Comparative chloroplast genome analysis of Sambucus L. (Viburnaceae): inference for phylogenetic relationships among the closely related Sambucus adnata Wall. ex DC Sambucus javanica Blume

Sambucus L. is found in the family Viburnaceae (syn. Adoxaceae) and encompasses approximately 29 accepted species. The complex morphology of these species has caused continued confusion concerning their nomenclature, classification, and identification. Despite previous attempts to resolve taxonomic complexities in the Sambucus genus, there are still unclear phylogenetic relationships among several species. In this study, the newly obtained plastome of Sambucus williamsii Hance. as well as the populations of Sambucus canadensis L., Sambucus javanica Blume, and Sambucus adnata Wall. ex DC were sequenced, and their sizes, structural similarity, gene order, gene number, and guanine-cytosine (GC) contents were analyzed. The phylogenetic analyses were conducted using the whole chloroplast genomes and protein-coding genes (PCGs). The findings revealed that the chloroplast genomes of Sambucus species exhibited typical quadripartite double-stranded DNA molecules. Their lengths ranged from 158,012 base pairs (bp) (S. javanica) to 158,716 bp (S. canadensis L). Each genome comprised a pair of inverted repeats (IRs), which separated the large single-copy (LSC) and small single-copy (SSC) regions. In addition, the plastomes contained 132 genes, encompassing 87 protein-coding, 37 tRNA, and four rRNA genes. In the simple sequence repeat (SSR) analysis, A/T mononucleotides had the highest proportion, with the most repetitive sequences observed in S. williamsii. The comparative genome analyses showed high similarities in structure, order, and gene contents. The hypervariable regions in the studied chloroplast genomes were trnT-GGU, trnF-GAA, psaJ, trnL-UAG, ndhF, and ndhE, which may be used as candidate barcodes for species discrimination in Sambucus genus. Phylogenetic analyses supported the monophyly of Sambucus and revealed the separation of S. javanica and S. adnata populations. Sambucus chinensis Lindl. was nested within S. javanica in the same clade, collaborating their conspecific treatment. These outcomes indicate that the chloroplast genome of Sambucus plants is a valuable genetic resource for resolving taxonomic discrepancies at the lower taxonomic levels and can be applied in molecular evolutionary studies.

Plastome evolution in the East Asian lobelias (Lobelioideae) using phylogenomic and comparative analyses

Lobelia species, as rich source of the alkaloid lobeline which has been shown to have important biological activity, have been used in folk medicine throughout East Asia to treat various diseases. However, Lobelia is a complex and varied genus in East Asia and is thus difficult to identify. Genomic resources would aid identification, however the availability of such information is poor, preventing a clear understanding of their evolutionary history from being established. To close this gap in the available genomic data, in this study, 17 plastomes of East Asian lobelias were newly sequenced and assembled. Although the plastomes of Lobelia sect. Hypsela, L. sect. Speirema, and L. sect. Rhynchopetalum shared the gene structure, the inverted repeat (IR)/large single copy (LSC) boundaries, genome size, and the number of repeats were variable, indicating the non-conservative nature of plastome evolution within these sections. However, the genomes of the Lobelia sect. Delostemon and L. sect. Stenotium showed rearrangements, revealing that these two sections might have undergone different evolutionary histories. We assessed nine hotspot genes and 27-51 simple sequence repeat motifs, which will also serve as valuable DNA barcode regions in future population genetics studies and for the delineation of plant species. Our phylogenetic analysis resolved the evolutionary positions of the five sections in agreement with previous evolutionary trees based on morphological features. Although phylogenetic reconstruction of Lobelioideae based on the rpoC2 gene has rarely been performed, our results indicated that it contains a considerable amount of phylogenetic information and offers great promise for further phylogenetic analysis of Lobelioideae. Our site-specific model identified 173 sites under highly positive selections. The branch-site model exhibited 11 positive selection sites involving four genes in the East Asian branches. These four genes may play critical roles in the adaptation of East Asian taxa to diverse environments. Our study is the first to detect plastome organization, phylogenetic utility, and signatures of positive selection in the plastomes of East Asian lobelias, which will help to further advance taxonomic and evolutionary studies and the utilization of medicinal plant resources.

