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Background: Numerous prior studies have extensively highlighted the significance of the microbiome in association with asthma. While several studies have concentrated on the asthma microbiome in previous research, there is currently a lack of publications that employ bibliometric methods to assess this area. Methods: In this study, the Web of Science Core Collection database was utilized as the data source, and the SCI-EXPANDED index was employed to ensure that the retrieved data were comprehensive and accurate. All original research articles and review articles related to the correlation between asthma and the microbiome were systematically searched from the inception of the database until June 20, 2023. These articles were subsequently visualized and analyzed using VOSviewer and CiteSpace software. Results: A total of 1366 relevant publications were acquired, indicating a consistent annual increase in global publications in the field. The United States and China emerged as the top two contributors to international publications. Among prolific authors, Susan V. Lynch achieved the highest publication record, with Hans Bisgaard and Jakob Stokholm sharing the second position. The majority of publications concentrated on allergy-related and microbiome areas, with a few comprehensive journals standing out. Journals with 40 or more publications included the Journal of Allergy and Clinical Immunology, Allergy, Frontiers in Immunology, and PLOS One. The top 5 cited journals were the Journal of Allergy and Clinical Immunology, PLOS One, American Journal of Respiratory and Critical Care Medicine, Clinical and Experimental Allergy, and Nature. Upon analyzing keywords, high-frequency terms, such as asthma, gut microbiota, microbiome, children, childhood asthma, allergy, risk, exposure, inflammation, diversity, and chain fatty acids emerged as representative terms in the field. Conclusion: This study systematically presented a comprehensive overview of the literature regarding the association between asthma and the microbiome over the last two decades. Through a bibliometric perspective, the findings may assist researchers with a better understanding of the essential information in the field.

The high susceptibility of raspberries to softening restricts the development of the raspberry industry. The primary causes of fruit softening are the breakdown of components linked to the cell wall and the destruction of the cell wall structure itself. Polygalacturonase (PG), a key enzyme that catalyzes pectin degradation, plays a critical role in fruit softening. However, there are currently limited studies on the mechanism of PG genes in raspberry fruit softening. In this study, a PG gene, RiPG2, was isolated from raspberry (Rubus idaeus L.). ‘Polka’ fruits and tomato plants overexpressing RiPG2 were obtained by Agrobacterium tumefaciens-mediated leaf disc transformation to elucidate the role of RiPG2 in fruit softening. The total length of the RiPG2 gene is 1185 bp, and the gene encodes a total of 394 amino acids. The GFP fusion protein was expressed at the chloroplast under laser confocal microscopy, indicating that the RiPG2 protein is localized to the chloroplasts. Phenotypic analysis revealed that the fruit firmness of three strains was considerably less than that of controls, but PG enzyme activity was increased. Overexpression of RiPG2 altered the content of cell wall components, with an increase in water-soluble pectin (WSP) and ion-bound pectin (ISP) but a decrease in protopectin, cellulose, hemicellulose, and covalently bound pectin (CSP). In addition, RiPG2 positively regulated the expression of cell wall metabolism-related genes such as SlEXP1, SlTBG4, SlXTH5, and SlPL. These results suggest that the RiPG2 gene regulates the structure and composition of the cell wall and acts synergistically with other cell wall metabolism-related genes to promote fruit softening. This study provides a new candidate gene for molecular breeding to improve raspberry firmness.

Countermeasures in weightlessness are a predominant technique for long-term residency in space. Head-down bed rest (HDBR) has long been used to simulate the physiological effects of spaceflight and test the efficacy of countermeasures. In 2019, the Astronaut Center of China (ACC) has held a 90-d HDBR on the effects of exercises’ intervention. Thirty-six subjects were recruited and randomized into 5 intervention groups: (a) control, (b) aerobic exercises, (c) resistance exercises, (d) concurrent aerobic and lower load resistance exercises, and (e) concurrent aerobic and high-load resistance exercises. Moreover, exercise interventions were performed in supine or 6° head-down tilt. They were provided with plain medical, psychological, and nutritional supports during the experiment. In addition, cardiovascular and pulmonary functions, muscle strength, bone density, and neuro–immune–endocrine functions were assessed over time. Subjects were monitored by clinical evaluations, psychological assessments, and nutritional status evaluations. All subjects spent 138 d in the bed rest study laboratory and received 2 follow-up tests per 3 months in the home recovery period. It was found that exercises in the 4 groups were effective interventions for aerobic capacity compared with control. The resistance exercises or concurrent aerobic and high-load resistance exercises improved isometric maximal voluntary contraction. However, the protection against bone loss still needs further exploration. Appropriate psychosocial and nutrition support techniques are worth to be reinforced.

