A Loop-Based and AGO-Incorporated Virtual Screening Model Targeting AGO-Mediated miRNA-mRNA Interactions for Drug Discovery to Rescue Bone Phenotype in Genetically Modified Mice

Zishen Yutai pills restore fertility in premature ovarian failure through regulating arachidonic acid metabolism and the ATK pathway

ETHNOPHARMACOLOGICAL RELEVANCE

The Zishen Yutai pills (ZYP), a Chinese medicinal formulation derived from the Qing Dynasty prescription "Shou Tai pills", have been documented to exhibit beneficial effects in clinical observations treating premature ovarian failure (POF). However, the anti-POF effects and its comprehensive systemic mechanism have not yet been clarified.

AIM OF THE REVIEW

Therapeutic effects and systemic mechanism of ZYP in POF were evaluated.

MATERIALS AND METHODS

After pulverization, sieving, and stirring, ZYP was administered intragastrically to cisplatin-induced POF mice at a dose of 1.95 mg/kg/d for 14 days. The anti-POF effects of ZYP were investigated by assessing the number of ovarian follicles at different developmental stages, as well as measuring serum estradiol (E2) levels and ovarian-expressed anti-Müllerian hormone (AMH). Reproductive performance and offspring health were evaluated to predict fertility restoration. Furthermore, a combination of proteomic and metabolomic profiling was employed to elucidate the underlying molecular mechanism of ZYP in treating POF. Western blot (WB) analyses and real-time quantitative polymerase chain reaction (RT-qPCR) were conducted to explore the mechanisms through which ZYP exerted its anti-POF effects.

RESULTS

We have demonstrated that oral administration of ZYP reversed the reduction in follicles at different developmental stages and stimulated the expressions of serum E2 and ovarian-expressed AMH in a cisplatin-induced POF model. Additionally, ZYP ameliorated follicle apoptosis in ovaries affected by cisplatin-induced POF. Furthermore, treatment with ZYP restored the quantity and quality of oocytes, as well as enhanced fertility. Our results revealed 62 differentially expressed proteins (DEPs) through proteomic analyses and identified 26 differentially expressed metabolites (DEMs) through metabolomic analyses. Both DEPs and DEMs were highly enriched in the arachidonic acid (AA) metabolism pathway. ZYP treatment effectively upregulated the protein and mRNA expression of critical targets in AA metabolism and the AKT pathway, including CYP17α1, HSD3β1, LHR, STAR, and AKT, in cisplatin-induced POF mice.

CONCLUSIONS

These results indicated that ZYP exerted protective effects against POF and restored fertility from cisplatin-induced apoptosis. ZYP could be a satisfying alternative treating POF.

Evaluation of long noncoding RNA (LncRNA) in pathogenesis of HELLP syndrome: diagnostic and future approach

HELLP syndrome is a disorder during pregnancy which is defined by elevation of liver enzymes, haemolysis, and low platelet count. This syndrome is a multifactorial one and both genetic and environmental components can have a crucial role in this syndrome's pathogenesis. Long noncoding RNAs (lncRNAs), are defined as long non-protein coding molecules (more than 200 nucleotides), which are functional units in most cellular processes such as cell cycle, differentiation, metabolism and some diseases progression. As these markers discovered, there has been some evidence that they have an important role in the function of some organs, such as placenta; therefore, alteration and dysregulation of these RNAs can develop or alleviate HELLP disorder. Although the role of lncRNAs has been shown in HELLP syndrome, the process is still unclear. In this review, our purpose is to evaluate the association between molecular mechanisms of lncRNAs and HELLP syndrome pathogenicity to elicit some novel approaches for HELLP diagnosis and treatment.

BeO nanotube as a promising material for anticancer drugs delivery system

In this research, the application of BeO nanotube (BeONT) as a nanocarrier for Fluorouracil (5-FU) anticancer drug has been studied by density functional theory (DFT) approach. The method ωB97XD with 6-31 G** basis set were employed. A precise surface study, shows that there are two directions for 5-FU adsorption that did not deliver any of the imaginary frequency vibrational spectra, identifying that all relaxation structures are at the lowest energy level. Based on our calculations, the energy of adsorption for 5FU@BeONT structures are range -120 to -168 kJ/mol, in the gas phase and -395 to 4-00 kJ/mol in the aqueous phase. The highest and the lowest values of adsorption energy are both in strong physical adsorption. Due to receiving an electronic charge from 5-FU, BeONT exhibited a p-type semiconducting feature for all positions. In addition, based on natural bond orbital (NBO) analysis, the direction of charge transfer was from fluorine's σ orbitals of the drug to n* orbitals (O and Be atoms) of BeONT with a considerable amount of transferred energy. BeONT can be employed as a potential strong carrier for 5-FU drugs for practical purposes based on our findings.

