Pan-transcriptomic analysis reveals alternative splicing control of cold tolerance in rice.

Plants have evolved complex mechanisms to adapt to harsh environmental conditions. Rice (Oryza sativa) is a staple food crop that is sensitive to low temperatures. However, its cold stress responses remain poorly understood, thus limiting possibilities for crop engineering to achieve greater cold tolerance. In this study, we constructed a rice pan-transcriptome and characterized its transcriptional regulatory landscape in response to cold stress. We performed Iso-Seq and RNA-Seq of 11 rice cultivars subjected to a time-course cold treatment. Our analyses revealed that alternative splicing-regulated gene expression plays a significant role in the cold stress response. Moreover, we identified CATALASE C (OsCATC) and Os03g0701200 as candidate genes for engineering enhanced cold tolerance. Importantly, we uncovered central roles for the 2 serine-arginine-rich proteins OsRS33 and OsRS2Z38 in cold tolerance. Our analysis of cold tolerance and resequencing data from a diverse collection of 165 rice cultivars suggested that OsRS2Z38 may be a key selection gene in japonica domestication for cold adaptation, associated with the adaptive evolution of rice. This study systematically investigated the distribution, dynamic changes, and regulatory mechanisms of alternative splicing in rice under cold stress. Overall, our work generates a rich resource with broad implications for understanding the genetic basis of cold response mechanisms in plants.

Predicting potential small molecule-miRNA associations utilizing truncated schatten p-norm.

MicroRNAs (miRNAs) have significant implications in diverse human diseases and have proven to be effectively targeted by small molecules (SMs) for therapeutic interventions. However, current SM-miRNA association prediction models do not adequately capture SM/miRNA similarity. Matrix completion is an effective method for association prediction, but existing models use nuclear norm instead of rank function, which has some drawbacks. Therefore, we proposed a new approach for predicting SM-miRNA associations by utilizing the truncated schatten p-norm (TSPN). First, the SM/miRNA similarity was preprocessed by incorporating the Gaussian interaction profile kernel similarity method. This identified more SM/miRNA similarities and significantly improved the SM-miRNA prediction accuracy. Next, we constructed a heterogeneous SM-miRNA network by combining biological information from three matrices and represented the network with its adjacency matrix. Finally, we constructed the prediction model by minimizing the truncated schatten p-norm of this adjacency matrix and we developed an efficient iterative algorithmic framework to solve the model. In this framework, we also used a weighted singular value shrinkage algorithm to avoid the problem of excessive singular value shrinkage. The truncated schatten p-norm approximates the rank function more closely than the nuclear norm, so the predictions are more accurate. We performed four different cross-validation experiments on two separate datasets, and TSPN outperformed various most advanced methods. In addition, public literature confirms a large number of predictive associations of TSPN in four case studies. Therefore, TSPN is a reliable model for SM-miRNA association prediction.

Molecular-Scale Geometric Design: Zigzag-Structured Intrinsically Stretchable Polymer Semiconductors.

Orienting intelligence and multifunction, stretchable semiconductors are of great significance in constructing next-generation human-friendly wearable electronic devices. Nevertheless, rendering semiconducting polymers mechanical stretchability without compromising intrinsic electrical performance remains a major challenge. Combining geometry-innovated inorganic systems and structure-tailored organic semiconductors, a molecular-scale geometric design strategy is proposed to obtain high-performance intrinsically stretchable polymer semiconductors. Originating from the linear regioregular conjugated polymer and corresponding para-modified near-linear counterpart, a series of zigzag-structured semiconducting polymers are developed with diverse ortho-type and meta-type kinking units quantitatively incorporated. They showcase huge edges in realizing stretchability enhancement for conformational transition, likewise with long-range π-aggregation and short-range torsion disorder taking effect. Assisted by additional heteroatom embedment and flexible alkyl-chain attachment, mechanical stretchability and carrier mobility could afford a two-way promotion. Among zigzag-structured species, o-OC8-5% with the initial field-effect mobility up to 1.92 cm2 V-1 s-1 still delivers 1.43 and 1.37 cm2 V-1 s-1 under 100% strain with charge transport parallel and perpendicular to the stretching direction, respectively, accompanied by outstanding performance retention and cyclic stability. This molecular design strategy contributes to an in-depth exploration of prospective intrinsically stretchable semiconductors for cutting-edge electronic devices.

