Highly cited publication performance in the ophthalmology category in the Web of Science database:a bibliometric analysis

AIM:To determine and evaluate the features of highly cited articles(HCAs)in the ophthalmology category in the Science Citation Index Expanded(SCI-EXPANDED)from 1991 to 2020.METHODS:The Web of Science Core Collection documents with at least 100 citations from their publication year until December 31,2020,were evaluated as highly cited.The examined features were the distribution of yearly output and its average number of per publication,HCAs,authors,institutions,journals,and nations.The publication performance of nations and organizations was assessed using six publication indicators.The Y-index was employed to compare the research outputs of various authors.RESULTS:Publications that had cited the most references were highly published in high-impact factor journals.The United States of America came out on top across all six publication indicators,and it was home to eight of the top 10 most productive institutions.The articles written by Breivik et al(2006)and Farrar et al(2001)were highly cited and had a significant impact in 2020.The authors had a higher number of highly cited articles published as corresponding authors than as first authors.CONCLUSION:The findings of the present study highlight the current scope of global research in ophthalmology.The findings can help policy-makers and advisory groups of research centers to develop future policies.In addition,the findings can guide researchers in this field.

Prevalence of Thumb Sucking Habits amongst Children at the Knust Basic School

Main Objective: To determine the prevalence of thumb sucking habits amongst children at the KNUST Basic School. Methodology: This study was quantitative and descriptive with the design being a cross-sectional type. The data was obtained from KNUST Basic School with a sample size of 200. Data was obtained through questionnaires and clinical examination. Results: Out of the 200 children studied, 19 (9.5%) were identified as thumb suckers, with a majority being females (13, 68.42%) and the rest being males (6, 31.58%). Most of the thumb suckers (47.37%) engaged in the habit due to hunger. The clinical manifestations observed among the thumb suckers included Class I malocclusion (94.7%), high arched palate (89.5%), anterior open bite (4), increased overjet (3, 15.8%), proclined maxillary incisors (4, 22.2%), linguoversion of mandibular incisors (1, 5.6%), unilateral posterior crossbite (2, 10.5%), speech changes (7, 41.2%), thinner thumb (7, 36.8%), elongated thumb (9, 47.4%), and callus formation on the thumb (2, 10.5%). Conclusion: Thumb sucking is a common oral habit which stimulates the growth of the orofacial complex from ages 0 to 3 years. The habit of thumb sucking is usually outgrown by age 3 but beyond this age, it turns out as a deleterious habit which has to be seen as such and measures put in place to stop thumb sucking.

Targeted anti-cancer therapy: Co-delivery of VEGF siRNA and Phenethyl isothiocyanate (PEITC) via cRGD-modified lipid nanoparticles for enhanced anti-angiogenic efficacy

Anti-tumor angiogenesis therapy, targeting the suppression of blood vessel growth in tumors, presents a potent approach in the battle against cancer. Traditional therapies have primarily concentrated on single-target techniques, with a specific emphasis on targeting the vascular endothelial growth factor, but have not reached ideal therapeutic efficacy. In response to this issue, our study introduced a novel nanoparticle system known as CS-siRNA/PEITC&L-cRGD NPs. These chitosan-based nanoparticles have been recognized for their excellent biocompatibility and ability to deliver genes. To enhance their targeted delivery capability, they were combined with a cyclic RGD peptide (cRGD). Targeted co-delivery of gene and chemotherapeutic agents was achieved through the use of a negatively charged lipid shell and cRGD, which possesses high affinity for integrin αvβ3 overexpressed in tumor cells and neovasculature. In this multifaceted approach, co-delivery of VEGF siRNA and phenethyl isothiocyanate (PEITC) was employed to target both tumor vascular endothelial cells and tumor cells simultaneously. The co-delivery of VEGF siRNA and PEITC could achieve precise silencing of VEGF, inhibit the accumulation of HIF-1α under hypoxic conditions, and induce apoptosis in tumor cells. In summary, we have successfully developed a nanoparticle delivery platform that utilizes a dual mechanism of action of anti-tumor angiogenesis and pro-tumor apoptosis, which provides a robust and potent strategy for the delivery of anti-cancer therapeutics.

Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.

Exploring non-invasive diagnostics for metabolic dysfunctionassociated fatty liver disease

The population with metabolic dysfunction-associated fatty liver disease(MAFLD)is increasingly common worldwide.Identification of people at risk of progression to advanced stages is necessary to timely offer interventions and appropriate care.Liver biopsy is currently considered the gold standard for the diagnosis and staging of MAFLD,but it has associated risks and limitations.This has spurred the exploration of non-invasive diagnostics for MAFLD,especially for steatohepatitis and fibrosis.These non-invasive approaches mostly include biomarkers and algorithms derived from anthropometric measurements,serum tests,imaging or stool metagenome profiling.However,they still need rigorous and widespread clinical validation for the diagnostic performance.

High glucose reduces Nrf2-dependent cRAGE release and enhances inflammasome-dependent IL-1βproduction in monocytes:the modulatory effects of EGCG

Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human diseases.However,the molecular mechanisms underlying sRAGE remain unclear.In this study,THP-1 monocytes were cultured in normal glucose(NG,5.5 mmol/L)and high glucose(HG,15 mmol/L)to investigate the effects of diabetesrelevant glucose concentrations on sRAGE and interleukin-1β(IL-1β)secretion.The modulatory effects of epigallocatechin gallate(EGCG)in response to HG challenge were also evaluated.HG enhanced intracellular reactive oxygen species(ROS)generation and RAGE expression.The secretion of sRAGE,including esRAGE and cRAGE,was reduced under HG conditions,together with the downregulation of a disintegrin and metallopeptidase 10(ADAM10)and nuclear factor erythroid 2-related factor 2(Nrf2)nuclear translocation.Mechanistically,the HG effects were counteracted by siRAGE and exacerbated by siNrf2.Chromatin immunoprecipitation results showed that Nrf2 binding to the ADAM10 promoter and HG interfered with this binding.Our data reinforce the notion that RAGE and Nrf2 might be sRAGE-regulating factors.Under HG conditions,the treatment of EGCG reduced ROS generation and RAGE activation.EGCG-stimulated cRAGE release was likely caused by the upregulation of the Nrf2-ADAM10 pathway.EGCG inhibited HG-mediated NLRP3 inflammasome activation at least partly by stimulating sRAGE,thereby reducing IL-1βrelease.

Conservation genomic investigation of an endangered conifer,Thuja sutchuenensis,reveals low genetic diversity but also low genetic load

Endangered species generally have small populations with low genetic diversity and a high genetic load.Thuja sutchuenensis is an endangered conifer endemic to southwestern China.It was once considered extinct in the wild,but in 1999 was rediscovered.However,little is known about its genetic load.We collected 67 individuals from five wild,isolated T.sutchuenensis populations,and used 636,151 SNPs to analyze the level of genetic diversity and genetic load in T.sutchuenensis to delineate the conservation units of T.sutchuenensis,based on whole transcriptome sequencing data,as well as target capture sequencing data.We found that populations of T.sutchuenensis could be divided into three groups.These groups had low levels genetic diversity and were moderately genetically differentiated.Our findings also indicate that T.sutchuenensis suffered two severe bottlenecks around the Last Glaciation Period and Last Glacial Maximum.Among Thuja species,T.sutchuenensis presented the lowest genetic load and hence might have purged deleterious mutations efficiently through purifying selection.However,distribution of fitness effects analysis indicated a high extinction risk for T.sutchuenensis.Multiple lines of evidence identified three management units for T.sutchuenensis.Although T.sutchuenensis possesses a low genetic load,low genetic diversity,suboptimal fitness,and anthropogenic pressures all present an extinction risk for this rare conifer.This might also hold true for many endangered plant species in the mountains all over the world.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Highly Thermoconductive,Strong Graphene‑Based Composite Films by Eliminating Nanosheets Wrinkles

