Phosphoantigens glue butyrophilin 3A1 and 2A1 to activate Vγ9Vδ2 T cells.

In both cancer and infections, diseased cells are presented to human Vγ9Vδ2 T cells through an 'inside out' signalling process whereby structurally diverse phosphoantigen (pAg) molecules are sensed by the intracellular domain of butyrophilin BTN3A11-4. Here we show how-in both humans and alpaca-multiple pAgs function as 'molecular glues' to promote heteromeric association between the intracellular domains of BTN3A1 and the structurally similar butyrophilin BTN2A1. X-ray crystallography studies visualized that engagement of BTN3A1 with pAgs forms a composite interface for direct binding to BTN2A1, with various pAg molecules each positioned at the centre of the interface and gluing the butyrophilins with distinct affinities. Our structural insights guided mutagenesis experiments that led to disruption of the intracellular BTN3A1-BTN2A1 association, abolishing pAg-mediated Vγ9Vδ2 T cell activation. Analyses using structure-based molecular-dynamics simulations, 19F-NMR investigations, chimeric receptor engineering and direct measurement of intercellular binding force revealed how pAg-mediated BTN2A1 association drives BTN3A1 intracellular fluctuations outwards in a thermodynamically favourable manner, thereby enabling BTN3A1 to push off from the BTN2A1 ectodomain to initiate T cell receptor-mediated γδ T cell activation. Practically, we harnessed the molecular-glue model for immunotherapeutics design, demonstrating chemical principles for developing both small-molecule activators and inhibitors of human γδ T cell function.

Reconstruction for beam blockage of lidar based on generative adversarial networks.

Doppler lidar is an active laser remote sensing instrument. However, beam blockage caused by low-altitude obstacles is a critical factor affecting the quality of lidar data. To reconstruct the line of sight velocities (LOSV) in areas with beam blockages and to evaluate the effectiveness of reconstruction results, the LOSV-filling network (LFnet) approach based on generative adversarial networks (GANs) and an evaluation scheme based on the degree of blockage are proposed in this paper. The LFnet comprises two adversarial models. The first adversarial model captures the structural features of LOSV to output the edge map, and the second adversarial fills in the blockage area using the edge map. We have built a packaged dataset consisting of training, validation and test datasets with mask sets. Then the sensitivity of the reconstruction effectiveness with different shielding conditions is studied, to reveal the mechanism of shielding influencing the reconstruction. A series of indicators were used to evaluate the model's performance, including the traditional indicators and the proposed indicator of root mean square error (RMSE). Finally, LFnet was demonstrated in a practical application in an airport. The complete process of an easterly gust front is reconstructed with RMSE less than 0.85 m/s, which has significance for flight safety.

Sequential covariate-adjusted randomization via hierarchically minimizing Mahalanobis distance and marginal imbalance.

In comparative studies, covariate balance and sequential allocation schemes have attracted growing academic interest. Although many theoretically justified adaptive randomization methods achieve the covariate balance, they often allocate patients in pairs or groups. To better meet the practical requirements where the clinicians cannot wait for other participants to assign the current patient for some economic or ethical reasons, we propose a method that randomizes patients individually and sequentially. The proposed method conceptually separates the covariate imbalance, measured by the newly proposed modified Mahalanobis distance, and the marginal imbalance, that is the sample size difference between the 2 groups, and it minimizes them with an explicit priority order. Compared with the existing sequential randomization methods, the proposed method achieves the best possible covariate balance while maintaining the marginal balance directly, offering us more control of the randomization process. We demonstrate the superior performance of the proposed method through a wide range of simulation studies and real data analysis, and also establish theoretical guarantees for the proposed method in terms of both the convergence of the imbalance measure and the subsequent treatment effect estimation.

Covalent Bonding of Salen Metal Complexes with Pyrene Chromophores to Porous Polymers for Photocatalytic Hydrogen Evolution.

