Coupling of N7-methyltransferase and 3'-5' exoribonuclease with SARS-CoV-2 polymerase reveals mechanisms for capping and proofreading.

The capping of mRNA and the proofreading play essential roles in SARS-CoV-2 replication and transcription. Here, we present the cryo-EM structure of the SARS-CoV-2 replication-transcription complex (RTC) in a form identified as Cap(0)-RTC, which couples a co-transcriptional capping complex (CCC) composed of nsp12 NiRAN, nsp9, the bifunctional nsp14 possessing an N-terminal exoribonuclease (ExoN) and a C-terminal N7-methyltransferase (N7-MTase), and nsp10 as a cofactor of nsp14. Nsp9 and nsp12 NiRAN recruit nsp10/nsp14 into the Cap(0)-RTC, forming the N7-CCC to yield cap(0) (7MeGpppA) at 5' end of pre-mRNA. A dimeric form of Cap(0)-RTC observed by cryo-EM suggests an in trans backtracking mechanism for nsp14 ExoN to facilitate proofreading of the RNA in concert with polymerase nsp12. These results not only provide a structural basis for understanding co-transcriptional modification of SARS-CoV-2 mRNA but also shed light on how replication fidelity in SARS-CoV-2 is maintained.

Moderate UV Exposure Enhances Learning and Memory by Promoting a Novel Glutamate Biosynthetic Pathway in the Brain.

Sunlight exposure is known to affect mood, learning, and cognition. However, the molecular and cellular mechanisms remain elusive. Here, we show that moderate UV exposure elevated blood urocanic acid (UCA), which then crossed the blood-brain barrier. Single-cell mass spectrometry and isotopic labeling revealed a novel intra-neuronal metabolic pathway converting UCA to glutamate (GLU) after UV exposure. This UV-triggered GLU synthesis promoted its packaging into synaptic vesicles and its release at glutamatergic terminals in the motor cortex and hippocampus. Related behaviors, like rotarod learning and object recognition memory, were enhanced after UV exposure. All UV-induced metabolic, electrophysiological, and behavioral effects could be reproduced by the intravenous injection of UCA and diminished by the application of inhibitor or short hairpin RNA (shRNA) against urocanase, an enzyme critical for the conversion of UCA to GLU. These findings reveal a new GLU biosynthetic pathway, which could contribute to some of the sunlight-induced neurobehavioral changes.

Observing heroic behavior and its influencing factors in immersive virtual environments.

Studying heroism in controlled settings presents challenges and ethical controversies due to its association with physical risk. Leveraging virtual reality (VR) technology, we conducted a three-study series with 397 participants from China to investigate heroic actions. Participants unexpectedly witnessed a criminal event in a simulated scenario, allowing observation of their tendency to physically intercept a thief. We examined situational factors (voluntariness, authority, and risk) and personal variables [gender, impulsivity, empathy, and social value orientation (SVO)] that may influence heroism. Also, the potential association between heroism and social conformity was explored. In terms of situational variables, voluntariness modulated participants' tendency to intercept the escaping thief, while perceived risk demonstrated its impact by interacting with gender. That is, in study 3 where the perceived risk was expected to be higher (as supported by an online study 5), males exhibited a greater inclination toward heroic behavior compared to females. Regarding other personal variables, the tendency to engage in heroic behavior decreased as empathy levels rose among males, whereas the opposite trend was observed for females. SVO influenced heroic behavior but without a gender interaction. Finally, an inverse relationship between heroism and social conformity was observed. The robustness of these findings was partly supported by the Chinese sample (but not the international sample) of an online study 4 that provided written descriptions of VR scenarios, indicating cultural variations. These results advance insights into motivational factors influencing heroism in the context of restoring order and highlight the power of VR technology in examining social psychological hypotheses beyond ethical constraints.

Structural basis of the recognition of adeno-associated virus by the neurological system-related receptor carbonic anhydrase IV.

