Technical review of endoscopic ultrasound-guided drainage/anastomosis and trans-endosonographically created route procedures for the treatment of pancreatic diseases.

Endoscopic ultrasound (EUS)-guided pancreatic duct drainage includes two procedures: EUS-guided drainage/anastomosis (EUS-D/A) and trans-papillary drainage with EUS-assisted pancreatic rendezvous. EUS-guided pancreatogastrostomy is the most common EUS-D/A procedure and is recommended as a salvage procedure in cases in which endoscopic retrograde cholangiopancreatography fails or is difficult. However, initial EUS-D/A is performed in patients with surgically altered anatomy at our institution. It is one of the most difficult interventional EUS procedures and has a high incidence of adverse events. The technical difficulties differ according to etiology, and the incidence of adverse events varies between initial EUS-D/A and subsequent trans-endosonographically/EUS-guided created route procedures. Hence, it is important to meticulously prepare a procedure based on the patient's condition and the available devices. The technical difficulties in EUS-D/A include: (1) determination of the puncture point, (2) selection of a puncture needle and guidewire, (3) guidewire manipulation, and (4) dilation of the puncture route and stenting. Proper technical procedures are important to increase the success rate and reduce the incidence and severity of adverse events. The complexity of EUS-D/A is also contingent on the severity of pancreatic fibrosis and stricture. In post-pancreatectomy cases, determination of the puncture site is important for success because of the remnant pancreas. Trans-endosonographically/EUS-guided created route procedures following initial EUS-D/A are also important for achieving the treatment goal. This article focuses on effective strategies for initial EUS-D/A, based on the etiology and condition of the pancreas. We mainly discuss EUS-D/A, including its indications, techniques, and success-enhancing strategies.

Toward Increasing the Credibility of RNA Design.

In the problem of RNA design, also known as inverse folding, RNA sequences are predicted that achieve the desired secondary structure at the lowest possible free energy and under certain constraints. The designed sequences have applications in synthetic biology and RNA-based nanotechnologies. There are also known cases of the successful use of inverse folding to discover previously unknown noncoding RNAs. Several computational methods have been dedicated to the problem of RNA design. They differ by algorithm and additional parameters, e.g., those determining the goal function in the sequence optimization process. Users can obtain many promising RNA sequences quite easily. The more difficult issue is to critically evaluate them and select the most favorable and reliable sequence that form1s the expected RNA structure. The latter problem is addressed in this paper. We propose an RNA design protocol extended to include sequence evaluation, for which a 3D structure is used. Experiments show that the accuracy of RNA design can be improved by adding a 3D structure prediction and analysis step.

gRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity. In this tutorial, we present gRNAde, a geometric RNA design pipeline operating on sets of 3D RNA backbone structures to design sequences that explicitly account for RNA 3D structure and dynamics. gRNAde is a graph neural network that uses an SE (3) equivariant encoder-decoder framework for generating RNA sequences conditioned on backbone structures where the identities of the bases are unknown. We demonstrate the utility of gRNAde for fixed-backbone re-design of existing RNA structures of interest from the PDB, including riboswitches, aptamers, and ribozymes. gRNAde is more accurate in terms of native sequence recovery while being significantly faster compared to existing physics-based tools for 3D RNA inverse design, such as Rosetta.

2D Janus carrier-enabled trojan horse: Gallium delivery for the sequential therapy of biofilm associated infection.

Biofilm-associated infections (BAIs) continue to pose a major challenge in the medical field. Nanomedicine, in particular, promises significant advances in combating BAIs through the introduction of a variety of nanomaterials and nano-antimicrobial strategies. However, studies to date have primarily focused on the removal of the bacterial biofilm and neglect the subsequent post-biofilm therapeutic measures for BAIs, rendering pure anti-biofilm strategies insufficient for the holistic recovery of affected patients. Herein, we construct an emerging dual-functional composite nanosheet (SiHx@Ga) that responds to pHs fluctuation in the biofilm microenvironment to enable a sequential therapy of BAIs. In the acidic environment of biofilm, SiHx@Ga employs the self-sensitized photothermal Trojan horse strategy to effectively impair the reactive oxygen species (ROS) defense system while triggering oxidative stress and lipid peroxidation of bacteria, engendering potent antibacterial and anti-biofilm effects. Surprisingly, in the post-treatment phase, SiHx@Ga adsorbs free pathogenic nucleic acids released after biofilm destruction, generates hydrogen with ROS-scavenging and promotes macrophage polarization to the M2 type, effectively mitigating damaging inflammatory burst and promoting tissue healing. This well-orchestrated strategy provides a sequential therapy of BAIs by utilizing microenvironmental variations, offering a conceptual paradigm shift in the field of nanomedicine anti-infectives.