Anisotropic Growth of Centimeter-Size CsCu2 I3 Single Crystals with Ultra-Low Trap Density for Aspect-Ratio-Dependent Photodetectors

Low-dimensional ternary copper iodide metal halide with strong quantum confinement effects has made great progress in optoelectronic fields. However, efficient regulation of anisotropic growth of metal halides single crystal still remains a great challenge. Herein, 2 cm size CsCu₂ I₃ single crystals with tunable aspect ratio and the trap states (n_trap ) as low as 5.38 × 10⁹  cm^-3 are fabricated by optimized anti-solvent vapor-assisted method, in which the growth cycle is shortened by half. Evidenced by real-time observation and the LaMer growth model, the rapid and anisotropic growth mechanism is ascribed to preferential 1D growth, promoted by high concentration and fast vapor rate. Furthermore, the aspect-ratio-dependent optoelectronic performance is observed, the on-off ratio for 2 cm CsCu₂ I₃ single crystal are enhanced 350 times compared with those of short and thick single crystal, which shows ultrahigh on-off ratio of 1570, D* of 1.34 × 10¹²  Jones, R_λ of 276.94 mA W^-1 , t _rise /t _decay of 0.37 and 1.08 ms, and EQE of 95.53%, which are clearly at very high level among lead-free perovskite-based photodetectors. This study not only provides a new strategy for overcoming anisotropic growth limitations of low-dimensional metal halides, but also paves a way for high-performance optoelectronic applications.

Threshold effects of green technology application on sustainable grain production: Evidence from China

Sustainable production is considered as an important approach to solve the dilemma of food insecurity. Green technologies have made contributions to improving food production and reducing environmental pollution. Studying the effects of green technologies on sustainable food production has great significance. The paper started with the influence mechanism of green technology application on the green total factor productivity of grain (GTFPG). With the GTFPG, green technology efficiency change of grain (GECG) and green technical progress change of grain (GTCG) measured, threshold models were constructed to explore the nonlinear impacts of various green technologies on GTFPG and the influence paths. Results indicated that the differences of GTFPG among provinces in China were decreased mainly due to the changes of GTCG, while the regional differences of GECG remained small. The impacts of green technologies had threshold effects that depended on the ecological effects of green technologies in different application stages, and were significantly different in the major and non-major grain producing areas. Meanwhile, significant differences existed in the influence paths of green technologies. In the major grain producing areas, green technologies were more likely to improve GTFPG through the GTCG path; while in the non-major grain producing areas, the GECG path and the GTCG path were both important to improve GTFPG. The differences of green technologies' threshold effects and influence paths in the major and non-major grain producing areas were caused by regional technology preference, resource endowment and technology compatibility. This study emphasizes that the development of green technologies should fully consider the resource endowment and economic development of different regions, as well as the applicability and adoption rate of green technologies.

The combination of salt and drought benefits selective ion absorption and nutrient use efficiency of halophyte Panicum antidotale

Soil salinity and water deficit often occur concurrently, but understanding their combined effects on plants' ion regulation is limited. With aim to identify if introducing drought with salinity alleviates salt stress's ionic effects, Panicum antidotale - a halophytic grass- was grown in the presence of single and combined stressors, i.e., drought and salt (low and high). Regulation of cations and anions along with the antioxidant capacity and modifications in leaf anatomy were investigated. Results showed a combination of low salt and drought minimally affected plant (dry) mass by improving the selective ions absorption and nutrient use efficiencies. The lowest ratio for efficiency of photosystem II and carbon assimilation (ΦPSII/ΦCO₂) suggested less generation of reactive oxygen species, which were probably detoxified with constitutively performing antioxidant enzymes. In contrast, the combination of high salinity and drought escalated the adverse effects caused due to individual stressors. The selective ion absorption increased, but the non-selective ions transport caused an ionic imbalance indicating the highest ratio of Na⁺/K⁺. Although the area of mesophyll increased, a reduction in epidermis (cell number and area) predicted a mechanical injury prone to water loss in these plants. The compromised activity of antioxidant enzymes also suggested treatment-induced oxidative damage. Yet, the synergistic interaction between high salinity and drought was not detrimental to the survival of P. antidotale. Therefore, we suggest planting this grass in habitats with harsh environmental conditions to meet the increasing fodder demands without compromising agricultural lands' productivity.

