Lipid metabolic reprogramming mediated by circulating Nrg4 alleviates metabolic dysfunction-associated steatotic liver disease during the early recovery phase after sleeve gastrectomy.

BACKGROUND: The metabolic benefits of bariatric surgery that contribute to the alleviation of metabolic dysfunction-associated steatotic liver disease (MASLD) have been reported. However, the processes and mechanisms underlying the contribution of lipid metabolic reprogramming after bariatric surgery to attenuating MASLD remain elusive. METHODS: A case-control study was designed to evaluate the impact of three of the most common adipokines (Nrg4, leptin, and adiponectin) on hepatic steatosis in the early recovery phase following sleeve gastrectomy (SG). A series of rodent and cell line experiments were subsequently used to determine the role and mechanism of secreted adipokines following SG in the alleviation of MASLD. RESULTS: In morbidly obese patients, an increase in circulating Nrg4 levels is associated with the alleviation of hepatic steatosis in the early recovery phase following SG before remarkable weight loss. The temporal parameters of the mice confirmed that an increase in circulating Nrg4 levels was initially stimulated by SG and contributed to the beneficial effect of SG on hepatic lipid deposition. Moreover, this occurred early following bariatric surgery. Mechanistically, gain- and loss-of-function studies in mice or cell lines revealed that circulating Nrg4 activates ErbB4, which could positively regulate fatty acid oxidation in hepatocytes to reduce intracellular lipid deposition. CONCLUSIONS: This study demonstrated that the rapid effect of SG on hepatic lipid metabolic reprogramming mediated by circulating Nrg4 alleviates MASLD.

The significance of gut microbiota in the etiology of autoimmune hepatitis: a narrative review.

Autoimmune hepatitis (AIH) is a chronic inflammatory disease of the liver that is mediated by autoimmunity and has complex pathogenesis. Its prevalence has increased globally. Since the liver is the first organ to be exposed to harmful substances, such as gut-derived intestinal microbiota and its metabolites, gut health is closely related to liver health, and the "liver-gut axis" allows abnormalities in the gut microbiota to influence the development of liver-related diseases such as AIH. Changes in the composition of the intestinal microbiota and its resultant disruption of the intestinal barrier and microbial transport are involved in multiple ways in the disruption of immune homeostasis and inflammation, thereby influencing the development of AIH. In terms of the mechanisms involved in immune, the gut microbiota or its metabolites, which is decreased in secondary bile acids, short-chain fatty acids (SCFAs), and polyamines, and increased in lipopolysaccharide (LPS), branched-chain amino acids (BCAA), tryptophan metabolite, amino acid, and bile acid, can disrupt immune homeostasis by activating various immune cells and immune-related signaling pathways, resulting in aberrant activation of the immune system. Clarifying this mechanism has significant clinical implications for the treatment of AIH with drugs that target intestinal microbiota and related signaling pathways. Therefore, this narrative review summarizes the progress in exploring the involvement of gut microbiota in the pathogenesis of AIH, with the aim of helping to improve the precise targeting of therapeutic treatments against AIH for the benefit of clinical AIH treatment.

PaLectinL7 enhances salt tolerance of sweet cherry by regulating lignin deposition in connection with PaCAD1.

Lectin receptor-like kinases (LecRLKs), a large family of plant receptor-like kinases, play an important role in plant response to abiotic stresses. However, little information is available about the roles of LecRLKs in the salt stress response of sweet cherry (Prunus avium). Here, an L-type LecRLK gene (PaLectinL7) was characterized from sweet cherry. Subcellular localization analysis revealed that PaLectinL7 is a plasma membrane protein. The expression of PaLectinL7 was up-regulated by salt, drought and exogenously gibberellin treatments. Overexpression of PaLectinL7 in the roots of Gisela 6 enhanced its tolerance to salt stress. Additionally, transcriptome analysis showed that lignin metabolic-related genes were regulated by PaLectinL7 overexpression. Meanwhile, the lignin contents and associated enzymes (CAD and COMT) rose concurrently with PaLectinL7 overexpression under salt stress. We also found that PaCAD1, a key enzyme involved in lignin metabolism, interacted with PaLectinL7 and could be phosphorylated by PaLectinL7 in vitro, suggesting that PaLectinL7 may regulate the enzyme activity of PaCAD1. Therefore, these results indicated that PaLectinL7, as a membrane-bound regulator, promoted lignin deposition by regulating the activities of enzymes related to lignin metabolism, thus enhancing salt tolerance.

