Using machine learning to identify environmental factors that collectively determine microbial community structure of activated sludge.

Activated sludge (AS) microbial communities are influenced by various environmental variables. However, a comprehensive analysis of how these variables jointly and nonlinearly shape the AS microbial community remains challenging. In this study, we employed advanced machine learning techniques to elucidate the collective effects of environmental variables on the structure and function of AS microbial communities.

Human midbrain dopaminergic progenitors.

Human midbrain dopaminergic progenitors (mDAPs) are one of the most representative cell types in both basic research and clinical applications. However, there are still many challenges for the preparation and quality control of mDAPs, such as the lack of standards. Therefore, the establishment of critical quality attributes and technical specifications for mDAPs is largely needed.

Human neural stem cells.

'Human neural stem cells' jointly drafted and agreed upon by experts from the Chinese Society for Stem Cell Research, is the first guideline for human neural stem cells (hNSCs) in China. This standard specifies the technical requirements, test methods, test regulations, instructions for use, labelling requirements, packaging requirements, storage requirements, transportation requirements and waste disposal requirements for hNSCs, which is applicable to the quality control for hNSCs. It was originally released by the China Society for Cell Biology on 30 August 2022.

Single-molecule study reveals Hmo1, not Hho1, promotes chromatin assembly in budding yeast.

Linker histone H1 plays a crucial role in various biological processes, including nucleosome stabilization, high-order chromatin structure organization, gene expression, and epigenetic regulation in eukaryotic cells. Unlike higher eukaryotes, little about the linker histone in is known. Hho1 and Hmo1 are two long-standing controversial histone H1 candidates in budding yeast.

Dynamically Quantifying Intracellular Elemental Sulfur and Predicting Pertinent Gene Transcription by Raman Spectroscopy in Living Cells.

The ability to monitor changes in metabolites and corresponding gene transcription within living cells is highly desirable. However, most current assays for quantification of metabolites or for gene transcription are destructive, precluding tracking the real-time dynamics of living cells. Here, we used the intracellular elemental sulfur in a cell as a proof-of-concept to link the quantity of metabolites and relevant gene transcription in living cells by a nondestructive Raman approach.

Inactivation of porcine epidemic diarrhea virus with electron beam irradiation under cold chain conditions.

The many instances of COVID-19 outbreaks suggest that cold chains are a possible route for the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, owing to the low temperatures of cold chains, which are normally below 0 °C, there are limited options for virus inactivation. Here, high-energy electron beam (E-beam) irradiation was used to inactivate porcine epidemic diarrhea virus (PEDV) under simulated cold chain conditions.

Blood identification at the single-cell level based on a combination of laser tweezers Raman spectroscopy and machine learning.

Laser tweezers Raman spectroscopy (LTRS) combines optical tweezers technology and Raman spectroscopy to obtain biomolecular compositional information from a single cell without invasion or destruction, so it can be used to "fingerprint" substances to characterize numerous types of biological cell samples. In the current study, LTRS was combined with two machine learning algorithms, principal component analysis (PCA)-linear discriminant analysis (LDA) and random forest, to achieve high-precision multi-species blood classification at the single-cell level. The accuracies of the two classification models were 96.

Structural insights into multifunctionality of human FACT complex subunit hSSRP1.

Human structure-specific recognition protein 1 (hSSRP1) is an essential component of the facilitates chromatin transcription complex, which participates in nucleosome disassembly and reassembly during gene transcription and DNA replication and repair. Many functions, including nuclear localization, histone chaperone activity, DNA binding, and interaction with cellular proteins, are attributed to hSSRP1, which contains multiple well-defined domains, including four pleckstrin homology (PH) domains and a high-mobility group domain with two flanking disordered regions. However, little is known about the mechanisms by which these domains cooperate to carry out hSSRP1's functions.

Classification of pathogens by Raman spectroscopy combined with generative adversarial networks.

Rapid identification of marine pathogens is very important in marine ecology. Artificial intelligence combined with Raman spectroscopy is a promising choice for identifying marine pathogens due to its rapidity and efficiency. However, considering the cost of sample collection and the challenging nature of the experimental environment, only limited spectra are typically available to build a classification model, which hinders qualitative analysis.

Combination of an Artificial Intelligence Approach and Laser Tweezers Raman Spectroscopy for Microbial Identification.

Raman spectroscopy is a nondestructive, label-free, highly specific approach that provides the chemical information on materials. Thus, it is suitable to be used as an effective analytical tool to characterize biological samples. Here we introduce a novel method that uses artificial intelligence to analyze biological Raman spectra and identify the microbes at a single-cell level.

Kinetic analysis of DNA compaction by mycobacterial integration host factor at the single-molecule level.

Nucleoid-associated proteins (NAPs) play an important role on chromosome condensation and organization. Mycobacterial integration host factor (mIHF) is one of the few mycobacterial NAPs identified so far. mIHF has the ability to stimulate mycobacteriophage L5 integration and compact DNA into nucleoid-like or higher order filamentous structures by atomic force microscopy observation.

Visualizing the Interaction Between the Qdot-labeled Protein and Site-specifically Modified λ DNA at the Single Molecule Level.

The fluorescence microscopy has made great contributions in dissecting the mechanisms of complex biological processes at the single molecule level. In single molecule assays for studying DNA-protein interactions, there are two important factors for consideration: the DNA substrate with enough length for easy observation and labeling a protein with a suitable fluorescent probe. 48.

Rapid, label-free identification of cerebellar structures using multiphoton microscopy.

The cerebellum is the prominent laminar structure of the mammalian brain that has been implicated in various psychiatric and neurological diseases. Although clinical brain imaging techniques have provided precise anatomic images of cerebellar structures, a definitive diagnosis still requires adequate resolution to identify individual layers in cerebellar cortex, the extent of tumor, even requires the histological tissue examination during surgical procedures. In this study, multiphoton microscopy (MPM), based on second harmonic generation (SHG) and two-photon excited fluorescence (TPEF), was perform on the rat cerebellar structures and pathology with the combination of image analysis methods.

A method for labeling proteins with tags at the native genomic loci in budding yeast.

Fluorescent proteins and epitope tags are often used as protein fusion tags to study target proteins. One prevailing technique in the budding yeast Saccharomyces cerevisiae is to fuse these tags to a target gene at the precise chromosomal location via homologous recombination. However, several limitations hamper the application of this technique, such as the selectable markers not being reusable, tagging of only the C-terminal being possible, and a "scar" sequence being left in the genome.