray and atmospheric pressure chemical ionization mass spectrometry for characterization of synthetic polymers.

RATIONALE: Thermogravimetry (TG) combined with electrospray and atmospheric chemical ionization (ESI+APCI) mass spectrometry (MS) was developed to rapidly characterize thermal decomposition products of synthetic polymers and plastic products. The ESI-based TG-MS method is useful for characterizing thermally labile, nonvolatile, and polar compounds over an extensive mass range; and the APCI-based TG-MS counterpart is useful for characterizing volatile and nonpolar compounds. Both polar and nonpolar compounds can be simultaneously detected by ESI+APCI-based TG-MS. METHODS: Analytes with different volatility were produced from TG operated at different temperatures, which were delivered through a heated stainless-steel tube to the ESI+APCI source where they reacted with the primary charged species generated from electrospray and atmospheric pressure chemical ionization (ESI+APCI) of solvent and nitrogen. The analyte ions were then detected by an ion trap mass spectrometer. RESULTS: A semi-volatile PEG 600 standard was used as the sample and protonated and sodiated molecular ions together with adduct ions including [(PEG)n + 15]+ , [(PEG)n + 18]+ , and [(PEG)n + 29]+ were detected by TG-ESI+APCI-MS. The technique was further utilized to characterize thermal decomposition products of nonvolatile polypropylene glycol (PPG) and polystyrene (PS) standards, as well as a PS-made water cup and coffee cup lid. The characteristic fragments of PPG and PS with mass differences of 58 and 104 between respective ion peaks were detected at the maximum decomposition temperature (Tmax ). CONCLUSIONS: The information obtained from the TG-ESI+APCI-MS analysis is useful in rapidly distinguishing different types of polymers and their products. In addition, the signals of the additives in the polymer products, including antioxidants and plasticizers, were also detected before the TG temperature reached Tmax .

Estimating intraclonal heterogeneity and subpopulation changes from bulk expression profiles in CMap.

The connectivity among signatures upon perturbations curated in the CMap library provides a valuable resource for understanding therapeutic pathways and biological processes associated with the drugs and diseases. However, because of the nature of bulk-level expression profiling by the L1000 assay, intraclonal heterogeneity and subpopulation compositional change that could contribute to the responses to perturbations are largely neglected, hampering the interpretability and reproducibility of the connections. In this work, we proposed a computational framework, Premnas, to estimate the abundance of undetermined subpopulations from L1000 profiles in CMap directly according to an ad hoc subpopulation representation learned from a well-normalized batch of single-cell RNA-seq datasets by the archetypal analysis. By recovering the information of subpopulation changes upon perturbation, the potentials of drug-resistant/susceptible subpopulations with CMap L1000 were further explored and examined. The proposed framework enables a new perspective to understand the connectivity among cellular signatures and expands the scope of the CMAP and other similar perturbation datasets limited by the bulk profiling technology.

Associations of Chinese Herbal Medicine Use with the Risks of Acute Exacerbation and Mortality in Patients with Chronic Obstructive Pulmonary Disease: A Nationwide Retrospective Cohort Study.

Objectives: This study aimed to assess the correlation of exacerbation and the mortality rate in patients with chronic obstructive pulmonary disease (COPD) between biomedical treatments with or without Chinese herbal medicine (CHM) as an adjunct. Design: A total of 81,261 COPD patients were identified from the National Health Insurance Research Database in Taiwan between 2001 and 2012. After screening and matching, 3176 COPD patients were included in the study. Statistical analyses were performed to assess the differences in the baseline characteristics. The authors used the Cox proportional hazard regression analysis to calculate the risks of mortality and hospitalization due to acute exacerbation of COPD within 1 year between a CHM user cohort and non-CHM user cohort. The cumulative incidence of mortality in COPD patients with or without CHM treatment was calculated by the Kaplan-Meier method. Results: COPD patients in the CHM user cohort demonstrated a significantly lower risk of mortality (p < 0.001) and acute exacerbation (p < 0.05), compared with the non-CHM user cohort. In addition, the CHM users exhibited a reduced cumulative incidence of mortality compared with the non-CHM user cohort (p < 0.001). Xiao Qing Long Tang and Fritillariae thunbergii were the most common Chinese herbal formula and single Chinese herb prescribed for COPD patients. Conclusion: Combining CHM with biomedical treatment might reduce the risk of acute exacerbation and incidence of mortality in patients with COPD.