Carbonic anhydrase IV (Car4) is a newly identified receptor that allows adeno-associated virus (AAV) 9P31 to cross the blood-brain barrier and achieve efficient infection in the central nervous system (CNS) in mouse models. However, the molecular mechanism by which engineered AAV capsids with 7-mer insertion in the variable region (VR) VIII recognize these novel cellular receptors is unknown. Here we report the cryo-EM structures of AAV9P31 and its complex with Mus musculus Car4 at atomic resolution by utilizing the block-based reconstruction (BBR) method. The structures demonstrated that Car4 binds to the protrusions at 3-fold axes of the capsid. The inserted 7-mer extends into a hydrophobic region near the catalytic center of Car4 to form stable interactions. Mutagenesis studies also identified the key residues in Car4 responsible for the AAV9P31 interaction. These findings provide new insights into the novel receptor recognition mechanism of AAV generated by directed evolution and highlight the application of the BBR method to studying the virus-receptor molecular mechanism.

Tectonic and orbital forcing of the South Asian monsoon in central Tibet during the late Oligocene.

The modern pattern of the Asian monsoon is thought to have formed around the Oligocene/Miocene transition and is generally attributed to Himalaya-Tibetan Plateau (H-TP) uplift. However, the timing of the ancient Asian monsoon over the TP and its response to astronomical forcing and TP uplift remains poorly known because of the paucity of well-dated high-resolution geological records from the TP interior. Here, we present a precession-scale cyclostratigraphic sedimentary section of 27.32 to 23.24 million years ago (Ma) during the late Oligocene epoch from the Nima Basin to show that the South Asian monsoon (SAM) had already advanced to the central TP (32°N) at least by 27.3 Ma, which is indicated by cyclic arid-humid fluctuations based on environmental magnetism proxies. A shift of lithology and astronomically orbital periods and amplified amplitude of proxy measurements as well as a hydroclimate transition around 25.8 Ma suggest that the SAM intensified at ~25.8 Ma and that the TP reached a paleoelevation threshold for enhancing the coupling between the uplifted plateau and the SAM. Orbital short eccentricity-paced precipitation variability is argued to be mainly driven by orbital eccentricity-modulated low-latitude summer insolation rather than glacial-interglacial Antarctic ice sheet fluctuations. The monsoon data from the TP interior provide key evidence to link the greatly enhanced tropical SAM at 25.8 Ma with TP uplift rather than global climate change and suggest that SAM's northward expansion to the boreal subtropics was dominated by a combination of tectonic and astronomical forcing at multiple timescales in the late Oligocene epoch.

NicE-C efficiently reveals open chromatin-associated chromosome interactions at high resolution.

Enhancer-promoter communication is known to regulate spatiotemporal dynamics of gene expression. Several methods are available to capture enhancer-promoter interactions, but they either require large amounts of starting materials and are costly, or provide a relative low resolution in chromatin contact maps. Here, we present nicking enzyme-assisted open chromatin interaction capture (NicE-C), a method that leverages nicking enzyme-mediated open chromatin profiling and chromosome conformation capture to enable robust and cost-effective detection of open chromatin interactions at high resolution, especially enhancer-promoter interactions. Using TNF stimulation and mouse kidney aging as models, we applied NicE-C to reveal characteristics of dynamic enhancer-promoter interactions.

HTCL-DDI: a hierarchical triple-view contrastive learning framework for drug-drug interaction prediction.

Drug-drug interaction (DDI) prediction can discover potential risks of drug combinations in advance by detecting drug pairs that are likely to interact with each other, sparking an increasing demand for computational methods of DDI prediction. However, existing computational DDI methods mostly rely on the single-view paradigm, failing to handle the complex features and intricate patterns of DDIs due to the limited expressiveness of the single view. To this end, we propose a Hierarchical Triple-view Contrastive Learning framework for Drug-Drug Interaction prediction (HTCL-DDI), leveraging the molecular, structural and semantic views to model the complicated information involved in DDI prediction. To aggregate the intra-molecular compositional and structural information, we present a dual attention-aware network in the molecular view. Based on the molecular view, to further capture inter-molecular information, we utilize the one-hop neighboring information and high-order semantic relations in the structural view and semantic view, respectively. Then, we introduce contrastive learning to enhance drug representation learning from multifaceted aspects and improve the robustness of HTCL-DDI. Finally, we conduct extensive experiments on three real-world datasets. All the experimental results show the significant improvement of HTCL-DDI over the state-of-the-art methods, which also demonstrates that HTCL-DDI opens new avenues for ensuring medication safety and identifying synergistic drug combinations.

