Transcriptome Analysis Revealed Potential Genes of Skeletal Muscle Thermogenesis in Mashen Pigs and Large White Pigs under Cold Stress.

Pigs are susceptible to cold stress due to the absence of brown fat caused by the partial deletion of uncoupling protein 1 during their evolution. Some local pig breeds in China exhibit potential cold adaptability, but research has primarily focused on fat and intestinal tissues. Skeletal muscle plays a key role in adaptive thermogenesis in mammals, yet the molecular mechanism of cold adaptation in porcine skeletal muscle remains poorly understood. This study investigated the cold adaptability of two pig breeds, Mashen pigs (MS) and Large White pigs (LW), in a four-day cold (4 °C) or normal temperature (25 °C) environment. We recorded phenotypic changes and collected blood and longissimus dorsi muscle for transcriptome sequencing. Finally, the PRSS8 gene was randomly selected for functional exploration in porcine skeletal muscle satellite cells. A decrease in body temperature and body weight in both LW and MS pigs under cold stress, accompanied by increased shivering frequency and respiratory frequency, were observed. However, the MS pigs demonstrated stable physiological homeostasis, indicating a certain level of cold adaptability. The LW pigs primarily responded to cold stress by regulating their heat production and glycolipid energy metabolism. The MS pigs exhibited a distinct response to cold stress, involving the regulation of heat production, energy metabolism pathways, and robust mitochondrial activity, as well as a stronger immune response. Furthermore, the functional exploration of PRSS8 in porcine skeletal muscle satellite cells revealed that it affected cellular energy metabolism and thermogenesis by regulating ERK phosphorylation. These findings shed light on the diverse transcriptional responses of skeletal muscle in LW and MS pigs under cold stress, offering valuable insights into the molecular mechanisms underlying cold adaptation in pigs.

Comprehensive analysis of differentially expressed circRNAs and ceRNA regulatory network in porcine skeletal muscle.

BACKGROUND: Circular RNA (circRNA), a novel class of non-coding RNA, has a closed-loop structure with important functions in skeletal muscle growth. The purpose of this study was to investigate the role of differentially expressed circRNAs (DEcircRNAs), as well as the DEcircRNA-miRNA-mRNA regulatory network, at different stages of porcine skeletal muscle development. Here, we present a panoramic view of circRNA expression in porcine skeletal muscle from Large White and Mashen pigs at 1, 90, and 180 days of age. RESULTS: We identified a total of 5819 circRNAs. DEcircRNA analysis at different stages showed 327 DEcircRNAs present in both breeds. DEcircRNA host genes were concentrated predominately in TGF-ß, MAPK, FoxO, and other signaling pathways related to skeletal muscle growth and fat deposition. Further prediction showed that 128 DEcircRNAs could bind to 253 miRNAs, while miRNAs could target 945 mRNAs. The constructed ceRNA network plays a vital role in skeletal muscle growth and development, and fat deposition. Circ_0015885/miR-23b/SESN3 in the ceRNA network attracted our attention. miR-23b and SESN3 were found to participate in skeletal muscle growth regulation, also playing an important role in fat deposition. Using convergent and divergent primer amplification, RNase R digestion, and qRT-PCR, circ_0015885, an exonic circRNA derived from Homer Scaffold Protein 1 (HOMER1), was confirmed to be differentially expressed during skeletal muscle growth. In summary, circ_0015885 may further regulate SESN3 expression by interacting with miR-23b to function in skeletal muscle. CONCLUSIONS: This study not only enriched the circRNA library in pigs, but also laid a solid foundation for the screening of key circRNAs during skeletal muscle growth and intramural fat deposition. In addition, circ_0015885/miR-23b/SESN3, a new network regulating skeletal muscle growth and fat deposition, was identified as important for increasing the growth rate of pigs and improving meat quality.

A seven-DNA methylation signature as a novel prognostic biomarker in breast cancer.