Micro-C Analysis Workflow Using Pairtools and Juicer.

Three-dimensional (3D) chromosome structures are closely related to various chromosomal functions, and deep analysis of the structures is crucial for the elucidation of the functions. In recent years, chromosome conformation capture (3C) techniques combined with next-generation sequencing analysis have been developed to comprehensively reveal 3D chromosome structures. Micro-C is one such method that can detect the structures at nucleosome resolution. In this chapter, I provide a basic method for Micro-C analysis. I present and discuss a series of data analyses ranging from mapping to basic downstream analyses, including loop detection.

Exploring Contact Distance Distributions with Google Colaboratory.

Hi-C and Micro-C are the three-dimensional (3D) genome assays that use high-throughput sequencing. In the analysis, the sequenced paired-end reads are mapped to a reference genome to generate a two-dimensional contact matrix for identifying topologically associating domains (TADs), chromatin loops, and chromosomal compartments. On the other hand, the distance distribution of the paired-end mapped reads also provides insight into the 3D genome structure by highlighting global contact frequency patterns at distances indicative of loops, TADs, and compartments. This chapter presents a basic workflow for visualizing and analyzing contact distance distributions from Hi-C data. The workflow can be run on Google Colaboratory, which provides a ready-to-use Python environment accessible through a web browser. The notebook that demonstrates the workflow is available in the GitHub repository at https://github.com/rnakato/Springer_contact_distance_plot.

CWL-Based Analysis Pipeline for Hi-C Data: From FASTQ Files to Matrices.

Over a decade has passed since the development of the Hi-C method for genome-wide analysis of 3D genome organization. Hi-C utilizes next-generation sequencing (NGS) technology to generate large-scale chromatin interaction data, which has accumulated across a diverse range of species and cell types, particularly in eukaryotes. There is thus a growing need to streamline the process of Hi-C data analysis to utilize these data sets effectively. Hi-C generates data that are much larger compared to other NGS techniques such as chromatin immunoprecipitation sequencing (ChIP-seq) or RNA-seq, making the data reanalysis process computationally expensive. In an effort to bridge this resource gap, the 4D Nucleome (4DN) Data Portal has reanalyzed approximately 600 Hi-C data sets, allowing users to access and utilize the analyzed data. In this chapter, we provide detailed instructions for the implementation of the common workflow language (CWL)-based Hi-C analysis pipeline adopted by the 4DN Data Portal ecosystem. This reproducible and portable pipeline generates standard Hi-C contact matrices in formats such as .hic or .mcool from FASTQ files. It enables users to output their own Hi-C data in the same format as those registered in the 4DN Data portal, facilitating comparative analysis using data registered in the portal. Our custom-made scripts are available on GitHub at https://github.com/kuzobuta/4dn_cwl_pipeline .

Step-by-Step Protocol to Generate Hi-C Contact Maps Using the rfy_hic2 Pipeline.

The Hi-C method has emerged as an indispensable tool for analyzing the 3D organization of the genome, becoming increasingly accessible and frequently utilized in chromatin research. To effectively leverage 3D genomics data obtained through advanced technologies, it is crucial to understand what processes are undertaken and what aspects require special attention within the bioinformatics pipeline. This protocol aims to demystify the Hi-C data analysis process for field newcomers. In a step-by-step manner, we describe how to process Hi-C data, from the initial sequencing of the Hi-C library to the final visualization of Hi-C contact data as heatmaps. Each step of the analysis is clearly explained to ensure an understanding of the procedures and their objectives. By the end of this chapter, readers will be equipped with the knowledge to transform raw Hi-C reads into informative visual representations, facilitating a deeper comprehension of the spatial genomic structures critical to cellular functions.

Analysis and Visualization of Multiple Hi-C and Micro-C Data with CustardPy.

Three-dimensional (3D) genome structure plays crucial roles in biological processes and disease pathogenesis. Hi-C and Micro-C, well-established methods for 3D genome analysis, can identify a variety of 3D genome structures. However, selecting appropriate pipelines and tools for the analysis and setting up the required computing environment can sometimes pose challenges. To address this, we have introduced CustardPy, a Docker-based pipeline specifically designed for 3D genome analysis. CustardPy is designed to compare and evaluate multiple samples and wraps several existing tools to cover the entire workflow from FASTQ mapping to visualization. In this chapter, we demonstrate how to analyze and visualize Hi-C data using CustardPy and introduce several 3D genome features observed in Hi-C data.

4D Genome Analysis Using PHi-C2.

