High-quality lateral monolayer-multilayer graphene junction formed by selective laser thinning for self-powered photodetection.

The formation of an asymmetric junction is key to graphene-based photodetectors of high-sensitive photodetectability, because such a junction can not only facilitate the diffusion or drift of photogenerated carriers but also realize a self-powered operation. Here, a monolayer-multilayer graphene junction photodetector is accomplished by selectively thinning part of a multilayer graphene to a high-quality monolayer. Benefiting from the large photoabsorption cross section of multilayer graphene and strong asymmetry caused by the significant differences in optoelectronic properties between monolayer and multilayer graphene, the monolayer-multilayer graphene junction shows a 7-fold increase in short-circuit photocurrent as compared with that at the monolayer graphene-metal contact in scanning photocurrent images. The asymmetric configuration also enables the photodetector to work at zero bias with minimized dark current noise and stand-by power consumption. Under global illumination with visible light, a photoswitching ratio of 3.4 × 103, a responsivity of 8.8 mA W-1, a specific detectivity of 1.3 × 108Jones and a response time of 11 ns can be obtained, suggesting a promising photoresponse. Moreover, it is worth mentioning that such a performance enhancement is achieved without compromising the broadband spectral response of graphene photodetector and it is hence applicable for long wavelength spectral range including infrared and terahertz.

Dysregulated serum lipid profile is associated with inflammation and disease activity in primary Sjögren's syndrome: a retrospective study in China.

PURPOSE: To investigate the relationship between the lipid profiles of patients with primary Sjögren's syndrome (pSS) and other clinical characteristics, laboratory examination, disease activity, and inflammatory factors. In addition, the risk factors for hyperlipidemia-related complications of pSS and the effect of hydroxychloroquine (HCQ) usage on the lipid profile were incorporated into this study. METHODS: This is a single-center, retrospective study that included 367 patients who were diagnosed with pSS at Tongji Hospital, School of Medicine, Tongji University, China from January 2010 to March 2022. Initially, demographic information, clinical characteristics, medication records, and complications of the patients were gathered. A case-control analysis compared the 12 systems involvement (ESSDAI domain), clinical symptoms, and laboratory tests between pSS patients with and without dyslipidemia. A simple linear regression model was employed to investigate the relationship between serum lipid profile and inflammatory factors. Logistics regression analysis was performed to assess variables for hyperlipidemia-related complications of pSS. The paired t-test was then used to evaluate the improvement in lipid profile among pSS patients. RESULTS: 48.7 % of all pSS patients had dyslipidemia, and alterations in lipid levels were related to gender, age, and smoking status but not body mass index (BMI). Dyslipidemia is more prevalent in pSS patients who exhibit heightened autoimmunity and elevated levels of inflammation. Higher concentrations of multiple highly inflammatory factors correlate with a more severe form of dyslipidemia. Non-traditional cardiovascular risk factors may contribute to hyperlipidemia-related complications of pSS, such as increased, low complement 3 (C3) and low C4. According to our study, HCQ usage may protect against lipid-related disease in pSS. CONCLUSION: Attention should be paid to the dyslipidemia of pSS. This research aims to clarify the population portrait of pSS patients with abnormal lipid profiles and provides insights into the correlation between metabolism and inflammation in individuals with pSS and the potential role they play in the advancement of the disease. These findings provide novel avenues for further understanding the underlying mechanisms of pSS pathogenesis.

Downregulation of WNK4 expression facilitates the proliferation of gastric cancer cells via activation of the STAT3 signaling pathway.

WNK lysine deficient protein kinase 4 (WNK4) has been shown to be significantly associated with cancer progression. Nevertheless, its involvement in gastric cancer (GC) is unclear. The objective of this work was to investigate the WNK4's regulatory mechanism in GC. Quantitative RT-PCR and immunoblots revealed that WNK4 expression was downregulated in GC and that low expression of WNK4 was strongly linked to poor prognosis. Functional assays including cell counting kit-8 assay and colony formation assay demonstrated that overexpression of WNK4 led to limited tumor proliferation both in vitro and in vivo, while the WNK4 reduction yielded to the opposite results. Gene Set Enrichment Analysis (GSEA) indicated a potential association between WNK4 and the signal transducer and activator of transcription (STAT3). WNK4 suppressed the phosphorylation of signal transducer and activator of transcription 3 (p-STAT3) in GC cells. The inhibition of the STAT3 pathway with Stattic reversed growth and proliferation induced by WNK4 knockdown in GC cells. These findings provide new insights for identifying key therapeutic targets for GC in the future.

