Inhibiting Demetalation of Fe─N─C via Mn Sites for Efficient Oxygen Reduction Reaction in Zinc-Air Batteries.

Demetalation caused by the electrochemical dissolution of metallic Fe atoms is a major challenge for the practical application of Fe─N─C catalysts. Herein, an efficient single metallic Mn active site is constructed to improve the strength of the Fe─N bond, inhibiting the demetalation effect of Fe─N─C. Mn acts as an electron donor inducing more delocalized electrons to reduce the oxidation state of Fe by increasing the electron density, thereby enhancing the Fe─N bond and inhibiting the electrochemical dissolution of Fe. The oxygen reduction reaction pathway for the dissociation of Fe─Mn dual sites can overcome the high energy barriers to direct O─O bond dissociation and modulate the electronic states of Fe─N4 sites. The resulting FeMn─N─C exhibits excellent ORR activity with a high half-wave potential of 0.92 V in alkaline electrolytes. FeMn─N─C as a cathode catalyst for Zn-air batteries has a cycle stability of 700 h at 25 °C and a long cycle stability of more than 210 h under extremely cold conditions at -40 °C. These findings contribute to the development of efficient and stable metal-nitrogen-carbon catalysts for various energy devices.

Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach.

The forthcoming massive genome data generated by the Earth BioGenome Project will open up a new era of comparative genomics, for which genome synteny analysis provides an important framework. Profiling genome synteny represents an essential step in elucidating genome architecture, regulatory blocks/elements and their evolutionary history. Here we describe PanSyn, ( https://github.com/yhw320/PanSyn ), the most comprehensive and up-to-date genome synteny pipeline, providing step-by-step instructions and application examples to demonstrate its usage. PanSyn inherits both basic and advanced functions from existing popular tools, offering a user-friendly, highly customized approach for genome macrosynteny analysis and integrated pan-evolutionary and regulatory analysis of genome architecture, which are not yet available in public synteny software or tools. The advantages of PanSyn include: (i) advanced microsynteny analysis by functional profiling of microsynteny genes and associated regulatory elements; (ii) comprehensive macrosynteny analysis, including the inference of karyotype evolution from ancestors to extant species; and (iii) functional integration of microsynteny and macrosynteny for pan-evolutionary profiling of genome architecture and regulatory blocks, as well as integration with external functional genomics datasets from three- or four-dimensional genome and ENCODE projects. PanSyn requires basic knowledge of the Linux environment and Perl programming language and the ability to access a computer cluster, especially for large-scale genomic comparisons. Our protocol can be easily implemented by a competent graduate student or postdoc and takes several days to weeks to execute for dozens to hundreds of genomes. PanSyn provides yet the most comprehensive and powerful tool for integrated evolutionary and functional genomics.

Deciphering the population structure and genetic basis of growth traits from whole-genome resequencing of the leopard coral grouper ( Plectropomus leopardus).

The leopard coral grouper ( Plectropomus leopardus) is a species of significant economic importance. Although artificial cultivation of P. leopardus has thrived in recent decades, the advancement of selective breeding has been hindered by the lack of comprehensive population genomic data. In this study, we identified over 8.73 million single nucleotide polymorphisms (SNPs) through whole-genome resequencing of 326 individuals spanning six distinct groups. Furthermore, we categorized 226 individuals with high-coverage sequencing depth (≥14×) into eight clusters based on their genetic profiles and phylogenetic relationships. Notably, four of these clusters exhibited pronounced genetic differentiation compared with the other populations. To identify potentially advantageous loci for P. leopardus, we examined genomic regions exhibiting selective sweeps by analyzing the nucleotide diversity ( θπ) and fixation index ( F ST) in these four clusters. Using these high-coverage resequencing data, we successfully constructed the first haplotype reference panel specific to P. leopardus. This achievement holds promise for enabling high-quality, cost-effective imputation methods. Additionally, we combined low-coverage sequencing data with imputation techniques for a genome-wide association study, aiming to identify candidate SNP loci and genes associated with growth traits. A significant concentration of these genes was observed on chromosome 17, which is primarily involved in skeletal muscle and embryonic development and cell proliferation. Notably, our detailed investigation of growth-related SNPs across the eight clusters revealed that cluster 5 harbored the most promising candidate SNPs, showing potential for genetic selective breeding efforts. These findings provide a robust toolkit and valuable insights into the management of germplasm resources and genome-driven breeding initiatives targeting P. leopardus.