Chromosome-level genome assembly provides new insights into Japanese chestnut (Castanea crenata) genomes.

Japanese chestnut (Castanea crenata Sieb. et Zucc) is an economically and ecologically important chestnut species in East Asia. Here, we presented a high-quality chromosome-level reference genome of the Japanese chestnut cultivar 'Tsukuba' by combining Nanopore long reads and Hi-C sequencing. The final assembly has a size of 718.30 Mb and consists of 12 pseudochromosomes ranging from 41.03 to 92.03 Mb, with a BUSCO complete gene percentage of 97.6%. A total of 421.37 Mb repetitive sequences and 46,744 gene models encoding 46,463 proteins were predicted in the genome. Genome evolution analysis showed that Japanese chestnut is closely related to Chinese chestnut and these species shared a common ancestor ~6.5 million years ago. This high-quality Japanese chestnut genome represents an important resource for the chestnut genomics community and will improve our understanding of chestnut biology and evolution.

A bZIP transcription factor VabZIP12 from blueberry induced by dark septate endocyte improving the salt tolerance of transgenic Arabidopsis.

Dark septate endophytes (DSEs) have attracted much attention due to their positive roles in plant growth as well as resistance to various abiotic stresses. However, there are no reports on the molecular mechanisms of DSE fungi to improve salt tolerance in plants. In this study, the blueberry seedlings inoculated with T010, a beneficial DSE fungus reported previously, grew more vigorously than the non-inoculated control under salt stress. Physiological indicators showed that T010 inoculation increased antioxidant activities of blueberry roots. To explore its molecular mechanism, we focused on the bZIP TFs VabZIP12, who was highly up-regulated with T010 inoculation under salt stress. Further studies showed that VabZIP12, as a transcription activator, could combine both G-Box 1 and G-Box 2 motifs. Moreover, overexpression of VabZIP12 enhanced salt stress tolerance through increasing the activities of the enzymatic antioxidants in the transgenic Arabidopsis with up-regulation the related genes. These results indicated that the induction of VabZIP12 contribute to improving the tolerance of blueberry to salt stress by T010 inoculation.

MFCIS: an automatic leaf-based identification pipeline for plant cultivars using deep learning and persistent homology.

Recognizing plant cultivars reliably and efficiently can benefit plant breeders in terms of property rights protection and innovation of germplasm resources. Although leaf image-based methods have been widely adopted in plant species identification, they seldom have been applied in cultivar identification due to the high similarity of leaves among cultivars. Here, we propose an automatic leaf image-based cultivar identification pipeline called MFCIS (Multi-feature Combined Cultivar Identification System), which combines multiple leaf morphological features collected by persistent homology and a convolutional neural network (CNN). Persistent homology, a multiscale and robust method, was employed to extract the topological signatures of leaf shape, texture, and venation details. A CNN-based algorithm, the Xception network, was fine-tuned for extracting high-level leaf image features. For fruit species, we benchmarked the MFCIS pipeline on a sweet cherry (Prunus avium L.) leaf dataset with >5000 leaf images from 88 varieties or unreleased selections and achieved a mean accuracy of 83.52%. For annual crop species, we applied the MFCIS pipeline to a soybean (Glycine max L. Merr.) leaf dataset with 5000 leaf images of 100 cultivars or elite breeding lines collected at five growth periods. The identification models for each growth period were trained independently, and their results were combined using a score-level fusion strategy. The classification accuracy after score-level fusion was 91.4%, which is much higher than the accuracy when utilizing each growth period independently or mixing all growth periods. To facilitate the adoption of the proposed pipelines, we constructed a user-friendly web service, which is freely available at http://www.mfcis.online .

Chromosome-scale genome assembly of sweet cherry (Prunus avium L.) cv. Tieton obtained using long-read and Hi-C sequencing.

