Downregulation of Glis3 in INS1 cells exposed to chronically elevated glucose contributes to glucotoxicity-associated ß cell dysfunction.

Chronically elevated levels of glucose are deleterious to pancreatic ß cells and contribute to ß cell dysfunction, which is characterized by decreased insulin production and a loss of ß cell identity. The Krüppel-like transcription factor, Glis3 has previously been shown to positively regulate insulin transcription and mutations within the Glis3 locus have been associated with the development of several pathologies including type 2 diabetes mellitus. In this report, we show that Glis3 is significantly downregulated at the transcriptional level in INS1 832/13 cells within hours of being subjected to high glucose concentrations and that diminished expression of Glis3 is at least partly attributable to increased oxidative stress. CRISPR/Cas9-mediated knockdown of Glis3 indicated that the transcription factor was required to maintain normal levels of both insulin and MafA expression and reduced Glis3 expression was concomitant with an upregulation of ß cell disallowed genes. We provide evidence that Glis3 acts similarly to a pioneer factor at the insulin promoter where it permissively remodels the chromatin to allow access to a transcriptional regulatory complex including Pdx1 and MafA. Finally, evidence is presented that Glis3 can positively regulate MafA transcription through its pancreas-specific promoter and that MafA reciprocally regulates Glis3 expression. Collectively, these results suggest that decreased Glis3 expression in ß cells exposed to chronic hyperglycemia may contribute significantly to reduced insulin transcription and a loss of ß cell identity.

Multiband task related components enhance rapid cognition decoding for both small and similar objects.

The cortically-coupled target recognition system based on rapid serial visual presentation (RSVP) has a wide range of applications in brain computer interface (BCI) fields such as medical and military. However, in the complex natural environment backgrounds, the identification of event-related potentials (ERP) of both small and similar objects that are quickly presented is a research challenge. Therefore, we designed corresponding experimental paradigms and proposed a multi-band task related components matching (MTRCM) method to improve the rapid cognitive decoding of both small and similar objects. We compared the areas under the receiver operating characteristic curve (AUC) between MTRCM and other 9 methods under different numbers of training sample using RSVP-ERP data from 50 subjects. The results showed that MTRCM maintained an overall superiority and achieved the highest average AUC (0.6562 ± 0.0091). We also optimized the frequency band and the time parameters of the method. The verification on public data sets further showed the necessity of designing MTRCM method. The MTRCM method provides a new approach for neural decoding of both small and similar RSVP objects, which is conducive to promote the further development of RSVP-BCI.

Exploring hidden diversity: Molecular insights into the Leporinus species of the rivers of the Brazilian states of Maranhão and Piauí.

The present study delved into the world of hidden diversity by examining specimens identified as Leporinus piau from the river basins of the northern Brazilian states of Maranhão and Piauí. Using genetic analyses that combined data from three mitochondrial markers and one nuclear marker, the study identified two well-supported groups, reinforcing the findings of previous publications. The first group, found in samples from the Itapecuru, Mearim, Turiaçu, and Pericumã basins, in Maranhão, appears to represent a relatively ancient diversification and the possibility of concealed cryptic diversity. The second group, comprising specimens from the Parnaíba (Piauí) and Mearim (Maranhão) basins, appears to have resulted from a more recent process of diversification and has a close relationship with Leporinus friderici from the type locality. Our findings not only confirm the existence of a complex scenario of cryptic diversity in the genus Leporinus from the study basins but also underscore the taxonomic inconsistencies within this group of fish. This study offers a comprehensive analysis of the species diversity of the Maranhão and Piauí basins, which are critical regions for the conservation of Amazonian fish, providing valuable insights for the sustainable management and conservation of these fish.

Identification of Vernonia patula Merr. and Its Similar Varieties Based on a Combination of HPLC Fingerprinting and Chemical Pattern Recognition.

