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In this article, the properties of solutions of Hadamard fractional differential equations are investigated on an infinite interval. The equations are subject to integral and discrete boundary conditions. A new proper compactness criterion is introduced in a unique space. By applying the monotone iterative technique, we have obtained two positive solutions. And, an error estimate is also shown at the end. This study innovatively uses a monotonic iterative approach to study Hadamard fractional boundary-value problems containing multiple fractional derivative terms on infinite intervals, and it enriches some of the existing conclusions. Meanwhile, it is potentially of practical significance in the research field of computational fluid dynamics related to blood flow problems and in the direction of the development of viscoelastic fluids.

Abstract In this paper, we consider the existence of solutions for a boundary value problem of singular two-term fractional differential equation with delay and sign-changing nonlinearity. By means of the Guo–Krasnosel’skii fixed point theorem and the Leray–Schauder nonlinear alternative theorem, we obtain some results on the existence and multiplicity of solutions, respectively.

AIM: To observe the clinical features of acute macular neuroretinopathy(AMN)induced by Omicron.METHODS: A retrospective study. A total of 9 patients(18 eyes)diagnosed with AMN from December 2022 to January 2023 in the Hospital of Chengdu University of Traditional Chinese Medicine were included. Patients underwent spectral-domain optical coherence tomography(SD-OCT), fundus fluorescein angiography(FFA), fundus photography, autofluorescence(AF), infrared reflectance(IR), optical coherence tomography angiography(OCTA)and multicolor, etc. Furthermore, they were followed up for 1～3mo and observed the prognosis.RESULTS: The initial symptom of the Omicron-induced AMN was the sudden onset of central/paracentral scotoma in the eyes with or without impaired vision and metamorphopsia, and the scotoma could persist for at least 3mo. The image features of AMN are as follows. First, the SD-OCT examination showed the rupture of outer retinal layers, scattered hyperreflective lesions, and atrophy of outer retinal layers. In severe cases, hyperreflective lesions were seen in the inner nuclear layer(INL)or with microcystic cavities under the retinal pigment epithelium(RPE). Second, the OCTA examination demonstrated the decreased blood flow density of the deep capillary plexus(DCP)of the macula. Third, the IR examination showed the weak reflection of lesion areas. Fourth, the fundus photography demonstrated the localized brown wedge-shaped lesion.CONCLUSIONS: The Omicron-induced AMN is mostly found in young females, and the characteristic manifestation of fundus is damage to the outer retinal layers. The extent of fundus lesions is related to the systemic inflammatory response and ocular microcirculatory changes after infection. The multimodal fundus image examination and a history of Omicron infection are helpful to diagnose the Omicron-induced AMN.

With the prevalence of myopia in Asia, the prevalence of high myopia is gradually increasing, and high myopia has undoubtedly become a public health problem in Asia and even around the globe. As a relatively common pathological change in the eyes of patients with high myopia, optic disc tilt may also become a risk factor for diseases such as glaucoma and macular degeneration, thereby increasing the risk of visual impairment. However, the mechanism of optic disc tilt in high myopia and the role of optic disc tilt in the aggravation of high myopia complications still needs to be further explored. Therefore, this article collects and organizes relevant literatures on optic disc tilt, and makes a comprehensive discussion on the mechanism of optic disc shape changing caused by high myopia and the impact on various complications, so as to provide a certain basis for clinical diagnosis and treatment of high myopia and its complications.