Abstract Background Accumulating evidence indicates that long non-coding RNAs (lncRNAs) are involving in the tumorigenesis and metastasis of lung cancer. The aim of the study is to systematically characterize the lncRNA-associated competing endogenous RNA (ceRNA) network and identify key lncRNAs in the development of stage I lung adenocarcinoma (LUAD). Methods Totally, 1,955 DEmRNAs, 165 DEmiRNAs and 1,107 DElncRNAs were obtained in 10 paired normal and LUAD tissues. And a total of 8,912 paired lncRNA-miRNA-mRNA network was constructed. Using the Cancer Genome Atlas (TCGA) dataset, the module of ME turquoise was revealed to be most relevant to the progression of LUAD though Weighted Gene Co-expression Network Analysis (WGCNA). Results Of the lncRNAs identified, LINC00639, RP4-676L2.1 and FENDRR were in ceRNA network established by our RNA-sequencing dataset. Using univariate Cox regression analysis, FENDRR was a risk factor of progression free survival (PFS) of stage I LUAD patients (HRs = 1.69, 95%CI 1.07–2.68, P

Abstract Background To identify hub genes from the competing endogenous RNA (ceRNA) network of lung adenocarcinoma (LUAD) and to explore their potential functions on prognosis of patients from a single-cell perspective. Methods We performed RNA-sequencing of LUAD to construct ceRNA regulatory network, integrating with public databases to identify the vital pathways related to patients’ prognosis and to reveal the expression level of hub genes under different conditions, the functional enrichment of co-expressed genes and their potential immune-related mechanisms. Results ZC3H12D-hsa-miR-4443-ENST00000630242 axis was found to be related with LUAD. Lower ZC3H12D expression was significantly associated with shorter overall survival (OS) of patients (HR = 2.007, P

Background Fasting has been widely used to improve various metabolic diseases in humans. Adaptive fasting is necessary for metabolic adaptation during prolonged fasting, which could overcome the great advantages of short-term fasting. The liver is the main organ responsible for energy metabolism and metabolic homeostasis. To date, we lack literature that describes the physiologically relevant adaptations of the liver during prolonged fasting and refeeding. For that reason, this study aims to evaluate the response of the liver of Sprague-Dawley (SD) rats to prolonged fasting and refeeding. Methods Sixty-six male SD rats were divided into the fasting groups, which were fasted for 0, 4, 8, 12, 24, 48, 72, or 96 h, and the refeeding groups, which were refed for 1, 3, or 6 days after 96 h of fasting. Serum glucose, TG, FFA, β-hydroxybutyrate, insulin, glucagon, leptin, adiponectin and FGF21 levels were assessed. The glucose content, PEPCK activity, TG concentration and FFA content were measured in liver tissue, and the expression of genes involved in gluconeogenesis (PEPCK and G6Pase), ketogenesis (PPARα, CPT-1a and HMGCS2) and the protein expression of nutrient-sensing signaling molecules (AMPK, mTOR and SIRT1) were determined by RT-qPCR and western blotting, respectively. Results Fasting significantly decreased the body weight, which was totally recovered to baseline after 3 days of refeeding. A 4-day fast triggered an energy metabolic substrate shift from glucose to ketones and caused serum hormone changes and changes in the protein expression levels of nutrient-sensing signaling molecules. Glycogenolysis served as the primary fuel source during the first 24 h of fasting, while gluconeogenesis supplied the most glucose thereafter. Serum FFA concentrations increased significantly with 48 h of fasting. Serum FFAs partly caused high serum β-hydroxybutyrate levels, which became an important energy source with the prolongation of the fasting duration. One day of refeeding quickly reversed the energy substrate switch. Nutrient-sensing signaling molecules (AMPK and SIRT1 but not mTOR signaling) were highly expressed at the beginning of fasting (in the first 4 h). Serum insulin and leptin decreased with fasting initiation, and serum glucagon increased, but adiponectin and FGF21 showed no significant changes. Herein, we depicted in detail the timing of the metabolic response and adaptation of the liver to a 4-day water-only fast and subsequent refeeding in rats, which provides helpful support for the design of safe prolonged and intermittent fasting regimens.