MHTAN-DTI: Metapath-based hierarchical transformer and attention network for drug-target interaction prediction.

Drug-target interaction (DTI) prediction can identify novel ligands for specific protein targets, and facilitate the rapid screening of effective new drug candidates to speed up the drug discovery process. However, the current methods are not sensitive enough to complex topological structures, and complicated relations between multiple node types are not fully captured yet. To address the above challenges, we construct a metapath-based heterogeneous bioinformatics network, and then propose a DTI prediction method with metapath-based hierarchical transformer and attention network for drug-target interaction prediction (MHTAN-DTI), applying metapath instance-level transformer, single-semantic attention and multi-semantic attention to generate low-dimensional vector representations of drugs and proteins. Metapath instance-level transformer performs internal aggregation on the metapath instances, and models global context information to capture long-range dependencies. Single-semantic attention learns the semantics of a certain metapath type, introduces the central node weight and assigns different weights to different metapath instances to obtain the semantic-specific node embedding. Multi-semantic attention captures the importance of different metapath types and performs weighted fusion to attain the final node embedding. The hierarchical transformer and attention network weakens the influence of noise data on the DTI prediction results, and enhances the robustness and generalization ability of MHTAN-DTI. Compared with the state-of-the-art DTI prediction methods, MHTAN-DTI achieves significant performance improvements. In addition, we also conduct sufficient ablation studies and visualize the experimental results. All the results demonstrate that MHTAN-DTI can offer a powerful and interpretable tool for integrating heterogeneous information to predict DTIs and provide new insights into drug discovery.

Rice kinase OsMRLK63 contributes to drought tolerance by regulating reactive oxygen species production.

Drought is a major adverse environmental factor that plants face in nature but the molecular mechanism by which plants transduce stress signals and further endow themselves with tolerance remains unclear. Malectin/malectin-like domains containing receptor-like kinases (MRLKs) have been proposed to act as receptors in multiple biological signaling pathways, but limited studies show their roles in drought-stress signaling and tolerance. In this study, we demonstrate OsMRLK63 in rice (Oryza sativa L.) functions in drought tolerance by acting as the receptor of 2 rapid alkalization factors, OsRALF45 and OsRALF46. We show OsMRLK63 is a typical receptor-like kinase that positively regulates drought tolerance and reactive oxygen species (ROS) production. OsMRLK63 interacts with and phosphorylates several nicotinamide adenine dinucleotide phosphate (NADPH) oxidases with the primarily phosphorylated site at Ser26 in the N-terminal of RESPIRATORY BURST OXIDASE HOMOLOGUE A (OsRbohA). The application of the 2 small signal peptides (OsRALF45/46) on rice can greatly alleviate the dehydration of plants induced by mimic drought. This function depends on the existence of OsMRLK63 and the NADPH oxidase-dependent ROS production. The 2 RALFs interact with OsMRLK63 by binding to its extracellular domain, suggesting they may act as drought/dehydration signal sensors for the OsMRLK63-mediated process. Our study reveals a OsRALF45/46-OsMRLK63-OsRbohs module which contributes to drought-stress signaling and tolerance in rice.

Neuroplasticity of visual brain network induced by hypoxia.

The effects of hypoxia on brain function remain largely unknown. This study aimed to clarify this issue by visual-stimulated functional magnetic resonance imaging design. Twenty-three college students with a 30-d high-altitude exposure were tested before, 1 week and 3 months after returning to sea level. Brain functional magnetic resonance imaging and retinal electroretinogram were acquired. One week after returning to sea level, decreased blood oxygenation level dependent in the right lingual gyrus accompanied with increased blood oxygenation level dependent in the frontal cortex and insular cortex, and decreased amplitude of electroretinogram a-wave in right eye; moreover, the bilateral lingual gyri showed increased functional connectivity within the dorsal visual stream pathway, and the blood oxygenation level dependent signals in the right lingual gyrus showed positive correlation with right retinal electroretinogram a-wave. Three months after returning to sea level, the blood oxygenation level dependent signals recovered to normal level, while intensively increased blood oxygenation level dependent signals in a broad of brain regions and decreased retinal electroretinogram were also existed. In conclusion, hypoxic exposure has long-term effects on visual cortex, and the impaired retinal electroretinogram may contribute to it. The increased functional connectivity of dorsal stream may compensate for the decreased function of retinal photoreceptor cells to maintain normal visual function.