Alkali metal-doped borospherenes M@C4B32 (M = K, Na, and Li) as a highly efficient alternative for the drug delivery

CONTEXT

Nanomaterials enjoy a great surface-to-surface area ratio, small size, extremely high stability, satisfactory bio-compatibility, improved permeability, specificity in receptor targeting, and tunable lifetime. This paper investigates alkali metal-doped borospherenes M@C4B32 (in which M denotes K, Na, and Li) as a highly efficient alternative for the delivery of drugs using density functional theory (DFT) calculations. A borospherene with a B₃₆ nanocage doped with four C atoms (i.e., C4B32) recently showed promising performance. Therefore, the present work investigates C4B32 nanoclusters doped with alkali metals for the effective delivery of drugs.

METHODS

This paper primarily seeks to evaluate the interaction between thioguanine (TG) as a cancer drug and pristine M@C4B32 through DFT (PBE/6-31 + G (d)) calculations. The UV-Vis spectroscopy indicated a redshift in the complex electronic spectra to higher wavelengths (i.e., lower energy levels). Hence, K@C4B32 was concluded to be effective in TG delivery.

Improved deep convolutional neural networks using chimp optimization algorithm for Covid19 diagnosis from the X-ray images

Applying Deep Learning (DL) in radiological images (i.e., chest X-rays) is emerging because of the necessity of having accurate and fast COVID-19 detectors. Deep Convolutional Neural Networks (DCNN) have been typically used as robust COVID-19 positive case detectors in these approaches. Such DCCNs tend to utilize Gradient Descent-Based (GDB) algorithms as the last fully-connected layers' trainers. Although GDB training algorithms have simple structures and fast convergence rates for cases with large training samples, they suffer from the manual tuning of numerous parameters, getting stuck in local minima, large training samples set requirements, and inherently sequential procedures. It is exceedingly challenging to parallelize them with Graphics Processing Units (GPU). Consequently, the Chimp Optimization Algorithm (ChOA) is presented for training the DCNN's fully connected layers in light of the scarcity of a big COVID-19 training dataset and for the purpose of developing a fast COVID-19 detector with the capability of parallel implementation. In addition, two publicly accessible datasets termed COVID-Xray-5 k and COVIDetectioNet are used to benchmark the proposed detector known as DCCN-Chimp. In order to make a fair comparison, two structures are proposed: i-6c-2 s-12c-2 s and i-8c-2 s-16c-2 s, all of which have had their hyperparameters fine-tuned. The outcomes are evaluated in comparison to standard DCNN, Hybrid DCNN plus Genetic Algorithm (DCNN-GA), and Matched Subspace classifier with Adaptive Dictionaries (MSAD). Due to the large variation in results, we employ a weighted average of the ensemble of ten trained DCNN-ChOA, with the validation accuracy of the weights being used to determine the final weights. The validation accuracy for the mixed ensemble DCNN-ChOA is 99.11%. LeNet-5 DCNN's ensemble detection accuracy on COVID-19 is 84.58%. Comparatively, the suggested DCNN-ChOA yields over 99.11% accurate detection with a false alarm rate of less than 0.89%. The outcomes show that the DCCN-Chimp can deliver noticeably superior results than the comparable detectors. The Class Activation Map (CAM) is another tool used in this study to identify probable COVID-19-infected areas. Results show that highlighted regions are completely connected with clinical outcomes, which has been verified by experts.

