Postnatal development of rat retina: a continuous observation and comparison between the organotypic retinal explant model and in vivo development.

JOURNAL/nrgr/04.03/01300535-202503000-00033/figure1/v/2024-06-17T092413Z/r/image-tiff The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures. However, the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies. Thus, we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina. In this study, we showed that postnatal retinal explants undergo normal development, and exhibit a consistent structure and timeline with retinas in vivo. Initially, we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells. We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin, respectively. Ki-67- and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis, and exhibited a high degree of similarity in abundance and distribution between groups. Additionally, we used Ceh-10 homeodomain-containing homolog, glutamate-ammonia ligase (glutamine synthetase), neuronal nuclei, and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells, Müller glia, mature neurons, and microglia, respectively. The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas. Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development. The findings confirm the accuracy and credibility of this model and support its use for long-term, systematic, and continuous observation.

Infrared and Visible Image Fusion Algorithm Based on Double-Domain Transform Filter and Contrast Transform Feature Extraction.

Current challenges in visible and infrared image fusion include color information distortion, texture detail loss, and target edge blur. To address these issues, a fusion algorithm based on double-domain transform filter and nonlinear contrast transform feature extraction (DDCTFuse) is proposed. First, for the problem of incomplete detail extraction that exists in the traditional transform domain image decomposition, an adaptive high-pass filter is proposed to decompose images into high-frequency and low-frequency portions. Second, in order to address the issue of fuzzy fusion target caused by contrast loss during the fusion process, a novel feature extraction algorithm is devised based on a novel nonlinear transform function. Finally, the fusion results are optimized and color-corrected by our proposed spatial-domain logical filter, in order to solve the color loss and edge blur generated in the fusion process. To validate the benefits of the proposed algorithm, nine classical algorithms are compared on the LLVIP, MSRS, INO, and Roadscene datasets. The results of these experiments indicate that the proposed fusion algorithm exhibits distinct targets, provides comprehensive scene information, and offers significant image contrast.

Cytotoxic iridoid glycosides from the leaves of Paederia scandens.

A phytochemical investigation on the 80% EtOH extract of the leaves of Paederia scandens (Lour.) Merr. resulted into the isolation of three undescribed iridoid glycosides, 10-O-trans-p-coumaroyl-(4R,6R)-3,4-dihydro-3α-methylthiopaederoside (1), 10-O-trans-feruloyl-(4S,6R)-3,4-dihydro-2'-O-3α-paederoside (2), and 10-O-trans-caffeoyl-paederosidic acid ethyl ester (3). The structures of the new compounds were elucidated by spectral methods such as 1D and 2D (1H-1H COSY, HMQC, and HMBC) NMR spectroscopy, as well as high resolution mass spectrometry. The isolated compounds were tested in vitro for cytotoxic activity against five endocrine tumor cell lines. As a result, compound 1 exhibited some cytotoxicities against all the tested tumor cell lines with IC50 value less than 20.0 µM.

Boron-Doped Dinickel Phosphide to Enhance Polysulfide Conversion and Suppress Shuttling in Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are promising for next-generation high-energy energy storage systems. However, the slow reaction kinetics render mobile polysulfides hardly controlled, yielding shuttling effects and eventually damaging Li metal anodes. To improve the cyclability of Li-S batteries, high-efficiency catalysts are desired to accelerate polysulfide conversion and suppress the shuttling effect. Herein, we studied a doping system with Ni2P and Ni2B as the end members and found a B-doped Ni2P catalyst that demonstrates high activity for Li-S batteries. As anionic dopants, B demonstrates an interesting reverse electron transfer to P and tunes the electronic structure of Ni2P dramatically. The resultant B-doped Ni2P exhibits short Ni-B bonds and strong Ni-S interaction, and the electron donation of B to P further enhances the adsorption of polysulfide on catalysts. The S-S bonds of polysulfides were activated appropriately, therefore decreasing a low energy barrier for conversion reactions.

Layered Cathode with Ultralow Strain Empowers Rapid-Charging and Slow-Discharging Capability in Sodium Ion Battery.