BACKGROUND: Breast cancer (BC) is a common malignant tumor and its incidence and mortality rates are ranked first among female cancers. So far, there has been no effective biomarkers for BC prognosis. METHODS: The DNA methylation data of BC was downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and Functional ANnoTation of The Mammalian Genome databases. The RNA-Seq data and clinical information of patients were downloaded from TCGA. R packages edgeR and minfi were used for differentially methylated genes (DMGs) screening. Then, the DMGs were collected for gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis by the online tool database for annotation, visualization and integrated discovery (DAVID) and Reactome. Cox regression analysis was used to screen candidate differentially methylated sites (DMSs) for BC prognosis. Logrank test was used to explore the correlation between DMSs and survival time. Correlation analysis was used to investigate the correlation between DNA methylation and gene expression. RESULTS: We identified 276 DMGs which contained 1454 DMSs in those three datasets. Also, six DMGs that contained seven DMSs were identified by Cox regression analysis. Interestingly, their expression levels were negatively correlated with the DNA methylation level and not affected by age, subtypes, or tumor stages. CONCLUSIONS: We proposed that these seven differentially DNA methylation sites can be used as a novel prognostic biomarker for BC area under curve (AUC) = 0.74), which may facilitate research and benefit the clinical treatment of BC.

Identification of MFI2-AS1, a Novel Pivotal lncRNA for Prognosis of Stage III/IV Colorectal Cancer.

BACKGROUND: Long noncoding RNAs (lncRNAs) have been shown to play pivotal role in pathogenesis and prognosis of cancers. Identification of novel clinical biomarkers in advanced stage colorectal cancer (CRC) is warranted. AIMS: To identify potential lncRNAs associated with progression of stage III/IV CRC and illuminate regulatory mechanisms. METHODS: Differentially expressed lncRNAs, mRNAs and miRNAs (DElncRNAs, DEmRNAs, and DEmiRNAs) were extracted between stage III/IV CRC and normal tissues. We used DEGs to construct a ceRNA network and analyzed correlations between key lncRNAs and overall survivals (OS) of stage III/IV CRC patients. Weighted gene co-expression network analysis (WGCNA) was applied to a pivotal lncRNA. We conducted functional enrichment analysis on target genes and constructed lncRNA-TF-mRNA network by overlapping mRNAs co-expressed with the key lncRNA and target genes of transcriptional factors (TFs). RESULTS: A total of 26 DElncRNAs, 398 DEmiRNAs, 2155 DEmRNAs were identified. A ceRNA network was constructed with 16 lncRNAs, 20 miRNAs, and 59 mRNAs, in which MFI2-AS1 exhibited promising diagnostic efficiency. (AUC was 0.938.) MFI2-AS1 was negatively correlated to OS of stage III/IV CRC patients (P value < 0.05). KEGG analysis showed potential mRNA targets of MFI2-AS1 mainly involved in cell cycle and cytokine-cytokine receptor interaction. We identified 17 potential TFs of MFI2-AS1 and built a lncRNA-TF-mRNA network. CONCLUSION: Our study provides novel insights into lncRNAs associated regulatory networks and reveals a promising lncRNA biomarker, MFI2-AS1, as an independent prognostic indicator and potential therapeutic target for CRC.

A Novel Change Detection Method for Natural Disaster Detection and Segmentation from Video Sequence.

Change detection (CD) is critical for natural disaster detection, monitoring and evaluation. Video satellites, new types of satellites being launched recently, are able to record the motion change during natural disasters. This raises a new problem for traditional CD methods, as they can only detect areas with highly changed radiometric and geometric information. Optical flow-based methods are able to detect the pixel-based motion tracking at fast speed; however, they are difficult to determine an optimal threshold for separating the changed from the unchanged part for CD problems. To overcome the above problems, this paper proposed a novel automatic change detection framework: OFATS (optical flow-based adaptive thresholding segmentation). Combining the characteristics of optical flow data, a new objective function based on the ratio of maximum between-class variance and minimum within-class variance has been constructed and two key steps are motion detection based on optical flow estimation using deep learning (DL) method and changed area segmentation based on an adaptive threshold selection. Experiments are carried out using two groups of video sequences, which demonstrated that the proposed method is able to achieve high accuracy with F1 value of 0.98 and 0.94, respectively.