Vernonia patula Merr. (VP) is a traditional medicine used by the Zhuang and Yao people, known for its therapeutic properties in treating anemopyretic cold and other diseases. Distinguishing VP from similar varieties such as Praxelis clematidea (PC), Ageratum conyzoides L. (AC) and Ageratum houstonianum Mill (AH) was challenging due to their similar traits and plant morphology. The HPLC fingerprints of 40 batches of VP and three similar varieties were established. SPSS 20.0 and SIMCA-P 13.0 were used to statistically analyze the chromatographic peak areas of 37 components. The results showed that the similarity of the HPLC fingerprints for each of the four varieties was >0.9, while the similarity between the control chromatogram of VP and its similar varieties was <0.678. Cluster analysis and partial least squares discriminant analysis provided consistent results, indicating that all four varieties could be individually clustered together. Through further analysis, we found isochlorogenic acid A and isochlorogenic acid C were present only in the original VP, while preconene II was present in the three similar varieties of VP. These three components are expected to be identification points for accurately distinguishing VP from PC, AC and AH.

Finding Highly Similar Regions of Genomic Sequences Through Homomorphic Encryption.

Finding highly similar regions of genomic sequences is a basic computation of genomic analysis. Genomic analyses on a large amount of data are efficiently processed in cloud environments, but outsourcing them to a cloud raises concerns over the privacy and security issues. Homomorphic encryption (HE) is a powerful cryptographic primitive that preserves privacy of genomic data in various analyses processed in an untrusted cloud environment. We introduce an efficient algorithm for finding highly similar regions of two homomorphically encrypted sequences, and describe how to implement it using the bit-wise and word-wise HE schemes. In the experiment, our algorithm outperforms an existing algorithm by up to two orders of magnitude in terms of elapsed time. Overall, it finds highly similar regions of the sequences in real data sets in a feasible time.

A clustering effectiveness measurement model based on merging similar clusters.

This article presents a clustering effectiveness measurement model based on merging similar clusters to address the problems experienced by the affinity propagation (AP) algorithm in the clustering process, such as excessive local clustering, low accuracy, and invalid clustering evaluation results that occur due to the lack of variety in some internal evaluation indices when the proportion of clusters is very high. First, depending upon the "rough clustering" process of the AP clustering algorithm, similar clusters are merged according to the relationship between the similarity between any two clusters and the average inter-cluster similarity in the entire sample set to decrease the maximum number of clusters Kmax. Then, a new scheme is proposed to calculate intra-cluster compactness, inter-cluster relative density, and inter-cluster overlap coefficient. On the basis of this new method, several internal evaluation indices based on intra-cluster cohesion and inter-cluster dispersion are designed. Results of experiments show that the proposed model can perform clustering and classification correctly and provide accurate ranges for clustering using public UCI and NSL-KDD datasets, and it is significantly superior to the three improved clustering algorithms compared with it in terms of intrusion detection indices such as detection rate and false positive rate (FPR).

Post-stroke Chinese pure alexia: linguistic features and neuropsychological profiles.

PURPOSE: Very few cases of Chinese pure alexia have been reported to date. We aim to summarize the linguistic features and neuropsychological profiles of Chinese pure alexia through a case series study. METHODS: 11 consecutive patients with post-stroke Chinese pure alexia and 11 healthy controls were included. The Aphasia Battery of Chinese (ABC) and 68-Chinese character oral reading test (68-character test) were used to evaluate the reading and writing ability. Reading errors were classified based on the performance of 68-character test. Neuropsychological profiles were evaluated with corresponding scales. The possible correlation between the reading ability and the writing ability or neuropsychological performance was analyzed. RESULTS: The patients had a correct rate of 43.7 ± 23.2% in the 68-character test, significantly lower (P < 0.001) than that of controls. Shape-similar error was the most common type of reading error (101/209, 48.3%). The ABC total writing score rate of the patients ranged from 68.9% to 98.7% (median, 90.5%), significantly lower (P < 0.001) than that of the controls. The patients also showed worse performance in MMSE, auditory verbal learning test, Boston naming test, intersecting pentagons copying and clock-drawing test (all P < 0.05). In the patient group, the correct rate of 68-character test was significantly correlated with the ABC total writing score rate (P = 0.008), the score rate of Boston naming test (P = 0.017), and the clock-drawing test score (P = 0.010). CONCLUSION: Shape-similar errors may be a characteristic of Chinese pure alexia. The correlation between visuospatial dysfunction and pure alexia might explain the frequent occurrence of shape-similar errors in Chinese pure alexia.

Microstructural Characterization and Corrosion Behavior of Similar and Dissimilar Welded Advanced High-Strength Steels (AHSS) by Rotary Friction Welding.