Hi-C methods reveal 3D genome features but lack correspondence to dynamic chromatin behavior. PHi-C2, Python software, addresses this gap by transforming Hi-C data into polymer models. After the optimization algorithm, it enables us to calculate 3D conformations and conduct dynamic simulations, providing insights into chromatin dynamics, including the mean-squared displacement and rheological properties. This chapter introduces PHi-C2 usage, offering a tutorial for comprehensive 4D genome analysis.

Processing and Visualization of Protec-Seq Data for the Generation of Calibrated, Genome-Wide Double Double-Strand Break (dDSB) Maps.

This chapter describes the computational pipeline for the processing and visualization of Protec-Seq data, a method for purification and genome-wide mapping of double-stranded DNA protected by a specific protein at both ends. In the published case, the protein of choice was Saccharomyces cerevisiae Spo11, a conserved topoisomerase-like enzyme that makes meiotic double-strand breaks (DSBs) to initiate homologous recombination, ensuring proper segregation of homologous chromosomes and fertility. The isolated DNA molecules were thus termed double DSB (dDSB) fragments and were found to represent 34 to several hundred base-pair long segments that are generated by Spo11 and are enriched at DSB hotspots, which are sites of topological stress. In order to allow quantitative comparisons between dDSB profiles across experiments, we implemented calibrated chromatin immunoprecipitation sequencing (ChIP-Seq) using the meiosis-competent yeast species Saccharomyces kudriavzevii as calibration strain. Here, we provide a detailed description of the computational methods for processing, analyzing, and visualizing Protec-Seq data, comprising the download of the raw data, the calibrated genome-wide alignments, and the scripted creation of either arc plots or Hi-C-style heatmaps for the illustration of chromosomal regions of interest. The workflow is based on Linux shell scripts (including wrappers for publicly available, open-source software) as well as R scripts and is highly customizable through its modular structure.

An electrochemical sensor based on 2D Zn-MOFs and 2D C-Ti3C2Tx composite materials for rapid and direct detection of various foodborne pathogens.

Rapid screening for foodborne pathogens is crucial for food safety. A rapid and one-step electrochemical sensor has been developed for the detection of Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Salmonella typhimurium (S. typhimurium). Through the construction of aptamer/two-dimensional carboxylated Ti3C2Tx (2D C-Ti3C2Tx)/two-dimensional Zn-MOF (2D Zn-MOF) composites, the recognition elements, signal tags, and signal amplifiers are integrated on the electrode surface. Pathogens are selectively captured using the aptamer, which increases the impedance of the electrode surface，leads to a decrease in the 2D Zn-MOF current. Bacteria can be rapidly quantified using a one-step detection method and the replacement of aptamers. The detection limits for E. coli, S. aureus, and S. typhimurium are 6, 5, and 5 CFU·mL-1, respectively. The sensor demonstrated reliable detection capabilities in real-sample testing. Therefore, the one-step sensor based on the 2D Zn-MOF and 2D C-Ti3C2Tx has significant application value in the detection of foodborne pathogens.

Analysis of Forsythia suspensa fruit and leaf extracts using UHPLC-Q-Exactive-Orbitrap/MS: In vivo antioxidant activity on D-galactose-induced aging mice.

Making health-enhancing tea from Forsythia suspensa leaves has been a tradition of Chinese folk culture for centuries. However, these leaves were not officially recognized as a new food source until 2017 by the Chinese government. In this study, ethyl acetate fractions from Forsythia suspensa fruit and leaves exhibited excellent antioxidant activity in vitro antioxidant assays and in vivo D-galactose-induced aging mice model. The antioxidant activity of the leaves was higher than that of fruit both in vitro and in vivo. The chemical constituents present in these ethyl acetate fractions were comprehensively analyzed using UHPLC-Q-Exactive-Orbitrap/MS. A total of 20 compounds were identified, among which forsythoside E, (+)-epipinoresinol, dihydromyricetin, chlorogenic acid, and ursolic acid were exclusively detected in the ethyl acetate fraction of Forsythia suspensa leaves, but absent in the ethyl acetate fraction derived from its fruit. This study provides theoretical support for the utilization of Forsythia suspensa fruit and leaves.

Diosmetin-7-O-ß-D-glucopyranoside from Pogostemonis Herba alleviated SARS-CoV-2-induced pneumonia by reshaping macrophage polarization and limiting viral replication.

