Reduced expression of cathepsin F predicts poor prognosis in patients with clear cell renal cell carcinoma.

Abnormalities in the extracellular matrix (ECM) play important roles in the regulation and progression of clear cell renal cell carcinoma (ccRCC). The cysteine cathepsin is one of the major proteases involved in ECM remodeling and has been shown to be aberrantly expressed in multiple cancer types. However, the clinical significance and biological function of distinct cysteine cathepsins in ccRCC remain poorly understood. In this study, several bioinformatics databases, including UALCAN, TIMER, GEPIA and the Human Protein Atlas datasets, were used to analyze the expression and prognostic value of different cysteine cathepsin family members in ccRCC. We found that the expression level of CTSF was downregulated in tumor tissues and closely related to the poor survival of ccRCC patients. Further in vitro experiments suggested that CTSF overexpression suppressed the proliferation and migration of ccRCC cells. Moreover, the expression of CTSF was shown to be associated with several immune-infiltrating cells and immunomodulators in ccRCC. These results indicated that CTSF might be a promising diagnostic and prognostic marker in ccRCC.

The NAC056 transcription factor confers freezing tolerance by positively regulating expression of CBFs and NIA1 in Arabidopsis.

Freezing stress can seriously affect plant growth and development, but the mechanisms of these effects and plant responses to freezing stress require further exploration. Here, we identified a NAM, ATAF1/2, and CUC2 (NAC)-family transcription factor (TF), NAC056, that can promote freezing tolerance in Arabidopsis. NAC056 mRNA levels are strongly induced by freezing stress in roots, and the nac056 mutant exhibits compromised freezing tolerance. NAC056 acts positively in response to freezing by directly promoting key C-repeat-binding factor (CBF) pathway genes. Interestingly, we found that CBF1 regulates nitrate assimilation by regulating the nitrate reductase gene NIA1 in plants; therefore, NAC056-CBF1-NIA1 form a regulatory module for the assimilation of nitrate and the growth of roots under freezing stress. In addition, 35S::NAC056 transgenic plants show enhanced freezing tolerance, which is partially reversed in the cbfs triple mutant. Thus, NAC056 confers freezing tolerance through the CBF pathway, mediating plant responses to balance growth and freezing stress tolerance.

Roles of CcDFR and CcOMT9 in the cyanidin biosynthesis and development of Cordyceps cicadae.

Introduction: Cordyceps cicadae is a traditional Chinese medicinal fungus known for its rich production of bioactive substances, particularly cyanidin, an anthocyanin commonly found in plants with notable anti-inflammatory, anti-tumor, antiviral, and antibacterial properties. This study revealed two key genes, CcDFR and CcOMT9, affecting cyanidin biosynthesis in C. cicadae. Methods: The roles of these genes in cyanidin production, growth, and development were elucidated through the gene knockout method, phenotypic analysis, transcriptomics, and metabolomics. Results: CcDFR deletion led to reduced cyanidin-3-O-glucoside (C3G), suppressed expression of cyanidin biosynthesis genes, impaired synnemata formation, decreased polysaccharide and adenosine content, and diminished chitinase activity. Meanwhile, the ΔCcOMT9 mutant exhibited an increase in C3G production, promoted expression of cyanidin biosynthesis genes and rising bioactive compounds, suppressed RNA methylation, and led to phenylalanine accumulation with no effect on fruiting body formation. Discussion: We revealed a distinct anthocyanin biosynthesis pathway in C. cicadae and identified two genes with opposite functions, laying the foundation for future genetic modification of cyanidin-producing strains using modern biological techniques. This will shorten the production period of this valuable compound, facilitating the industrial-scale production of cyanidin.

Low-frequency band noise generated by industrial recirculating aquaculture systems exhibits a greater impact on Micropterus salmoidess.