Microenvironment with NIR-Controlled ROS and Mechanical Tensions for Manipulating Cell Activities in Wound Healing.

The extracellular matrix (ECM) orchestrates cell behavior and tissue regeneration by modulating biochemical and mechanical signals. Manipulating cell-material interactions is crucial for leveraging biomaterials to regulate cell functions. Yet, integrating multiple cues in a single material remains a challenge. Here, near-infrared (NIR)-controlled multifunctional hydrogel platforms, named PIC/CM@NPs, are introduced to dictate fibroblast behavior during wound healing by tuning the matrix oxidative stress and mechanical tensions. PIC/CM@NPs are prepared through cell adhesion-medicated assembly of collagen-like polyisocyanide (PIC) polymers and cell-membrane-coated conjugated polymer nanoparticles (CM@NPs), which closely mimic the fibrous structure and nonlinear mechanics of ECM. Upon NIR stimulation, PIC/CM@NPs composites enhance fibroblast cell proliferation, migration, cytokine production, and myofibroblast activation, crucial for wound closure. Moreover, they exhibit effective and toxin removal antibacterial properties, reducing inflammation. This multifunctional approach accelerates healing by 95%, highlighting the importance of integrating biochemical and biophysical cues in the biomaterial design for advanced tissue regeneration.

Restricted Boltzmann Machines Implemented by Spin-Orbit Torque Magnetic Tunnel Junctions.

Artificial intelligence has surged forward with the advent of generative models, which rely heavily on stochastic computing architectures enhanced by true random number generators with adjustable sampling probabilities. In this study, we develop spin-orbit torque magnetic tunnel junctions (SOT-MTJs), investigating their sigmoid-style switching probability as a function of the driving voltage. This feature proves to be ideally suited for stochastic computing algorithms such as the restricted Boltzmann machines (RBM) prevalent in pretraining processes. We exploit SOT-MTJs as both stochastic samplers and network nodes for RBMs, enabling the implementation of RBM-based neural networks to achieve recognition tasks for both handwritten and spoken digits. Moreover, we further harness the weights derived from the preceding image and speech training processes to facilitate cross-modal learning from speech to image generation. Our results clearly demonstrate that these SOT-MTJs are promising candidates for the development of hardware accelerators tailored for Boltzmann neural networks and other stochastic computing architectures.

The Angiotensin Antagonist Losartan Modulates Social Reward Motivation and Punishment Sensitivity via Modulating Midbrain-Striato-Frontal Circuits.