ETHNOPHARMACOLOGICAL RELEVANCE: Viral pneumonia is the leading cause of death after SARS-CoV-2 infection. Despite effective at early stage, long-term treatment with glucocorticoids can lead to a variety of adverse effects and limited benefits. The Chinese traditional herb Pogostemonis Herba is the aerial part of Pogostemon Cablin (Blanco) Benth., which has potent antiviral, antibacterial, anti-inflammatory, and anticancer effects. It was used widely for treating various throat and respiratory diseases, including COVID-19, viral infection, cough, allergic asthma, acute lung injury and lung cancer. AIM OF THE STUDY: To investigate the antiviral and anti-inflammatory effects of chemical compounds from Pogostemonis Herba in SARS-CoV-2-infected hACE2-overexpressing mouse macrophage RAW264.7 cells and hACE2 transgenic mice. MATERIALS AND METHODS: The hACE2-overexpressing RAW264.7 cells were exposed with SARS-CoV-2. The cell viability was detected by CCK8 assay and cell apoptotic rate was by flow cytometric assay. The expressions of macrophage M1 phenotype markers (TNF-α and IL-6) and M2 markers (IL-10 and Arg-1) as well as the viral loads were detected by qPCR. The mice were inoculated intranasally with SARS-CoV-2 omicron variant to induce viral pneumonia. The levels of macrophages, neutrophils, and T cells in the lung tissues of infected mice were analyzed by full spectrum flow cytometry. The expressions of key proteins were detected by Western blot assay. RESULTS: Diosmetin-7-O-ß-D-glucopyranoside (DG) presented the strongest anti-SARS-CoV-2 activity. Intervention with DG at the concentrations of 0.625-2.5 µM not only reduced the viral replication, cell apoptosis, and the productions of inflammatory cytokines (IL-6 and TNF-α) in SARS-CoV-2-infected RAW264.7 cells, but also reversed macrophage polarity from M1 to M2 phenotype. Furthermore, treatment with DG (25-100 mg/kg) alleviated acute lung injury, and reduced macrophage infiltration in SARS-COV-2-infected mice. Mechanistically, DG inhibited SARS-COV-2 gene expression and HK3 translation via targeting YTHDF1, resulting in the inactivation of glycolysis-mediated NF-κB pathway. CONCLUSIONS: DG exerted the potent antiviral and anti-inflammatory activities. It reduced pneumonia in SARS-COV-2-infected mice via inhibiting the viral replication and accelerating M2 macrophage polarization via targeting YTHDF1, indicating its potential for COVID-19 treatment.

3D-Based RNA Function Prediction Tools in rnaglib.

Understanding the connection between complex structural features of RNA and biological function is a fundamental challenge in evolutionary studies and in RNA design. However, building datasets of RNA 3D structures and making appropriate modeling choices remain time-consuming and lack standardization. In this chapter, we describe the use of rnaglib, to train supervised and unsupervised machine learning-based function prediction models on datasets of RNA 3D structures.

Microenvironment matters: In vitro 3D bone marrow niches differentially modulate survival, phenotype and drug responses of acute myeloid leukemia (AML) cells.

Acute myeloid leukemia (AML) is a deadly form of leukemia with ineffective traditional treatment and frequent chemoresistance-associated relapse. Personalized drug screening holds promise in identifying optimal regimen, nevertheless, primary AML cells undergo spontaneous apoptosis during cultures, invalidating the drug screening results. Here, we reconstitute a 3D osteogenic niche (3DON) mimicking that in bone marrow to support primary AML cell survival and phenotype maintenance in cultures. Specifically, 3DON derived from osteogenically differentiated mesenchymal stem cells (MSC) from healthy and AML donors are co-cultured with primary AML cells. The AML cells under the AML_3DON niche showed enhanced viability, reduced apoptosis and maintained CD33+ CD34-phenotype, associating with elevated secretion of anti-apoptotic cytokines in the AML_3DON niche. Moreover, AML cells under the AML_3DON niche exhibited low sensitivity to two FDA-approved chemotherapeutic drugs, further suggesting the physiological resemblance of the AML_3DON niche. Most interestingly, AML cells co-cultured with the healthy_3DON niche are highly sensitive to the same sample drugs. This study demonstrates the differential responses of AML cells towards leukemic and healthy bone marrow niches, suggesting the impact of native cancer cell niche in drug screening, and the potential of re-engineering healthy bone marrow niche in AML patients as chemotherapeutic adjuvants overcoming chemoresistance, respectively.

Stiff extracellular matrix drives the differentiation of mesenchymal stem cells toward osteogenesis by the multiscale 3D genome reorganization.