The effect of underwater noise environment generated by equipment in industrial recirculating aquaculture systems (RAS) on fish is evident. However, different equipment generate noise in various frequency ranges. Understanding the effects of different frequency ranges noise on cultured species is important for optimizing the underwater acoustic environment in RAS. Given this, the effects of underwater noise across various frequency bands in RAS on the growth, physiology, and collective behavior of juvenile largemouth bass (Micropterus salmoides) were comprehensively evaluated here. In this study, three control groups were established: low-frequency noise group (80-1000 Hz, 117 dB re 1µPa RMS), high-frequency noise group (1-19 kHz, 117 dB re 1µPa RMS), and ambient group. During a 30-day experiment, it was found that: 1) industrial RAS noise with different frequency bands all had a certain inhibitory effect on the growth of fish, which the weight gain rate and product of length and depth of caudal peduncle in the ambient group were significantly higher than those of the two noise groups, with the low-frequency noise group showing significantly lower values than the high-frequency noise group; 2) industrial RAS noise had a certain degree of adverse effect on the digestive ability of fish, with the low-frequency noise group being more affected; 3) industrial RAS noise affected the collective feeding behavior of fish, with the collective feeding signal propagation efficiency and feeding intensity of the noise groups being significantly lower than those of the ambient group, and the high-frequency noise group performing better than the low-frequency noise group as a whole therein. From the above, the underwater noise across different frequency bands generated by equipment operation in industrial RAS both had an impact on juvenile largemouth bass, with the low-frequency noise group being more severely affected.

Adaptive convolutional sparsity with sub-band correlation in the NSCT domain for MRI image fusion.

Objective.Multimodal medical image fusion (MMIF) technologies merges diverse medical images with rich information, boosting diagnostic efficiency and accuracy. Due to global optimization and single-valued nature, convolutional sparse representation (CSR) outshines the standard sparse representation (SR) in significance. By addressing the challenges of sensitivity to highly redundant dictionaries and robustness to misregistration, an adaptive convolutional sparsity scheme with measurement of thesub-band correlationin the non-subsampled contourlet transform (NSCT) domain is proposed for MMIF.Approach.The fusion scheme incorporates four main components: image decomposition into two scales, fusion of detail layers, fusion of base layers, and reconstruction of the two scales. We solved a Tikhonov regularization optimization problem with source images to obtain the base and detail layers. Then, after CSR processing, detail layers were sparsely decomposed using pre-trained dictionary filters for initial coefficient maps. NSCT domain'ssub-band correlationwas used to refine fusion coefficient maps, and sparse reconstruction produced the fused detail layer. Meanwhile, base layers were fused using averaging. The final fused image was obtained via two-scale reconstruction.Main results.Experimental validation of clinical image sets revealed that the proposed fusion scheme can not only effectively eliminate the interference of partial misregistration, but also outperform the representative state-of-the-art fusion schemes in the preservation of structural and textural details according to subjective visual evaluations and objective quality evaluations.Significance. The proposed fusion scheme is competitive due to its low-redundancy dictionary, robustness to misregistration, and better fusion performance. This is achieved by training the dictionary with minimal samples through CSR to adaptively preserve overcompleteness for detail layers, and constructing fusion activity level withsub-band correlationin the NSCT domain to maintain CSR attributes. Additionally, ordering the NSCT for reverse sparse representation further enhancessub-band correlationto promote the preservation of structural and textural details.

Ionic Liquids Modulating Local Microenvironment of Ni-Fe Binary Single Atom Catalyst for Efficient Electrochemical CO2 Reduction.