The development of the electric vehicle industry has spurred demand for secondary batteries capable of rapid-charging and slow-discharging. Among them, sodium-ion batteries (SIBs) with layered oxide as the cathode exhibit competitive advantages due to their comprehensive electrochemical performance. However, to meet the requirements of rapid-charging and slow-discharging scenarios, it is necessary to further enhance the rate performance of the cathode material to achieve symmetrical capacity at different rates. Simultaneously, minimizing lattice strain during asymmetric electrochemical processes is also significant in alleviating strain accumulation. In this study, the ordered distribution of transition metal layers and the diffusion pathway of sodium ions are optimized through targeted K-doping of sodium layers, leading to a reduction of the diffusion barrier and endowment of prominent rate performance. At a 20C rate, the capacity of the cathode can reach 94% of that at a 0.1C rate. Additionally, the rivet effect of the sodium layers resulted in a global volume strain of only 0.03% for the modified cathode during charging at a 10C rate and discharging at a 1C rate. In summary, high-performance SIBs, with promising prospects for rapid-charging and slow-discharging capability, are obtained through the regulation of sodium layers, opening up new avenues for commercial applications.

Crosstalk between Epigenetics and Metabolic Reprogramming in Metabolic Dysfunction-Associated Steatotic Liver Disease-Induced Hepatocellular Carcinoma: A New Sight.

Epigenetic and metabolic reprogramming alterations are two important features of tumors, and their reversible, spatial, and temporal regulation is a distinctive hallmark of carcinogenesis. Epigenetics, which focuses on gene regulatory mechanisms beyond the DNA sequence, is a new entry point for tumor therapy. Moreover, metabolic reprogramming drives hepatocellular carcinoma (HCC) initiation and progression, highlighting the significance of metabolism in this disease. Exploring the inter-regulatory relationship between tumor metabolic reprogramming and epigenetic modification has become one of the hot directions in current tumor metabolism research. As viral etiologies have given way to metabolic dysfunction-associated steatotic liver disease (MASLD)-induced HCC, it is urgent that complex molecular pathways linking them and hepatocarcinogenesis be explored. However, how aberrant crosstalk between epigenetic modifications and metabolic reprogramming affects MASLD-induced HCC lacks comprehensive understanding. A better understanding of their linkages is necessary and urgent to improve HCC treatment strategies. For this reason, this review examines the interwoven landscape of molecular carcinogenesis in the context of MASLD-induced HCC, focusing on mechanisms regulating aberrant epigenetic alterations and metabolic reprogramming in the development of MASLD-induced HCC and interactions between them while also updating the current advances in metabolism and epigenetic modification-based therapeutic drugs in HCC.

Development of the second version of Global Prediction System for Epidemiological Pandemic.

Coronavirus disease 2019 (COVID-19) is a severe global public health emergency that has caused a major crisis in the safety of human life, health, global economy, and social order. Moreover, COVID-19 poses significant challenges to healthcare systems worldwide. The prediction and early warning of infectious diseases on a global scale are the premise and basis for countries to jointly fight epidemics. However, because of the complexity of epidemics, predicting infectious diseases on a global scale faces significant challenges. In this study, we developed the second version of Global Prediction System for Epidemiological Pandemic (GPEP-2), which combines statistical methods with a modified epidemiological model. The GPEP-2 introduces various parameterization schemes for both impacts of natural factors (seasonal variations in weather and environmental impacts) and human social behaviors (government control and isolation, personnel gathered, indoor propagation, virus mutation, and vaccination). The GPEP-2 successfully predicted the COVID-19 pandemic in over 180 countries with an average accuracy rate of 82.7%. It also provided prediction and decision-making bases for several regional-scale COVID-19 pandemic outbreaks in China, with an average accuracy rate of 89.3%. Results showed that both anthropogenic and natural factors can affect virus spread and control measures in the early stages of an epidemic can effectively control the spread. The predicted results could serve as a reference for public health planning and policymaking.