Lung cancer is one of the leading causes of cancer-related deaths. Thus, it is important to find its biomarkers. Furthermore, there is an increasing number of studies reporting that long noncoding RNAs (lncRNAs) demonstrate dense linkages with multiple human complex diseases. Inferring new lncRNA-disease associations help to identify potential biomarkers for lung cancer and further understand its pathogenesis, design new drugs, and formulate individualized therapeutic options for lung cancer patients. This study developed a computational method (LDA-RLSURW) by integrating Laplacian regularized least squares and unbalanced bi-random walk to discover possible lncRNA biomarkers for lung cancer. First, the lncRNA and disease similarities were computed. Second, unbalanced bi-random walk was, respectively, applied to the lncRNA and disease networks to score associations between diseases and lncRNAs. Third, Laplacian regularized least squares were further used to compute the association probability between each lncRNA-disease pair based on the computed random walk scores. LDA-RLSURW was compared using 10 classical LDA prediction methods, and the best AUC value of 0.9027 on the lncRNADisease database was obtained. We found the top 30 lncRNAs associated with lung cancers and inferred that lncRNAs TUG1, PTENP1, and UCA1 may be biomarkers of lung neoplasms, non-small–cell lung cancer, and LUAD, respectively.

BackgroundCOVID-19, which emerged in December 2019, has spread rapidly around the world and has become a serious public health event endangering human life. With regard to COVID-19, there are still many unknowns, such as the exact case fatality rate (CFR). ObjectiveThe main objective of this study was to explore the value of the discharged CFR (DCFR) to make more accurate forecasts of epidemic trends of COVID-19 in Italy. MethodsWe retrieved the epidemiological data of COVID-19 in Italy published by the John Hopkins Coronavirus Resource Center. We then used the proportion of deaths to discharged cases（including deaths and recovered cases） to calculate the total DCFR (tDCFR), monthly DCFR (mDCFR), and stage DCFR (sDCFR). Furthermore, we analyzed the trend in the mDCFR between January and December 2020 using joinpoint regression analysis, used ArcGIS version 10.7 to visualize the spatial distribution of the epidemic CFR, and assigned different colors to each province based on the CFR or tDCFR. ResultsWe calculated the numbers and obtained the new indices of the tDCFR and mDCFR for calculating the fatality rate. The results showed that the tDCFR and mDCFR fluctuated greatly from January to May. They first showed a rapid increase followed by a rapid decline after reaching the peak. The map showed that the provinces with a high tDCFR were Emilia-Romagna, Puglia, and Lombardia. The change trend of the mDCFR over time was divided into the following 2 stages: the first stage (from January to May) and the second stage (from June to December). With regard to worldwide COVID-19 statistics, among 6 selected countries, the United States had the highest tDCFR (4.26%), while the tDCFR of the remaining countries was between 0.98% and 2.72%. ConclusionsWe provide a new perspective for assessing the fatality of COVID-19 in Italy, which can use ever-changing data to calculate a more accurate CFR and scientifically predict the development trend of the epidemic.

As a major reason for tumor metastasis, circulating tumor cell (CTC) is one of the critical biomarkers for cancer diagnosis and prognosis. On the one hand, CTC count is closely related to the prognosis of tumor patients; on the other hand, as a simple blood test with the advantages of safety, low cost and repeatability, CTC test has an important reference value in determining clinical results and studying the mechanism of drug resistance. However, the determination of CTC usually requires a big effort from pathologist and is also error-prone due to inexperience and fatigue. In this study, we developed a novel convolutional neural network (CNN) method to automatically detect CTCs in patients’ peripheral blood based on immunofluorescence in situ hybridization (imFISH) images. We collected the peripheral blood of 776 patients from Chifeng Municipal Hospital in China, and then used Cyttel to delete leukocytes and enrich CTCs. CTCs were identified by imFISH with CD45+, DAPI+ immunofluorescence staining and chromosome 8 centromeric probe (CEP8+). The sensitivity and specificity based on traditional CNN prediction were 95.3% and 91.7% respectively, and the sensitivity and specificity based on transfer learning were 97.2% and 94.0% respectively. The traditional CNN model and transfer learning method introduced in this paper can detect CTCs with high sensitivity, which has a certain clinical reference value for judging prognosis and diagnosing metastasis.