The Ni and Fe dual-atom catalysts still undergo strikingly attenuation under high current density and high overpotential. To ameliorate the issue, the ionic liquids with different cations or anions are used in this work to regulate the micro-surface of nitrogen-doped carbon supported Ni and Fe dual-atom sites catalyst (NiFe-N-C) by an impregnation method. The experimental data reveals the dual function of ionic liquids, which enhances CO2 adsorption ability and modulates electronic structure, facilitating CO2 anion radical (CO2 •¯) stabilization and decreasing onset potential. The theoretical calculation results prove that the attachment of ionic liquids modulates electronic structure, reduces energy barrier of CO2 •¯ formation, and enhances overall ECR performance. Based on these merits, BMImPF6 modified NiFe-N-C (NiFe-N-C/BMImPF6) achieves the high CO faradaic efficiency of 91.9% with a CO partial current density of -120 mA cm-2 at -1.0 V. When the NiFe-N-C/BMImPF6 is assembled as cathode of Zn-CO2 battery, it delivers the highest power density of 2.61 mW cm-2 at 2.57 mA cm-2 and superior cycling stability. This work will afford a direction to modify the microenvironment of other dual-atom catalysts for high-performance CO2 electroreduction.

Fracture detection in pediatric wrist trauma X-ray images using YOLOv8 algorithm.

Hospital emergency departments frequently receive lots of bone fracture cases, with pediatric wrist trauma fracture accounting for the majority of them. Before pediatric surgeons perform surgery, they need to ask patients how the fracture occurred and analyze the fracture situation by interpreting X-ray images. The interpretation of X-ray images often requires a combination of techniques from radiologists and surgeons, which requires time-consuming specialized training. With the rise of deep learning in the field of computer vision, network models applying for fracture detection has become an important research topic. In this paper, we use data augmentation to improve the model performance of YOLOv8 algorithm (the latest version of You Only Look Once) on a pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX), which is a public dataset. The experimental results show that our model has reached the state-of-the-art (SOTA) mean average precision (mAP 50). Specifically, mAP 50 of our model is 0.638, which is significantly higher than the 0.634 and 0.636 of the improved YOLOv7 and original YOLOv8 models. To enable surgeons to use our model for fracture detection on pediatric wrist trauma X-ray images, we have designed the application "Fracture Detection Using YOLOv8 App" to assist surgeons in diagnosing fractures, reducing the probability of error analysis, and providing more useful information for surgery.

EFFICACY OF SUPPLEMENTAL HEMOADSORPTION THERAPY ON SEVERE AND CRITICAL PATIENTS WITH COVID-19: AN EVIDENCE-BASED ANALYSIS.

ABSTRACT: Background: The COVID-19 pandemic has posed a disproportionately high threat to the global health system and social stability. COVID-19 damage can lead to hyperinflammation and tissue damage due to a "cytokine storm," which in turn contributes to an increase in the mortality rate. Extracorporeal hemoadsorption therapy (HAT) in patients with severe COVID-19 may improve organ function and stabilize hemodynamic status; however, the effects of supplemental HAT remain controversial. Methods: The Cochrane Library, Embase, and PubMed databases were comprehensively searched from inception to August 20, 2022, for potential studies. Results: A total of 648 patients with severe COVID-19 in three randomized controlled trials and 11 observational studies met the inclusion criteria. A meta-analysis indicated that supplemental HAT significantly improved the mortality rate of patients with severe COVID-19 compared with conventional therapy (relative risk [RR] = 0.74, 95% confidence interval [CI] = 0.56 to 0.96, P = 0.026). In subgroup analyses, supplemental HAT significantly decreased mortality rates in patients without extracorporeal membrane oxygenation (ECMO) support (RR = 0.59, 95% CI = 0.44-0.79, P < 0.0001), while a significant difference was not observed in patients requiring ECMO support (RR = 1.61, 95% CI = 0.63-4.09, P = 0.316). Standardized mean difference (SMD) meta-analysis showed that IL-6 removal was more significant in HAT group than conventional therapy group (SMD = 0.46, 95% CI = 0.01 to 0.91, P = 0.043), followed by C-reactive protein (SMD = 0.70, 95% CI = -0.04 to 1.44, P = 0.065) and IL-8 (SMD = 0.36, 95% CI = -0.34 to 1.07, P = 0.311). No evidence of substantial publication bias concerning mortality was observed. Conclusion: Given the better mortality outcomes, HAT confers clinical benefits to patients with severe COVID-19, which correlated with cytokine removal by HAT. Cytokine adsorption may not provide clinical benefits for patients with severe COVID-19 requiring ECMO and should be used with caution. However, because of the very low quality of evidence, multicenter randomized trials with large sample sizes are required to verify these findings.