Gene duplication and functional divergence of new genes contributed to the polar acclimation of Antarctic green algae.

Psychrophilic microalgae successfully survive in the extreme and highly variable polar ecosystems, which represent the energy base of most food webs and play a fundamental role in nutrient cycling. The success of microalgae is rooted in their adaptive evolution. Revealing how they have evolved to thrive in extreme polar environments will help us better understand the origin of life in polar ecosystems. We isolated a psychrophilic unicellular green alga, Microglena sp. YARC, from Antarctic sea ice which has a huge genome. Therefore, we predicted that gene replication may play an important role in its polar adaptive evolution. We found that its protein-coding gene number significantly increased and the duplication time was dated between 37 and 48 million years ago, which is consistent with the formation of the circumpolar Southern Ocean. Most duplicated paralogous genes were enriched in pathways related to photosynthesis, DNA repair, and fatty acid metabolism. Moreover, there were a total of 657 Microglena-specific families, including collagen-like proteins. The divergence in the expression patterns of the duplicated and species-specific genes reflects sub- and neo-functionalization during stress acclimation. Overall, key findings from this study provide new information on how gene duplication and their functional novelty contributed to polar algae adaptation to the highly variable polar environmental conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00203-z.

Tailoring Oxygen Reduction Reaction Kinetics on Perovskite Oxides via Oxygen Vacancies for Low-Temperature and Knittable Zinc-Air Batteries.

High kinetics oxygen reduction reaction (ORR) electrocatalysts under low temperature are critical and highly desired for temperature-tolerant energy conversion and storage devices, but remain insufficiently investigated. Herein, oxygen vacancy-rich porous perovskite oxide (CaMnO3 ) nanofibers coated with reduced graphene oxide coating (V-CMO/rGO) are developed as the air electrode catalyst for low-temperature and knittable Zn-air batteries. V-CMO/rGO exhibits top-level ORR activity among perovskite oxides and shows impressive kinetics under low temperature. Experimental and theoretical calculation results reveal that the synergistic effect between metal atoms and oxygen vacancies, as well as the accelerated kinetics and enhanced electric conductivity and mass transfer over the rGO coated nanofiber 3D network contribute to the enhanced catalytic activity. The desorption of ORR intermediate is promoted by the regulated electron filling. The V-CMO/rGO drives knittable and flexible Zn-air batteries under a low temperature of -40 °C with high peak power density of 56 mW cm-2 and long cycle life of over 80 h. This study provides insight of kinetically active catalyst and facilitates the ZABs application in harsh environment.

Endowing Porphyrinic Metal-Organic Frameworks with High Stability by a Linker Desymmetrization Strategy.

The fabricating of metal-organic frameworks (MOFs) that integrate high stability and functionality remains a long-term pursuit yet a great challenge. Herein, we develop a linker desymmetrization strategy to construct highly stable porphyrinic MOFs, namely, USTC-9 (USTC represents the University of Science and Technology of China), presenting the same topological structure as the well-known PCN-600 that readily loses crystallinity in air or upon conventional activation. For USTC-9, the involved porphyrinic linker (TmCPP-M) with carboxylate groups located in the meta-position presents a chair-shaped conformation with lower C2h symmetry than that (D4h) of the common porphyrinic carboxylate (TCPP) linker in PCN-600. As a result, the wrinkled and interlocked linker arrangements collectively contribute to the remarkable stability of USTC-9. Given the high stability and porosity as well as Lewis acidity, USTC-9(Fe) demonstrates its excellent performance toward catalytic CO2 cycloaddition with diverse epoxides at moderate temperature and atmospheric pressure.