The development of low-cost and efficient photocatalysts to achieve water splitting to hydrogen (H2) is highly desirable but remains challenging. Herein, we design and synthesize two porous polymers (Co-Salen-P and Fe-Salen-P) by covalent bonding of salen metal complexes and pyrene chromophores for photocatalytic H2 evolution. The catalytic results demonstrate that the two polymers exhibit excellent catalytic performance for H2 generation in the absence of additional noble-metal photosensitizers and cocatalysts. Particularly, the H2 generation rate of Co-Salen-P reaches as high as 542.5 µmol g-1 h-1, which is not only 6 times higher than that of Fe-Salen-P but also higher than a large amount of reported Pt-assisted photocatalytic systems. Systematic studies show that Co-Salen-P displays faster charge separation and transfer efficiencies, thereby accounting for the significantly improved photocatalytic activity. This study provides a facile and efficient way to fabricate high-performance photocatalysts for H2 production.

[Chemical composition and pharmacological effects of Cinnamomum camphora chvar. borneol essential oil: a review].

Cinnamomum camphora chvar. borneol, a rare camphor tree variant recently identified in China, is distinguished by its high concentration of D-borneol, also known as " plant gold" due to its significant value. The essential oil extracted from this variant,rich in monoterpenes and sesquiterpenes, demonstrates a broad spectrum of pharmacological activities, including analgesic, antiinflammatory, antioxidant, cognition-enhancing, anti-bacterial, and insecticidal effects. These properties, underscored by extensive research, highlight the oil's potential in the biomedical, chemical, and food sectors as a valuable commodity. Nonetheless, the safety profile of this valuable oil remains poorly characterized, with its chemical composition and therapeutic efficacy subject to variations in the factors like geographic origin, harvesting timing, part used for extraction, and processing techniques. Such variability poses challenges to its clinical application and hampers the efficient exploitation of this resource. This review synthesizes current studies on C. camphora chvar. borneol essential oil and provides a detailed examination of its chemical and pharmacological profiles. In this study, we discuss existing research gaps and propose strategies for advancing its clinical use and industrial application, aiming to provide a foundational reference for future investigations and the resolution of its commercial and therapeutic challenges.

Mussel-Inspired, Underwater Self-Healing Ionoelastomers Based on α-Lipoic Acid for Iontronics.

Weak adhesion and lack of underwater self-healability hinder advancing soft iontronics particularly in wet environments like sweaty skin and biological fluids. Mussel-inspired, liquid-free ionoelastomers are reported based on seminal thermal ring-opening polymerization of a biomass molecule of α-lipoic acid (LA), followed by sequentially incorporating dopamine methacrylamide as a chain extender, N,N'-bis(acryloyl) cystamine, and lithium bis(trifluoromethanesulphonyl) imide (LiTFSI). The ionoelastomers exhibit universal adhesion to 12 substrates in both dry and wet states, superfast self-healing underwater, sensing capability for monitoring human motion, and flame retardancy. The underwater self-repairabilitiy prolongs over three months without deterioration, and sustains even when mechanical properties greatly increase. The unprecedented underwater self-mendability benefits synergistically from the maximized availability of dynamic disulfide bonds and diverse reversible noncovalent interactions endowed by carboxylic groups, catechols, and LiTFSI, along with the prevented depolymerization by LiTFSI and tunability in mechanical strength. The ionic conductivity reaches 1.4 × 10-6 -2.7 × 10-5 S m-1 because of partial dissociation of LiTFSI. The design rationale offers a new route for creating a wide range of LA- and sulfur-derived supramolecular (bio)polymers with superior adhesion, healability, and other functionalities, and thus has technological implications for coatings, adhesives, binders and sealants, biomedical engineering and drug delivery, wearable and flexible electronics, and human-machine interfaces.

Deciphering and investigating fragment mechanism of quinolones using multi-collision energy mass spectrometry and computational chemistry strategy.