Sweet cherry (Prunus avium) is an economically significant fruit species in the genus Prunus. However, in contrast to other important fruit trees in this genus, only one draft genome assembly is available for sweet cherry, which was assembled using only Illumina short-read sequences. The incompleteness and low quality of the current sweet cherry draft genome limit its use in genetic and genomic studies. A high-quality chromosome-scale sweet cherry reference genome assembly is therefore needed. A total of 65.05 Gb of Oxford Nanopore long reads and 46.24 Gb of Illumina short reads were generated, representing ~190x and 136x coverage, respectively, of the sweet cherry genome. The final de novo assembly resulted in a phased haplotype assembly of 344.29 Mb with a contig N50 of 3.25 Mb. Hi-C scaffolding of the genome resulted in eight pseudochromosomes containing 99.59% of the bases in the assembled genome. Genome annotation revealed that more than half of the genome (59.40%) was composed of repetitive sequences, and 40,338 protein-coding genes were predicted, 75.40% of which were functionally annotated. With the chromosome-scale assembly, we revealed that gene duplication events contributed to the expansion of gene families for salicylic acid/jasmonic acid carboxyl methyltransferase and ankyrin repeat-containing proteins in the genome of sweet cherry. Four auxin-responsive genes (two GH3s and two SAURs) were induced in the late stage of fruit development, indicating that auxin is crucial for the sweet cherry ripening process. In addition, 772 resistance genes were identified and functionally predicted in the sweet cherry genome. The high-quality genome assembly of sweet cherry obtained in this study will provide valuable genomic resources for sweet cherry improvement and molecular breeding.

A de novo assembly of the sweet cherry (Prunus avium cv. Tieton) genome using linked-read sequencing technology.

The sweet cherry (Prunus avium) is one of the most economically important fruit species in the world. However, there is a limited amount of genetic information available for this species, which hinders breeding efforts at a molecular level. We were able to describe a high-quality reference genome assembly and annotation of the diploid sweet cherry (2n = 2x = 16) cv. Tieton using linked-read sequencing technology. We generated over 750 million clean reads, representing 112.63 GB of raw sequencing data. The Supernova assembler produced a more highly-ordered and continuous genome sequence than the current P. avium draft genome, with a contig N50 of 63.65 KB and a scaffold N50 of 2.48 MB. The final scaffold assembly was 280.33 MB in length, representing 82.12% of the estimated Tieton genome. Eight chromosome-scale pseudomolecules were constructed, completing a 214 MB sequence of the final scaffold assembly. De novo, homology-based, and RNA-seq methods were used together to predict 30,975 protein-coding loci. 98.39% of core eukaryotic genes and 97.43% of single copy orthologues were identified in the embryo plant, indicating the completeness of the assembly. Linked-read sequencing technology was effective in constructing a high-quality reference genome of the sweet cherry, which will benefit the molecular breeding and cultivar identification in this species.

Complete Genome Sequence of a Little Cherry Virus-2 Isolate from Sweet Cherry in China.

The first complete genome sequence of a little cherry virus-2 (LChV-2-TA) isolate from China was determined using small RNA deep sequencing combined with overlapping reverse transcriptase PCR (RT-PCR). Phylogenetic analysis revealed that LChV-2-TA grouped in a well-supported cluster with members of the genus Ampelovirus with close relationships to previously reported LChV-2 isolates.

The complete chloroplast genome of Vaccinium duclouxii, an endemic species in China.

Vaccinium duclouxii is an endemic species in China, which is distributed in Sichuan and Yunnan province of China. The chloroplast (cp) genome of V. duclouxii is 168,953 bp in size containing 123 unique genes, including 8 rRNA genes, 38 tRNA genes, and 77 protein-coding genes (PCGs). Phylogenetic analysis exhibited that V. duclouxii and V. macrocarpon were most related to Arbutus unedo.

Whole-Genome Characterization of Prunus necrotic ringspot virus Infecting Sweet Cherry in China.

Prunus necrotic ringspot virus (PNRSV) causes yield loss in most cultivated stone fruits, including sweet cherry. Using a small RNA deep-sequencing approach combined with end-genome sequence cloning, we identified the complete genomes of all three PNRSV strands from PNRSV-infected sweet cherry trees and compared them with those of two previously reported isolates.

Complete Genomic Characterization of Plum bark necrosis stem pitting-associated virus Infecting Sweet Cherry in China.

Plum bark necrosis stem pitting-associated virus (PBNSPaV) causes the plum bark necrosis stem pitting-associated disease. We obtained the complete genome of a PBNSPaV isolate (PBNSPaV-TA) using small RNA deep sequencing followed by overlapping RT-PCR. To our knowledge, this is the first report of a completed genome of PBNSPaV identified from cherry trees.

Complete nucleotide sequence of little cherry virus 1 (LChV-1) infecting sweet cherry in China.