Improved chromosomal-level genome assembly and re-annotation of leopard coral grouper.

Plectropomus leopardus, as known as leopard coral grouper, is a valuable marine fish that has gradually been bred artificially. To promote future conservation, molecular breeding, and comparative studies, we generated an improved high-quality chromosomal-level genome assembly of leopard coral grouper using Nanopore long-reads, Illumina short reads, and the Hi-C sequencing data. The draft genome is 849.74 Mb with 45 contigs and N50 of 35.59 Mb. Finally, a total of 846.49 Mb corresponding to 99.6% of the contig sequences was anchored to 24 pseudo-chromosomes using Hi-C technology. A final set of 25,965 genes is annotated after manual curation of the predicted gene models, and BUSCO analysis yielded a completeness score of 99.5%. This study significantly improves the utility of the grouper genome and provided a reference for the study of molecular breeding, genomics and biology in this species.

Exon shuffling potentiates a diverse repertoire of brown algal NB-ARC-TPR candidate immune receptor proteins via alternative splicing.

Like other organisms, brown algae are subject to diseases caused by bacteria, fungi, and viruses. Brown algal immunity mechanisms are not well characterized; however, there is evidence suggesting that pathogen receptors exist in brown algae. One key protein family likely associated with brown algal innate immunity possesses an NB-ARC domain analogous to innate immune proteins in plants and animals. In this study, we conducted an extensive survey of NB-ARC genes in brown algae and obtained insights into the domain organization and evolutionary history of the encoded proteins. Our data show that brown algae possess an ancient NB-ARC-tetratricopeptide repeat (NB-TPR) domain architecture. We identified an N-terminal effector domain, the four-helix bundle, which was not previously found associated with NB-ARC domains. The phylogenetic tree including NB-ARC domains from all kingdoms of life suggests the three clades of brown algal NB-TPRs are likely monophyletic, whereas their TPRs seem to have distinct origins. One group of TPRs exhibit intense exon shuffling, with various alternative splicing and diversifying selection acting on them, suggesting exon shuffling is an important mechanism for evolving ligand-binding specificities. The reconciliation of gene duplication and loss events of the NB-ARC genes reveals that more independent gene gains than losses have occurred during brown algal evolution, and that tandem duplication has played a major role in the expansion of NB-ARC genes. Our results substantially enhance our understanding of the evolutionary history and exon shuffling mechanisms of the candidate innate immune repertoire of brown algae.

KDM6B protects T-ALL cells from NOTCH1-induced oncogenic stress.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematopoietic neoplasm resulting from the malignant transformation of T-cell progenitors. While activating NOTCH1 mutations are the dominant genetic drivers of T-ALL, epigenetic dysfunction plays a central role in the pathology of T-ALL and can provide alternative mechanisms to oncogenesis in lieu of or in combination with genetic mutations. The histone demethylase enzyme KDM6A (UTX) is also recurrently mutated in T-ALL patients and functions as a tumor suppressor. However, its gene paralog, KDM6B (JMJD3), is never mutated and can be significantly overexpressed, suggesting it may be necessary for sustaining the disease. Here, we used mouse and human T-ALL models to show that KDM6B is required for T-ALL development and maintenance. Using NOTCH1 gain-of-function retroviral models, mouse cells genetically deficient for Kdm6b were unable to propagate T-ALL. Inactivating KDM6B in human T-ALL patient cells by CRISPR/Cas9 showed KDM6B-targeted cells were significantly outcompeted over time. The dependence of T-ALL cells on KDM6B was proportional to the oncogenic strength of NOTCH1 mutation, with KDM6B required to prevent stress-induced apoptosis from strong NOTCH1 signaling. These studies identify a crucial role for KDM6B in sustaining NOTCH1-driven T-ALL and implicate KDM6B as a novel therapeutic target in these patients.

Ancient homomorphy of molluscan sex chromosomes sustained by reversible sex-biased genes and sex determiner translocation.