Research Progress of Heavy-Metal-Free Quantum Dot Light-Emitting Diodes.

At present, heavy-metal-free quantum dot light-emitting diodes (QLEDs) have shown great potential as a research hotspot in the field of optoelectronic devices. This article reviews the research on heavy-metal-free quantum dot (QD) materials and light-emitting diode (LED) devices. In the first section, we discussed the hazards of heavy-metal-containing quantum dots (QDs), such as environmental pollution and human health risks. Next, the main representatives of heavy-metal-free QDs were introduced, such as InP, ZnE (E=S, Se and Te), CuInS2, Ag2S, and so on. In the next section, we discussed the synthesis methods of heavy-metal-free QDs, including the hot injection (HI) method, the heat up (HU) method, the cation exchange (CE) method, the successful ionic layer adsorption and reaction (SILAR) method, and so on. Finally, important progress in the development of heavy-metal-free QLEDs was summarized in three aspects (QD emitter layer, hole transport layer, and electron transport layer).

Hybrid Hydrogen Bonding Strategy to Construct Instantaneous Self-Healing Highly Elastic Ionohydrogel for Multi-Functional Electronics.

Gels show great promise for applications in wearable electronics, biomedical devices, and energy storage systems due to their exceptional stretchability and adjustable electrical conductivity. However, the challenge lies in integrating multiple functions like elasticity, instantaneous self-healing, and a wide operating temperature range into a single gel. To address this issue, a hybrid hydrogen bonding strategy to construct gel with these desirable properties is proposed. The intricate network of hybrid strong weak hydrogen bonds within the polymer matrix enables these ionohydrogel to exhibit remarkable instantaneous self-healing, stretching up to five times their original length within seconds. Leveraging these properties, the incorporation of ionic liquids, water, and zinc salts into hybrid hydrogen bond crosslinked network enables conductivity and redox reaction, making it a versatile ionic skin for real-time monitoring of human movements and respiratory. Moreover, the ionohydrogel can be used as electrolyte in the assembly of a zinc-ion battery, ensuring a reliable power supply for wearable electronics, even in extreme conditions (-20 °C and extreme deformations). This ionohydrogel electrolyte simplifies the diverse structural requirements of gels to meet the needs of various electronic applications, offering a new approach for multi-functional electronics.

Functional significance of DNA methylation: epigenetic insights into Sjögren's syndrome.

Sjögren's syndrome (SjS) is a systemic, highly diverse, and chronic autoimmune disease with a significant global prevalence. It is a complex condition that requires careful management and monitoring. Recent research indicates that epigenetic mechanisms contribute to the pathophysiology of SjS by modulating gene expression and genome stability. DNA methylation, a form of epigenetic modification, is the fundamental mechanism that modifies the expression of various genes by modifying the transcriptional availability of regulatory regions within the genome. In general, adding a methyl group to DNA is linked with the inhibition of genes because it changes the chromatin structure. DNA methylation changes the fate of multiple immune cells, such as it leads to the transition of naïve lymphocytes to effector lymphocytes. A lack of central epigenetic enzymes frequently results in abnormal immune activation. Alterations in epigenetic modifications within immune cells or salivary gland epithelial cells are frequently detected during the pathogenesis of SjS, representing a robust association with autoimmune responses. The analysis of genome methylation is a beneficial tool for establishing connections between epigenetic changes within different cell types and their association with SjS. In various studies related to SjS, most differentially methylated regions are in the human leukocyte antigen (HLA) locus. Notably, the demethylation of various sites in the genome is often observed in SjS patients. The most strongly linked differentially methylated regions in SjS patients are found within genes regulated by type I interferon. This demethylation process is partly related to B-cell infiltration and disease progression. In addition, DNA demethylation of the runt-related transcription factor (RUNX1) gene, lymphotoxin-α (LTA), and myxovirus resistance protein A (MxA) is associated with SjS. It may assist the early diagnosis of SjS by serving as a potential biomarker. Therefore, this review offers a detailed insight into the function of DNA methylation in SjS and helps researchers to identify potential biomarkers in diagnosis, prognosis, and therapeutic targets.

A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy.