An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere.

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Exploring the multifaceted role of adenosine nucleotide translocase 2 in cellular and disease processes: A comprehensive review.

Adenosine nucleotide translocases (ANTs) are a family of proteins abundant in the inner mitochondrial membrane, primarily responsible for shuttling ADP and ATP across the mitochondrial membrane. Additionally, ANTs are key players in balancing mitochondrial energy metabolism and regulating cell death. ANT2 isoform, highly expressed in undifferentiated and proliferating cells, is implicated in the development and drug resistance of various tumors. We conduct a detailed analysis of the potential mechanisms by which ANT2 may influence tumorigenesis and drug resistance. Notably, the significance of ANT2 extends beyond oncology, with roles in non-tumor cell processes including blood cell development, gastrointestinal motility, airway hydration, nonalcoholic fatty liver disease, obesity, chronic kidney disease, and myocardial development, making it a promising therapeutic target for multiple pathologies. To better understand the molecular mechanisms of ANT2, this review summarizes the structural properties, expression patterns, and basic functions of the ANT2 protein. In particular, we review and analyze the controversy surrounding ANT2, focusing on its role in transporting ADP/ATP across the inner mitochondrial membrane, its involvement in the composition of the mitochondrial permeability transition pore, and its participation in apoptosis.

Integration of large and diverse angiosperm DNA fragments into Asian Gnetum mitogenomes.

BACKGROUND: Horizontal gene transfer (HGT) events have rarely been reported in gymnosperms. Gnetum is a gymnosperm genus comprising 25‒35 species sympatric with angiosperms in West African, South American, and Southeast Asian rainforests. Only a single acquisition of an angiosperm mitochondrial intron has been documented to date in Asian Gnetum mitogenomes. We wanted to develop a more comprehensive understanding of frequency and fragment length distribution of such events as well as their evolutionary history in this genus. RESULTS: We sequenced and assembled mitogenomes from five Asian Gnetum species. These genomes vary remarkably in size and foreign DNA content. We identified 15 mitochondrion-derived and five plastid-derived (MTPT) foreign genes. Our phylogenetic analyses strongly indicate that these foreign genes were transferred from diverse eudicots-mostly from the Rubiaceae genus Coptosapelta and ten genera of Malpighiales. This indicates that Asian Gnetum has experienced multiple independent HGT events. Patterns of sequence evolution strongly suggest DNA-mediated transfer between mitochondria as the primary mechanism giving rise to these HGT events. Most Asian Gnetum species are lianas and often entwined with sympatric angiosperms. We therefore propose that close apposition of Gnetum and angiosperm stems presents opportunities for interspecific cell-to-cell contact through friction and wounding, leading to HGT. CONCLUSIONS: Our study reveals that multiple HGT events have resulted in massive amounts of angiosperm mitochondrial DNA integrated into Asian Gnetum mitogenomes. Gnetum and its neighboring angiosperms are often entwined with each other, possibly accounting for frequent HGT between these two phylogenetically remote lineages.

Development of a predictive model for 1-year postoperative recovery in patients with lumbar disk herniation based on deep learning and machine learning.

Background: The aim of this study is to develop a predictive model utilizing deep learning and machine learning techniques that will inform clinical decision-making by predicting the 1-year postoperative recovery of patients with lumbar disk herniation. Methods: The clinical data of 470 inpatients who underwent tubular microdiscectomy (TMD) between January 2018 and January 2021 were retrospectively analyzed as variables. The dataset was randomly divided into a training set (n = 329) and a test set (n = 141) using a 10-fold cross-validation technique. Various deep learning and machine learning algorithms including Random Forests, Extreme Gradient Boosting, Support Vector Machines, Extra Trees, K-Nearest Neighbors, Logistic Regression, Light Gradient Boosting Machine, and MLP (Artificial Neural Networks) were employed to develop predictive models for the recovery of patients with lumbar disk herniation 1 year after surgery. The cure rate score of lumbar JOA score 1 year after TMD was used as an outcome indicator. The primary evaluation metric was the area under the receiver operating characteristic curve (AUC), with additional measures including decision curve analysis (DCA), accuracy, sensitivity, specificity, and others. Results: The heat map of the correlation matrix revealed low inter-feature correlation. The predictive model employing both machine learning and deep learning algorithms was constructed using 15 variables after feature engineering. Among the eight algorithms utilized, the MLP algorithm demonstrated the best performance. Conclusion: Our study findings demonstrate that the MLP algorithm provides superior predictive performance for the recovery of patients with lumbar disk herniation 1 year after surgery.