RATIONALE: Quinolones show characteristic fragments in mass spectrometry (MS) analysis due to their common core structures, and energy-dependent differences among these fragments are generated through the same fragmentation pathway of different molecules. Computational chemistry, which provides quantitative results of molecule parameters, is helpful for investigating the mechanisms of chemistry. METHODS: MS/MS spectra of five quinolones, namely norfloxacin (NOR), enoxacin (ENO), enrofloxacin (ENR), gatifloxacin (GAT), and lomefloxacin (LOM), were acquired for deciphering fragmentation pathways under multi-collision energy (CE). Computational methods were used for excluding little possibility pathways from the point of view of energy and stable conformations, whereas optimized collision energy (OCE) and maximum relative intensity (MRI) of major competitive fragments were investigated and confirmed using computational results. RESULTS: Fragmentation results of NOR, ENO, ENR, and GAT were deciphered using experimental and computational data, of which fragmentation regularities were summarized. Fragmentation pathways of LOM were deciphered under the guidance of foregoing regularities. Meanwhile, the whole process was validated by comparing OCE and MRI and computational energy results, which showed good agreement. CONCLUSIONS: A strategy for explaining quinolone fragmentation results of multi-CE values and deciphering fragment mechanism using computational methods was developed. Relevant data and strategy may provide ideas for how to design and decipher new drug molecules with similar structures.

"One Stone Two Birds" Strategy of Synthesizing the Battery Material Lithium Sulfide: Aluminothermal Reduction of Lithium Sulfate.

Lithium sulfide (Li2S) is a critical material for clean energy technologies, i.e., the cathode material in lithium-sulfur batteries and the raw material for making sulfide solid electrolytes in all-solid-state batteries. However, its practical application at a large scale is hindered by its industrial production method of reducing lithium sulfate with carbon materials at high temperatures, which emits carbon dioxide and is time-consuming. We hereby report a method of synthesizing Li2S by thermally reducing lithium sulfate with aluminum. Compared with the carbothermal method, this aluminothermal approach has several advantages, such as operation at lower temperatures, completion in minutes, no emission of greenhouse gases, and valuable byproducts of aluminum oxide (Al2O3). The home-made Li2S demonstrates competitive performance in battery tests versus the commercial counterpart. Moreover, using the byproduct Al2O3 to coat the cathode side of the separator can enhance the battery's capacity without influencing its rate capability. Thus, this "one stone two birds" method has great potential for practical applications of developing Li-S batteries.

ABTS as Both Activator and Electron Shuttle to Activate Persulfate for Diclofenac Degradation: Formation and Contributions of ABTS•+, SO4•-, and •OH.

The activation of peroxydisulfate (PDS) by organic compounds has attracted increasing attention. However, some inherent drawbacks including quick activator decomposition and poor anti-interference capacity limited the application of organic compound-activated PDS. It was interestingly found that 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonate) (ABTS) could act as both activator and electron shuttle for PDS activation to enhance diclofenac (DCF) degradation over a pH range of 2.0-11.0. Multiple reactive species of ABTS•+, •OH, and SO4•- were generated in the PDS/ABTS system, while only ABTS•+ and •OH directly contributed to DCF degradation. ABTS•+, generated via the reactions of ABTS with PDS, SO4•-, and •OH, was the dominant reactive species of DCF degradation. No significant decomposition of ABTS was observed in the PDS/ABTS system, and ABTS acted as both activator and electron shuttle. Four possible degradation pathways of DCF were proposed, and the toxicity of DCF decreased after treatment with the PDS/ABTS system. The PDS/ABTS system had good anti-interference capacity to common natural water constituents. Additionally, ABTS was encapsulated into cellulose to obtain ABTS@Ce beads, and the PDS/ABTS@Ce system possessed excellent performance on DCF degradation. This study proposes a new perspective to reconsider the mechanism of activating PDS with organic compounds and highlights the considerable contribution of organic radicals on contaminant removal.

The analgesic effects and neural oscillatory mechanisms of virtual reality scenes based on distraction and mindfulness strategies in human volunteers.