Diaphragms simulation, fabrication, and testing of a high temperature fiber optic F-P accelerometer based on MEMS.

High-sensitivity detection of vibrations under high temperatures is a topic of great interest in modern engineering such as thermal engine deep-sea aquaculture factory ship, aerospace, high temperature casting, energy, etc. As traditional accelerometers and some fiber optic F-P accelerometers have shown their sensing limits at about 400 °C and 650 °C, respectively, a high temperature fiber optic F-P accelerometer based on MEMS technology is proposed. To obtain a high-performance chip for the sensor, an examination of the theoretical performance of an L and Г-shaped cantilever beam diaphragm shows a sensitivity of 15.05 nm/g and 53.7 nm/g, respectively, and a wide working frequency range. Thanks to the designed sensor's various protections, frequency measurements with a high-temperature performance of 850 °C are recorded. The L-shaped cantilever beams diaphragm allows the sensor measurements at 850 °C with a repeatability of 5.46%, a working frequency range of 100-1000 Hz, an experimental sensitivity of 389 mV/g, an overall stability of 8 jumps at its adjacent frequency resolution range over 150 measurements, a linearity of 0.9856 and a maximum relative error maintained below 1.72%. In the field of application, it also exhibits a good relative error of measurement respecting the technical specification of 5 Hz.

SMAX1 interacts with DELLA protein to inhibit seed germination under weak light conditions via gibberellin biosynthesis in Arabidopsis.

Karrikins (KARs) were first identified as a class of small-molecule chemicals derived from smoke that promote seed germination. However, the implied mechanism is still not well understood. Here, we find that KAR signaling mutants have a lower germination percentage than that of wild type under weak light conditions, and KARs promote seed germination through transcriptional activation of gibberellin (GA) biosynthesis via SMAX1. SMAX1 interacts with the DELLA proteins REPRESSOR of ga1-3-LIKE 1 (RGL1) and RGL3. The interaction enhances the transcriptional activity of SMAX1 and inhibits GIBBERELLIN 3-oxidase 2 (GA3ox2) gene expression. The KAR signaling mutant seed germination defect under weak light is partially rescued by exogenous application of GA3 or by GA3ox2 overexpression, and the rgl1 rgl3 smax1 triple mutant exhibits higher germination rates under weak light than the smax1 mutant. Thus, we show a crosstalk between KAR and GA signaling pathways via a SMAX1-DELLA module in regulating seed germination in Arabidopsis.

Exploring the association between selective serotonin reuptake inhibitors and rhabdomyolysis risk based on the FDA pharmacovigilance database.

Rhabdomyolysis is a syndrome potentially fatal and has been associated with selective serotonin reuptake inhibitors (SSRIs) treatment in a few case reports. Herein, we purpose to establish the correlation between SSRIs use and rhabdomyolysis using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database. We conducted an analysis on reports that were submitted to the FAERS database during the period between January 1, 2004, and December 31, 2022. Four algorithms, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), were employed to quantify the signals of rhabdomyolysis associated with SSRIs. In total, 16,011,277 non-duplicated reports were obtained and analyzed. Among 33,574 reports related to rhabdomyolysis, SSRIs were classified as primary suspected drug in 889 cases. Disproportionality analysis identified a positive signal between rhabdomyolysis and SSRIs (ROR: 2.86, 95% CI 2.67-3.05; PRR: 2.84, χ2: 1037.16; IC0.25 = 1.39; EBGM0.5 = 2.64). Among six SSRIs, fluvoxamine had the strongest signal (ROR: 11.64, 95% CI 8.00-16.93; PRR: 11.38, χ2: 265.51; IC0.25 = 2.41; EBGM0.5 = 8.31), whereas no significant signal of rhabdomyolysis was detected for paroxetine (ROR: 1.83, 95% CI 1.55-2.15; PRR: 1.82, χ2: 53.82; IC0.25 = 0.73; EBGM0.5 = 1.59). After excluding cases co-administered with statins, the signal of rhabdomyolysis associated with SSRIs remains significant. Our analysis reveals that there are differences in safety signals among six SSRIs in respect to the risk of rhabdomyolysis, with fluvoxamine displaying the highest risk signal, while paroxetine did not show a significant signal. Given the potentially lethal nature of rhabdomyolysis, healthcare professionals should inform patients of the potential risk of rhabdomyolysis associated with SSRIs prior to initiating treatment.