Sensitivity-enhanced strain sensor based on a shape-modulated multimode fiber.

In this Letter, we demonstrate a sensitivity-enhanced strain sensor based on a shape-modulated multimode fiber (MMF). In contrast to conventional single-mode-multimode-single-mode (SMS) fiber structures, which typically contain a single cylindrical homogeneous MMF section, the shape of the MMF section in this investigation is modulated by lateral offset splicing of multiple MMF segments. Simulation results show that the designed shape-modulated MMF has a higher peak mechanical strain than that of a cylindrical MMF. Experimental results demonstrate that the strain sensitivity achieved by the shaped-modulated MMF-formed SMS fiber structure is as high as -55.63 pm/µÎµ, which is 33 times higher than that for a cylindrical MMF-formed conventional SMS fiber structure at -1.65 pm/µÎµ. This high sensitivity and low-fabrication cost SMS fiber sensor has the potential to be a promising candidate in precise strain measurement applications.

Robust Ru/Ce@Co Catalyst with an Optimized Support Structure for Propane Oxidation.

Short carbon chain alkanes, as typical volatile organic compounds (VOCs), have molecular structural stability and low molecular polarity, leading to an enormous challenge in the catalytic oxidation of propane. Although Ru-based catalysts exhibit a surprisingly high activity for the catalytic oxidation of propane to CO2 and H2O, active RuOx species are partially oxidized and sintered during the oxidation reaction, leading to a decrease in catalytic activity and significantly inhibiting their application in industrial processes. Herein, the Ru/Ce@Co catalyst is synthesized with a specific structure, in which cerium dioxide is dispersed in a thin layer on the surface of Co3O4, and Ru nanoparticles fall preferentially on cerium oxide with high dispersity. Compared with the Ru/CeO2 and Ru/Co3O4 catalysts, the Ru/Ce@Co catalyst demonstrates excellent catalytic activity and stability for the oxidation of propane, even under severe operating conditions, such as recycling reaction, high space velocity, a certain degree of moisture, and high temperature. Benefiting from this particular structure, the Ru/Ce@Co (5:95) catalyst with more Ce3+ species leads to the Ru species being anchored more firmly on the CeO2 surface with a low-valent state and has a strong potential for adsorption and activation of propane and oxygen, which is beneficial for RuOx species with high activity and stability. This work provides a novel strategy for designing high-efficiency Ru-based catalysts for the catalytic combustion of short carbon alkanes.

Suppression of cracking in drying colloidal suspensions with chain-like particles.

The prevention of drying-induced cracking is crucial in maintaining the mechanical integrity and functionality of colloidal deposits and coatings. Despite exploring various approaches, controlling drying-induced cracking remains a subject of great scientific interest and practical importance. By introducing chain-like particles composed of the same material and with comparable size into commonly used colloidal suspensions of spherical silica nanoparticles, we can significantly reduce the cracks formed in dried particle deposits and achieve a fivefold increase in the critical cracking thickness of colloidal silica coatings. The mechanism underlying the crack suppression is attributed to the increased porosity and pore sizes in dried particle deposits containing chain-like particle, which essentially leads to reduction in internal stresses developed during the drying process. Meanwhile, the nanoindentation measurements reveal that colloidal deposits with chain-like particles exhibit a smaller reduction in hardness compared to those reported using other cracking suppression approaches. This work demonstrates a promising technique for preparing colloidal coatings with enhanced crack resistance while maintaining desirable mechanical properties.

Chemical Constituents of a Marine-derived Fungus Fusarium oxysporum F0888 and their Antibacterial Activity.

Five new compounds, including four hydroxyphenylacetic acid derivatives, stachylines H-K (1-4), a derivative of hydroxyphenylethanol (5), as well as seven known compounds were obtained from a marine-derived fungus Fusarium oxysporum F0888 isolated from sediments in the South China Sea. The structures and absolute configurations of new compounds were determined by spectroscopic (IR, NMR, and HR-ESI-MS) analyses, comparison of optical rotations, and the modified Mosher's MTPA ester method. Antimicrobial and anti-inflammatory activities of compounds 1-12 were tested. Unfortunately, all of isolated compounds were inactivity.