Identification of functional lncRNAs in gastric cancer by integrative analysis of GEO and TCGA data.

Gastric cancer (GC) is a prevalent malignant cancer of digestive system, identification of novel diagnostic and prognostic biomarkers for GC is urgently demanded. The aim of this study was to determine potential long noncoding RNAs (lncRNAs) associated with the pathogenesis and prognosis of GC. Raw noncoding RNA microarray data (GSE53137, GSE70880, and GSE99417) was downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes between GC and adjacent normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile after gene reannotation and batch normalization. Differentially expressed genes were further confirmed by The Cancer Genome Atlas (TCGA) database. Competing endogenous RNA (ceRNA) network, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway, survival analysis were extensively applied to identify hub lncRNAs and discover potential biomarkers related to diagnosis and prognosis of GC. In total of 246 integrated differential genes including 15 lncRNAs and 241 messenger RNAs (mRNAs) were obtained after intersections of differential genes between GEO and TCGA database. ceRNA network comprised of three lncRNAs (UCA1, HOTTIP, and HMGA1P4), 26 microRNAs (miRNAs) and 72 mRNAs. Functional analysis revealed that three lncRNAs were mainly dominated in cell cycle and cellular senescence. Survival analysis showed that HMGA1P4 was statistically related to the overall survival rate. For the first time, we identified that HMGA1P4, a target of miR-301b/miR-508, is involved in cell cycle and senescence process by regulating CCNA2 in GC. Finally, the expression levels of three lncRNAs were validated to be upregulated in GC tissues. Thus, three lncRNAs including UCA1, HOTTIP, and HMGA1P4 may contribute to GC development and their potential functions might be associated with the prognosis of GC.

Rydberg-atom-based digital communication using a continuously tunable radio-frequency carrier.

Up to now, the measurement of radio-frequency (RF) electric field achieved using the electromagnetically-induced transparency (EIT) of Rydberg atoms has proved to be of high-sensitivity and shows a potential to produce a promising atomic RF receiver at resonance between two chosen Rydberg states. In this paper, we study the extension of the feasibility of digital communication via this quantum-based antenna over a continuously tunable RF-carrier at off-resonance. Our experiment shows that the digital communication at a rate of 500 kbps can be performed reliably within a tunable bandwidth of 200 MHz near a 10.22 GHz carrier. Outside of this range, the bit error rate (BER) increases, rising to, for example, 15% at an RF-detuning of ±150 MHz. In the measurement, the time-varying RF field is retrieved by detecting the optical power of the probe laser at the center frequency of RF-induced symmetric or asymmetric Autler-Townes splitting in EIT. Prior to the digital test, we studied the RF-reception quality as a function of various parameters including the RF detuning and found that a choice of linear gain response to the RF-amplitude can suppress the signal distortion. The modulating signal can be decoded at speeds up to 500 kHz in the tunable bandwidth. Our test consolidates the physical basis for reliable communication and spectral sensing over a wider broadband RF-carrier, which paves a way for the concurrent multi-channel communications founded on the same pair of Rydberg states.

Selection of candidate genes affecting meat quality and preliminary exploration of related molecular mechanisms in the Mashen pig.