Advanced high-strength steels (AHSSs) are designed for meeting strict requirements, especially in the automotive industry, as a means to directly influence the reduction in the carbon footprint. As rotary friction welding (RFW) has many important advantages over other welding technologies, it plays an important role in the automotive sector. On the above basis, in this work, combinations of the first (complex phase (CP)), second (TWIP (TW)), and third (quenched and partitioned (Q&P)) generations of similar and dissimilar high-alloyed advanced steels have been joined by the RFW process. Having a specific microstructure, rods of CP/CP, Q&P/Q&P, CP/TW, and Q&P/TW steels were welded by employing a homemade adaptation machine under fixed parameters. Microstructural characterization has allowed us to corroborate the metallic bonding of all the tested advanced steels and to identify the different zones formed after welding. Results indicate that the welding zone widens in the center of the workpiece, and under the current friction action, the intermixing region shows the redistribution of solute elements, mostly in the dissimilarly welded steels. Furthermore, because of their complex chemistry and the different mechanical properties of the used steels, dissimilarly welded steels present the most noticeable differences in hardness. The TWIP steel has the lower hardness values, whilst the CP and Q&P steels have the higher ones. As a direct effect of the viscoplastic behavior of the steels established by the thermomechanical processing, interlayers and oxidation products were identified, as well as some typical RFW defects. The electrochemical response of the welded steels has shown that the compositional and microstructural condition mostly affect the corrosion trend. This means that the dissimilarly welded steels are more susceptible to corrosion, especially at the TWIP-steel interface, which is attributed to the energy that is stored in the distorted microstructure of each steel plate as a consequence of the thermomechanical processing during RFW.

Streamlining biosimilar development based on 20 years' experience.

INTRODUCTION: Biosimilar clinical programs could be streamlined by prudent application of improved methodologies and knowledge accumulated over the past 20 years. This review focuses on whether complex comparative efficacy trials are routinely needed and how to achieve a more tailored approach to biosimilar development. AREAS COVERED: Key learnings over the past 20 years are summarized. It is noted that a one size fits all approach to biosimilar development is not appropriate: biological medicines fall within a wide spectrum of complexity, with blurring at the interface between biological products and small molecules. The interrelationship between quality, potency, pharmacokinetics, pharmacology, immunogenicity, efficacy, and safety are reviewed. Current regulatory thinking is reviewed with a look into what future challenges lie ahead. EXPERT OPINION: To tailor regulatory requirements for marketing approval of biosimilars, it is proposed that a biosimilarity report be introduced. This report would integrate quality, pharmacology, immunogenicity, efficacy and safety findings and address how the clinical program could be tailored based on the totality of evidence.

AptaDB: a comprehensive database integrating aptamer-target interactions.

Aptamers have emerged as research hotspots of the next generation due to excellent performance benefits and application potentials in pharmacology, medicine, and analytical chemistry. Despite the numerous aptamer investigations, the lack of comprehensive data integration has hindered the development of computational methods for aptamers and the reuse of aptamers. A public access database named AptaDB, derived from experimentally validated data manually collected from the literature, was hence developed, integrating comprehensive aptamer-related data, which include six key components: (i) experimentally validated aptamer-target interaction information, (ii) aptamer property information, (iii) structure information of aptamer, (iv) target information, (v) experimental activity information, and (vi) algorithmically calculated similar aptamers. AptaDB currently contains 1350 experimentally validated aptamer-target interactions, 1230 binding affinity constants, 1293 aptamer sequences, and more. Compared to other aptamer databases, it contains twice the number of entries found in available databases. The collection and integration of the above information categories is unique among available aptamer databases and provides a user-friendly interface. AptaDB will also be continuously updated as aptamer research evolves. We expect that AptaDB will become a powerful source for aptamer rational design and a valuable tool for aptamer screening in the future. For access to AptaDB, please visit http://lmmd.ecust.edu.cn/aptadb/.

Heterodox underdetermination: Metaphysical options for discernibility and (non-)entanglement.