Extracellular matrix (ECM) stiffness is a major driver of stem cell fate. However, the involvement of the three-dimensional (3D) genomic reorganization in response to ECM stiffness remains unclear. Here, we generated comprehensive 3D chromatin landscapes of mesenchymal stem cells (MSCs) exposed to various ECM stiffness. We found that there were more long-range chromatin interactions, but less compartment A in MSCs cultured on stiff ECM than those cultured on soft ECM. However, the switch from compartment B in MSCs cultured on soft ECM to compartment A in MSCs cultured on stiff ECM included genes encoding proteins primarily enriched in cytoskeleton organization. At the topologically associating domains (TADs) level, stiff ECM tends to have merged TADs on soft ECM. These merged TADs on stiff ECM include upregulated genes encoding proteins enriched in osteogenesis, such as SP1, ETS1, and DCHS1, which were validated by quantitative real-time polymerase chain reaction and found to be consistent with the increase of alkaline phosphatase staining. Knockdown of SP1 or ETS1 led to the downregulation of osteogenic marker genes, including COL1A1, RUNX2, ALP, and OCN in MSCs cultured on stiff ECM. Our study provides an important insight into the stiff ECM-mediated promotion of MSC differentiation towards osteogenesis, emphasizing the influence of mechanical cues on the reorganization of 3D genome architecture and stem cell fate.

Quantification of Total Ketone Bodies in Biological Matrices Using Stable Isotope-Labeled Internal Standards and RP-UHPLC-MS/MS.

Acetoacetate (AcAc) and D-beta-hydroxybutyrate (D-ßOHB), the two major ketone bodies found in circulation, are linked to multiple physiological and pathophysiological states. Therefore, analytical methodologies surrounding the quantification of total ketone body (TKB) concentrations in biological matrices are paramount. Traditional methods to quantify TKBs relied on indirect spectrophotometric assays with narrow dynamic ranges, which have been significantly improved upon by modern mass spectrometry (MS)-based approaches. However, the lack of stable isotope-labeled internal standards (ISs) for AcAc and the need to distinguish D-ßOHB from its closely related structural and enantiomeric isomers pose significant obstacles. Here, we provide a protocol to synthesize and quantify a [13C] stable isotope-labeled IS for AcAc, which, in conjunction with a commercially available [2H] stable isotope-labeled IS for ßOHB, allows TKBs to be measured across multiple biological matrices. This rapid (7 min) analysis employs reverse phase ultra-high performance liquid chromatography (RP-UHPLC) coupled to tandem MS (MS/MS) to distinguish ßOHB from three structural isomers using parallel reaction monitoring (PRM), providing excellent specificity and selectivity. Finally, a method is provided that distinguishes D-ßOHB from L-ßOHB using a simple one-step derivatization to produce the corresponding diastereomers, which can be chromatographically resolved using the same rapid RP-UHPLC separation with new PRM transitions. In summary, this method provides a rigorous analytical pipeline for the analysis of TKBs in biological matrices via leveraging two authentic stable isotope-labeled ISs and RP-UHPLC-MS/MS.

Advances in Chiral Metabolomic Profiling and Biomarker Discovery.

Chiral metabolomics entails the enantioselective measurement of the metabolome present in a biological system. Over recent years, it has garnered significant interest for its potential in discovering disease biomarkers and aiding clinical diagnostics. D-Amino acids and D-hydroxy acids, traditionally overlooked as unnatural, are now emerging as novel signaling molecules and potential biomarkers for a range of metabolic disorders, brain diseases, kidney disease, diabetes, and cancer. Despite their significance, simultaneous measurements of multiple classes of chiral metabolites in a biological system remain challenging. Hence, limited information is available regarding the metabolic pathways responsible for synthesizing D-amino/hydroxy acid and their associated pathophysiological mechanisms in various diseases. Capitalizing on recent advancements in sensitive analytical techniques, researchers have developed various targeted chiral metabolomic methods for the analysis of chiral biomarkers. Here, we highlight the pivotal role of chiral metabolic profiling studies in disease diagnosis, prognosis, and therapeutic interventions. Furthermore, we describe cutting-edge chromatographic and mass spectrometry methods that enable enantioselective analysis of chiral metabolites. These advanced techniques are instrumental in unraveling the complexities of disease biomarkers, contributing to the ongoing efforts in disease biomarker discovery.

Three-dimensional printing in orthopaedic surgery: A review of current and future applications.

Three-dimensional (3D) printing is a form of technology in which 3D physical models are created. It has been used in a variety of surgical specialities ranging from cranio-maxillo-facial to orthopaedic surgery and is currently an area of much interest within the medical profession. Within the field of orthopaedic surgery, 3D printing has several clinical applications including surgical education, surgical planning, manufacture of patient-specific prostheses/patient specific instruments and bone tissue engineering. This article reviews the current practices of 3D printing in orthopaedic surgery in both clinical and pre-clinical settings along with discussing its potential future applications.