OBJECTIVE: The aim of this study was to select the candidate genes affecting meat quality and preliminarily explore the related molecular mechanisms in the Mashen pig. METHODS: The present study explored genetic factors affecting meat quality in the Mashen pig using RNA sequencing (RNA-Seq). We sequenced the transcriptomes of 180-day-old Mashen and Large White pigs using longissimus dorsi to select differentially expressed genes (DEGs). RESULTS: The results indicated that a total of 425 genes were differentially expressed between Mashen and Large White pigs. A gene ontology enrichment analysis revealed that DEGs were mainly enriched for biological processes associated with metabolism and muscle development, while a Kyoto encyclopedia of genes and genomes analysis showed that DEGs mainly participated in signaling pathways associated with amino acid metabolism, fatty acid metabolism, and skeletal muscle differentiation. A MCODE analysis of the protein-protein interaction network indicated that the four identified subsets of genes were mainly associated with translational initiation, skeletal muscle differentiation, amino acid metabolism, and oxidative phosphorylation pathways. CONCLUSION: Based on the analysis results, we selected glutamic-oxaloacetic transaminase 1, malate dehydrogenase 1, pyruvate dehydrogenase 1, pyruvate dehydrogenase kinase 4, and activator protein-1 as candidate genes affecting meat quality in pigs. A discussion of the related molecular mechanisms is provided to offer a theoretical basis for future studies on the improvement of meat quality in pigs.

Field Distortion and Optimization of a Vapor Cell in Rydberg Atom-Based Radio-Frequency Electric Field Measurement.

Highly excited Rydberg atoms in a room-temperature vapor cell are promising for developing a radio-frequency (RF) electric field (E-field) sensor and relevant measurement standards with high accuracy and sensitivity. The all-optical sensing approach is based on electromagnetically-induced transparency and Autler-Townes splitting induced by the RF E-field. Systematic investigation of measurement uncertainty is of great importance for developing a national measurement standard. The presence of a dielectric vapor cell containing alkali atoms changes the magnitude, polarization, and spatial distribution of the incident RF field. In this paper, the field distortion of rubidium vapor cells is investigated, in terms of both field strength distortion and depolarization. Full-wave numerical simulation and analysis are employed to determine general optimization solutions for minimizing such distortion and validated by measuring the E-field vector distribution inside different vapor cells. This work can improve the accuracy of atom-based RF E-field measurements and contributes to the development of related RF quantum sensors.

Novel splice isoforms of pig myoneurin and their diverse mRNA expression patterns.

OBJECTIVE: The aim of this study was to clone alternative splicing isoforms of pig myoneurin (MYNN), predict the structure and function of coding protein, and study temporal and spatial expression characteristics of each transcript. METHODS: Alternative splice isoforms of MYNN were identified using RNA sequencing (RNA-seq) and cloning techniques. Quantitative real-time polymerase chain reaction (qPCR) was employed to detect expression patterns in 11 tissues of Large White (LW) and Mashen (MS) pigs, and to study developmental expression patterns in cerebellum (CE), stomach (ST), and longissimus dorsi (LD). RESULTS: The results showed that MYNN had two alternatively spliced isoforms, MYNN-1 (GenBank accession number: KY470829) and MYNN-2 (GenBank accession number: KY670835). MYNN-1 coding sequence (CDS) is composed of 1,830 bp encoding 609 AA, whereas MYNN-2 CDS is composed of 1,746 bp encoding 581 AA. MYNN-2 was 84 bp less than MYNN-1 and lacked the sixth exon. MYNN-2 was found to have one C2H2 type zinc finger protein domain less than MYNN-1. Two variants were ubiquitously expressed in all pig tissues, and there were significant differences in expression of different tissues (p<0.05; p<0.01). The expression of MYNN-1 was significantly higher than that of MYNN-2 in almost tissues (p<0.05; p<0.01), which testified that MYNN-1 is the main variant. The expression of two isoforms decreased gradually with increase of age in ST and CE of MS pig, whereas increased gradually in LW pig. In LD, the expression of two isoforms increased first and then decreased with increase of age in MS pig, and decreased gradually in LW pig. CONCLUSION: Two transcripts of pig MYNN were successfully cloned and MYNN-1 was main variant. MYNN was highly expressed in ST, CE, and LD, and their expression was regular. We speculated that MYNN plays important roles in digestion/absorption and skeletal muscle growth, whereas the specific mechanisms require further elucidation.