Broadly speaking, there are three views on whether Leibniz's Principle of the Identity of Indiscernibles (PII) is violated in the case of similar particles. According to the earliest view, PII is always violated (call this the no discernibility view); according to the more recent weak discernibility view, PII is at least valid in a weak sense. No and weak discernibility have been referred to as orthodoxy. Steven French has argued that although PII is violated, similar particles can still be regarded as individuals, or, alternatively, as non-individuals: French famously concluded therefore that metaphysics is underdetermined by physics. Call this thesis orthodox underdetermination. Most recently, some authors have turned against orthodoxy by arguing that PII is valid in more than a weak sense - call this the new discernibility view, also referred to as heterodoxy. Since heterodoxy is backed up by physical considerations, metaphysics now seems to be determined by physics: physics indicates that PII is valid. In this paper, I argue that with respect to entangled states, there are two ways to establish PII's validity, which yield two different ontological interpretations of entanglement. Therefore, a form of underdetermination returns within the heterodox framework. I argue that heterodox underdetermination deserves some attention, because the two ontological interpretations might yield different explanations of the violation of Bell inequalities.

The compensatory increase of Gli-similar 3 inhibited neuronal apoptosis through regulating Mps one binder kinase activator 1b (MOB1b): a possible strategy for the functional recovery after spinal cord injury.

Spinal cord injury (SCI) is a devastating disease characterized by neuronal apoptosis. Gli-similar 3 (GLIS3), a transcriptional factor, was involved in cell apoptosis and associated with the transcription of downstream target genes related to neuronal function. However, the function of GLIS3 in SCI remains unknown. Therefore, we used the mouse model of SCI to explore the role of GLIS3 in SCI. The results showed that GLIS3 expression was significantly increased in spinal cord tissues of SCI mice, and GLIS3 overexpression promoted the functional recovery, reserved histological changes, and inhibited neuronal apoptosis after SCI. Through online tools, the potential target genes of GLIS3 were analyzed and we found that Mps one binder kinase activator 1b (Mob1b) had a strong association with SCI among these genes. MOB1b is a core component of Hippo signaling pathway, which was reported to inhibit cell apoptosis. MOB1b expression was significantly increased in mice at 7 days post-SCI and GLIS3 overexpression further increased its expression. Dual-luciferase reporter assay revealed that GLIS3 bound to the promoter of Mob1b and promoted its transcription. In conclusion, our findings reveal that the compensatory increase of GLIS3 promotes functional recovery after SCI through inhibiting neuronal apoptosis by transcriptionally regulating MOB1b. Our study provides a novel target for functional recovery after SCI.

Graph-guided deep hashing networks for similar patient retrieval.

With the rapid growth and widespread application of electronic health records (EHRs), similar patient retrieval has become an important task for downstream clinical decision support such as diagnostic reference, treatment planning, etc. However, the high dimensionality, large volume, and heterogeneity of EHRs pose challenges to the efficient and accurate retrieval of patients with similar medical conditions to the current case. Several previous studies have attempted to alleviate these issues by using hash coding techniques, improving retrieval efficiency but merely exploring underlying characteristics among instances to preserve retrieval accuracy. In this paper, drug categories of instances recorded in EHRs are regarded as the ground truth to determine the pairwise similarity, and we consider the abundant semantic information within such multi-labels and propose a novel framework named Graph-guided Deep Hashing Networks (GDHN). To capture correlation dependencies among the multi-labels, we first construct a label graph where each node represents a drug category, then a graph convolution network (GCN) is employed to derive the multi-label embedding of each instance. Thus, we can utilize the learned multi-label embeddings to guide the patient hashing process to obtain more informative and discriminative hash codes. Extensive experiments have been conducted on two datasets, including a real-world dataset concerning IgA nephropathy from Peking University First Hospital, and a publicly available dataset from MIMIC-III, compared with traditional hashing methods and state-of-the-art deep hashing methods using three evaluation metrics. The results demonstrate that GDHN outperforms the competitors at different hash code lengths, validating the superiority of our proposal.

Development of sequential online extraction electrospray ionization mass spectrometry for accurate authentication of highly-similar Atractylodis Macrocephalae.

The accurate and rapid authentication techniques and strategies for highly-similar foods are still lacking. Herein, a novel sequential online extraction electrospray ionization mass spectrometry (S-oEESI-MS) was developed to achieve spatio-temporally resolved ionization and comprehensive characterization of complex foods with multi-components (high, medium, and low polarity substances). Meanwhile, a characteristic marker screening method and an integrated research strategy based on MS fingerprinting, characteristic marker and chemometrics modeling were established, which are especially suitable for the accurate and rapid authentication of highly-similar foods that are difficult to be authenticated by traditional techniques (e.g., LC-MS). Thirty-two batches of highly-similar Atractylodis macrocephalae rhizome from four different origins were used as model samples. As a result, S-oEESI-MS enabled a more comprehensive MS characterization of substance profiles in complex plant samples in 1.0 min. Further, 22 characteristic markers of Atractylodis macrocephalae were ingeniously screened out and combined with multivariate statistical analysis model, the accurate authentication of highly-similar Atractylodis macrocephalae was realized. This study presents a comprehensive strategy for accurate authentication and origin analysis of highly-similar foods, which has potentially significant applications for ensuring food quality and safety.