Little cherry virus 1 (LChV-1), associated with little cherry disease (LCD), has a significant impact on fruit quality of infected sweet cherry trees. We report the full genome sequence of an isolate of LChV-1 from Taian, China (LChV-1-TA), detected by small-RNA deep sequencing and amplified by overlapping RT-PCR. The LChV-1-TA genome was 16,932 nt in length and contained nine open reading frames (ORFs), with sequence identity at the overall genome level of 76%, 76%, and 78% to LChV-1 isolates Y10237 (UW2 isolate), EU715989 (ITMAR isolate) and JX669615 (V2356 isolate), respectively. Based on the phylogenetic analysis of HSP70h amino acid sequences of Closteroviridae family members, LChV-1-TA was grouped into a well-supported cluster with the members of the genus Velarivirus and was also closely related to other LChV-1 isolates. This is the first report of the complete nucleotide sequence of LChV-1 infecting sweet cherry in China.

Rapid detection of Prunus necrotic ringspot virus using magnetic nanoparticle-assisted reverse transcription loop-mediated isothermal amplification.

Prunus necrotic ringspot virus (PNRSV) has seriously reduced the yield of Prunus species worldwide. In this study, a highly efficient and specific two-step reverse transcription loop-mediated isothermal amplification (RT-LAMP) was developed to detect PNRSV. Total RNA was extracted from sweet cherry leaf samples using a commercial kit based on a magnetic nanoparticle technique. Transcripts were used as the templates for the assay. The results of this assay can be detected using agarose gel electrophoresis or by assessing in-tube fluorescence after adding SYBR Green I. The assay is highly specific for PNRSV, and it is more sensitive than reverse-transcription polymerase chain reaction (RT-PCR). Restriction enzyme digestion verified further the reliability of this RT-LAMP assay. To our knowledge, this is the first report of the application of RT-LAMP to PNRSV detection in Prunus species.

Evaluating vehicle re-entrained road dust and its potential to deposit to Lake Tahoe: a bottom-up inventory approach.

Identifying hotspot areas impacted by emissions of dust from roadways is an essential step for mitigation. This paper develops a detailed road dust PM10 emission inventory using a bottom-up approach and evaluates the potential for the dust to deposit to Lake Tahoe where it can affect water clarity. Previous studies of estimates of quantities of atmospheric deposition of fine sediment particles ("FSP", <16 µm in diameter) to the lake were questioned due to low confidence in the results and insufficient data. A bottom-up approach that integrates measured road dust emission factors, five years of meteorological data, a traffic demand model and GIS analysis was used to estimate the near field deposition of airborne particulate matter <16 µm, and assess the relationship between trip location and the potential magnitude of this source of atmospheric deposition to the lake. Approximately ~20 Mg year(-1) of PM10 and ~36 Mg year(-1) Total Suspended Particulate (TSP) from roadway emissions of dust are estimated to reach the lake. We estimate that the atmospheric dry deposition of particles to the lake attributable to vehicle travel on paved roads is approximately 0.6% of the Total Maximum Daily Loadings (TMDL) of FSP that the lake can receive and still meet water quality standards.

Particulate emission factors for mobile fossil fuel and biomass combustion sources.

PM emission factors (EFs) for gasoline- and diesel-fueled vehicles and biomass combustion were measured in several recent studies. In the Gas/Diesel Split Study (GD-Split), PM(2.5) EFs for heavy-duty diesel vehicles (HDDV) ranged from 0.2 to ~2 g/mile and increased with vehicle age. EFs for HDDV estimated with the U.S. EPA MOBILE 6.2 and California Air Resources Board (ARB) EMFAC2007 models correlated well with measured values. PM(2.5) EFs measured for gasoline vehicles were ~two orders of magnitude lower than those for HDDV and did not correlate with model estimates. In the Kansas City Study, PM(2.5) EFs for gasoline-powered vehicles (e.g., passenger cars and light trucks) were generally <0.03 g/mile and were higher in winter than summer. EMFAC2007 reported higher PM(2.5) EFs than MOBILE 6.2 during winter, but not during summer, and neither model captured the variability of the measured EFs. Total PM EFs for heavy-duty diesel military vehicles ranged from 0.18±0.03 and 1.20±0.12 g/kg fuel, corresponding to 0.3 and 2 g/mile, respectively. These values are comparable to those of on-road HDDV. EFs for biomass burning measured during the Fire Laboratory at Missoula Experiment (FLAME) were compared with EFs from the ARB Emission Estimation System (EES) model. The highest PM(2.5) EFs (76.8±37.5 g/kg) were measured for wet (>50% moisture content) Ponderosa Pine needles. EFs were generally <20 g/kg when moisture content was <20%. The EES model agreed with measured EFs for fuels with low moisture content but underestimated measured EFs for fuel with moisture content >40%. Average EFs for dry chamise, rice straw, and dry grass were within a factor of three of values adopted by ARB in California's San Joaquin Valley (SJV). Discrepancies between measured and modeled emission factors suggest that there may be important uncertainties in current PM(2.5) emission inventories.