BACKGROUND: Virtual reality (VR) has been widely used as a non-pharmacological adjunct to pain management. However, there is no consensus on what type of VR content is the best for pain alleviation and by what means VR modulates pain perception. We used three experiments to explore the analgesic effect of VR scenes in healthy adult volunteers. METHODS: We first compared the effect of immersive VR on pain perception with active (i.e. non-immersive, two-dimensional video) and passive (i.e. no VR or audiovisual input) controls at both subjective perceptual (Experiment 1) and electrophysiological (electroencephalography) levels (Experiment 2), and then explored possible analgesic mechanisms responsible for VR scenes conveying different strategies (e.g. exploration or mindfulness; Experiment 3). RESULTS: The multisensory experience of the VR environment lowered pain intensity and unpleasantness induced by contact heat stimuli when compared with two control conditions (P=0.001 and P<0.001, respectively). The reduced pain intensity rating correlated with decreased P2 amplitude (r=0.433, P<0.001) and increased pre-stimulus spontaneous gamma oscillations (r=-0.339, P=0.004) by 32-channel electroencephalography. A VR exploration scene induced a strong sense of immersion that was associated with increased pre-stimulus gamma oscillations (r=0.529, P<0.001), whereas a VR mindfulness meditation scene had a minor effect on immersive feelings but induced strong pre-stimulus alpha oscillations (r=-0.550, P<0.001), which led to a comparable analgesic effect. CONCLUSIONS: Distinct neural mechanisms are responsible for VR-induced analgesia, deepening our understanding of the analgesic benefits of VR and its neural electrophysiological correlates. These findings support further development of digital healthcare.

Simultaneous quantification of fatty acids in serum with dual derivatization by liquid chromatography-tandem mass spectrometry.

Fatty acids have multitudinous biological functions and play a crucial role in many biological processes, but due to poor ionization efficiency and lack of appropriate internal standards, the comprehensive quantification of fatty acids by liquid chromatography-tandem mass spectrometry is still challenging. In this study, a new, accurate, and reliable method for quantifying 30 fatty acids in serum using dual derivatization was proposed. Indole-3-acetic acid hydrazide derivants of fatty acids were used as the internal standard and indole-3-carboxylic acid hydrazide derivants of them were used to quantify. The derivatization conditions were systematically optimized and the method validation results showed good linearity with R2  > 0.9942, low detection limit (0.03-0.6 nM), precision (1.6%-9.8% for intra-day and 4.6%-14.1% for inter-day), recovery (88.2%-107.2% with relative standard deviation < 10.5%), matrix effect (88.3%-105.2% with the relative standard deviation < 9.9%) and stability (3.4%-13.8% for fatty acids derivants in 24 h at 4°C and 4.2%-13.8% for three freeze-thaw cycles). Finally, this method was successfully applied to quantify fatty acids in serum samples of Alzheimer's patients. In contrast to the healthy control group, nine fatty acids showed a significant increase in the Alzheimer's disease group.

Curative effect of external fixation combined with kirschner wire versus hollow screw in the treatment of first metacarpal bone base fracture.

PURPOSE: This study was conducted aimed at comparing the curative effect of external fixation combined with Kirschner wire fixation versus hollow screw fixation in the treatment of first metacarpal bone base fracture. METHODS: The current retrospective study included a total of 80 patients diagnosed with first metacarpal bone base fracture who were admitted in Wuxi 9th People's Hospital Affiliated to Soochow University between October 2017 and October 2020. The patients enrolled were equally divided into the combined group (40 cases, receiving external fixation combined with Kirschner wire fixation), and the control group (40 cases, receiving hollow screw fixation). Perioperative indices were collected and compared between the two groups. Pain scores before operation and three months, six months, and one year after operation were compared. Additionally, we compared the finger function in the last follow-up visit ( the follow-up period was 1 year) and rate of complications. RESULTS: Operation time, amount of bleeding, length of incision, length of hospital stay, and fracture healing time did not differ between the two groups (all P > 0.05). Pain score was comparable between the two groups before operation (P = 0.704). Despite lower results showing at 3, 6, and 12 months after operation in both groups, the pain score did not significantly differ in any time point between the two groups (all P > 0.05). Additionally, no significant differences were observed in finger function and rate of complications at the last follow-up between the two groups (both P > 0.05). CONCLUSION: External fixation combined with Kirschner wire fixation and hollow screw fixation exhibited similar curative effect in treating first metacarpal bone base fracture, indicating both surgery methods may be considered as the preferred approach.