China lung cancer screening (CLUS) version 2.0 with new techniques implemented: Artificial intelligence, circulating molecular biomarkers and autofluorescence bronchoscopy.

OBJECTIVE: The present study, CLUS version 2.0, was conducted to evaluate the performance of new techniques in improving the implementation of lung cancer screening and to validate the efficacy of LDCT in reducing lung cancer-specific mortality in a high-risk Chinese population. METHODS: From July 2018 to February 2019, high-risk participants from six screening centers in Shanghai were enrolled in our study. Artificial intelligence, circulating molecular biomarkers and autofluorescencebronchoscopy were applied during screening. RESULTS: A total of 5087 eligible high-risk participants were enrolled in the study; 4490 individuals were invited, and 4395 participants (97.9%) finally underwent LDCT detection. Positive screening results were observed in 857 (19.5%) participants. Solid nodules represented 53.6% of all positive results, while multiple nodules were the most common location type (26.8%). Up to December 2020, 77 participants received lung resection or biopsy, including 70 lung cancers, 2 mediastinal tumors, 1 tracheobronchial tumor, 1 malignant pleural mesothelioma and 3 benign nodules. Lung cancer patients accounted for 1.6% of all the screened participants, and 91.4% were in the early stage (stage 0-1). CONCLUSIONS: LDCT screening can detect a high proportion of early-stage lung cancer patients in a Chinese high-risk population. The utilization of new techniques would be conducive to improving the implementation of LDCT screening.

A protocol for measuring the response of Arabidopsis roots to gravity and treatment for simulated microgravity.

We present a protocol to quantify the response of both normal and mutant Arabidopsis seedlings to gravity and simulated microgravity under earth-normal gravity conditions. We describe the steps to simulate microgravity using a three-dimensional (3D) clinostat, which changes the rate and direction at random and consistently rotates the axis horizontally and vertically to counteract the standard gravity at the Earth's surface. We then detail the gravity stimulation experiment, followed by the assessment of root responses using ImageJ-based analysis. For complete details on the use and execution of this protocol, please refer to Xu et al. (2022).1.

Metagenomics analysis of the effects of Agaricus bisporus mycelia on microbial diversity and CAZymes in compost.

Agaricus bisporus growth alters the lignocellulosic composition and structure of compost. However, it is difficult to differentiate the enzyme activities of A. bisporus mycelia from the wider microbial community owing to the complication of completely speareting the mycelia from compost cultures. Macrogenomics analysis was employed in this study to examine the fermentation substrate of A. bisporus before and after mycelial growth, and the molecular mechanism of substrate utilization by A. bisporus mycelia was elucidated from the perspective of microbial communities and CAZymes in the substrate. The results showed that the relative abundance of A. bisporus mycelia increased by 77.57-fold after mycelial colonization, the laccase content was significantly increased and the lignin content was significantly decreased. Analysis of the CAZymes showed that AA10 family was extremely differentiated. Laccase-producing strains associated with AA10 family were mostly bacteria belonging to Thermobifida and Thermostaphylospora, suggesting that these bacteria may play a synergistic role in lignin decomposition along with A. bisporus mycelia. These findings provide preliminary evidence for the molecular mechanism of compost utilization by A. bisporus mycelia and offer a reference for the development and utilization of strains related to lignocellulose degradation.