Immunotherapy has revolutionized cancer treatment, but inconsistent responses persist. Our study delves into the intriguing phenomenon of enhanced immunotherapy sensitivity in older individuals with cancers. Through a meta-analysis encompassing 25 small-to-mid-sized trials of immune checkpoint blockade (ICB), we demonstrate that older individuals exhibit heightened responsiveness to ICB therapy. To understand the underlying mechanism, we reanalyze single-cell RNA sequencing (scRNA-seq) data from multiple studies and unveil distinct upregulation of exhausted and cytotoxic T cell markers within the tumor microenvironment (TME) of older patients. Recognizing the potential role of gut microbiota in modulating the efficacy of immunotherapy, we identify an aging-enriched enterotype linked to improved immunotherapy outcomes in older patients. Fecal microbiota transplantation experiments in mice confirm the therapeutic potential of the aging-enriched enterotype, enhancing treatment sensitivity and reshaping the TME. Our discoveries confront the prevailing paradox and provide encouraging paths for tailoring cancer immunotherapy strategies according to an individual's gut microbiome profile.

Physiology and pharmacological targeting of phase separation.

Liquid-liquid phase separation (LLPS) in biology describes a process by which proteins form membraneless condensates within a cellular compartment when conditions are met, including the concentration and posttranslational modifications of the protein components, the condition of the aqueous solution (pH, ionic strength, pressure, and temperature), and the existence of assisting factors (such as RNAs or other proteins). In these supramolecular liquid droplet-like inclusion bodies, molecules are held together through weak intermolecular and/or intramolecular interactions. With the aid of LLPS, cells can assemble functional sub-units within a given cellular compartment by enriching or excluding specific factors, modulating cellular function, and rapidly responding to environmental or physiological cues. Hence, LLPS is emerging as an important means to regulate biology and physiology. Yet, excessive inclusion body formation by, for instance, higher-than-normal concentrations or mutant forms of the protein components could result in the conversion from dynamic liquid condensates into more rigid gel- or solid-like aggregates, leading to the disruption of the organelle's function followed by the development of human disorders like neurodegenerative diseases. In summary, well-controlled formation and de-formation of LLPS is critical for normal biology and physiology from single cells to individual organisms, whereas abnormal LLPS is involved in the pathophysiology of human diseases. In turn, targeting these aggregates or their formation represents a promising approach in treating diseases driven by abnormal LLPS including those neurodegenerative diseases that lack effective therapies.

Gut microbiome for predicting immune checkpoint blockade-associated adverse events.

BACKGROUND: The impact of the gut microbiome on the initiation and intensity of immune-related adverse events (irAEs) prompted by immune checkpoint inhibitors (ICIs) is widely acknowledged. Nevertheless, there is inconsistency in the gut microbial associations with irAEs reported across various studies. METHODS: We performed a comprehensive analysis leveraging a dataset that included published microbiome data (n = 317) and in-house generated data from 16S rRNA and shotgun metagenome samples of irAEs (n = 115). We utilized a machine learning-based approach, specifically the Random Forest (RF) algorithm, to construct a microbiome-based classifier capable of distinguishing between non-irAEs and irAEs. Additionally, we conducted a comprehensive analysis, integrating transcriptome and metagenome profiling, to explore potential underlying mechanisms. RESULTS: We identified specific microbial species capable of distinguishing between patients experiencing irAEs and non-irAEs. The RF classifier, developed using 14 microbial features, demonstrated robust discriminatory power between non-irAEs and irAEs (AUC = 0.88). Moreover, the predictive score from our classifier exhibited significant discriminative capability for identifying non-irAEs in two independent cohorts. Our functional analysis revealed that the altered microbiome in non-irAEs was characterized by an increased menaquinone biosynthesis, accompanied by elevated expression of rate-limiting enzymes menH and menC. Targeted metabolomics analysis further highlighted a notably higher abundance of menaquinone in the serum of patients who did not develop irAEs compared to the irAEs group. CONCLUSIONS: Our study underscores the potential of microbial biomarkers for predicting the onset of irAEs and highlights menaquinone, a metabolite derived from the microbiome community, as a possible selective therapeutic agent for modulating the occurrence of irAEs.

Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts.

The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts.

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

Novel circular RNA circ-0002727 regulates miR-144-3p/KIF14 pathway to promote lung adenocarcinoma progression.