Comparison of diaphyseal and metaphyseal ulnar shortening osteotomies for the treatment of ulnar impaction syndrome.

BACKGROUND: Ulnar shortening osteotomy (USO) is a common surgical procedure for the treatment of ulnar impaction syndrome (UIS). The purpose of this study was to compare the results of metaphyseal and diaphyseal USO.  METHODS: This retrospective study compared the clinical outcomes and complications of 32 patients who underwent diaphyseal step-cut USO (n = 10), diaphyseal oblique USO (n = 12), or metaphyseal USO (n = 10). RESULTS: Patient characteristics, ulnar variance, wrist range of motion, preoperative pain, grip strength, and functional scores (quick disability of the arm, shoulder, and hand and patient-rated wrist evaluation) were comparable. Both operation time (79.5 vs. 138/139 min) and incision length (7.80 vs. 9.67/13.00 cm) were shorter in the metaphyseal USO than in the diaphyseal oblique/step-cut USO. Compared with diaphyseal oblique/step-cut USO, metaphyseal osteotomies were associated with greater improvement in the pain on postoperative day 3 and shorter bone healing time. The requirements for implant removal were the same among the three groups. No complications were observed in any group. CONCLUSION: Compared with diaphyseal USO, metaphyseal USO has advantages for operation time and incision length, early postoperative pain, bone healing in UIS management. The results suggested that metaphyseal USO could be widely applied to the surgical treatment of UIS. However, the long-term outcomes of these techniques still require further evaluation using more large-scale, randomized clinical trials.

HDAC2 exacerbates rheumatoid arthritis progression via the IL-17-CCL7 signaling pathway.

Histone deacetylases (HDACs) have been reported to regulate the immune response in rheumatoid arthritis (RA). The current study aimed to explore key HDACs and their molecular mechanism in RA. First, the expression of HDAC1, HDAC2, HDAC3 and HDAC8 in RA synovial tissue was determined by qRT-PCR. The effects of HDAC2 on the proliferation, migration, invasion, and apoptosis of fibroblast-like synoviocytes (FLS) in vitro were studied. Furthermore, collagen-induced arthritis (CIA) rat models were established to evaluate the severity of arthritis in joints, and the levels of inflammatory factors were examined by immunohistochemistry staining, ELISA, and qRT-PCR. Transcriptome sequencing was used to screen differentially expressed genes (DEGs) with HDAC2 silencing in the synovial tissue of CIA rat, and downstream signaling pathways were predicted by enrichment analysis. The results showed that HDAC2 was highly expressed in the synovial tissue of RA patients and CIA rats. Overexpressed HDAC2 promoted FLS proliferation, migration, and invasion and inhibited FLS apoptosis in vitro, resulting in secretion of inflammatory factors and RA exacerbation in vivo. There were 176 DEGs, including 57 downregulated and 119 upregulated genes, after silencing HDAC2 in CIA rats. DEGs were primarily enriched in Platinum drug resistance, IL-17 as well as the PI3K-Akt signaling pathways. CCL7, which was implicated in the IL-17 signaling pathway, was downregulated after HDAC2 silencing. Furthermore, CCL7 overexpression aggravated the development of RA, which was demonstrated to be effectively attenuated by HDAC2 suppression. In conclusion, this study demonstrated that HDAC2 exacerbated the progression of RA by regulating the IL-17-CCL7 signaling pathway, suggesting that HDAC2 may be a promising therapeutic target for RA treatment.

Robust Learning with Noisy Ship Trajectories by Adaptive Noise Rate Estimation.