Structural Modulation of Covalent Organic Frameworks for Efficient Hydrogen Peroxide Electrocatalysis.

The electrochemical production of hydrogen peroxide (H2O2) using metal-free catalysts has emerged as a viable and sustainable alternative to the conventional anthraquinone process. However, the precise architectural design of these electrocatalysts poses a significant challenge, requiring intricate structural engineering to optimize electron transfer during the oxygen reduction reaction (ORR). Herein, we introduce a novel design of covalent organic frameworks (COFs) that effectively shift the ORR from a four-electron to a more advantageous two-electron pathway. Notably, the JUC-660 COF, with strategically charge-modified benzyl moieties, achieved a continuous high H2O2 yield of over 1200 mmol g-1 h-1 for an impressive duration of over 85 hours in a flow cell setting, marking it as one of the most efficient metal-free and non-pyrolyzed H2O2 electrocatalysts reported to date. Theoretical computations alongside in-situ infrared spectroscopy indicate that JUC-660 markedly diminishes the adsorption of the OOH* intermediate, thereby steering the ORR towards the desired pathway. Furthermore, the versatility of JUC-660 was demonstrated through its application in the electro-Fenton reaction, where it efficiently and rapidly removed aqueous contaminants. This work delineates a pioneering approach to altering the ORR pathway, ultimately paving the way for the development of highly effective metal-free H2O2 electrocatalysts.

An Ion-Mediated Spiking Chemical Neuron based on Mott Memristor.

Artificial spiking neurons capable of interpreting ionic information into electrical spikes are critical to mimic biological signaling systems. Mott memristors are attractive for constructing artificial spiking neurons due to their simple structure, low energy consumption, and rich neural dynamics. However, challenges remain in achieving ion-mediated spiking and biohybrid-interfacing in Mott neurons. Here, a biomimetic spiking chemical neuron (SCN) utilizing an NbOx Mott memristor and oxide field-effect transistor-type chemical sensor is introduced. The SCN exhibits both excitation and inhibition spiking behaviors toward ionic concentrations akin to biological neural systems. It demonstrates spiking responses across physiological and pathological Na+ concentrations (1-200 × 10-3 m). The Na+-mediated SCN enables both frequency encoding and time-to-first-spike coding schemes, illustrating the rich neural dynamics of Mott neuron. In addition, the SCN interfaced with L929 cells facilitates real-time modulation of ion-mediated spiking under both normal and salty cellular microenvironments.

A Customized Augmented Lagrangian Method for Block-Structured Integer Programming.

Integer programming with block structures has received considerable attention recently and is widely used in many practical applications such as train timetabling and vehicle routing problems. It is known to be NP-hard due to the presence of integer variables. We define a novel augmented Lagrangian function by directly penalizing the inequality constraints and establish the strong duality between the primal problem and the augmented Lagrangian dual problem. Then, a customized augmented Lagrangian method is proposed to address the block-structures. In particular, the minimization of the augmented Lagrangian function is decomposed into multiple subproblems by decoupling the linking constraints and these subproblems can be efficiently solved using the block coordinate descent method. We also establish the convergence property of the proposed method. To make the algorithm more practical, we further introduce several refinement techniques to identify high-quality feasible solutions. Numerical experiments on a few interesting scenarios show that our proposed algorithm often achieves a satisfactory solution and is quite effective.

2'-O-methylation at internal sites on mRNA promotes mRNA stability.