Few-Electrode EEG from the Wearable Devices Using Domain Adaptation for Depression Detection.

Nowadays, major depressive disorder (MDD) has become a crucial mental disease that endangers human health. Good results have been achieved by electroencephalogram (EEG) signals in the detection of depression. However, EEG signals are time-varying, and the distributions of the different subjects' data are non-uniform, which poses a bad influence on depression detection. In this paper, the deep learning method with domain adaptation is applied to detect depression based on EEG signals. Firstly, the EEG signals are preprocessed and then transformed into pictures by two methods: the first one is to present the three channels of EEG separately in the same image, and the second one is the RGB synthesis of the three channels of EEG. Finally, the training and prediction are performed in the domain adaptation model. The results indicate that the domain adaptation model can effectively extract EEG features and obtain an average accuracy of 77.0 ± 9.7%. This paper proves that the domain adaptation method can effectively weaken the inherent differences of EEG signals, making the diagnosis of different users more accurate.

GPI-Anchored Protein Homolog IcFBR1 Functions Directly in Morphological Development of Isaria cicadae.

Isaria cicadae is a famous edible and medicinal fungus in China and Asia. The molecular basis of morphogenesis and synnemal formation needs to be understood in more detail because this is the main source of biomass production in I. cicadae. In the present study, a fruiting body formation-related gene with a glycosylphosphatidylinositol (GPI) anchoring protein (GPI-Ap) gene homolog IcFBR1 was identified by screening random insertion mutants. Targeted deletion of IcFBR1 resulted in abnormal formation of synnemata, impairing aerial hyphae growth and sporulation. The IcFBR1 mutants were defective in the utilization of carbon sources with reduced polysaccharide contents and the regulation of amylase and protease activities. Transcriptome analysis of ΔIcfbr1 showed that IcFBR1 deletion influenced 49 gene ontology terms, including 23 biological processes, 9 molecular functions, and 14 cellular components. IcFBR1 is therefore necessary for regulating synnemal development, secondary metabolism, and nutrient utilization in this important edible and medicinal fungus. This is the first report illustrating that the function of IcFBR1 is associated with the synnemata in I. cicadae.

Karrikin signaling regulates hypocotyl shade avoidance response by modulating auxin homeostasis in Arabidopsis.

Shade affects all aspects of plant growth and development, including seed germination, hypocotyl elongation, petiole growth, leaf hyponasty, and flowering time. Here, we found that mutations in the key Arabidopsis karrikins signal perception-associated KARRIKIN INSENSITIVE 2 (KAI2) gene, encoding an α/ß-fold hydrolase, and the MORE AXILLARY GROWTH 2 (MAX2) gene, encoding an F-box protein, led to greater hypocotyl elongation under shade avoidance conditions. We further verified that these phenotypes were caused by perception of the endogenous KAI2-ligands (KLs), and that this phenotype is independent of strigolactone biosynthetic or signaling pathways. Upon perception of a KL, it is probable that the target protein forms a complex with the KAI2/MAX2 proteins, which are degraded through the action of the 26S proteasome. We demonstrated that SUPPRESSOR OF MAX2-1 (SMAX1) is the degradation target for the KAI2/MAX2 complex in the context of shade avoidance. KAI2 and MAX2 require SMAX1 to limit the hypocotyl growth associated with shade avoidance. Treatment with l-kynurenine, an inhibitor of auxin accumulation, partially restored elongation of kai2 mutant hypocotyls under simulated shade. Furthermore, KAI2 is involved in regulating auxin accumulation and polar auxin transport, which may contribute to the hypocotyl shade response. In addition, SMAX1 gene overexpression promoted the hypocotyl shade response. RNA-sequencing analysis revealed that SMAX1-overexpression affected the expression of many auxin homeostasis genes, especially under simulated shade. Altogether, our data support the conclusion that KL signaling regulates shade avoidance by modulating auxin homeostasis in the hypocotyl.