Ship trajectory classification is of great significance for shipping analysis and marine security governance. However, in order to cover up their illegal fishing or espionage activities, some illicit ships will forge the ship type information in the Automatic Identification System (AIS), and this label noise will significantly impact the algorithm's classification accuracy. Sample selection is a common and effective approach in the field of learning from noisy labels. However, most of the existing methods based on sample selection need to determine the noise rate of the data through prior means. To address these issues, we propose a noise rate adaptive learning mechanism that operates without prior conditions. This mechanism is integrated with the robust training paradigm JoCoR (joint training with co-regularization), giving rise to a noise rate adaptive learning robust training paradigm called A-JoCoR. Experimental results on real-world trajectories provided by the Danish Maritime Authority verified the effectiveness of A-JoCoR. It not only realizes the adaptive learning of the data noise rate during the training process, but also significantly improves the classification performance compared with the original method.

A Soybean Sucrose Non-Fermenting Protein Kinase 1 Gene, GmSNF1, Positively Regulates Plant Response to Salt and Salt-Alkali Stress in Transgenic Plants.

Soybean is one of the most widely grown oilseed crops worldwide. Several unfavorable factors, including salt and salt-alkali stress caused by soil salinization, affect soybean yield and quality. Therefore, exploring the molecular basis of salt tolerance in plants and developing genetic resources for genetic breeding is important. Sucrose non-fermentable protein kinase 1 (SnRK1) belongs to a class of Ser/Thr protein kinases that are evolutionarily highly conserved direct homologs of yeast SNF1 and animal AMPKs and are involved in various abiotic stresses in plants. The GmPKS4 gene was experimentally shown to be involved with salinity tolerance. First, using the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique, the GmSNF1 protein was shown to interact with the GmPKS4 protein. Second, the GmSNF1 gene responded positively to salt and salt-alkali stress according to qRT-PCR analysis, and the GmSNF1 protein was localized in the nucleus and cytoplasm using subcellular localization assay. The GmSNF1 gene was then heterologously expressed in yeast, and the GmSNF1 gene was tentatively identified as having salt and salt-alkali tolerance function. Finally, the salt-alkali tolerance function of the GmSNF1 gene was demonstrated by transgenic Arabidopsis thaliana, soybean hairy root complex plants overexpressing GmSNF1 and GmSNF1 gene-silenced soybean using VIGS. These results indicated that GmSNF1 might be useful in genetic engineering to improve plant salt and salt-alkali tolerance.

Modulating Electronic Structures of Iron Clusters through Orbital Rehybridization by Adjacent Single Copper Sites for Efficient Oxygen Reduction.

The atom-cluster interaction has recently been exploited as an effective way to increase the performance of metal-nitrogen-carbon catalysts for oxygen reduction reaction (ORR). However, the rational design of such catalysts and understanding their structure-property correlations remain a great challenge. Herein, we demonstrate that the introduction of adjacent metal (M)-N4 single atoms (SAs) could significantly improve the ORR performance of a well-screened Fe atomic cluster (AC) catalyst by combining density functional theory (DFT) calculations and experimental analysis. The DFT studies suggest that the Cu-N4 SAs act as a modulator to assist the O2 adsorption and cleavage of O-O bond on the Fe AC active center, as well as optimize the release of OH* intermediates to accelerate the whole ORR kinetic. The depositing of Fe AC with Cu-N4 SAs on nitrogen doped mesoporous carbon nanosheet are then constructed through a universal interfacial monomicelles assembly strategy. Consistent with theoretical predictions, the resultant catalyst exhibits an outstanding ORR performance with a half-wave potential of 0.92 eV in alkali and 0.80 eV in acid, as well as a high power density of 214.8 mW cm-2 in zinc air battery. This work provides a novel strategy for precisely tuning the atomically dispersed poly-metallic centers for electrocatalysis.