Abstract Background Associations of drugs with diseases provide important information for expediting drug development. Due to the number of known drug-disease associations is still insufficient, and considering that inferring associations between them through traditional in vitro experiments is time-consuming and costly. Therefore, more accurate and reliable computational methods urgent need to be developed to predict potential associations of drugs with diseases. Methods In this study, we present the model called weighted graph regularized collaborative non-negative matrix factorization for drug-disease association prediction (WNMFDDA). More specifically, we first calculated the drug similarity and disease similarity based on the chemical structures of drugs and medical description information of diseases, respectively. Then, to extend the model to work for new drugs and diseases, weighted $$K$$ K nearest neighbor was used as a preprocessing step to reconstruct the interaction score profiles of drugs with diseases. Finally, a graph regularized non-negative matrix factorization model was used to identify potential associations between drug and disease. Results During the cross-validation process, WNMFDDA achieved the AUC values of 0.939 and 0.952 on Fdataset and Cdataset under ten-fold cross validation, respectively, which outperforms other competing prediction methods. Moreover, case studies for several drugs and diseases were carried out to further verify the predictive performance of WNMFDDA. As a result, 13(Doxorubicin), 13(Amiodarone), 12(Obesity) and 12(Asthma) of the top 15 corresponding candidate diseases or drugs were confirmed by existing databases. Conclusions The experimental results adequately demonstrated that WNMFDDA is a very effective method for drug-disease association prediction. We believe that WNMFDDA is helpful for relevant biomedical researchers in follow-up studies.

Transforming growth factor-β(TGF-β)is a multifunctional biologic factor involved in the regulation of cell proliferation, apoptosis, differentiation, immune function and inflammatory response of the body. TGF-β signaling pathway-mediated myofibroblast transformation and overaccumulation of extracellular matrix(ECM)leads to retinal tissue contraction and impaired function. Various cytokine signals are involved in the fibrotic response in retinal tissue, but TGF-β is the most critical factor affecting the pathogenesis of retinal fibrotic disease. In terms of the eye, pathological fibrotic diseases such as corneal opacities, submacular fibrosis and proliferative retinal diseases cause visual impairment and blindness in millions of people worldwide, and this remains one of the major areas of unmet clinical need in ophthalmology. Therefore, this article focuses on the research progress related to the pathogenesis and therapeutic prospects of TGF-β in proliferative retinal diseases, with a view to provide more molecular targets for the prevention and treatment of proliferative retinal diseases and offer new ideas for the research of new drugs.

MicroRNAs(miRNAs)are micromolecule non-coding RNA that play a key role in post-transcriptional regulation of gene expression and are involved in regulating various biological processes such as cell differentiation, proliferation and metabolism.The expression of miRNAs varies significantly in the process of the occurrence and development of diabetic retinopathy(DR), many domestic and foreign studies have shown that miRNAs are closely related to the physiological and pathological mechanism of DR by regulating gene expression. Partial miRNAs that specifically expressed can regulate the level of oxidative stress and inflammatory response in the retina and affect the occurrence and development of DR. Therefore, the progression of DR can be delayed by enhancing or inhibiting these miRNAs. The combination of single or multiple miRNAs can serve as novel transcriptome biomarkers for DR, and it is also a potential effective target for future treatment of DR. Current detection of specific miRNAs in blood or body fluids is helpful for early intervention and follow-up of DR. Therefore, this review focuses on the research progress of miRNAs and their molecular mechanisms, therapeutic prospects and biomarkers involved in DR regulation.

Increasing evidences suggest that miRNAs play a key role in the occurrence and progression of many complex human diseases. Therefore, targeting dysregulated miRNAs with small molecule drugs in the clinical has become a new treatment. Nevertheless, it is high cost and time-consuming for identifying miRNAs-targeted with drugs by biological experiments. Thus, more reliable computational method for identification associations of drugs with miRNAs urgently need to be developed. In this study, we proposed an efficient method, called GNMFDMA, to predict potential associations of drug with miRNA by combining graph Laplacian regularization with non-negative matrix factorization. We first calculated the overall similarity matrices of drugs and miRNAs according to the collected different biological information. Subsequently, the new drug-miRNA association adjacency matrix was reformulated based on the K nearest neighbor profiles so as to put right the false negative associations. Finally, graph Laplacian regularization collaborative non-negative matrix factorization was used to calculate the association scores of drugs with miRNAs. In the cross validation, GNMFDMA obtains AUC of 0.9193, which outperformed the existing methods. In addition, case studies on three common drugs (i.e., 5-Aza-CdR, 5-FU and Gemcitabine), 30, 31 and 34 of the top-50 associations inferred by GNMFDMA were verified. These results reveal that GNMFDMA is a reliable and efficient computational approach for identifying the potential drug-miRNA associations.