Preparation of multiwalled carbon nanotubes/hydroxyl-terminated silicone oil fiber and its application to analysis of crude oils.

A simple and efficient method to analyze the volatile and semivolatile organic compounds in crude oils has been developed based on direct immersion solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (DI-SPME-GC × GC/TOFMS). A novel fiber, multiwalled carbon nanotubes/hydroxyl-terminated silicone oil (MWNTs-TSO-OH), was prepared by sol-gel technology. Using standard solutions, the extraction conditions were optimized such as extraction mode, extraction temperature, extraction time, and salts effect. With the optimized conditions, a real crude oil sample was extracted and then analyzed in detail. It shows that the proposed method is very effective in simultaneously analyzing the normal and branched alkanes, cycloalkanes, aromatic hydrocarbons, and biomarkers of crude oil such as steranes and terpanes. Furthermore, the method showed good linearity (r > 0.999), precision (RSD < 8%), and detection limits ranging from 0.2 to 1.6 ng/L.

Formation and identification of unresolved complex mixtures in lacustrine biodegraded oil from Nanxiang Basin, China.

A comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC/TOFMS) method has been developed for the formation and identification of unresolved complex mixtures (UCMs) in lacustrine biodegraded oils that with the same source rock, similar maturity, and increasing degradation rank from Nanxiang Basin, China. Normal alkanes, light hydrocarbons, isoprenoids, steranes, and terpanes are degraded gradually from oil B330 to oil G574. The compounds in biodegraded oil (oil G574) have fewer types, the polarity difference of compounds in different types is minor, and the relative content of individual compounds is similar. All the features make the compounds in biodegraded oil coelute in GC analysis and form the raised "baseline hump" named UCMs. By injecting standard materials and analyzing mass spectrums of target compounds, it is shown that cyclic alkanes with one to five rings are the major components of UCMs. Furthermore, UCMs were divided into six classes. Classes I and II, composed of alkyl-cyclohexanes, alkyl-naphthanes, and their isomers, are originated from the enrichment of hydrocarbons resistant to degradation in normal oils. Classes III ~ VI, composed of sesquiterpenoids, tricyclic terpanes, low molecular steranes, diasteranes, norhopanes, and their isomers, are probably from some newly formed compounds during the microbial transformation of oil.

Pre-expanded thoracodorsal artery perforator-based flaps for repair of severe scarring in cervicofacial regions.

BACKGROUND: Reconstruction of cervicofacial scarring continues to present challenges for surgical treatment. Here we present our clinical experience in repairing cervicofacial scarring using pre-expanded thoracodorsal artery perforator flaps. METHODS: From January 2007 to December 2012, 15 patients were treated for severe cervicofacial scarring. In the first surgical stage, expanders were implanted subcutaneously in the zone nourished by thoracodorsal artery perforators. The expansion generally took 3 to 6 months. In the second surgical stage, the cervicofacial cicatricial contracture was released and the secondary defect was covered with local flaps. The remaining wound was covered by the free thoracodorsal artery perforator expanded flap, which was anastomosed to the facial vascular bundle. The donor site was closed directly in all the patients. RESULTS: The postoperative follow-up time ranged from 1 to 5 years. The deformities were corrected, all flaps survived completely and none were bulky. The maximum length of the flaps was 32 cm (mean, 22.4 ± 4.2 cm), and the maximum width was 17 cm (mean, 14.4 ± 2.2 cm). All patients exhibited recovery of neck movement, and there was no recurrence of neck contracture. CONCLUSION: The pre-expanded thoracodorsal artery perforator flap is an ideal method for reconstruction of severe cervicofacial cicatricial contracture.

miR-10a-5p Regulates the Proliferation and Differentiation of Porcine Preadipocytes Targeting the KLF11 Gene.