2'-O-methylation (Nm) is a prominent RNA modification well known in noncoding RNAs and more recently also found at many mRNA internal sites. However, their function and base-resolution stoichiometry remain underexplored. Here, we investigate the transcriptome-wide effect of internal site Nm on mRNA stability. Combining nanopore sequencing with our developed machine learning method, NanoNm, we identify thousands of Nm sites on mRNAs with a single-base resolution. We observe a positive effect of FBL-mediated Nm modification on mRNA stability and expression level. Elevated FBL expression in cancer cells is associated with increased expression levels for 2'-O-methylated mRNAs of cancer pathways, implying the role of FBL in post-transcriptional regulation. Lastly, we find that FBL-mediated 2'-O-methylation connects to widespread 3' UTR shortening, a mechanism that globally increases RNA stability. Collectively, we demonstrate that FBL-mediated Nm modifications at mRNA internal sites regulate gene expression by enhancing mRNA stability.

Analyzing Differences in Hematological and Immunological Characteristics Related to Common Gene Mutations in Myelodysplastic Syndromes.

BACKGROUND: Genetic mutations play a crucial role in the development and progression of myelodysplastic syndromes (MDS), impacting the immune microenvironment and influencing the choice of treatment regimen, as well as the efficacy and prognosis of patients. The objective of this study was to examine variations in hematological and immunological characteristics associated with common gene mutations in MDS patients and establish a foundation for the precise treatment of MDS. METHODS: The hematological, immunological, and other clinical features of 71 recently diagnosed MDS patients from January 1, 2019, to July 31, 2023, were retrospectively analyzed. These patients were categorized based on their gene mutations, and the variances in hematological and immunological characteristics among distinct groups were compared. RESULTS: Hematological variances were observed among different gene mutation groups. Specifically, platelet counts in the splicing factor 3B subunit 1 (SF3B1) mutation group were notably higher compared to the wild-type group (p = 0.009). Conversely, in the additional sex combs like 1 (ASXL1) mutation groups, monocyte ratios were significantly elevated in comparison to the wild-type group (p = 0.046), and in the ten-eleven translocation 2 (TET2) mutation group, lymphocyte ratios were significantly lower (p = 0.022). Additionally, the leukocyte (p = 0.005), neutrophil ratio (p = 0.002), and lymphocyte ratio (p = 0.001) were significantly higher in the Runt-related transcription factor 1 (RUNX1) mutation group. Regarding immunological distinctions, the Natural Killer (NK) cell ratio demonstrated a significant increase in the SF3B1 mutation group (p = 0.005). Moreover, the TET2 mutation group exhibited a significantly higher Interleukin-8 (IL-8) level (p = 0.017). In contrast, the U2 small nuclear RNA auxiliary factor 1 (U2AF1) group displayed significantly lower levels of IL-1ß (p = 0.033), IL-10 (p = 0.033), and Tumour Necrosis Factor-α (TNF-α) (p = 0.009). CONCLUSION: Distinct variations exist in the immune microenvironment of MDS associated with different genetic mutations. Further studies are imperative to delve into the underlying mechanisms that drive these differences.

Biodiversity of Demersal Fish Communities in the Cosmonaut Sea Revealed by DNA Barcoding Analyses.

The Cosmonaut Sea is one of the least accessed regions in the Southern Ocean, and our knowledge about the fish biodiversity in the region is sparse. In this study, we provided a description of demersal fish diversity in the Cosmonaut Sea by analysing cytochrome oxidase I (COI) barcodes of 98 fish samples that were hauled by trawling during the 37th and 38th Chinese National Antarctic Research Expedition (CHINARE) cruises. Twenty-four species representing 19 genera and 11 families, namely, Artedidraconidae, Bathydraconidae, Bathylagidae, Channichthyidae, Liparidae, Macrouridae, Muraenolepididae, Myctophidae, Nototheniidae, Paralepididae and Zoarcidae, were discriminated and identified, which were largely identical to local fish occurrence records and the general pattern of demersal fish communities at high Antarctic shelf areas. The validity of a barcoding gap failed to be detected and confirmed across all species due to the indicative signals of two potential cryptic species. Nevertheless, DNA barcoding still demonstrated to be a very efficient and sound method for the discrimination and classification of Antarctic fishes. In the future, various sampling strategies that cover all geographic sections and depth strata of the Cosmonaut Sea are encouraged to enhance our understanding of local fish communities, within which DNA barcoding can play an important role in either molecular taxonomy or the establishment of a dedicated local reference database for eDNA metabarcoding analyses.