Graphene-based thermally conductive composites have been proposed as effective thermal management materials for cooling high-power electronic devices.However,when flexible graphene nanosheets are assembled into macroscopic thermally conductive composites,capillary forces induce shrinkage of graphene nanosheets to form wrinkles during solution-based spontaneous drying,which greatly reduces the thermal conductivity of the composites.Herein,graphene nanosheets/aramid nanofiber(GNS/ANF)composite films with high thermal conductivity were prepared by in-plane stretching of GNS/ANF composite hydrogel networks with hydrogen bonds andπ-πinteractions.The in-plane mechanical stretching eliminates graphene nanosheets wrinkles by suppressing inward shrinkage due to capillary forces during drying and achieves a high in-plane orientation of graphene nanosheets,thereby creating a fast in-plane heat transfer channel.The composite films(GNS/ANF-60 wt%)with eliminated graphene nanosheets wrinkles showed a significant increase in thermal conductivity(146 W m^(−1)K^(−1))and tensile strength(207 MPa).The combination of these excellent properties enables the GNS/ANF composite films to be effectively used for cooling flexible LED chips and smartphones,showing promising applications in the thermal management of high-power electronic devices.

Exciting lattice oxygen of nickel–iron bi-metal alkoxide for efficient electrochemical oxygen evolution reaction

High efficiency,cost-effective and durable electrocatalysts are of pivotal importance in energy conversion and storage systems.The electro-oxidation of water to oxygen plays a crucial role in such energy conversion technologies.Herein,we report a robust method for the synthesis of a bimetallic alkoxide for efficient oxygen evolution reaction(OER)for alkaline electrolysis,which yields current density of 10 mA cm^(-2)at an overpotential of 215 mV in 0.1 M KOH electrolyte.The catalyst demonstrates an excellent durability for more than 540 h operation with negligible degradation in activity.Raman spectra revealed that the catalyst underwent structure reconstruction during OER,evolving into oxyhydroxide,which was the active site proceeding OER in alkaline electrolyte.In-situ synchrotron X-ray absorption experiment combined with density functional theory calculation suggests a lattice oxygen involved electrocatalytic reaction mechanism for the in-situ generated nickel–iron bimetal-oxyhydroxide catalyst.This mechanism together with the synergy between nickel and iron are responsible for the enhanced catalytic activity and durability.These findings provide promising strategies for the rational design of nonnoble metal OER catalysts.

Applications of SMILE-extracted lenticules in ophthalmology

AIM:To review recent innovations,challenges,and applications of small incision lenticule extraction(SMILE)extracted lenticule for treating ocular disorders.METHODS:A literature review was performed in the PubMed database,which was last updated on 30 December 2021.There was no limit regarding language.The authors evaluated the reference lists of the collected papers to find any relevant research.RESULTS:Due to the simplicity and accuracy of modern femtosecond lasers and the extensive development of SMILE surgery,many healthy human corneal stromal lenticules were extracted during surgery,motivating some professionals to investigate the SMILE lenticule reusability in different ocular disorders.In addition,new approaches had been developed to preserve,modify,and bioengineer the corneal stroma,leading to the optimal use of discarded byproducts such as lenticules from SMILE surgery.The lenticules can be effectively re-implanted into the autologous or allogenic corneas of human subjects to treat refractive errors,corneal ectasia,and corneal perforation and serve as a patch graft for glaucoma drainage devices with better cosmetic outcomes.CONCLUSION:SMILE-extracted lenticules could be a viable alternative to human donor corneal tissue.