Background: Lung adenocarcinoma (LUAD) is the most predomintnt lung cancer subtype with increasing morbidity and mortality. Previous studies have shown that aquaporin (AQP) family genes were correlated with tumor progression and metastasis in several kinds of malignancies. However, their biological behaviors and prognostic values in LUAD have not been comprehensively elucidated.Methods: RNA sequencing and real-time reverse transcription PCR (RT-PCR) were used to assess AQP1/3/4/5 gene expressions in LUAD patients using GEPIA and UALCAN databases. And then Kaplan–Meier analysis, cBioPortal, Metascape, GeneMANIA, TISIDB, and TIMER were utilized to determine the prognostic value, mutation frequency, and immune cell infiltration of AQP family members in LUAD.Results: We found that AQP3 expression was significantly elevated and AQP1 expression was markedly reduced in LUAD patients, whereas the expression levels of AQP4 and AQP5 exhibited no significant changes. The Kaplan–Meier survival analysis indicated that the higher expressions of AQP1/4/5 were related to longer overall survival (OS). Of interest, AQP3 was significantly correlated with the clinical tumor stage and lower AQP3 expression showed favorable prognosis in stage I LUAD patients, which indicated that AQP3 may be a potential prognostic biomarker for patients. Through functional enrichment analysis, the functions of these four AQPs genes were mainly involved in the passive transport by aquaporins, water homeostasis, and protein tetramerization. Moreover, AQP1/3/4/5 expression was strongly associated with tumor-infiltrating lymphocytes (TILs) in LUAD.Conclusion: AQP3 can be used as a prognosis and survival biomarker for stage I LUAD. These findings may provide novel insights into developing molecular targeted therapies in LUAD.

Fasting shows great potential in preventing chronic diseases and has to be surmounted under some extraordinary circumstances. This study aimed to investigate the safety, time effects of metabolic homeostasis and health indexes during prolonged fasting. Thirteen participants were recruited to conduct a 10-day complete fasting (CF) in a controlled health research building under medical supervision including 3-day Baseline (BL), 10-day CF, 4-day calorie restriction (CR) and 5-day full recovery (FR). Body healthy status was assessed by surveying pulse, blood pressure, body weight (BW), blood glucose and ketones, body composition and nutritional and biochemistry indexes at different times. BW declined about 7.28 kg (−9.8%) after 10-day CF, accompanied by increased pulse and decreased systolic blood pressure, but there were no changes to the myocardial enzymogram. Body composition analysis showed fat mass was constantly lost, but lean mass could recover after CR. The energy substrate switch from glucose to ketone occurred and formed a stable dynamic balance between 3–6 days of CF. The lipid metabolism presented increased total cholesterol, LDL-C, ApoA1 and almost no changes to TG and HDL-C. Prolonged CF did not influence liver function, but induced a slight decrease of kidney function. The interesting results came from the marked increase of lipid-soluble vitamins and a significant decrease of sodium and chlorine. Adults could well tol-erate a 10-day CF. A new metabolic homeostasis was achieved. No vitamins but NaCl supplement should be considered. These findings provide evidence to design a new fasting strategy for clinical practice.

Osteocalcin (OCN) was the most abundant noncollagen protein and considered as an endocrine factor. However, the functions of Undercarboxylated osteocalcin (ucOCN) on osteoclast and bone resorption are not well understood. In the present study, preosteoclast RAW264.7 cells and bone marrow mononuclear cells (BMMs) were treated with ucOCN purified from prokaryotic bacteria. Our results showed that ucOCN attenuated the proliferation of RAW264.7 cells with a concentration dependant manner by MTS assay. Scrape wounding assay revealed the decreased motility of RAW264.7 cells after ucOCN treatment. RT-qPCR results manifested the inhibitory effects of ucOCN on the expression of osteoclastic marker genes in RAW264.7 cells during inducing differentiation of RANKL. It was also observed that ucOCN inhibited the formation of multinucleated cells from RAW264.7 cells and BMMs detected by TRAP staining. The number and area of bone resorb pits were also decreased after treatment with ucOCN during their osteoclast induction by toluidine blue staining. The formation and integrity of the osteoclast actin ring were impaired by ucOCN by immunofluorescent staining. Time dependant treatment of ucOCN during osteoclastic induction demonstrated the inhibitory effects mainly occurred at the early stage of osteoclastogenesis. Signaling analysis of luciferase activity of the CRE or SRE reporter and ERK1/2 phosphorylation showed the selective inhibitor or siRNA of Gprc6a (a presumptive ucOCN receptor) could attenuate the promotion of ucOCN on CRE-luciferase activity. Taken together, we provided the first evidence that ucOCN had negative effects on the early differentiation and bone resorption of osteoclasts via Gprc6a.

Microgravity impacts various aspects of human health. Yet the mechanisms of spaceflight-induced health problems are not elucidated. Here, we mapped the fusion systemic analysis of the serum metabolome and the circulating microRNAome in a hindlimb unloading rat model to simulate microgravity. The response of serum metabolites and microRNAs to simulated microgravity was striking. Integrated pathway analysis of altered serum metabolites and target genes of the significantly altered circulating miRNAs with Integrated Molecular Pathway-Level Analysis (IMPaLA) software was mainly suggestive of modulation of neurofunctional signaling pathways. Particularly, we revealed significantly increased miR-383-5p and decreased aquaporin 4 (AQP4) in the hippocampus. Using rabies virus glycoprotein–modified exosomes, delivery of miR-383-5p inhibited the expression of AQP4 not only in rat C6 glioma cells in vitro but also in the hippocampus in vivo. Using bioinformatics to map the crosstalk between the circulating metabolome and miRNAome could offer opportunities to understand complex biological systems under microgravity. Our present results suggested that the change of miR-383-5p level and its regulation of target gene AQP4 was one of the potential molecular mechanisms of microgravity-induced cognitive impairment in the hippocampus.