Diabetic retinopathy(DR)is one of the chronic microvascular complications of diabetes mellitus in the eye, leading to an increasing incidence of visual quality loss and even blindness in diabetic patients. However, so far, the mechanism of pathological changes leading to DR is very complex and not completely elucidated, and clinical treatment is mostly based on different stages of DR with symptomatic treatment, such as retinal laser photocoagulation, anti-vascular endothelial factor treatment, vitreous excision and membrane peeling surgery, etc. There is still a lack of safe and effective treatment methods, and it is therefore necessary to find new targets for diagnosis and treatment. With the development of molecular biology analysis technology, circular RNA(circRNA)has become one of the important research hotspots at present. It is reported that under the stimulation of various factors, the regulated expression of genes-circRNA regulates the development of DR by regulating the functions of retinal microvascular pericytes, retinal microvascular endothelial cells, and retinal pigment epithelial cells, which are involved in the pathological processes such as retinal basement membrane thickening, vascular leakage, apoptosis, inflammatory response and neovascularization. Therefore, this paper focuses on the research progress of cyclic RNA, competitive endogenous RNA and microRNA in the molecular mechanism of DR pathological alterations and therapeutic prospects, in order to provide some reference for clinical and basic research.

The blood-retinal barrier is an important structural basis for maintaining the homeostasis of the retinal environment, but there is still a lack of further research on its complete structure and function. The in vitro blood-retinal barrier model has the characteristics of controllable, efficient, fast and stable, and has become an effective tool to study the specific structure and function of the barrier. This paper mainly reviews the structure, function and in vitro model of blood-retinal barrier, which is helpful to promote the study of physiology, biochemistry, pathopharmacology and clinic of blood-retinal barrier. It also provides a common and key experimental basis for the study of fundus vascular diseases such as diabetic retinopathy.

This paper investigates the problem of global exponential tracking control for switched nonlinear systems with linear uncertain parameters and without persistency of excitation. A switched model reference adaptive control technique, using the mode-dependent average dwell time method and a concurrent learning approach, is proposed for the first time. A sufficient condition is provided to ensure that the dynamics of the state tracking error and the adaptive weight error converge to zero exponentially rapidly. Consequently, the relationship among the average dwell time of each subsystem, the concurrent learning algorithm, and the performance of uncertain switched systems is established. Furthermore, the transient performance bounds of the state tracking error and the adaptive weight error are studied. Finally, an illustrative numerical example is provided to demonstrate the effectiveness of the proposed method.

AIM: To observe the effect of traditional Chinese medicine(TCM)of bushenhuoxue on primary visual cortex(PVC)brain-derived neurotrophic factor(BDNF)in rat model of chronic elevated intraocular pressure(EIOP), and explore the mechanism of it initially. METHODS: The rat model of chronic EIOP was established by unilaterally cauterizing 3 episcleral veins, then 30 rats were divided into 3 groups randomly: control group, model group, and treatment group. After given drugs or normal saline for 8 weeks, the rats were put to death. The effect of intraocular pressure(IOP), expression of BDNF and ultrastructure of neuron cell in the PVC was observed. RESULTS: Unilaterally cauterizing episcleral veins increased IOP of the rat model obviously, there was significant difference compared with pre-operation(P

This article discusses adaptive preassigned finite-time stability of nonlinear systems with unknown time-varying powers and full-state constraints. By introducing a concept of practical preassigned finite-time stable, constructing finite-time performance functions and nonlinear transformed functions, and integrating high-power and low-power terms into dynamic surface control design, an adaptive state-feedback controller is designed to eliminate the effects of unknown powers and serious unknown parameters in system dynamics, and decrease the computational burden in previous design methods. It is proved that all the signals of the closed-loop system are bounded, asymmetric time-varying full-state constraints are not transgressed, and systemstates converge to a prescribed arbitrarily small region around zero after a preassigned settling time. Two simulation examples show the effectiveness and advantages of this control scheme. [ABSTRACT FROM AUTHOR]