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

Properties of the phase diagram from the Nambu-Jona-Lasino model with a scalar-vector interaction

We investigated the properties of the phase diagram of high-order susceptibilities,speed of sound,and polytropic index based on an extended Nambu-Jona-Lasinio model with an eight-quark scalar-vector interaction.Non-monotonic behavior was observed in all these quantities around the phase transition boundary,which also revealed the properties of the critical point.Further,this study indicated that the chiral phase transition boundary and critical point could vary depending on the scalarvector coupling constant G_(SV).At finite densities and temperatures,the negative G_(SV)term exhibited attractive interactions,which enhanced the critical point temperature and reduced the chemical potential.The G_(SV)term also affected the properties of the high-order susceptibilities,speed of sound,and polytropic index near the critical point.The non-monotonic(peak or dip)structures of these quantities shifted to a low baryon chemical potential(and high temperature)with a negative G_(SV).G_(SV)also changed the amplitude and range of the nonmonotonic regions.Therefore,the scalar-vector interaction was useful for locating the phase boundary and critical point in QCD phase diagram by comparing the experimental data.The study of the non-monotonic behavior of high-order susceptibilities,speed of sound,and polytropic index is of great interest,and further observations related to high-order susceptibilities,speed of sound,and polytropic index being found and applied to the search for critical points in heavy-ion collisions and the study of compact stars are eagerly awaited.

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other.The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity.In this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored.We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis changed.The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the neurons.In addition,by increasing the coupling strength of memristor synapses,synchronization performance is promoted.The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

Cannabinoids and endocannabinoids as therapeutics for nervous system disorders:preclinical models and clinical studies

Cannabinoids are lipophilic substances derived from Cannabis sativa that can exert a variety of effects in the human body.They have been studied in cellular and animal models as well as in human clinical trials for their therapeutic benefits in several human diseases.Some of these include central nervous system(CNS)diseases and dysfunctions such as forms of epilepsy,multiple sclerosis,Parkinson’s disease,pain and neuropsychiatric disorders.In addition,the endogenously produced cannabinoid lipids,endocannabinoids,are critical for normal CNS function,and if controlled or modified,may represent an additional therapeutic avenue for CNS diseases.This review discusses in vitro cellular,ex vivo tissue and in vivo animal model studies on cannabinoids and their utility as therapeutics in multiple CNS pathologies.In addition,the review provides an overview on the use of cannabinoids in human clinical trials for a variety of CNS diseases.Cannabinoids and endocannabinoids hold promise for use as disease modifiers and therapeutic agents for the prevention or treatment of neurodegenerative diseases and neurological disorders.

The effect of abiotic stresses on plant C:N:P homeostasis and their mitigation by silicon

In crop plants, various environmental stresses affect the balance of carbon, nitrogen, and phosphorus(C:N:P), leading to biochemical and physiological alterations and reductions in yield. Silicon(Si) is a beneficial element that alleviates plant stress. Most studies involving silicon have focused on physiological responses, such as improvements in photosynthetic processes, water use efficiency, and antioxidant defense systems. But recent research suggests that stressed plants facing either limited or excessive resources(water, light, nutrients, and toxic elements), strategically employ Si to maintain C:N:P homeostasis, thereby minimizing biomass losses. Understanding the role of Si in mitigating the impact of abiotic stresses on plants by regulating C:N:P homeostasis holds great potential for advancing sustainable agricultural practices in crop production. This review presents recent advances in characterizing the influence of environmental stresses on C:N:P homeostasis, as well as the role of Si in preserving C:N:P equilibrium and attenuating biological damage associated with abiotic stress. It underscores the beneficial effects of Si in sustaining C:N:P homeostasis and increasing yield via improved nutritional efficiency and stress mitigation.