A Recursive Prediction-Based Feature Enhancement for Small Object Detection.

Transformer-based methodologies in object detection have recently piqued considerable interest and have produced impressive results. DETR, an end-to-end object detection framework, ingeniously integrates the Transformer architecture, traditionally used in NLP, into computer vision for sequence-to-sequence prediction. Its enhanced variant, DINO, featuring improved denoising anchor boxes, has showcased remarkable performance on the COCO val2017 dataset. However, it often encounters challenges when applied to scenarios involving small object detection. Thus, we propose an innovative method for feature enhancement tailored to recursive prediction tasks, with a particular emphasis on augmenting small object detection performance. It primarily involves three enhancements: refining the backbone to favor feature maps that are more sensitive to small targets, incrementally augmenting the number of queries for small objects, and advancing the loss function for better performance. Specifically, The study incorporated the Switchable Atrous Convolution (SAC) mechanism, which features adaptable dilated convolutions, to increment the receptive field and thus elevate the innate feature extraction capabilities of the primary network concerning diminutive objects. Subsequently, a Recursive Small Object Prediction (RSP) module was designed to enhance the feature extraction of the prediction head for more precise network operations. Finally, the loss function was augmented with the Normalized Wasserstein Distance (NWD) metric, tailoring the loss function to suit small object detection better. The efficacy of the proposed model is empirically confirmed via testing on the VISDRONE2019 dataset. The comprehensive array of experiments indicates that our proposed model outperforms the extant DINO model in terms of average precision (AP) small object detection.

Enantio- and Diastereoselective Desymmetrization of 1,1'-Biaryl-2,6-dicarbaldehydes by Copper-Catalyzed 1,2-Addition of Silicon Nucleophiles.

A desymmetrizing 1,2-addition of silicon nucleophiles to biaryl derivatives containing an 2,6-dicarbaldehyde-1-yl unit is reported. The reaction is catalyzed by copper with a triazolium-derived N-heterocyclic carbene as the chiral ligand and an Si-B reagent as the silicon pronucleophile. The practical methodology furnishes axially chiral aromatic carbaldehydes decorated with a centrally chiral α-hydroxysilane moiety in moderate to high yields and with high enantio- as well as excellent diastereoselectivities. The silicon nucleophile always attacks at either carbonyl group away from the ortho substituent on the phenyl ring at C1 of the 2,6-dicarbaldehyde-1-yl fragment. The resulting axially and centrally chiral products can be further converted into valuable biaryl compounds with hardly any erosion of the enantiomeric excess.

Enantioselective Dearomatization of Pyridinium Salts by Copper-Catalyzed C4-Selective Addition of Silicon Nucleophiles.

A copper-catalyzed C4-selective addition of silicon nucleophiles released from an Si-B reagent to prochiral pyridinium triflates is reported. The dearomatization proceeds with excellent enantioselectivity using Cu(CH3CN)4PF6 as the precatalyst and (R,R)-Ph-BPE (1,2-bis[(2R,5R)-2,5-diphenylphospholan-1-yl]ethane) as the chiral ligand. A carbonyl group at C3 is required for this, likely acting a weak donor group to preorganize and direct the nucleophilic attack towards C4. The resulting 4-silylated 1,4-dihydropyridines can be further converted into functionalized piperidine derivatives.

99.92%-Fidelity cnot Gates in Solids by Noise Filtering.

Inevitable interactions with the reservoir largely degrade the performance of entangling gates, which hinders practical quantum computation from coming into existence. Here, we experimentally demonstrate a 99.920(7)%-fidelity controlled-not gate by suppressing the complicated noise in a solid-state spin system at room temperature. We found that the fidelity limited at 99% in previous works results from considering only static classical noise, and, thus, in this work, a complete noise model is constructed by also considering the time dependence and the quantum nature of the spin bath. All noises in the model are dynamically corrected by an exquisitely designed shaped pulse, giving the resulting error below 10^{-4}. The residual gate error is mainly originated from the longitudinal relaxation and the waveform distortion that can both be further reduced technically. Our noise-resistant method is universal and will benefit other solid-state spin systems.