In the swine industry, meat quality, color, and texture are influenced by the excessive differentiation of fat cells. miRNAs have emerged as integral regulators of adipose development. This study delves into the influence of miR-10a-5b on the proliferation and differentiation of pig preadipocytes. Our findings reveal that miR-10a-5b is prevalent across various tissues. It hinders preadipocyte proliferation, amplifies the expression of adipogenic genes, promotes lipid accumulation, and, as a result, advances preadipocyte differentiation. We predict that KLF11 is the target gene of miRNA. A dual-fluorescence reporter assay was conducted to validate the binding sites of miR-10a-5b on the 3'UTR of the KLF11 mRNA. Results showed that miR-10a-5b targeted KLF11 3'UTR and reduced the fluorescence activity of the dual-fluorescent reporter vector. Our research also indicates that miR-10a-5b targets and downregulates the expression of both mRNA and the protein levels of KLF11. During the differentiation of the preadipocytes, KLF11 inhibited adipose differentiation and was able to suppress the promotion of adipose differentiation by miR-10a-5b. This underscores miR-10a-5b's potential as a significant regulator of preadipocyte behavior by modulating KLF11 expression, offering insights into the role of functional miRNAs in fat deposition.

[Effects of Phosphogypsum and Suaeda salsa on the Soil Moisture, Salt, and Bacterial Community Structure of Salinized Soil].

The improvement of saline soil is an important issue that cannot be ignored in the farmland soil environment. The change in soil salinity will inevitably affect the soil bacterial community. This experiment was based on moderately saline soil in the Hetao Irrigation Area, conducted by applying phosphogypsum (LSG), interplanting Suaeda salsa with Lycium barbarum (JP) and applying phosphogypsum and interplanting S. salsa with L. barbarum (LSG+JP),and the local unimproved soil of a L. barbarum orchard was used as the control (CK), to explore the effects of different improvement methods on soil moisture, salinity, nutrients, and bacterial community structure diversity during the growth period of L. barbarum. The results showed that compared with that under CK, the LSG+JP treatment significantly decreased the soil EC value and pH value from the flowering stage to the deciduous stage (P<0.05), with an average decrease of 39.96% and 7.25%, respectively; the LSG+JP treatment significantly increased soil organic matter (OM) and available phosphorus (AP) content during the whole growth period (P<0.05), with an average annual increase of 81.85% and 203.50%, respectively. The total nitrogen (TN) content was significantly increased in the flowering and deciduous stages (P<0.05), with an annual average increase of 48.91%. The Shannon index of LSG+JP in the early stage of improvement was increased by 3.31% and 6.54% compared with that of CK, and the Chao1 index was increased by 24.95% and 43.26% compared with that of CK, respectively. The dominant bacteria in the soil were Proteobacteria, Bacteroidetes, Actinobacteria, and Acidobacteria, and the dominant genus was Sphingomonas. Compared with that in CK, the relative abundance of Proteobacteria in the improved treatment increased by 0.50%-16.27% from the flowering stage to the deciduous stage, and the relative abundance of Actinobacteria in the improved treatment increased by 1.91%-4.98% compared with that in CK in the flowering and full-fruit stages. Redundancy analysis (RDA) results showed that pH, water content (WT), and AP were important factors affecting bacterial community composition, and the correlation heatmap showed that Proteobacteria, Bacteroidetes, and EC values were significantly negatively correlated (P<0.001); Actinobacteria and Nitrospirillum were significantly negatively correlated with EC values (P<0.01). In conclusion, the application of phosphogypsum and interplanting S. salsa with L. barbarum (LSG+JP) could significantly reduce soil salinity, increase nutrients, and improve the diversity of soil bacterial community structure, which is beneficial to the long-term improvement of saline soil in the Hetao Irrigation Area and the maintenance of soil ecological health.