Fugitive dust emissions from paved road travel in the Lake Tahoe basin.

The clarity of water in Lake Tahoe has declined substantially over the past 40 yr. Causes of the degradation include nitrogen and phosphorous fertilization of the lake waters and increasing amounts of inorganic fine sediment that can scatter light. Atmospheric deposition is a major source of fine sediment. A year-round monitoring study of road dust emissions around the lake was completed in 2007 using the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) system developed at the Desert Research Institute (DRI). Results of this study found that, compared with the summer season, road dust emissions increased by a factor of 5 in winter, on average, and about a factor of 10 when traction control material was applied to the roads after snow events. For winter and summer, road dust emission factors (grams coarse particulate matter [PM10] per vehicle kilometer traveled [g/vkt]) showed a decreasing trend with the travel speed of the road. The highest emission factors were observed on very low traffic volume roads on the west side of the lake. These roads were composed of either a 3/8-in. gravel material or had degraded asphalt. The principle factors influencing road dust emissions in the basin are season, vehicle speed (or road type), road condition, road grade, and proximity to other high-emitting roads. Combined with a traffic volume model, an analysis of the total emissions from the road sections surveyed indicated that urban areas (in particular South Lake Tahoe) had the highest emitting roads in the basin.

The In-Plume Emission Test Stand: an instrument platform for the real-time characterization of fuel-based combustion emissions.

The In-Plume Emission Test Stand (IPETS) characterizes gaseous and particulate matter (PM) emissions from combustion sources in real time. Carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and other gases are quantified with a closed-path Fourier transform infrared spectrometer (FTIR). Particle concentrations, chemical composition, and other particle properties are characterized with an electrical low-pressure impactor (ELPI), a light-scattering particle detector, an optical particle counter, and filter samples amenable to different laboratory analysis. IPETS measurements of fuel-based emission factors for a diesel generator are compared with those from a Mobile Emissions Laboratory (MEL). IPETS emission factors ranged from 0.3 to 11.8, 0.2 to 3.7, and 22.2 to 32.8 g/kg fuel for CO, NO2, and NO, respectively. IPETS PM emission factors ranged from 0.4 to 1.4, 0.3 to 1.8, 0.3 to 2.2, and 1 to 3.4 g/kg fuel for filter, photoacoustic, nephelometer, and impactor measurements, respectively. Observed linear regression statistics for IPETS versus MEL concentrations were as follows: CO slope = 1.1, r2 = 0.99; NO slope = 1.1, r2 = 0.92; and NO2 slope = 0.8, r2 = 0.96. IPETS versus MEL PM regression statistics were: filter slope = 1.3, r2 = 0.80; ELPI slope = 1.7, r2 = 0.87; light-scattering slope = 2.7, r2 = 0.92; and photoacoustic slope = 2.1, r2 = 0.91. Lower temperatures in the dilution air (approximately 25 degrees C for IPETS vs. approximately 50 degrees C for MEL) may result in greater condensation of semi-volatile compounds on existing particles, thereby explaining the 30% difference for filters. The other PM measurement devices are highly correlated with the filter, but their factory-default PM calibration factors do not represent the size and optical properties of diesel exhaust. They must be normalized to a simultaneous filter measurement.

In-Plume Emission Test Stand 2: emission factors for 10- to 100-kW U.S. military generators.

Although emissions of air pollutants from some military tactical equipment are not subject to the emissions standards, local communities near military bases must conform to the National Ambient Air Quality Standards. Military diesel generators are widely used in training. A portable in-plume system was used to measure fuel-based emission factors (EFs) for particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbons (HCs) for 30-, 60-, and 100-kW generators at five load levels and for cold starts. It was found that EFs depend on multiple parameters including engine size, engine load, unit age, and total running hours. The average CO EF of generators tested was 5% lower, and the average NOx EF was 63% lower than AP-42 estimates; average PM EF was 80% less than the AP-42 estimates. A 2002 model-year 60-kW engine produced 25% less PM than a 1995 engine of the same family with similar running hours. CO EFs decrease with increasing engine load, NOx EFs increase up to mid-loads and decrease slightly at high loads, PM EFs increase with loads for 30- and 60-kW engines. CO and PM have higher EFs and NOx has a lower EF during cold starts than during hot-stabilized operation. PM chemical source profiles were also examined.