Social deficits and dysregulations in dopaminergic midbrain-striato-frontal circuits represent transdiagnostic symptoms across psychiatric disorders. Animal models suggest that interactions between the dopamine (DA) and renin-angiotensin system (RAS) may modulate learning and reward-related processes. The present study therefore examined the behavioral and neural effects of the Angiotensin II type 1 receptor (AT1R) antagonist losartan on social reward and punishment processing in humans. A preregistered randomized double-blind placebo-controlled between-subject pharmacological design was combined with a social incentive delay (SID) functional MRI (fMRI) paradigm during which subjects could avoid social punishment or gain social reward. Healthy volunteers received a single-dose of losartan (50 mg, n = 43, female = 17) or placebo (n = 44, female = 20). We evaluated reaction times (RTs) and emotional ratings as behavioral and activation and functional connectivity as neural outcomes. Relative to placebo, losartan modulated the reaction time and arousal differences between social punishment and social reward. On the neural level the losartan-enhanced motivational salience of social rewards was accompanied by stronger ventral striatum-prefrontal connectivity during reward anticipation. Losartan increased the reward-neutral difference in the ventral tegmental area (VTA) and attenuated VTA associated connectivity with the bilateral insula in response to punishment during the outcome phase. Thus, losartan modulated approach-avoidance motivation and emotional salience during social punishment versus social reward via modulating distinct core nodes of the midbrain-striato-frontal circuits. The findings document a modulatory role of the renin-angiotensin system in these circuits and associated social processes, suggesting a promising treatment target to alleviate social dysregulations.SIGNIFICANCE STATEMENT Social deficits and anhedonia characterize several mental disorders and have been linked to the midbrain-striato-frontal circuits of the brain. Based on initial findings from animal models we here combine the pharmacological blockade of the Angiotensin II type 1 receptor (AT1R) via losartan with functional MRI (fMRI) to demonstrate that AT1R blockade enhances the motivational salience of social rewards and attenuates the negative impact of social punishment via modulating the communication in the midbrain-striato-frontal circuits in humans. The findings demonstrate for the first time an important role of the AT1R in social reward processing in humans and render the AT1R as promising novel treatment target for social and motivational deficits in mental disorders.

Proteomics Platform Reveals Broad-Spectrum Nanobodies for SARS-CoV-2 Variant Neutralization.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of different variants of concerns with immune evasion that have been prevalent over the past three years. Nanobodies, the functional variable regions of camelid heavy-chain-only antibodies, have garnered interest in developing neutralizing antibodies due to their smaller size, structural stability, ease of production, high affinity, and low immunogenicity, among other characteristics. In this work, we describe an integrated proteomics platform for the high-throughput screening of nanobodies against different SARS-CoV-2 spike variants. To demonstrate this platform, we immunized a camel with subunit 1 (S1) of the wild-type spike protein and constructed a nanobody phage library. The binding and neutralizing activities of the nanobodies against 72 spike variants were then measured, resulting in the identification of two nanobodies (C-282 and C-39) with broad neutralizing activity against six non-Omicron variants (D614G, Alpha, Beta, Gamma, Delta, Kappa) and five Omicron variants (BA.1-5). Their neutralizing capability was validated using in vitro pseudovirus-based neutralization assays. All these results demonstrate the utility of our proteomics platform to identify new nanobodies with broad neutralizing capability and to develop a treatment for patients with SARS-CoV-2 variant infection in the future.

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes.

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

Effect of ST36 electroacupuncture on the switch of skeletal muscle fibres in mice with sciatic nerve dissociation.

Skeletal muscle is striated muscle that moves autonomously and is innervated by peripheral nerves. Peripheral nerve injury is very common in clinical treatment. However, the commonly used treatment methods often focus on the regeneration of the injured nerve but overlook the pathological changes in the injured skeletal muscle. Acupuncture, as the main treatment for denervated skeletal muscle atrophy, is used extensively in clinical practice. In the present study, a mouse model of lower limb sciatic nerve detachment was constructed and treated with electroacupuncture Stomach 36 to observe the atrophy of lower limb skeletal muscle and changes in skeletal muscle fibre types before and after electroacupuncture Stomach 36 treatment. Mice with skeletal muscle denervation showed a decrease in the proportion of IIa muscle fibres and an increase in the proportion of IIb muscle fibres, after electroacupuncture Stomach 36. The changes were reversed by specific activators of p38 MAPK, which increased IIa myofibre ratio. The results suggest that electroacupuncture Stomach 36 can reverse the change of muscle fibre type from IIb to IIa after denervation of skeletal muscle by inhibiting p38 MAPK. The results provide an important theoretical basis for the treatment of clinical peripheral nerve injury diseases with electroacupuncture, in addition to novel insights that could facilitate the study of pathological changes of denervated skeletal muscle.

Perfluorinated Amines: Accelerating Lithium Electrodeposition by Tailoring Interfacial Structure and Modulated Solvation for High-Performance Batteries.