EARRINGS: an efficient and accurate adapter trimmer entails no a priori adapter sequences.

MOTIVATION: Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e. adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. RESULTS: Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e. EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. AVAILABILITY AND IMPLEMENTATION: EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenetic Regulation of WNT3A Enhancer during Regeneration of Injured Cortical Neurons.

Traumatic brain injury is known to reprogram the epigenome. Chromatin immunoprecipitation-sequencing of histone H3 lysine 27 acetylation (H3K27ac) and tri-methylation of histone H3 at lysine 4 (H3K4me3) marks was performed to address the transcriptional regulation of candidate regeneration-associated genes. In this study, we identify a novel enhancer region for induced WNT3A transcription during regeneration of injured cortical neurons. We further demonstrated an increased mono-methylation of histone H3 at lysine 4 (H3K4me1) modification at this enhancer concomitant with a topological interaction between sub-regions of this enhancer and with promoter of WNT3A gene. Together, this study reports a novel mechanism for WNT3A gene transcription and reveals a potential therapeutic intervention for neuronal regeneration.

Ash2l interacts with Oct4-stemness circuitry to promote super-enhancer-driven pluripotency network.

Pluripotency and cell fates can be modulated through the regulation of super-enhancers; however, the underlying mechanisms are unclear. Here, we showed a novel mechanism in which Ash2l directly binds to super-enhancers of several stemness genes to regulate pluripotency and self-renewal in pluripotent stem cells. Ash2l recruits Oct4/Sox2/Nanog (OSN) to form Ash2l/OSN complex at the super-enhancers of Jarid2, Nanog, Sox2 and Oct4, and further drives enhancer activation, upregulation of stemness genes, and maintains the pluripotent circuitry. Ash2l knockdown abrogates the OSN recruitment to all super-enhancers and further hinders the enhancer activation. In addition, CRISPRi/dCas9-mediated blocking of Ash2l-binding motifs at these super-enhancers also prevents OSN recruitment and enhancer activation, validating that Ash2l directly binds to super-enhancers and initiates the pluripotency network. Transfection of Ash2l with W118A mutation to disrupt Ash2l-Oct4 interaction fails to rescue Ash2l-driven enhancer activation and pluripotent gene upregulation in Ash2l-depleted pluripotent stem cells. Together, our data demonstrated Ash2l formed an enhancer-bound Ash2l/OSN complex that can drive enhancer activation, govern pluripotency network and stemness circuitry.

Two-photon STED nanoscopy realizing 100-nm spatial resolution utilizing high-peak-power sub-nanosecond 655-nm pulses.

We developed two-photon excitation stimulated emission depletion (STED) nanoscopy using high-peak-power sub-nanosecond 655-nm pulses. The STED pulse exhibited ideal optical properties and sufficient pulse energy to realize a 70-nm spatial resolution in the compact setup with electrically controllable components. For biological applications, we screened suitable fluorescent dyes or proteins and realized the sub-100 nm spatial resolution imaging of presynaptic protein clusters in fixed primary cultured neurons without severe photobleaching. We expect this method to enable visualization of ultrastructures and the cluster dynamics of biomolecules representing physiological functions in living cells and tissue.

Dlk1-Dio3 locus-derived lncRNAs perpetuate postmitotic motor neuron cell fate and subtype identity.

The mammalian imprinted Dlk1-Dio3 locus produces multiple long non-coding RNAs (lncRNAs) from the maternally inherited allele, including Meg3 (i.e., Gtl2) in the mammalian genome. Although this locus has well-characterized functions in stem cell and tumor contexts, its role during neural development is unknown. By profiling cell types at each stage of embryonic stem cell-derived motor neurons (ESC~MNs) that recapitulate spinal cord development, we uncovered that lncRNAs expressed from the Dlk1-Dio3 locus are predominantly and gradually enriched in rostral motor neurons (MNs). Mechanistically, Meg3 and other Dlk1-Dio3 locus-derived lncRNAs facilitate Ezh2/Jarid2 interactions. Loss of these lncRNAs compromises the H3K27me3 landscape, leading to aberrant expression of progenitor and caudal Hox genes in postmitotic MNs. Our data thus illustrate that these lncRNAs in the Dlk1-Dio3 locus, particularly Meg3, play a critical role in maintaining postmitotic MN cell fate by repressing progenitor genes and they shape MN subtype identity by regulating Hox genes.