ACSL4 promotes microglia-mediated neuroinflammation by regulating lipid metabolism and VGLL4 expression.

Acyl-CoA synthetase long-chain family member 4 (ACSL4) is an important isozyme in polyunsaturated fatty acid (PUFA) metabolism. The role of ACSL4 in the lipopolysaccharide (LPS)-induced inflammation of microglia, and the effects of ACSL4-mediated inflammation on the progression of Parkinson's disease (PD) are unknown. In this study, we found that ACSL4 expression was increased after LPS stimulation. Knocking down ACSL4 in microglia decreased proinflammatory cytokine production. Mechanistically, ACSL4 reduced vestigial-like family member 4(VGLL4) expression to promote NF-κB signal transduction; and ACSL4 regulated lipid composition after LPS stimulation. In addition, knocking down ACSL4 alleviated neuroinflammation in a systemic LPS model and acute l-methyl-4-phenyl-l,2,3,6-tetrahydropyridine (MPTP) model. These data revealed ACSL4 to be a novel regulator that promotes microglia-mediated neuroinflammation by regulating VGLL4 expression and lipid metabolism.

Deciphering the Allosteric Activation Mechanism of SIRT6 Using Molecular Dynamics Simulations.

As a member of the histone deacetylase protein family, the NAD+-dependent SIRT6 plays an important role in maintaining genomic stability and regulating cell metabolism. Interestingly, SIRT6 has been found to have a preference for hydrolyzing long-chain fatty acyls relative to deacetylation, and it can be activated by fatty acids. However, the mechanisms by which SIRT6 recognizes different substrates and can be activated by small molecular activators are still not well understood. In this study, we carried out extensive molecular dynamic simulations to shed light on these mechanisms. Our results revealed that the binding of the myristoylated substrate stabilizes the catalytically favorable conformation of NAD+, while the binding of the acetyl-lysine substrate leads to a loose binding of NAD+ in SIRT6. Based on these observations, we proposed a reasonable allosteric binding mode for myristic acid, which can enhance the catalytic activity of SIRT6 by stabilizing the binding of NAD+ with His131 as well as the acetylated substrate. Furthermore, our molecular dynamics simulations demonstrated that synthetic SIRT6 activators, such as UBCS039, MDL-801, and 12q, block the flipping of ribose in NAD+ and therefore can stabilize substrate-NAD+-His131 interactions in a manner similar to fatty acids. In summary, our newly proposed activation mechanism of SIRT6 highlights the importance of protein-substrate interactions, which would facilitate the rational design of new SIRT6 activators.

Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification.

In this study, a machine learning (ML) framework is developed toward target-oriented inverse design of the electrochemical oxidation (EO) process for water purification. The XGBoost model exhibited the best performances for prediction of reaction rate (k) based on training the data set relevant to pollutant characteristics and reaction conditions, indicated by Rext2 of 0.84 and RMSEext of 0.79. Based on 315 data points collected from the literature, the current density, pollutant concentration, and gap energy (Egap) were identified to be the most impactful parameters available for the inverse design of the EO process. In particular, adding reaction conditions as model input features allowed provision of more available information and an increase in the sample size of the data set to improve the model accuracy. The feature importance analysis was performed for revealing the data pattern and feature interpretation by using Shapley additive explanations (SHAP). The ML-based inverse design for the EO process was generalized to a random case for tailoring the optimum conditions with phenol and 2,4-dichlorophenol (2,4-DCP) serving as model pollutants. The resulting predicted k values were close to the experimental k values by experimental verification, accounting for the relative error lower than 5%. This study provides a paradigm shift from conventional trial-and-error mode to data-driven mode for advancing research and development of the EO process by a time-saving, labor-effective, and environmentally friendly target-oriented strategy, which makes electrochemical water purification more efficient, more economic, and more sustainable in the context of global carbon peaking and carbon neutrality.

Integrating Target and Shadow Features for SAR Target Recognition.