Mechanical models and measurement methods of solid stress in tumors.

In addition to genetic mutations, biomechanical factors also affect the structures and functions of the tumors during tumor growth, including solid stress, interstitial fluid pressure, stiffness, and microarchitecture. Solid stress affects tumors by compressing cancer and stromal cells and deforming blood and lymphatic vessels which reduce supply of oxygen, nutrients and drug delivery, making resistant to treatment. Researchers simulate the stress by creating mechanical models both in vitro and in vivo. Cell models in vitro are divided into two dimensions (2D) and three dimensions (3D). 2D models are simple to operate but exert pressure on apical surface of the cells. 3D models, the multicellular tumor spheres, are more consistent with the actual pathological state in human body. However, the models are more difficult to establish compared with the 2D models. Besides, the procedure of the animal models in vivo is even more complex and tougher to operate. Then, researchers challenged to quantify the solid stress through some measurement methods. We compared the advantages and limitations of these models and methods, which may help to explore new therapeutic targets for normalizing the tumor's physical microenvironment. KEY POINTS: •This is the first review to conclude the mechanical models and measurement methods in tumors. •The merit and demerit of these models and methods are compared. •Insights into further models are discussed.

Regulating the crystal orientation of vapor-transport-deposited GeSe thin films by a post-annealing treatment.

Recently, GeSe has emerged as a highly promising photovoltaic absorber material due to its excellent optoelectronic properties, nontoxicity, and high stability. Although many advantages make GeSe well suited for thin-film solar cells, the power conversion efficiency of the GeSe thin-film solar cell is still much below the theoretical maximum efficiency. One of the challenges lies in controlling the crystal orientation of GeSe to enhance solar cell performance. The two-step preparation of GeSe thin films has not yet been reported to grow along the [111] orientation. In this work, we study the effect of a post-annealing treatment on the GeSe thin films and the performance of the solar cells. It was found that amorphous GeSe films can be converted into polycrystalline films with different orientations by changing the post-annealing temperature. [111]-oriented and [100]-oriented GeSe thin films were successfully prepared on the same substrate by optimizing the annealing conditions. With the structure of Au/GeSe/CdS/ITO cell devices, PCEs of 0.14% and 0.16% were ultimately achieved.

Spatially synchronous fringe detection: a method to facilitate the alignment of an echelle grating mosaic by separating the compensative angular errors.

Alignment of mosaic gratings is traditionally supported by two interferometric verifications: on the zero order to verify the grating surfaces and on the blaze to verify the groove direction. In the case of low frequency echelle grating an interferometric measurement on the zero order is hardly feasible due to extremely low contrast of the fringes. The complete alignment has then to be carried out on high order (close to the blaze) where the two misalignment errors (the tip and rotation) show the same effect on the interferogram. The acquisition of a low and a high diffraction order image simultaneously, referred to as the spatially synchronous fringe detection method (SSFD), is used to analyze the misalignment. Iterative adjustment with the autocollimation configuration at the low and high order is used to separate the compensative errors of Δ Î¸ x and Δ Î¸ z. A prototype mosaic with two 110m m×220m m segments has been aligned with the support of this method. A numerical simulation of the alignment procedure as well as the error orientation analysis of this mosaic grating are presented. The mosaic grating with an accuracy of Δ Î¸ x<0.64µr a d, Δ Î¸ y<1.13µr a d, Δ Î¸ z<0.65µr a d and a wavefront RMS error of 0.149λ has been completed. This method can greatly facilitate the alignment of an echelle mosaic for an astronomical spectrograph.