When a gene is active, its DNA sequence is 'transcribed' to form a molecule of RNA. Many of these RNAs act as templates for making proteins. But for some genes, the protein molecules are not their final destinations. Their RNA molecules instead help to control gene activity, which can alter the behaviour or the identity of a cell. For example, experiments performed in individual cells suggest that so-called long non-coding RNAs (or lncRNAs for short) guide how stem cells develop into different types of mature cells. However, it is not clear whether lncRNAs play the same critical role in embryos.Yen et al. used embryonic stem cells to model how motor neurons develop in the spinal cord of mouse embryos. This revealed that motor neurons produce large amounts of a specific group of lncRNAs, particularly one called Meg3. Further experiments showed that motor neurons in mouse embryos that lack Meg3 do not correctly silence a set of genes called the Hox genes, which are crucial for laying out the body plans of many different animal embryos. These neurons also incorrectly continue to express genes that are normally active in an early phase of the stem-like cells that make motor neurons.There is wide interest in how lncRNAs help to regulate embryonic development. With this new knowledge of how Meg3 regulates the activity of Hox genes in motor neurons, research could now be directed toward investigating whether lncRNAs help other tissues to develop in a similar way.

Advanced easySTED microscopy based on two-photon excitation by electrical modulations of light pulse wavefronts.

We developed a compact stimulated emission depletion (STED) two-photon excitation microscopy that utilized electrically controllable components. Transmissive liquid crystal devices inserted directly in front of the objective lens converted the STED light into an optical vortex while leaving the excitation light unaffected. Light pulses of two different colors, 1.06 and 0.64 µm, were generated by laser diode-based light sources, and the delay between the two pulses was flexibly controlled so as to maximize the fluorescence suppression ratio. In our experiments, the spatial resolution of this system was up to three times higher than that obtained without STED light irradiation, and we successfully visualize the fine microtubule network structures in fixed mammalian cells without causing significant photo-damage.

Identifying Regions Enriched in a ChIP-seq Data Set (Peak Finding).

This protocol demonstrates how to use MACS software to call peaks in a ChIP-seq data set. MACS is one of the most widely used peak-calling programs. The protocol describes how to run MACS in a UNIX environment and on Galaxy and how to extract the sequences of ±50 bp around the summits of the 500 MACS peaks with the most significant P values.

Analysis of Microarray and RNA-seq Expression Profiling Data.

Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple experiments spanning a variety of cell types, treatments, or environmental conditions. Expression profiling is accomplished by assaying mRNA levels with microarrays or next-generation sequencing technologies (RNA-seq). This introduction describes normalization and analysis of data generated from microarray or RNA-seq experiments.

Motif Finding.

Here we provide an introduction to sequence motifs, including prediction of transcription factor-binding sites and general approaches to finding motifs enriched in a set of regulatory sequences.

Peak-Finding Algorithms.

Microarray and next-generation sequencing technologies have greatly expedited the discovery of genomic DNA that can be enriched using various biochemical methods. Chromatin immunoprecipitation (ChIP) is a general method for enriching chromatin fragments that are specifically recognized by an antibody. The resulting DNA fragments can be assayed by microarray (ChIP-chip) or sequencing (ChIP-seq). This introduction focuses on ChIP-seq data analysis. The first step of analyzing ChIP-seq data is identifying regions in the genome that are enriched in a ChIP sample; these regions are called peaks.

Discovering cis-Regulatory Motifs.

This protocol describes a suite of tools for motif finding, using cis-regulatory motifs as an example. The first part of this protocol demonstrates the use of MEME (ab initio motif discovery), JASPAR (a motif database), Clover (searching for enriched known motifs), and MAST (scanning a sequence for motif sites) on a set of computationally predicted CREB-binding sequences downloaded from the UCSC Table Browser. The second part of the protocol shows how to use MEME-ChIP, an integrated suite of tools for analyzing ChIP-seq data, to discover motifs in STAT1 ChIP-seq peaks and compare them with known motifs in the JASPAR database.