Synthetic aperture radar (SAR) sensor often produces a shadow in pairs with the target due to its slant-viewing imaging. As a result, shadows in SAR images can provide critical discriminative features for classifiers, such as target contours and relative positions. However, shadows possess unique properties that differ from targets, such as low intensity and sensitivity to depression angles, making it challenging to extract depth features from shadows directly using convolutional neural networks (CNN). In this paper, we propose a new SAR image-classification framework to utilize target and shadow information comprehensively. First, we design a SAR image segmentation method to extract target regions and shadow masks. Second, based on SAR projection geometry, we propose a data-augmentation method to compensate for the geometric distortion of shadows due to differences in depression angles. Finally, we introduce a feature-enhancement module (FEM) based on depthwise separable convolution (DSC) and convolutional block attention module (CBAM), enabling deep networks to fuse target and shadow features adaptively. The experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that when only using target and shadow information, the published deep-learning models can still achieve state-of-the-art performance after embedding the FEM.

Lamprey Wound Healing and Regenerative Effects: The Collaborative Efforts of Diverse Drivers.

Skin is a natural barrier between the body and the external environment, and this important multifunctional organ plays roles in body temperature regulation, sensory stimulation, mucus secretion, metabolite excretion and immune defense. Lampreys, as ancient vertebrates, rarely experience infection of damaged skin during farming and efficiently promote skin wound healing. However, the mechanism underlying these wound healing and regenerative effects is unclear. Our histology and transcriptomics results demonstrate that lampreys regenerate a nearly complete skin structure in damaged epidermis, including the secretory glands, and will almost not be infected, even if experiencing full-thickness damage. In addition, ATGL, DGL and MGL participate in the lipolysis process to provide space for infiltrating cells. A large number of red blood cells migrate to the site of injury and exert proinflammatory effects, upregulating the expression of proinflammatory factors such as IL-8 and IL-17. Based on a lamprey skin damage healing model, adipocytes and red blood cells in the subcutaneous fat layer can promote wound healing, which provides a new approach for the study of skin healing mechanisms. Transcriptome data reveal that mechanical signal transduction pathways are mainly regulated by focal adhesion kinase and that the actin cytoskeleton plays an important role in the healing of lamprey skin injuries. We identified RAC1 as a key regulatory gene that is necessary and partially sufficient for wound regeneration. Insights into the mechanisms of lamprey skin injury and healing will provide a theoretical basis for overcoming the challenges associated with chronic healing and scar healing in the clinic.

Seed settling and trapping during submerged secondary dispersal: Implications for saltmarsh recruitment and restoration.

Given the decline of global salt marshes, there is a pressing need to pinpoint the key processes that limit and facilitate seed-based pioneer recruitment. Secondary seed dispersal, in the form of short-distance submerged movement, is a prerequisite for initiating pioneer establishment in adjacent tidal flats but has not been fully appreciated and understood. In this study, using a settling tube and race-track flume, seeds of four global occurring saltmarsh species were studied in terms of their settlement speed and trapping opportunity to understand how seed traits and physical settings affect submerged dispersal behavior and thus seed-based saltmarsh recruitment. Present study led to the following novel insights: 1) Seeds have density-dependent settling speeds, which are comparable to that of fine sand, but much faster than that of very fine sand and silt. Since the latter is the type of sediment commonly found in many estuaries worldwide (such as the Scheldt), seeds will typically settle faster than local sediments. A sufficiently long hydrodynamic-calm period allows slowly settling sediment to bury settled seeds, otherwise, seeds will remain uncovered if the period is short. 2) Seed trapping ratio increased linearly with surface roughness (a proxy for local topographic complexity), but this effect becomes smaller with increasing hydrodynamic intensity. Seed drag coefficient was identified as the key biotic factor contributing to interspecies variability in trapping ratio. Overall, present results suggest that submerged seed dispersal may form a primary bottleneck for salt marsh recruitment by limiting seed availability via two mechanisms: i) reduced chance of seed burial through asynchronous settling of seeds and sediment particles; ii) reduced probability of seed trapping due to encountering smooth tidal flat surfaces. This study provide mechanistic and data basis for the targeted application of biophysical models in predicting outcomes of saltmarsh recruitment and long-term maintenance, thereby informing seed-based conservation and restoration.