NAFLD and type 2 diabetes: A practical guide for the joint management / Esteatosis hepática metabólica y diabetes mellitus tipo 2: Una guía práctica para el manejo conjunto

Non-alcoholic fatty liver disease (NAFLD) is becoming a major cause of liver disease-related morbidity, as well as mortality. Importantly, NAFLD is considered a mediator of systemic diseases including cardiovascular disease. Its prevalence is expected to increase, mainly due to its close association with obesity and type 2 diabetes mellitus (T2D). In addition, T2D and NAFLD share common pathophysiological mechanisms, and one can lead to or worsen the other. Therefore, a close collaboration between primary care physician, endocrinologists and hepatologists is essential to optimize the management of patients with NAFLD and T2D. Here, we summarize relevant aspects about NAFLD and T2D that all clinician managing these patients should know as well as current therapeutic options for the treatment of T2D associated with NAFLD. (AU)

La esteatosis hepática metabólica (EHmet) se está convirtiendo en una de las causas más importantes de morbimortalidad relacionada con las enfermedades hepáticas. Es importante destacar que la EHmet se considera un mediador de enfermedades sistémicas, incluidas las enfermedades cardiovasculares. Se espera que su prevalencia aumente, principalmente debido a su estrecha relación con la obesidad y la diabetes mellitus tipo 2 (DM2). Además, la DM2 y la EHmet comparten mecanismos fisiopatológicos comunes y una puede provocar o empeorar la otra. Por lo tanto, una estrecha colaboración entre el médico de atención primaria, endocrinólogos y hepatólogos es fundamental para optimizar el manejo de los pacientes con EHmet y DM2. En esta guía resumimos aspectos relevantes sobre EHmet y DM2 que todo médico que maneja a estos pacientes debe conocer, así como las opciones terapéuticas actuales para el tratamiento de DM2 asociada a EHmet. (AU)

Multi-dimension metabolic prognostic model for gastric cancer.

Background: Metabolic reprogramming is involved in different stages of tumorigenesis. There are six widely recognized tumor-associated metabolic pathways, including cholesterol catabolism process, fatty acid metabolism, glutamine metabolic process, glycolysis, one carbon metabolic process, and pentose phosphate process. This study aimed to classify gastric cancer patients into different metabolic bio-similar clusters. Method: We analyzed six tumor-associated metabolic pathways and calculated the metabolic pathway score through RNA-seq data using single sample gene set enrichment analysis. The consensus clustering analysis was performed to classify patients into different bio-similar clusters by multi-dimensional scaling. Kaplan-Meier curves were presented between different metabolic bio-similar groups for OS analysis. Results: A training set of 370 patients from the Cancer Genome Atlas database with primary gastric cancer was chosen. Patients were classified into four metabolic bio-similar clusters, which were identified as metabolic non-specificity, metabolic-active, cholesterol-silence, and metabolic-silence clusters. Survival analysis showed that patients in metabolic-active cluster and metabolic-silence cluster have significantly poor prognosis than other patients (p=0.031). Patients in metabolic-active cluster and metabolic-silence cluster had significantly higher intra-tumor heterogeneity than other patients (p=0.032). Further analysis was performed in metabolic-active cluster and cholesterol-silence cluster. Three cell-cycle-related pathways, including G2M checkpoints, E2F targets, and MYC targets, were significantly upregulated in metabolic-active cluster than in cholesterol-silence cluster. A validation set of 192 gastric cancer patients from the Gene Expression Omnibus data portal verified that metabolic bio-similar cluster can predict prognosis in gastric cancer. Conclusion: Our study established a multi-dimension metabolic prognostic model in gastric cancer, which may be feasible for predicting clinical outcome.

Stability of dyadic exchange: Experimental evidence for the impact of shared group membership.