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challenging. Purpose To quantify CAC scores automatically from a single CTA scan. Materials and Methods In this retrospective study, a deep learning method to quantify CAC scores automatically from a single CTA scan was developed on training and validation sets of 292 patients and 73 patients collected from March 2019 to July 2020. Virtual noncontrast scans obtained with a spectral CT scanner were used to develop the algorithm to alleviate tedious manual annotation of calcium regions. The proposed method was validated on an independent test set of 240 CTA scans collected from three different CT scanners from August 2020 to November 2020 using the Pearson correlation coefficient, the coefficient of determination, or r2, and the Bland-Altman plot against the semiautomatic Agatston score at noncontrast CT. The cardiovascular risk categorization performance was evaluated using weighted κ based on the Agatston score (CAC score risk categories: 0-10, 11-100, 101-400, and >400). Results Two hundred forty patients (mean age, 60 years ± 11 [standard deviation]; 146 men) were evaluated. The positive correlation between the automatic deep learning CTA and semiautomatic noncontrast CT CAC score was excellent (Pearson correlation = 0.96; r2 = 0.92). The risk categorization agreement based on deep learning CTA and noncontrast CT CAC scores was excellent (weighted κ = 0.94 [95% CI: 0.91, 0.97]), with 223 of 240 scans (93%) categorized correctly. All patients who were miscategorized were in the direct neighboring risk groups. The proposed method's differences from the noncontrast CT CAC score were not statistically significant with regard to scanner (P = .15), sex (P = .051), and section thickness (P = .67). Conclusion A deep learning automatic calcium scoring method accurately quantified coronary artery calcium from CT angiography images and categorized risk. © RSNA, 2021 See also the editorial by Goldfarb and Cao et al in this issue.

Polarization-sensitive imaging based on incoherent holography.

The polarization-sensitive imaging technology is proposed based on incoherent holography. The distribution of state of polarization (SoP) of the object light field can be reconstructed by measuring the phase difference and amplitude ratio of two components of the Jones vector on the basis of incoherent self-interference theory and the accurate point spread function (PSF) of the incoherent holographic system. In the analysis of Fresnel diffraction, we develop a new method to greatly simplify the calculation of the accurate PSF by means of imaging property of lens and symbolic mathematics tools. In the recording process, we utilize the automation of phase shift, photography, and synthesization of color hologram to greatly shorten the total recording time of a group of phase-shifted holograms. The experimental results show that the proposed technology can accurately realize polarization-sensitive imaging and it is much simpler for complete linearly polarized light.

Physiological and transcriptomic analyses reveal novel insights into the cultivar-specific response to alkaline stress in alfalfa (Medicago sativa L.).

Soil alkalization severely limits plant growth and development, however, the mechanisms of alkaline response in plants remain largely unknown. In this study, we performed physiological and transcriptomic analyses using two alfalfa cultivars (Medicago sativa L.) with different sensitivities to alkaline conditions. The chlorophyll content and shoot fresh mass drastically declined in the alkaline-sensitive cultivar Algonquin (AG) following alkaline treatment (0-25 mM Na2CO3 solution), while the alkaline-tolerant cultivar Gongnong NO.1 (GN) maintained relatively stable growth and chlorophyll content. Compared with AG, GN had higher contents of Ca2+ and Mg2+; the ratios of Ca2+ and Mg2+ to Na+, proline and soluble sugar, as well as higher enzyme activities of peroxidase (POD) and catalase (CAT) under the alkaline conditions. Furthermore, transcriptomic analysis identified three categories of alkaline-responsive differentially expressed genes (DEGs) between the two cultivars: 48 genes commonly induced in both the cultivars (CAR), 574 genes from the tolerant cultivar (TAR), and 493 genes from the sensitive cultivar (SAR). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that CAR genes were mostly involved in phenylpropanoid biosynthesis, lipid metabolism, and DNA replication and repair; TAR genes were significantly enriched in metabolic pathways, such as biosynthesis of amino acids and secondary metabolites including flavonoids, and the MAPK signaling pathway; SAR genes were specifically enriched in vitamin B6 metabolism. Taken together, the results identified candidate pathways associated with genetic variation in response to alkaline stress, providing novel insights into the mechanisms underlying alkaline tolerance in alfalfa.