Modulating interfacial electrochemistry represents a prevalent approach for mitigating lithium dendrite growth and enhancing battery performance. Nevertheless, while most additives exhibit inhibitory characteristics, the accelerating effects on interfacial electrochemistry have garnered limited attention. In this work, perfluoromorpholine (PFM) with facilitated kinetics is utilized to preferentially adsorb on the lithium metal interface. The PFM molecules disrupt the solvation structure of Li+ and enhance the migration of Li+. Combined with the benzotrifluoride, a synergistic acceleration-inhibition system is formed. The ab initio molecular dynamics (AIMD) and density functional theory (DFT) calculation of the loose outer solvation clusters and the key adsorption-deposition step supports the fast diffusion and stable interface electrochemistry with an accelerated filling mode with C─F and C─H groups. The approach induces the uniform lithium deposition. Excellent cycling performance is achieved in Li||Li symmetric cells, and even after 200 cycles in Li||NCM811 full cells, 80% of the capacity is retained. This work elucidates the accelerated electrochemical processes at the interface and expands the design strategies of acceleration fluorinated additives for lithium metal batteries.

LSMMD-MA: scaling multimodal data integration for single-cell genomics data analysis.

MOTIVATION: Modality matching in single-cell omics data analysis-i.e. matching cells across datasets collected using different types of genomic assays-has become an important problem, because unifying perspectives across different technologies holds the promise of yielding biological and clinical discoveries. However, single-cell dataset sizes can now reach hundreds of thousands to millions of cells, which remain out of reach for most multimodal computational methods. RESULTS: We propose LSMMD-MA, a large-scale Python implementation of the MMD-MA method for multimodal data integration. In LSMMD-MA, we reformulate the MMD-MA optimization problem using linear algebra and solve it with KeOps, a CUDA framework for symbolic matrix computation in Python. We show that LSMMD-MA scales to a million cells in each modality, two orders of magnitude greater than existing implementations. AVAILABILITY AND IMPLEMENTATION: LSMMD-MA is freely available at https://github.com/google-research/large_scale_mmdma and archived at https://doi.org/10.5281/zenodo.8076311.

Identification of seven variants in the col4a1 gene that alter RNA splicing by minigene assay.

Type IV collagen is an integral component of basement membranes. Mutations in COL4A1, one of the key genes encoding Type IV collagen, can result in a variety of diseases. It is clear that a significant proportion of mutations that affect splicing can cause disease directly or contribute to the susceptibility or severity of disease. Here, we analyzed exonic mutations and intronic mutations described in the COL4A1 gene using bioinformatics programs and identified candidate mutations that may alter the normal splicing pattern through a minigene system. We identified seven variants that induce splicing alterations by disrupting normal splice sites, creating new ones, or altering splice regulatory elements. These mutations are predicted to impact protein function. Our results help in the correct molecular characterization of variants in COL4A1 and may help develop more personalized treatment options.

Design and analysis of unequal aperture off-axis optical integrator for solar simulators.

The unequal aperture off-axis optical integrator design method is proposed to improve the irradiation uniformity of solar simulators and solve the problem of limited uniformity of optical integrator due to aberrations and uneven distribution of incident radiation. Firstly, the unequal aperture off-axis optical integrator structure is designed based on the scalar diffraction theory to analyze the factors affecting the optical homogenization ability of the optical integrator. Then, the relationship between sub-eye lens aperture and arrangement is explored in combination with Lagrange invariance principle and semi-definite programming theory. Finally, the optimum off-axis amount of sub-eye lens with different ring band is determined from the perspective of geometric optics by using the aberration theory and following the principle of edge light, so as to improve the evenness of optical integrator. The design results are verified by the simulation analysis. The simulation results show that: In the picture plane of optical integrator, the irradiation non-uniformity in the ф 26 mm irradiation plane is 14.87%, which is better than 26.02% in the traditional optical integrator. At the same time, at the effective irradiated surface, the irradiation non-uniformity of 0.53% within the ф 300 mm reaches the irradiation standard of the class A + solar simulator, and the irradiance only decreases by 16.5% compared with the traditional optical integrator, which still meets the index requirement of a solar constant. The goal of improving the evenness of optical integrator is realized without greatly affecting irradiance and without introducing aspherical design.