Contrary to classic theory prediction, sex-chromosome homomorphy is prevalent in the animal kingdom but it is unclear how ancient homomorphic sex chromosomes avoid chromosome-scale degeneration. Molluscs constitute the second largest, Precambrian-originated animal phylum and have ancient, uncharacterized homomorphic sex chromosomes. Here, we profile eight genomes of the bivalve mollusc family of Pectinidae in a phylogenetic context and show 350 million years sex-chromosome homomorphy, which is the oldest known sex-chromosome homomorphy in the animal kingdom, far exceeding the ages of well-known heteromorphic sex chromosomes such as 130-200 million years in mammals, birds and flies. The long-term undifferentiation of molluscan sex chromosomes is potentially sustained by the unexpected intertwined regulation of reversible sex-biased genes, together with the lack of sexual dimorphism and occasional sex chromosome turnover. The pleiotropic constraint of regulation of reversible sex-biased genes is widely present in ancient homomorphic sex chromosomes and might be resolved in heteromorphic sex chromosomes through gene duplication followed by subfunctionalization. The evolutionary dynamics of sex chromosomes suggest a mechanism for 'inheritance' turnover of sex-determining genes that is mediated by translocation of a sex-determining enhancer. On the basis of these findings, we propose an evolutionary model for the long-term preservation of homomorphic sex chromosomes.

Research Progress and Potential Applications of Spermidine in Ocular Diseases.

Spermidine, a natural polyamine, exists in almost all human tissues, exhibiting broad properties like anti-aging, autophagy induction, anti-inflammation, anti-oxidation, cell proliferation activation, and ion channel regulation. Considering that spermidine is already present in human nutrition, recent studies targeting supplementing exogenous sources of this polyamine appear feasible. The protective role of spermidine in various systems has been illuminated in the literature, while recent progress of spermidine administration in ocular diseases remains to be clarified. This study shows the current landscape of studies on spermidine and its potential to become a promising therapeutic agent to treat ocular diseases: glaucoma, optic nerve injury, age-related macular degeneration (AMD), cataracts, dry eye syndrome, and bacterial keratitis. It also has the potential to become a potent biomarker to predict keratoconus (KC), cataracts, uveitis, glaucoma, proliferative diabetic retinopathy (PDR), proliferative vitreoretinopathy (PVR), and retinopathy of prematurity (ROP). We also summarize the routes of administration and the effects of spermidine at different doses.

Adaptive Bird-like Genome Miniaturization During the Evolution of Scallop Swimming Lifestyle.

Genome miniaturization drives key evolutionary innovations of adaptive traits in vertebrates, such as the flight evolution of birds. However, whether similar evolutionary processes exist in invertebrates remains poorly understood. Derived from the second-largest animal phylum, scallops are a special group of bivalve molluscs and acquire the evolutionary novelty of the swimming lifestyle, providing excellent models for investigating the coordinated genome and lifestyle evolution. Here, we show for the first time that genome sizes of scallops exhibit a generally negative correlation with locomotion activity. To elucidate the co-evolution of genome size and swimming lifestyle, we focus on the Asian moon scallop (Amusium pleuronectes) that possesses the smallest known scallop genome while being among scallops with the highest swimming activity. Whole-genome sequencing of A. pleuronectes reveals highly conserved chromosomal macrosynteny and microsynteny, suggestive of a highly contracted but not degenerated genome. Genome reduction of A. pleuronectes is facilitated by significant inactivation of transposable elements, leading to reduced gene length, elevated expression of genes involved in energy-producing pathways, and decreased copy numbers and expression levels of biomineralization-related genes. Similar evolutionary changes of relevant pathways are also observed for bird genome reduction with flight evolution. The striking mimicry of genome miniaturization underlying the evolution of bird flight and scallop swimming unveils the potentially common, pivotal role of genome size fluctuation in the evolution of novel lifestyles in the animal kingdom.

The role of zinc in the adaptive evolution of polar phytoplankton.