[Effects of Microbial Fertilizer on Physicochemical Properties and Bacterial Communities of Saline Soil Under Brackish Water Irrigation].

The improvement of saline soil with microbial fertilizer has numerous advantages including high efficiency, green environmental protection, etc. At the same time, applying microbial fertilizer is an effective way to safely use brackish water. Based on the moderately saline soil in the Hetao irrigation area, four treatments of F1 (4500 kg·km-2), F2 (7500 kg·km-2), F3 (10500 kg·km-2), and CK without microbial fertilizer were applied under brackish water irrigation using Lycium barbarum as the indicator plants. The aim was to study the effects of different microbial fertilizer application rates on soil ions, soil moisture content, pH value, nutrients, and bacterial community in four key growth stages of L. barbarum (flowering stage, fruit expansion stage, full fruit stage, and deciduous stage). The results showed that, compared with that in CK, F1 only significantly decreased Na+ content in the first two growth stages (P<0.05), whereas F2 and F3 significantly decreased Na+ content in the whole growth period (P<0.05), with an average reduction of 33.66% and 57.98%, respectively, and F3 significantly increased soil moisture content (MC), organic matter (OM), alkaline hydrolysis nitrogen (AN), and available phosphorus (AP) contents (P<0.05) during the whole growth period. In the flourishing period of L. barbarum, the Shannon index of F3 increased by 4.41% compared with that of CK. The dominant bacterial phyla in the soil were Proteobacteria, Bacteroidetes, and Actinobacteria, and the dominant bacterial genera were Sphingomonas and Pseudomonas. The most abundant functions of bacterial communities in the study area were chemoheterotrophy and aerobic chemoheterotrophy, with an average relative abundance of 15.07% and 13.16%, respectively. The application of microbial fertilizer increased the chitinolysis function and chloroplast functions of soil bacteria, which F2 increased to the highest degree. Canonical correlation analysis (CCA) showed that MC, Na+, and OM were important factors affecting the composition of the bacterial community. The correlation heat map showed that MC was positively correlated with Planctomycetes (P<0.01), and Gp6 was positively correlated with AN (P<0.01). Compared with that in CK, the F3 treatment increased the relative abundance of Gp6 and optimized the community structure during the growth period. In conclusion, the application of 10500 kg·km-2 microbial fertilizer (F3 treatment) under brackish water irrigation could significantly reduce soil salinity, increase nutrients, and improve the diversity of the soil bacterial community structure, which is conducive to the safe utilization of brackish water and the maintenance of soil ecological health.

NanoSIMS analysis of water content in bridgmanite at the micron scale: An experimental approach to probe water in Earth's deep mantle.

Water, in trace amounts, can greatly alter chemical and physical properties of mantle minerals and exert primary control on Earth's dynamics. Quantifying how water is retained and distributed in Earth's deep interior is essential to our understanding of Earth's origin and evolution. While directly sampling Earth's deep interior remains challenging, the experimental technique using laser-heated diamond anvil cell (LH-DAC) is likely the only method available to synthesize and recover analog specimens throughout Earth's lower mantle conditions. The recovered samples, however, are typically of micron sizes and require high spatial resolution to analyze their water abundance. Here we use nano-scale secondary ion mass spectrometry (NanoSIMS) to characterize water content in bridgmanite, the most abundant mineral in Earth's lower mantle. We have established two working standards of natural orthopyroxene that are likely suitable for calibrating water concentration in bridgmanite, i.e., A119(H2O) = 99 ± 13 µg/g (1SD) and A158(H2O) = 293 ± 23 µg/g (1SD). We find that matrix effect among orthopyroxene, olivine, and glass is less than 10%, while that between orthopyroxene and clinopyroxene can be up to 20%. Using our calibration, a bridgmanite synthesized by LH-DAC at 33 ± 1 GPa and 3,690 ± 120 K is measured to contain 1,099 ± 14 µg/g water, with partition coefficient of water between bridgmanite and silicate melt ∼0.025, providing the first measurement at such condition. Applying the unique analytical capability of NanoSIMS to minute samples recovered from LH-DAC opens a new window to probe water and other volatiles in Earth's deep mantle.