A real-time object detection model for orchard pests based on improved YOLOv4 algorithm.

Accurate and efficient real-time detection of orchard pests was essential and could improve the economic benefits of the fruit industry. The orchard pest dataset, PestImgData, was built through a series of methods such as web crawler, specimen image collection and data augmentation. PestImgData was composed of two parts, PestImgData-1 and PestImgData-2. It contained 24,796 color images and covered 7 types of orchard pests. Based on the PestImgData and YOLOv4 algorithm, this paper conducted a preliminary study on the real-time object detection of orchard pests from 4 perspectives: transfer learning, activation function, anchor box, and batch normalization. In addition, this paper also visualized the feature learning ability of the detection models. On the basis of the above research, three improvement measures were adopted: the post-processing NMS algorithm was upgraded to DIoU-NMS, the training method was upgraded to 2-time finetuning training and the training data was enhanced. The performance of the improved model, F-D-YOLOv4-PEST, had been effectively improved. The mean average precision of F-D-YOLOv4-PEST was 92.86%, and the detection time of a single picture was 12.22 ms, which could meet the real-time detection requirements. In addition, in the case of high overlap area or high density, F-D-YOLOv4-PEST still maintained good performance. In the testing process of the laboratory and the greenhouse, including the wired network and the wireless network, F-D-YOLOv4-PEST could locate and classify pests as expected. This research could provide technical reference for the intelligent identification of agricultural pests based on deep learning.

Arabidopsis ETHYLENE INSENSITIVE 3 directly regulates the expression of PG1ß-like family genes in response to aluminum stress.

The genes in the subfamily PG1ß (beta subunit of poly-galacturonase isoenzyme 1) have a clear effect on the biosynthesis pathway of pectin, a main component of the cell wall. However, the detailed functions of the PG1ß-like gene members in Arabidopsis (AtPG1-3) have not yet been determined. In this study, we investigated their functional roles in response to aluminum (Al) stress. Our results indicate that the PG1ß-like gene members are indeed involved in the Al-stress response and they can modulate its accumulation in roots to achieve optimum root elongation and hence better seedling growth. We found that transcription factor EIN3 (ETHYLENE INSENSITIVE 3) alters pectin metabolism and the EIN3 gene responds to Al stress to affect the pectin content in the root cell walls, leading to exacerbation of the inhibition of root growth, as reflected by the phenotypes of overexpressing lines. We determined that EIN3 can directly bind to the promoter regions of PG1-3, which act downstream of EIN3. Thus, our results show that EIN3 responds to Al stress in Arabidopsis directly through regulating the expression of PG1-3. Hence, EIN3 mediates their functions by acting as a biomarker in their molecular biosynthesis pathways, and consequently orchestrates their biological network in response to Al stress.

Pectin methylesterase gene AtPMEPCRA contributes to physiological adaptation to simulated and spaceflight microgravity in Arabidopsis.

Pectin is biosynthesized in a highly methylated form and is partially de-methylated by pectin methylesterase (PME) activity. Plant PMEs play a critical role in cell wall remodeling in many physiological processes. Here, we studied Arabidopsis seedlings, which had been exposed to simulated or actual microgravity. Simulated microgravity inhibited total PME activity in Arabidopsis seedlings. We identified that AtPMEPCRA expression played a major role in the microgravity-induced inhibition of PME activity. atpmepcra mutants did not exhibit the enlarged leaf area of Arabidopsis seedlings observed under spaceflight microgravity. The downregulation of AtPMEPCRA expression in response to microgravity was due, in part, to changes in methylation patterns. The sexual offspring of the plants grown during spaceflight retained the methylation changes at AtPMEPCRA locus for one generation and thus contribute to the physiological adaptation to microgravity among F1 offspring seed generation. We conclude that AtPMEPCRA contributes to the spaceflight-induced transgenerational responses in Arabidopsis.