Multifunctional phototheranostic agent ZnO@Ag for anti-infection through photothermal/photodynamic therapy

To overcome the limitations of traditional therapeutics, nanotechnology offers a synergistic therapeutic approach for the treatment of bacterial infection and biofilms that has attracted attention. Herein, we report on a ZnO@Ag nanocomposite with good biocompatibility synthesized by doping ZnO NPs with silver nanoparticles (Ag NPs). ZnO@Ag nanocomposites were synthesized with varying ratios of Ag NPs (0.5%, 2%, 8%). Under the same experimental conditions, ZnO@8%Ag exhibited outstanding properties compared to the other nanocomposites and the pristine ZnO NPs. ZnO@8%Ag demonstrated excellent photothermal and photodynamic properties. Also, ZnO@8%Ag demonstrated over 99% inhibition of Staphylococcus aureus (S. aureus) under photothermal therapy (PTT) or photodynamics therapy (PDT) as a result of the excessive generation of reactive oxygen species (ROS) by the Ag+ released, while the pristine ZnO showed an insignificant inhibition rate compared to the PBS group (control). Furthermore, ZnO@8%Ag completely disrupted S. aureus biofilm under a combined PTT/PDT treatment, a synergetic trimodal therapy, although the molecular mechanism of biofilm inhibition remains unclear. Hence, the excellent photothermal, photodynamic, biocompatibility, and bactericidal properties of ZnO@8%Ag present it as an appropriate platform for bacterial and biofilm treatment or other biomedically related applications.

Uncovering interactions between mycobacterial respiratory complexes to target drug-resistant Mycobacterium tuberculosis

Mycobacterium tuberculosis remains a leading cause of infectious disease morbidity and mortality for which new drug combination therapies are needed. Mycobacterial bioenergetics has emerged as a promising space for the development of novel therapeutics. Further to this, unique combinations of respiratory inhibitors have been shown to have synergistic or synthetic lethal interactions, suggesting that combinations of bioenergetic inhibitors could drastically shorten treatment times. Realizing the full potential of this unique target space requires an understanding of which combinations of respiratory complexes, when inhibited, have the strongest interactions and potential in a clinical setting. In this review, we discuss (i) chemical-interaction, (ii) genetic-interaction and (iii) chemical-genetic interaction studies to explore the consequences of inhibiting multiple mycobacterial respiratory components. We provide potential mechanisms to describe the basis for the strongest interactions. Finally, whilst we place an emphasis on interactions that occur with existing bioenergetic inhibitors, by highlighting interactions that occur with alternative respiratory components we envision that this information will provide a rational to further explore alternative proteins as potential drug targets and as part of unique drug combinations.

Extracting abundance information from DNA ‐based data

The accurate extraction of species-abundance information from DNA-based data (metabarcoding, metagenomics) could contribute usefully to diet analysis and food-web reconstruction, the inference of species interactions, the modelling of population dynamics and species distributions, the biomonitoring of environmental state and change, and the inference of false positives and negatives. However, multiple sources of bias and noise in sampling and processing combine to inject error into DNA-based data sets. To understand how to extract abundance information, it is useful to distinguish two concepts. (i) Within-sample across-species quantification describes relative species abundances in one sample. (ii) Across-sample within-species quantification describes how the abundance of each individual species varies from sample to sample, such as over a time series, an environmental gradient or different experimental treatments. First, we review the literature on methods to recover across-species abundance information (by removing what we call "species pipeline biases") and within-species abundance information (by removing what we call "pipeline noise"). We argue that many ecological questions can be answered with just within-species quantification, and we therefore demonstrate how to use a "DNA spike-in" to correct for pipeline noise and recover within-species abundance information. We also introduce a model-based estimator that can be used on data sets without a physical spike-in to approximate and correct for pipeline noise.

Fluidic Flow Enhances the Differentiation of Placental Trophoblast-Like 3D Tissue from hiPSCs in a Perfused Macrofluidic Device

The human placenta serves as a multifunctional organ to maintain the proper development of a fetus. However, our knowledge of the human placenta is limited due to the lack of appropriate experimental models. In this work, we created an in vitro placental trophoblast-like model via self-organization of human induced pluripotent stem cells (hiPSCs) in a perfused 3D culture macrofluidic device. This device allowed cell seeding, in situ trophoblast lineage differentiation, and formation of trophoblast-like tissues from hiPSCs in a biomimetic microenvironment. It incorporated extracellular matrix (ECM) and fluid flow in a single device. After trophoblast lineage differentiation, we were able to generate the 3D clusters with major cell types of the human placenta, including trophoblast progenitor cytotrophoblasts (CTBs), differentiated subtypes, syncytiotrophoblasts (STBs), and extravillous trophoblasts (EVTs) under long-term 3D culture (∼23 days). Moreover, the formed tissues exhibited enhanced expressions of CTB-, STB-, and EVT-related markers at the level of genes and proteins under a dynamic culture compared with static conditions. RNA-seq analysis revealed the higher expression of trophoblast-specific genes in 3D tissues, indicating the essential role of fluid flow to promote the trophoblast differentiation of hiPSCs. The established placental 3D model combined a bioengineering strategy with developmental principles, providing a promising platform for the study of placental biology in a biomimetic microenvironment in health and disease.