Objective: Circular RNAs (circRNAs) have been shown to participate in various cancers via sponging miRNAs (microRNAs). However, their role in lung adenocarcinoma (LUAD) remains elusive. Methods: The transcriptome data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed genes (DEgenes) were identified and further used to constructed a circRNA-associated competing endogenous RNA (ceRNA) network. Real-Time qPCR analysis was conducted to examine gene expression at transcriptional level. The regulatory mechanisms of circRNA-miRNA-gene were validated by dual-luciferase reporter array and RNA pull-down assay. Cell growth, migration and invasion were evaluated by CCK-8 assay, colony formation assay and transwell assay, respectively. Results: Based on public microarray data, we systematically constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs and 49 DEgenes. Among the ceRNA network, we found that circ-0002727 was a key regulatory and was further confirmed to be upregulated in LUAD cancer cells. Subsequently, we found that silencing of circ-0002727 significantly suppressed the LUAD cell proliferation, migration and invasion in vitro. Mechanistically, we showed that circ-0002727 could competitively bind miR-144-3p to enhance the KIF14 expression in LUAD cells. Rescue assays indicated that circ-0002727 could regulate LUAD cell proliferation through modulating miR-144-3p/KIF14 pathway. Besides, KIF14 expression level was positively correlated with TNM stage and metastasis, and patients with high KIF14 expression suffered poor prognosis. Conclusion: Taken together, our study revealed that circ-0002727 could act as a ceRNA to regulate LUAD progression via modulating miR-144-3p/KIF14 pathway, providing a potential therapeutic target for LUAD.

Machine learning assisted vector atomic magnetometry.

Multiparameter sensing such as vector magnetometry often involves complex setups due to various external fields needed in explicitly connecting one measured signal to one parameter. Here, we propose a paradigm of indirect encoding for vector atomic magnetometry based on machine learning. We encode the three-dimensional magnetic-field information in the set of four simultaneously acquired signals associated with the optical rotation of a laser beam traversing the atomic sample. The map between the recorded signals and the vectorial field information is established through a pre-trained deep neural network. We demonstrate experimentally a single-shot all optical vector atomic magnetometer, with a simple scalar-magnetometer design employing only one elliptically-polarized laser beam and no additional coils. Magnetic field amplitude sensitivities of about 100 [Formula: see text] and angular sensitivities of about [Formula: see text] (for a magnetic field of around 140 nT) are derived from the neural network. Our approach can reduce the complexity of the architecture of vector magnetometers, and may shed light on the general design of multiparameter sensing.

Inverse design of anisotropic bone scaffold based on machine learning and regenerative genetic algorithm.

Introduction: Triply periodic minimal surface (TPMS) is widely used in the design of bone scaffolds due to its structural advantages. However, the current approach to designing bone scaffolds using TPMS structures is limited to a forward process from microstructure to mechanical properties. Developing an inverse bone scaffold design method based on the mechanical properties of bone structures is crucial. Methods: Using the machine learning and genetic algorithm, a new inverse design model was proposed in this research. The anisotropy of bone was matched by changing the number of cells in different directions. The finite element (FE) method was used to calculate the TPMS configuration and generate a back propagation neural network (BPNN) data set. Neural networks were used to establish the relationship between microstructural parameters and the elastic matrix of bone. This relationship was then used with regenerative genetic algorithm (RGA) in inverse design. Results: The accuracy of the BPNN-RGA model was confirmed by comparing the elasticity matrix of the inverse-designed structure with that of the actual bone. The results indicated that the average error was below 3.00% for three mechanical performance parameters as design targets, and approximately 5.00% for six design targets. Discussion: The present study demonstrated the potential of combining machine learning with traditional optimization method to inversely design anisotropic TPMS bone scaffolds with target mechanical properties. The BPNN-RGA model achieves higher design efficiency, compared to traditional optimization methods. The entire design process is easily controlled.

The mechanistic role of cardiac glycosides in DNA damage response and repair signaling.

Cardiac glycosides (CGs) are a class of bioactive organic compounds well-known for their application in treating heart disease despite a narrow therapeutic window. Considerable evidence has demonstrated the potential to repurpose CGs for cancer treatment. Chemical modification of these CGs has been utilized in attempts to increase their anti-cancer properties; however, this has met limited success as their mechanism of action is still speculative. Recent studies have identified the DNA damage response (DDR) pathway as a target of CGs. DDR serves to coordinate numerous cellular pathways to initiate cell cycle arrest, promote DNA repair, regulate replication fork firing and protection, or induce apoptosis to avoid the survival of cells with DNA damage or cells carrying mutations. Understanding the modus operandi of cardiac glycosides will provide critical information to better address improvements in potency, reduced toxicity, and the potential to overcome drug resistance. This review summarizes recent scientific findings of the molecular mechanisms of cardiac glycosides affecting the DDR signaling pathway in cancer therapeutics from 2010 to 2022. We focus on the structural and functional differences of CGs toward identifying the critical features for DDR targeting of these agents.

Predicting cardiovascular risk in a Chinese primary Sjögren's syndrome population: development and assessment of a predictive nomogram.