Zinc is an essential trace metal for oceanic primary producers with the highest concentrations in polar oceans. However, its role in the biological functioning and adaptive evolution of polar phytoplankton remains enigmatic. Here, we have applied a combination of evolutionary genomics, quantitative proteomics, co-expression analyses and cellular physiology to suggest that model polar phytoplankton species have a higher demand for zinc because of elevated cellular levels of zinc-binding proteins. We propose that adaptive expansion of regulatory zinc-finger protein families, co-expanded and co-expressed zinc-binding proteins families involved in photosynthesis and growth in these microalgal species and their natural communities were identified to be responsible for the higher zinc demand. The expression of their encoding genes in eukaryotic phytoplankton metatranscriptomes from pole-to-pole was identified to correlate not only with dissolved zinc concentrations in the upper ocean but also with temperature, suggesting that environmental conditions of polar oceans are responsible for an increased demand of zinc. These results suggest that zinc plays an important role in supporting photosynthetic growth in eukaryotic polar phytoplankton and that this has been critical for algal colonization of low-temperature polar oceans.

Rapid and Label-Free Classification of Blood Leukocytes for Immune State Monitoring.

A fully automated and label-free sample-to-answer white blood cell (WBC) cytometry platform for rapid immune state monitoring is demonstrated. The platform integrates (1) a WBC separation process using the multidimensional double spiral (MDDS) device and (2) an imaging process where images of the separated WBCs are captured and analyzed. Using the deep-learning-based image processing technique, we analyzed the captured bright-field images to classify the WBCs into their subtypes. Furthermore, in addition to cell classification, we can detect activation-induced morphological changes in WBCs for functional immune assessment, which could allow the early detection of various diseases. The integrated platform operates in a rapid (<30 min), fully automated, and label-free manner. The platform could provide a promising solution to future point-of-care WBC diagnostics applications.

Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common endocrine metabolic disease, involving a carbohydrate intolerance of variable severity during pregnancy. The incidence of GDM-related complications and adverse pregnancy outcomes has declined, in part, due to early screening. Machine learning (ML) models are increasingly used to identify risk factors and enable the early prediction of GDM. OBJECTIVE: The aim of this study was to perform a meta-analysis and comparison of published prognostic models for predicting the risk of GDM and identify predictors applicable to the models. METHODS: Four reliable electronic databases were searched for studies that developed ML prediction models for GDM in the general population instead of among high-risk groups only. The novel Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias of the ML models. The Meta-DiSc software program (version 1.4) was used to perform the meta-analysis and determination of heterogeneity. To limit the influence of heterogeneity, we also performed sensitivity analyses, a meta-regression, and subgroup analysis. RESULTS: A total of 25 studies that included women older than 18 years without a history of vital disease were analyzed. The pooled area under the receiver operating characteristic curve (AUROC) for ML models predicting GDM was 0.8492; the pooled sensitivity was 0.69 (95% CI 0.68-0.69; P<.001; I2=99.6%) and the pooled specificity was 0.75 (95% CI 0.75-0.75; P<.001; I2=100%). As one of the most commonly employed ML methods, logistic regression achieved an overall pooled AUROC of 0.8151, while non-logistic regression models performed better, with an overall pooled AUROC of 0.8891. Additionally, maternal age, family history of diabetes, BMI, and fasting blood glucose were the four most commonly used features of models established by the various feature selection methods. CONCLUSIONS: Compared to current screening strategies, ML methods are attractive for predicting GDM. To expand their use, the importance of quality assessments and unified diagnostic criteria should be further emphasized.

Switchable hydrophilic solvent-based dispersive liquid-liquid microextraction coupled with high-performance liquid chromatography for the determination of four types of sulfonylurea herbicides in soils.