The higher the enrichment factor, the more significant the enrichment of the differential proteins in the pathway Bioinformatics analysis of the gene expression profile of retinal pigmental epithelial cells based in single-cell RNA sequencing in myopic mice Arch Med Sci 2, February / 2021 577 tration of kynurenic acid transiently increases. Through the single-cell RNA sequencing of the RPE cells, it was found that the cells were exposed to hypoxia during the development of myopia and that hypoxia might lead to functional limitations in the RPE cells [8]. Thus, it can be inferred that RPE cells are exposed to hypoxia during myopia; as RPE cells are oxygen-consuming cells, this hypoxia may activate glycolysis and oxidative phosphorylation in the cells [10-12]. [Extracted from the article]

This paper studies the problem of output feedback stabilisation for a class of stochastic nonlinear time-delay systems with the unknown output function. For stochastic nonlinear time-delay systems, the maximal open sector Δ of output function is given. As long as output function belongs to any closed sector included in Δ, by constructing a reduced-order observer and C² Lyapunov- Krasovskii functional and using the homogeneous domination method, an output feedback controller can be developed to guarantee the closed-loop system globally asymptotically stable in probability. [ABSTRACT FROM AUTHOR]

This paper further considers more general high-order stochastic nonlinear system driven by noise of unknown covariance and its adaptive state-feedback stabilization problem. A smooth state feedback controller is designed to guarantee that the origin of the closed-loop system is globally stable in probability. [ABSTRACT FROM AUTHOR]

This article further discusses the problem of output-feedback regulation for more general stochastic nonlinear systems with stochastic integral input-to-state stable inverse dynamics, and focuses on solving the important and unsolved problem proposed in Yu and Xie (Yu, X., and Xie, X.J. (2010), 'Output Feedback Regulation of Stochastic Nonlinear Systems with Stochastic iISS Inverse Dynamics', IEEE Transactions on Automatic Control, 55, 304-320): How to weaken the conditions on nonlinearities in drift and diffusion vector fields? Under the weaker conditions, how to make full use of the known information of stochastic nonlinear systems to design an adaptive output-feedback controller such that all the closed-loop signals are almost surely bounded and the output is driven to zero almost surely? [ABSTRACT FROM AUTHOR]

This article investigates the problem of output-feedback stabilisation for a class of high-order stochastic non-linear systems in which the diffusion terms depend on unmeasurable states besides the output. By introducing a new rescaling transformation, adopting an effective observer and choosing the appropriate Lyapunov function, an output-feedback controller is constructed to ensure that the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability, the output can be regulated to the origin almost surely, and the problem of inverse optimal stabilisation in probability is solved. The efficiency of the output-feedback controller is demonstrated by several simulation examples. [ABSTRACT FROM AUTHOR]

For a class of MIMO systems with input and output unmodeled dynamics, bounded disturbances and any relative degree, using the idea of Kp = L2D2S2 factorization, the design and analysis of robust direct model reference adaptive control are further investigated in this article. By establishing the Lp and L2δ relationship properties between the input and output, multivariable swapping lemmas and relating all the signals in the closed-loop system with the normalizing signal, stability and robustness of adaptive system are analyzed rigorously. Compared with the existing results, the proof procedure is more compact and simple. A simulation example verifies the effectiveness of the control scheme. [ABSTRACT FROM AUTHOR]

Motivated by the idea of high frequency gain matrix KP ?=? LDU factorization, the purpose of this paper is to study the problem of robust direct model reference adaptive control for more general multivariable plants with unmodeled dynamics and disturbances. For multivariable plants, by reproving some properties similar to those in robust adaptive control theory for SISO plants and redefining the normalizing signal, the relationship between all the signals in the closed-loop plant and the normalizing signal can be established, and the stability and robustness of the closed-loop plant are analyzed rigorously from a qualitative point of view. [ABSTRACT FROM AUTHOR]

An introduction to a series of articles on the theory of stochastic control systems is presented.