A Comprehensive Survey on Advanced Persistent Threat (APT) Detection Techniques

The increase in number of people using the Internet leads to increased cyberattack opportunities.Advanced Persistent Threats,or APTs,are among the most dangerous targeted cyberattacks.APT attacks utilize various advanced tools and techniques for attacking targets with specific goals.Even countries with advanced technologies,like the US,Russia,the UK,and India,are susceptible to this targeted attack.APT is a sophisticated attack that involves multiple stages and specific strategies.Besides,TTP(Tools,Techniques,and Procedures)involved in the APT attack are commonly new and developed by an attacker to evade the security system.However,APTs are generally implemented in multiple stages.If one of the stages is detected,we may apply a defense mechanism for subsequent stages,leading to the entire APT attack failure.The detection at the early stage of APT and the prediction of the next step in the APT kill chain are ongoing challenges.This survey paper will provide knowledge about APT attacks and their essential steps.This follows the case study of known APT attacks,which will give clear information about the APT attack process—in later sections,highlighting the various detection methods defined by different researchers along with the limitations of the work.Data used in this article comes from the various annual reports published by security experts and blogs and information released by the enterprise networks targeted by the attack.

Amyloid-beta and tau protein beyond Alzheimer's disease

The aggregation of amyloid-beta peptide and tau protein dysregulation are implicated to play key roles in Alzheimer's disease pathogenesis and are considered the main pathological hallmarks of this devastating disease.Physiologically,these two proteins are produced and expressed within the normal human body.However,under pathological conditions,abnormal expression,posttranslational modifications,conformational changes,and truncation can make these proteins prone to aggregation,triggering specific disease-related cascades.Recent studies have indicated associations between aberrant behavior of amyloid-beta and tau proteins and various neurological diseases,such as Alzheimer's disease,Parkinson's disease,and amyotrophic lateral sclerosis,as well as retinal neurodegenerative diseases like Glaucoma and age-related macular degeneration.Additionally,these proteins have been linked to cardiovascular disease,cancer,traumatic brain injury,and diabetes,which are all leading causes of morbidity and mortality.In this comprehensive review,we provide an overview of the connections between amyloid-beta and tau proteins and a spectrum of disorders.

Boehmeria nivea var. strigosa (Urticaceae), a new variety from Southwest China

Boehmeria nivea var.strigosa Zeng Y.Wu&Y.Zhao,a new variety of B.nivea(Urticaceae)from Southwest China,is here described based on evidence from morphology and molecular phylogeny.This new variety is mainly characterized by its green abaxial leaf blade,partly connate stipules,and densely patent strigose hairs on stems and potioles.The phylogenetic analysis based on rbc L,nrDNA and rbc L+nrDNA datasets,revealed that all individuals of B.nivea var.strigosa formed a monophyletic group.The conservation status of B.nivea var.strigosa is assessed as“Near Threatened”(NT)according to IUCN evaluation criteria.The discovery of this new variety is not only crucial for the taxonomy of ramie,but also provides reference for the exploration and utilization of ramie.

Benzydamine hydrochloride ameliorates ethanol-induced inflammation in RAW 264.7 macrophages by stabilizing redox homeostasis

Objective:To evaluate the protective effect of benzydamine hydrochloride against ethanol-induced oxidative stress and inflammation in RAW 264.7 macrophages.Methods:RAW 264.7 macrophages were treated with ethanol(100 mM)and benzydamine hydrochloride(7.5μM).The imflammatory status was confirmed by measuring pro-(TNF-αand IL-6)and anti-inflammatory(IL-10)cytokines through ELISA and RT-PCR assays.Reactive oxygen species generation and mitochondrial membrane potential were investigated to study the protective role of benzydamine hydrochloride against ethanol-induced oxidative stress.Apoptosis detection was also investigated using flow cytometry and acridine orange/ethidium bromide staining.Results:Benzydamine hydrochloride significantly decreased the secretion of TNF-αand IL-6,as well as the generation of reactive oxygen species inside the cells,thereby stabilizing the mitochondrial membrane potential and reducing DNA fragmentation.The ethanol-induced cellular necrosis was also reversed by the administration of benzydamine hydrochloride.Conclusions:Benzydamine hydrochloride ameliorates ethanol-induced cell apoptosis and inflammation in RAW macrophages.