In this study, switchable hydrophilic solvent-based dispersive liquid-liquid microextraction coupled with high-performance liquid chromatography was developed for the determination of four sulfonylurea herbicides in soils. For the first time, the sample pretreatment was achieved due to the similar acid-base status of sulfonylurea herbicides and switchable hydrophilic solvent. In the extraction step, sulfonylurea herbicides were extracted as anions and transferred to an alkaline solution with switchable hydrophilic solvent anions. In the concentration step, two types of anions were transformed to their molecular state after the aqueous solution was acidified. In addition, the dispersion and microextraction processes were completed efficiently with the simultaneous formation of analytes and extractants. The factors affecting the extraction performance were optimized. Under the optimized conditions, good linearity was observed for each herbicide with correlation coefficients ranging from 0.9952 to 0.9978. The limits of detection were in the range of 0.1-0.2 µg/g. Moreover, the relative recoveries of the sulfonylurea herbicides at spiking levels of 0.5, 1, and 1.5 µg/g in soil samples were between 75 and 111% (relative standard deviations: 0.4-11.4%). Therefore, the proposed method in this study could be successfully applied to the analysis of four types of sulfonylurea herbicides in soil samples.

Microfluidic Particle Separation and Detection System Based on Standing Surface Acoustic Wave and Lensless Imaging.

OBJECTIVE: Separation and detection of micro-particles or cells from bio-samples by point-of-care (POC) systems are critical for biomedical and healthcare diagnostic applications. Among various microfluidic separation techniques, acoustophoresis-based technique has the advantages of label-free and good biocompatibility. However, most of the existing separation techniques are bulky and require additional equipment for analysis. METHODS: We proposed a platform, which integrates an acoustophoresis-based separation device and a lensless imaging sensor into a compact standalone system to tackle this challenge. Standing Surface Acoustic Wave (SSAW) is utilized for label-free particle separation, while lensless imaging is employed for seamless particle detection and counting using self-developed dual-threshold motion detection algorithms. In particular, we specially optimized the design of microfluidic channel and interdigital transducers (IDTs) for higher performance bioparticle separation, designed a heat dissipation system for the suppression of fluid temperature, and proposed a novel frequency-temperature-curve based method to determine the appropriate signal driving frequency for IDTs. RESULTS: At 2 µL/min flow rate, separation efficiency of 93.52% and purity of 94.29% for 15 µm microbead were achieved in mixed 5µm and 15µm microbead solution at a 25 dBm RF driving power, and similar results for mixed 10 µm and 15 µm microbead solution. CONCLUSIONS: The results showed that the integrated platform has an excellent capability to seamlessly separate, distinguish, and count microbeads of different sizes. SIGNIFICANCE: Such a platform and the design methodologies offer a promising POC solution for label-free cell separation and detection in biomedical diagnostics.

Autophagy and senescence of rat retinal precursor cells under high glucose.

Backgrounds: Diabetic retinopathy (DR) is a common diabetic ocular disease characterized by retinal ganglion cell (RGC) changes. An abnormal environment, hyperglycemia, may progressively alter the structure and function of RGCs, which is a primary pathological feature of retinal neurodegeneration in DR. Accumulated studies confirmed autophagy and senescence play a vital role in DR; however, the underlying mechanisms need to be clarified. Methods: This study included the microarray expression profiling dataset GSE60436 from Gene Expression Omnibus (GEO) to conduct the bioinformatics analysis. The R software was used to identify autophagy-related genes (ARGs) that were differentially expressed in fibrovascular membranes (FVMs) and normal retinas. Co-expression and tissue-specific expression were elicited for the filtered genes. The genes were then analyzed by ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). R28 cells were cultured with high glucose, detected by reverse transcription-quantitative (RT-qPCR) and stained by apoptosis kit. Results: In the retina, 31 differentially expressed ARGs (24 up-regulated genes) were discovered and enriched. The enrichment results revealed that differentially expressed ARGs were significantly enriched in autophagy, apoptosis, aging, and neural function. Four hub genes (i.e., TP53, CASP1, CCL2, and CASP1) were significantly up-regulated. Upregulation of cellular autophagy and apoptosis level was detected in the hyperglycemia model in vitro. Conclusions: Our results provide evidence for the autophagy and cellular senescence mechanisms involved in retinal hyperglycemia injury, and the protective function of autophagy is limited. Further study may favour understanding the disease progression and neuroprotection of DR.

Correction: Huang et al. Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring. Sensors 2021, 21, 512.

The authors wish to make the following correction to their paper [...].