Copper-Catalyzed Highly Enantioselective Addition of a Silicon Nucleophile to 3-Substituted 2H-Azirines Using an Si-B Reagent.

3-Substituted 2H-azirines can be considered strained cyclic ketimines, and highly enantioselective addition reactions of silicon nucleophiles to either acyclic or cyclic ketimines have been elusive so far. The present work closes this gap for those azirines by means of a copper-catalyzed silylation using a silyl boronic ester as a latent silicon nucleophile. The resulting C-silylated, unprotected (N-H) aziridines are obtained in high yields and with excellent enantioselectivities and can be further converted into valuable compounds with hardly any erosion of the enantiomeric excess.

Intussusceptive Angiogenesis in Human Metastatic Malignant Melanoma.

Angiogenesis supplies oxygen and nutrients to growing tumors. Inhibiting angiogenesis may stop tumor growth, but vascular endothelial growth factor inhibitors have limited effect in most tumors. This limited effect may be explained by an additional, less vascular endothelial growth factor-driven form of angiogenesis known as intussusceptive angiogenesis. The importance of intussusceptive angiogenesis in human tumors is not known. Epifluorescence and confocal microscopy was used to visualize intravascular pillars, the hallmark structure of intussusceptive angiogenesis, in tumors. Human malignant melanoma metastases, patient-derived melanoma xenografts in mice (PDX), and genetically engineered v-raf murine sarcoma viral oncogene homolog B1 (BRAF)-induced, phosphatase and TENsin homolog deleted on chromosome 10 (PTEN)-deficient (BPT) mice (BrafCA/+Ptenf/fTyr-Cre+/0-mice) were analyzed for pillars. Gene expression in human melanoma metastases and PDXs was analyzed by RNA sequencing. Matrix metalloproteinase 9 (MMP9) protein expression and T-cell and macrophage infiltration in tumor sections were determined with multiplex immunostaining. Intravascular pillars were detected in human metastases but rarely in PDXs and not in BPT mice. The expression of MMP9 mRNA was higher in human metastases compared with PDXs. High expression of MMP9 protein as well as infiltration of macrophages and T-cells were detected in proximity to intravascular pillars. MMP inhibition blocked formation of pillars, but not tubes or tip cells, in vitro. In conclusion, intussusceptive angiogenesis may contribute to the growth of human melanoma metastases. MMP inhibition blocked pillar formation in vitro and should be further investigated as a potential anti-angiogenic drug target in metastatic melanoma.

High prevalence of hypertension and target organ damage in patients with 11ß-hydroxylase deficiency.

BACKGROUND: Prevalence of hypertension and hypertension-mediated organ damage (HMOD) had not been well studied in patients with 11ß-hydroxylase deficiency (11ß-OHD). OBJECTIVE: The study was to assess the prevalence and risk factors of hypertension and HMOD in patients with 11ß-OHD. DESIGN: Retrospective cohort analysis in a single medical centre. PATIENTS: Twenty-eight patients with 11ß-OHD were recruited between January 2003 and June 2021, and their diagnosis had been confirmed by Sanger sequencing. MEASUREMENTS: Blood pressure and clinical indicators for the assessment of HMOD occurrence were collected from the medical records. Medication adherence of antihypertensive drugs and glucocorticoids were determined by the patients' biochemistry. Logistic regression was used to identify factors associated with HMOD. RESULTS: Prevalence of hypertension and HMOD in the cohort was 100% and 50%, respectively. The kidneys (71.43%) are the organ most commonly damaged by high blood pressure, followed by the heart (64.29%), eyes (57.14%) and brain (21.43%). Risk factors of HMOD were hypokalemia (odds ratio [OR]: 9.16; 95% confidence interval [CI]: 1.634-51.43; p = .012), blood pressure ≥ 180/110 mmHg (OR: 22.0, 95% CI: 3.08-157.34; p = .002) and irregular glucocorticoid use (OR: 3.18, 95% CI: 1.13-8.98; p = .021). Blood pressure ≥ 180/110 mmHg was an independent predictor for HMOD. CONCLUSION: Hypertension and HMOD are prevalent in patients with 11ß-OHD in our study. These findings illustrate the importance of early HMOD evaluation and optimal glucocorticoid medication in 11ß-OHD patients.