Corrigendum: NanoSIMS analysis of water content in bridgmanite at the micron scale: an experimental approach to probe water in Earth's deep mantle.

[This corrects the article DOI: 10.3389/fchem.2023.1166593.].

The clonal expression genes associated with poor prognosis of liver cancer.

The extensive spatial genomic intratumor heterogeneity (ITH) in liver cancer hindered treatment development and limited biomarker design. Early events that drive tumor malignant transformation in tumor founder cells are clonally present in all tumor cell populations, which provide stable biomarkers for the localization of tumor cells and patients' prognosis. In the present study, we identified the recurrently clonal somatic mutations and copy number alterations (CNAs) (893 clonal somatic mutations and 6,617 clonal CNAs) in 353 liver cancer patients from The Cancer Genome Atlas (TCGA) and evaluated their prognosis potential. We showed that prognosis-related clonal alterations might play essential roles in tumor evolution. We identified 32 prognosis related clonal alterations differentially expressed between paired normal and tumor samples, that their expression was cross-validated by three independent cohorts (50 paired samples in TCGA, 149 paired samples in GSE76297, and 9 paired samples in SUB6779164). These clonal expression alterations were also significantly correlated with clinical phenotypes. Using stepwise regression, we identified five (UCK2, EFNA4, KPAN2, UBE2T, and KIF14) and six (MCM10, UCK2, IQGAP3, EFNA4, UBE2T, and KPNA2) clonal expression alterations for recurrence and survival model construction, respectively. Furthermore, in 10 random repetitions, we showed strong applicability of the multivariate Cox regression models constructed based on the clonal expression genes, which significantly predicted the outcomes of the patients in all the training and validation sets. Taken together, our work may provide a new avenue to overcome spatial ITH and refine biomarker design across cancer types.

The formulation of irrigation and nitrogen application strategies under multi-dimensional soil fertility targets based on preference neural network.

With the aim of improving soil fertility, it is of great significance to put forward optimal irrigation and nitrogen fertilizer application strategies for improving land productivity and alleviating non-point source pollution effects. To overcome this task, a 6-hidden layer neural network with a preference mechanism, namely Preference Neural network (PNN), has been developed in this study based on the field data from 2018 to 2020. PNN takes soil total nitrogen, organic matter, total salt, pH, irrigation time and target soil depth as input, and irrigation amount and nitrogen application rate (N rate) as output, and the prior preference matrix was used to adjust the learning of weight matrix of each layer. The outcomes indicated that the predictive accuracy of PNN for irrigation amount were (R2 = 0.913, MAE = 0.018, RMSE = 0.022), and for N rate were (R2 = 0.943, MAE = 0.009, RMSE = 0.011). The R2 predicted by PNN at the irrigation amount and N rate were 40.03% to more than 99% and 40.33% to more than 99% higher than those obtained using support vector regression (SVR), linear regression (LR), logistic regression (LOR) and traditional back propagation neural network (BPNN), respectively. In addition, compared with the neural network (Reverse Multilayer Perceptron, RMLP) with the same structure but no preference structure, the R2 of the predicted irrigation amount and N rate by PNN increased by 25.81% and 27.99%, respectively. The results showed that, through the irrigation of 93 to 102, 92 to 98 and 92 to 98 mm, along with nitrogen applications of 65 to 71, 64 to 73 and 72 to 81 kg/hm2 at 17, 59 and 87 days after sowing, respectively, the organic matter, total nitrogen, total salt content and pH of the soil would reach high fertility levels simultaneously.