Leaf senescence plays an important role in the improvement of maize kernel yields. However, the underlying regulatory mechanisms of leaf senescence in maize are largely unknown. We isolated ZmVQ52 and studied the function of ZmVQ52 which encoded, a VQ family transcription factor. ZmVQ52 is constitutively expressed in maize tissues, and mainly expressed in the leaf; it is located in the nucleus of maize protoplasts. Four WRKY family proteins-ZmWRKY20, ZmWRKY36, ZmWRKY50, and ZmWRKY71-were identified as interacting with ZmVQ52. The overexpression of ZmVQ52 in Arabidopsis accelerated premature leaf senescence. The leaf of the ZmVQ52-overexpression line showed a lower chlorophyll content and higher senescence rate than the WT. A number of leaf senescence regulating genes were up-regulated in the ZmVQ52-overexpression line. Additionally, hormone treatments revealed that the leaf of the ZmVQ52-overexpressed line was more sensitive to salicylic acid (SA) and jasmonic acid (JA), and had an enhanced tolerance to abscisic acid (ABA). Moreover, a transcriptome analysis of the ZmVQ52-overexpression line revealed that ZmVQ52 is mainly involved in the circadian pathway and photosynthetic pathways.

Forest aboveground biomass (AGB) was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat), Moderate Resolution Imaging Spectro-radiometer (MODIS) imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH) field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (%) of less than 20%, and 80% of total provinces had relative errors less than 50%.

The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM) covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard Advanced Land Observing Satellite (ALOS) collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I) model only using backscattering coefficients of ALOS/PALSAR data; (II) model only using penetration depth; (III) model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.

Non-Supported Liquid Membrane Extraction (NSLME) is a new development extraction technology based on Supported Liquid Membrane Extraction (SLME). Sample extraction assembly is composed of three phases: an acceptor phase: phosphate–sodium dihydrogen phosphate buffer solution at the bottom; an organic phase: chloroform applied as the non-supported liquid membrane in the middle layer; and a donor phase: aqueous solution samples containing alkaloids in the upper layer. The whole system is maintained stable by density difference among the three layers that avoided the mutual interferences. The alkaloid in the donor phase can spread to the underlying acidic acceptor phase, where it is able to form water soluble salt in the acid environment, and thus cannot return to the middle organic phase. Therefore, the transmission of alkaloid is a one-way path, and the extraction of alkaloids can be achieved and enriched. In this study, the extraction of alkaloid was carried out by using matrine aqueous solution as the donor phase, and the extraction quantity and efficiency were investigated by GC/MS. This study evaluated the relationship between extracted quantity and extraction time. The effects of extraction temperature, membrane thickness, pH value of acceptor phase on extraction quantity and efficiency were also studied, and the optimal extraction condition was found. The extracted quantity achieved the largest amount at 45 °C when pure phosphoric acid was applied as the acceptor phase; the organic solvent volume was 0.2 mL. The extraction of alkaloid from Radix Sophorae Tonkinensis was performed under the optimized condition. The extraction rate of matrine was up to 54% after a four-hour extraction. A huge advantage of NSLME technology is that the extracted alkaloid enjoyed high purity compared with that extracted by the traditional Liquid–Liquid Extraction (LLE).

The alkaloids in the processed Rhizoma Corydalis and the crude Rhizoma Corydalis were qualitatively and semiquantitatively analyzed using gas chromatography-mass spectrometry (GC/MS) method. The processing herb drug procedure was carried out according to the standard method of Chinese Pharmacopoeia. The samples were extracted using Soxhlet extractor with different solvents: methanol and acetone. The extraction effect on different solvents was investigated. The results showed that 11 kinds of alkaloids were identified from the crude Rhizoma Corydalis and only two were from the processed Rhizoma Corydalis. A total of 13 kinds of alkaloids were all based on two backbones. The alkaloids in the processed sample were less than those in the crude Rhizoma Corydalis significantly, while almost the corydaline has been changed in conformation after the sample had undergone processing, which provided support for the conclusion of reducing toxicity when the herbal medicine having been undergone a traditional drugs treatment process.