Ancient Mitogenomes Reveal the Origins and Genetic Structure of the Neolithic Shimao Population in Northern China

Shimao City is considered an important political and religious center during the Late Neolithic Longshan period of the Middle Yellow River basin. The genetic history and population dynamics among the Shimao and other ancient populations, especially the Taosi-related populations, remain unknown. Here, we sequenced 172 complete mitochondrial genomes, ranging from the Yangshao to Longshan period, from individuals related to the Shimao culture in northern Shaanxi Province and Taosi culture in southern Shanxi Province, Middle Yellow River basin. Our results show that the populations inhabiting Shimao City had close genetic connections with an earlier population in the Middle Neolithic Yangshao period of northern Shaanxi Province, revealing a mostly local origin for the Shimao Society. In addition, among the populations in other regions of the Yellow River basin, the Shimao-related populations had the closest maternal affinity with the contemporaneous Taosi populations from the Longshan period. The Shimao-related populations also shared more affinity with present-day northern Han populations than with the minorities and southern Han in China. Our study provides a new perspective on the genetic origins and structure of the Shimao people and the population dynamics in the Middle Yellow River basin during the Neolithic period.

The Antioxidant Properties of Mushroom Polysaccharides can Potentially Mitigate Oxidative Stress, Beta-Cell Dysfunction and Insulin Resistance

Diabetes mellitus is a prevalent metabolic and endocrine illness affecting people all over the world and is of serious health and financial concern. Antidiabetic medicine delivered through pharmacotherapy, including synthetic antidiabetic drugs, are known to have several negative effects. Fortunately, several natural polysaccharides have antidiabetic properties, and the use of these polysaccharides as adjuncts to conventional therapy is becoming more common, particularly in underdeveloped nations. Oxidative stress has a critical role in the development of diabetes mellitus (DM). The review of current literature presented here focusses, therefore, on the antioxidant properties of mushroom polysaccharides used in the management of diabetic complications, and discusses whether these antioxidant properties contribute to the deactivation of the oxidative stress-related signalling pathways, and to the amelioration of β-cell dysfunction and insulin resistance. In this study, we conducted a systematic review of the relevant information concerning the antioxidant and antidiabetic effects of mushrooms from electronic databases, such as PubMed, Scopus or Google Scholar, for the period 1994 to 2021. In total, 104 different polysaccharides from mushrooms have been found to have antidiabetic effects. Most of the literature on mushroom polysaccharides has demonstrated the beneficial effects of these polysaccharides on reactive oxygen and nitrogen species (RONS) levels. This review discuss the effects of these polysaccharides on hyperglycemia and other alternative antioxidant therapies for diabetic complications through their applications and limits, in order to gain a better understanding of how they can be used to treat DM. Preclinical and phytochemical investigations have found that most of the active polysaccharides extracted from mushrooms have antioxidant activity, reducing oxidative stress and preventing the development of DM. Further research is necessary to confirm whether mushroom polysaccharides can effectively alleviate hyperglycemia, and the mechanisms by which they do this, and to investigate whether these polysaccharides might be utilized as a complementary therapy for the prevention and management of DM in the future.

Boosting Output Performance of Triboelectric Nanogenerator via Mutual Coupling Effects Enabled Photon-Carriers and Plasmon

Boosting the output performance of triboelectric nanogenerators via some unique methods is always a meaningful way to speed up their commercialization. However, the available approach to boost performance is mainly restricted to one physics effect based and the basic research of boosting performance via mutual coupling effects is little research. Herein, a new strategy is creatively proposed based on charge traps from mutual coupling effects, generated from g-C3 N4 /MXene-Au composites, to further promote the output performance of triboelectric nanogenerator. It is found that photon-generated carriers coupling surface plasmon effect enables composites filled into tribo-material with visible light is an excellent value in boosting performance. The charge traps from mutual coupling effects for boosting performance are analyzed theoretically and verified by experiments. The output power of boosting-triboelectric nanogenerator (TENG) achieves a sixfold enhancement (20 mW) of normal TENG with polydimethylsiloxane (PDMS) in ambient conditions. This work provides a profound understanding of the working mechanism of mutual coupling effects boosting the performance of TENG and an effective way for promoting TENG output.

Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress

Endoplasmic reticulum stress (ER stress) is a condition that is defined by abnormal accumulation of unfolded proteins. It plays an important role in maintaining cellular protein, lipid, and ion homeostasis. By triggering the unfolded protein response (UPR) under ER stress, cells restore homeostasis or undergo apoptosis. Chronic ER stress is implicated in many human diseases. Despite extensive studies on related signaling mechanisms, reliable image biomarkers for ER stress remain lacking. To address this deficiency, we have validated a morphological image biomarker for ER stress and have developed a deep learning-based assay to enable automated detection and analysis of this marker for screening studies. Specifically, ER under stress exhibits abnormal morphological patterns that feature ring-shaped structures called whorls (WHs). Using a highly specific chemical probe for unfolded and aggregated proteins, we find that formation of ER whorls is specifically associated with the accumulation of the unfolded and aggregated proteins. This confirms that ER whorls can be used as an image biomarker for ER stress. To this end, we have developed ER-WHs-Analyzer, a deep learning-based image analysis assay that automatically recognizes and localizes ER whorls similarly as human experts. It does not require laborious manual annotation of ER whorls for training of deep learning models. Importantly, it reliably classifies different patterns of ER whorls induced by different ER stress drugs. Overall, our study provides mechanistic insights into morphological patterns of ER under stress as well as an image biomarker assay for screening studies to dissect related disease mechanisms and to accelerate related drug discoveries. It demonstrates the effectiveness of deep learning in recognizing and understanding complex morphological phenotypes of ER.

Research Advances in Gametogenesis and Embryogenesis Using Pluripotent Stem Cells

The previous studies of human gametogenesis and embryogenesis have left many unanswered questions, which hinders the understanding of the physiology of these two vital processes and the development of diagnosis and treatment strategies for related diseases. Although many results have been obtained from animal studies, particularly mouse research, the results cannot be fully applied to humans due to species differences in physiology and pathology. However, due to ethical and material limitations, the direct study of human gametes and embryos is very difficult. The emergence and rapid development of organoids allow the construction of organoid systems that simulate gametogenesis and embryogenesis in vitro, and many studies have successfully established organoid systems for some parts of or even the entire processes of gametogenesis and embryogenesis. These studies typically start with the establishment of mouse models and then modify these models to obtain human organoid models. These organoid models can be used to obtain a better understanding of the signaling pathways, molecular mechanisms, genetics, and epigenetic changes involved in gametogenesis and embryogenesis and could also be applied to clinical applications, such as drug screening. Here, we discuss the formation of primordial stem cell-like cells (PGCLCs), and in vitro-induced gametes and embryoids using pluripotent stem cells (PSCs). We also analyze their applications and limitations.

Multifunctional Chemical Sensing Platform Based on Dual-Resonant Infrared Plasmonic Perfect Absorber for On-Chip Detection of Poly(ethyl cyanoacrylate)

Multifunctional chemical sensing is highly desirable in industry, agriculture, and environmental sciences, but remains challenging due to the diversity of chemical substances and reactions. Surface-enhanced infrared absorption (SEIRA) spectroscopy can potentially address the above problems by ultra-sensitive detection of molecular fingerprint vibrations. Here, a multifunctional chemical sensing platform based on dual-resonant SEIRA device for sensitive and multifunctional on-chip detection of poly(ethyl cyanoacrylate) (PECA) is reported. It is experimentally demonstrated that the SEIRA sensing platform achieves multiple functions required by the PECA glue industry, including vibrational detection, thickness measurement, and in situ observation of polymerization and curing, which are usually realized by separately using a spectrometer, a viscometer, and an ellipsometer in the past. Specifically, the all-in-one sensor offers a dual-band fingerprint vibration identification, sub-nm level detection limit, and ultrahigh sensitivity of 0.76%/nm in thickness measurement, and second-level resolution in real-time observation of polymerization and curing. This work not only provides a valuable toolkit for ultra-sensitive and multifunctional on-chip detection of PECA, but also gives new insights into the SEIRA technology for multi-band, multi-functional, and on-chip chemical sensing.