Background: Patients with primary Sjögren's syndrome (pSS) are at increased risk of cardiovascular morbidity as compared with the general population. Objectives: A retrospective study on 349 Chinese patients with pSS was conducted to identify potential risk factors for cardiovascular events and develop a cardiovascular risk nomogram. Design: This is a retrospective observational study. Methods: The study included 349 patients who were diagnosed with pSS at Tongji Hospital, School of Medicine, Tongji University, China from January 2010 to March 2022. The least absolute shrinkage and selection operator (LASSO) was used to select features for the cardiovascular risk model. The features selected in LASSO were used to build the cardiovascular risk model in a multivariate logistic regression analysis. C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis were used to assess the predictive model. Internal validation was performed by bootstrapping. Results: Sex, joint pain as an initial symptom, dry mouth, oral ulcers, dental caries, Raynaud's phenomenon, fatigue, diabetes, elevated thyroid-stimulating hormone (TSH) level, and elevated systolic blood pressure were included in the nomogram for the prediction of cardiovascular risk. Our model had good discrimination (C-index: 0.824, 95% confidence interval: 0.712-0.936) and good calibration (C-index in the interval validation: 0.8). Decision curve analysis indicated that our nomogram demonstrated clinical usefulness for intervention in a cardiovascular disease possibility threshold of 3%. Conclusion: The cardiovascular risk nomogram incorporating sex, initial joint pain, dry mouth, oral ulcer, dental caries, Raynaud's phenomenon, fatigue, diabetes, elevated TSH, and systolic blood pressure could be used in the prediction of cardiovascular risk in patients with pSS and the guidance of further treatment.

Research Progress of AlGaN-Based Deep Ultraviolet Light-Emitting Diodes.

AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs) have great application prospects in sterilization, UV phototherapy, biological monitoring and other aspects. Due to their advantages of energy conservation, environmental protection and easy miniaturization realization, they have garnered much interest and been widely researched. However, compared with InGaN-based blue LEDs, the efficiency of AlGaN-based DUV LEDs is still very low. This paper first introduces the research background of DUV LEDs. Then, various methods to improve the efficiency of DUV LED devices are summarized from three aspects: internal quantum efficiency (IQE), light extraction efficiency (LEE) and wall-plug efficiency (WPE). Finally, the future development of efficient AlGaN-based DUV LEDs is proposed.

Chronic Epstein-Barr virus infection: A potential junction between primary Sjögren's syndrome and lymphoma.

Primary Sjögren's syndrome (pSS) is an autoimmune disease that targets exocrine glands, leading to exocrine dysfunction. Due to its propensity to infect epithelial and B cells, Epstein-Barr virus (EBV) is hypothesized to be related with pSS. Through molecular mimicry, the synthesis of specific antigens, and the release of inflammatory cytokines, EBV contributes to the development of pSS. Lymphoma is the most lethal outcome of EBV infection and the development of pSS. As a population-wide virus, EBV has had a significant role in the development of lymphoma in people with pSS. In the review, we will discuss the possible causes of the disease.

MYO10 regulates genome stability and cancer inflammation through mediating mitosis.

Genomic instability can promote inflammation and tumor development. Previous research revealed an unexpected layer of regulation of genomic instability by a cytoplasmic protein MYO10; however, the underlying mechanism remained unclear. Here, we report a protein stability-mediated mitotic regulation of MYO10 in controlling genome stability. We characterized a degron motif and phosphorylation residues in the degron that mediate ß-TrCP1-dependent MYO10 degradation. The level of phosphorylated MYO10 protein transiently increases during mitosis, which is accompanied by a spatiotemporal cellular localization change first accumulating at the centrosome then at the midbody. Depletion of MYO10 or expression of MYO10 degron mutants, including those found in cancer patients, disrupts mitosis, increases genomic instability and inflammation, and promotes tumor growth; however, they also increase the sensitivity of cancer cells to Taxol. Our studies demonstrate a critical role of MYO10 in mitosis progression, through which it regulates genome stability, cancer growth, and cellular response to mitotic toxins.

Recent Advances on GaN-Based Micro-LEDs.

GaN-based micro-size light-emitting diodes (µLEDs) have a variety of attractive and distinctive advantages for display, visible-light communication (VLC), and other novel applications. The smaller size of LEDs affords them the benefits of enhanced current expansion, fewer self-heating effects, and higher current density bearing capacity. Low external quantum efficiency (EQE) resulting from non-radiative recombination and quantum confined stark effect (QCSE) is a serious barrier for application of µLEDs. In this work, the reasons for the poor EQE of µLEDs are reviewed, as are the optimization techniques for improving the EQE of µLEDs.