Pair stability refers to the extent to which exchange occurs between the same actors over time. In a stable pair, actors know what to expect of one another and have a sense of predictability as to the outcome of the exchange. When actors are split into discrete groups, shared group membership contributes to formation of new ties and maintenance of existing ties due to the mechanism of attraction to similar others. Using the formal framework of biased net theory, we propose three hypotheses which link shared group membership with the odds of pair stability. These hypotheses are tested against data from an experiment (N = 180) in which participants were first split into two groups and then given a series of opportunities to share resources with one another. Results of the experiment are consistent with the hypotheses.

Study on Proportioning Scheme of Coal System Rocky Similar Material Based on Orthogonal Test.

Similar materials play an important role in model testing. In order to meet the demand for similar materials in modeling tests, such as those on coal mining, coal system rocky similar materials were formulated using yellow sand as a coarse aggregate, heavy calcium carbonate as a fine aggregate, and cement and gypsum as binders. Based on the orthogonal experimental design method, four influencing factors, namely the aggregate-binder ratio, heavy calcium carbonate content, cement-gypsum ratio, and moisture content, were selected. Each factor was designed at five levels. Through weighing, uniaxial compression, Brazilian splitting, and variable-angle plate shear tests on 225 specimens under 25 different ratios, five physico-mechanical property indicators of the material, including density, compressive strength, tensile strength, cohesion, and internal friction angle, were obtained under different ratios. The test results indicate that the similar materials formulated with the above raw materials had a wide range of mechanical properties, which met the simulation needs of different types of coal rocks, such as main coking coal, anthracite, shale, etc., in the similar model test. Range analysis was adopted to analyze the sensitivities to each factor, which showed that the density and internal friction angle of similar materials are mainly controlled by the aggregate-binder ratio; the cement-gypsum ratio mainly controls the compressive strength, tensile strength, and cohesion of the material. Analysis of variance (ANOVA) was adopted to analyze the sensitivities to each factor, which showed that the aggregate-binder ratio had a highly significant effect on the density of the material, the cement-gypsum ratio had a highly significant effect on the compressive and tensile strength of the material, the cement-gypsum ratio had a significant effect on the cohesion and density of the material, and the moisture content had a significant effect on the compressive strength of the material. The remaining factors did not significantly affect the material parameters. The results of this study can provide some reference for the selection of coal system rocky similar materials in subsequent physical modeling tests.

Research on Similarity Simulation Experiment of Mine Pressure Appearance in Surface Gully Working Face Based on BOTDA.

In order to study the mountain deflection characteristics and the pressure law of the working face after the mining of a shallow coal seam under the valley terrain, a geometric size of 5.0 × 0.2 × 1.33 m is used in the physical similarity model. Brillouin optical time domain analysis (BOTDA) technology is applied to a similar physical model experiment to monitor the internal strain of the overlying rock. In this paper, the strain law of the horizontal optical fiber at different stages of the instability of the mountain structure is analyzed. Combined with the measurement of the strain field on the surface of the model via digital image correlation (DIC) technology, the optical fiber strain characteristics of the precursor of mountain instability are given. The optical fiber characterization method of working face pressure is proposed, and the working face pressures at different mining stages in gully terrain are characterized. Finally, the relationship between the deflection instability of the mountain and the strong ground pressure on the working face is discussed. The sudden increase in the strain peak point of the horizontally distributed optical fiber strain curve can be used to distinguish the strong ground pressure. At the same time, this conclusion is verified by comparing the measured underground ground pressure values. The research results can promote the application of optical fiber sensing technology in the field of mine engineering.

Prediction of solar irradiance using convolutional neural network and attention mechanism-based long short-term memory network based on similar day analysis and an attention mechanism.

As one of the future's most promising clean energy sources, solar energy is the key to developing renewable energy. The randomness of solar irradiance can affect the efficiency of photovoltaic power generation, which makes photovoltaic power generation planning extremely difficult. The main goal of this study is to accurately predict solar irradiance and establish a prediction model with meteorological characteristics to improve prediction accuracy. This paper proposes a convolutional neural network (CNN) and attention mechanism-based long short-term memory network (A-LSTM) to predict solar irradiance the next day. In addition, the prediction accuracy is further improved by combining similar day analyses. A similar day prediction model is constructed by selecting solar energy data from Andhra Pradesh, India. The experimental results show that the method proposed in this paper can predict solar irradiance more accurately, providing a new idea for photovoltaic power generation planning.