Improved deep convolutional neural networks using chimp optimization algorithm for Covid19 diagnosis from the X-ray images

Applying Deep Learning (DL) in radiological images (i.e., chest X-rays) is emerging because of the necessity of having accurate and fast COVID-19 detectors. Deep Convolutional Neural Networks (DCNN) have been typically used as robust COVID-19 positive case detectors in these approaches. Such DCCNs tend to utilize Gradient Descent-Based (GDB) algorithms as the last fully-connected layers' trainers. Although GDB training algorithms have simple structures and fast convergence rates for cases with large training samples, they suffer from the manual tuning of numerous parameters, getting stuck in local minima, large training samples set requirements, and inherently sequential procedures. It is exceedingly challenging to parallelize them with Graphics Processing Units (GPU). Consequently, the Chimp Optimization Algorithm (ChOA) is presented for training the DCNN's fully connected layers in light of the scarcity of a big COVID-19 training dataset and for the purpose of developing a fast COVID-19 detector with the capability of parallel implementation. In addition, two publicly accessible datasets termed COVID-Xray-5 k and COVIDetectioNet are used to benchmark the proposed detector known as DCCN-Chimp. In order to make a fair comparison, two structures are proposed: i-6c-2 s-12c-2 s and i-8c-2 s-16c-2 s, all of which have had their hyperparameters fine-tuned. The outcomes are evaluated in comparison to standard DCNN, Hybrid DCNN plus Genetic Algorithm (DCNN-GA), and Matched Subspace classifier with Adaptive Dictionaries (MSAD). Due to the large variation in results, we employ a weighted average of the ensemble of ten trained DCNN-ChOA, with the validation accuracy of the weights being used to determine the final weights. The validation accuracy for the mixed ensemble DCNN-ChOA is 99.11%. LeNet-5 DCNN's ensemble detection accuracy on COVID-19 is 84.58%. Comparatively, the suggested DCNN-ChOA yields over 99.11% accurate detection with a false alarm rate of less than 0.89%. The outcomes show that the DCCN-Chimp can deliver noticeably superior results than the comparable detectors. The Class Activation Map (CAM) is another tool used in this study to identify probable COVID-19-infected areas. Results show that highlighted regions are completely connected with clinical outcomes, which has been verified by experts.

Critical signaling pathways governing colitis-associated colorectal cancer: Signaling, therapeutic implications, and challenges

Long-term colitis in people with inflammatory bowel disease (IBD) may lead to colon cancer called colitis-associated colorectal cancer (CAC). Since the advent of preclinical prototypes of CAC, various immunological messaging cascades have been identified as implicated in developing this disease. The toll-like receptor (TLR)s, Janus kinase (JAK)-signal transducer and activator of transcription (STAT), Nuclear factor-kappa B (NF-κB), mammalian target of rapamycin complex (mTOR), autophagy, and oxidative stress are only a few of the molecular mechanisms that have been recognized as major components to CAC progression. These pathways may also represent attractive medicinal candidates for the prevention and management of CAC. CAC signaling mechanisms at the molecular level and how their dysregulation may cause illness are summarized in this comprehensive overview.

Histone methyltransferase Setdb1 mediates osteogenic differentiation by suppressing the expression of miR-212-3p under mechanical unloading

Emerging evidence indicates that multiple mechanisms are involved in bone loss induced by mechanical unloading. Thus far, few study has established the pathophysiological role of histone modification for osteogenic differentiation under mechanical unloading. Here we demonstrated that the histone H3 lysine 9 (H3K9) methyltransferase Setdb1, which was sensitive to mechanical unloading, was increased during osteogenic differentiation of MC3T3-E1 cells for the first time. Knockdown of Setdb1 significantly blocked osteoblast function in vivo and in vitro. Through bioinformatics analysis of candidate miRNAs regulated by H3K9me3, we further identified that Setdb1 inhibited the expression of miR-212-3p by regulating the formation of H3K9me3 in the promoter region. Mechanically, we revealed that miR-212-3p was upregulated under mechanical unloading and suppressed osteogenic differentiation by directly downregulating High mobility group box 1 protein (Hmgb1) expression. Furthermore, we verified the molecular mechanism of the SETDB1/miR-212-3p/HMGB1 pathway in hFOB cells under mechanical unloading. In summary, these data demonstrate the essential function of the Setdb1/miR-212-3p/Hmgb1 pathway in osteogenic differentiation under mechanical unloading, and present a potential protective strategies against bone loss induced by mechanical unloading.

Design and Prediction of Aptamers Assisted by In Silico Methods

An aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX process is time-consuming, and the characterization of aptamer candidates selected through it requires additional effort. Here, we describe in silico methods in order to suggest the most efficient way to develop aptamers and minimize the laborious effort required to screen and optimise aptamers. We investigated several methods for the estimation of aptamer-target molecule binding through conformational structure prediction, molecular docking, and molecular dynamic simulation. In addition, examples of machine learning and deep learning technologies used to predict the binding of targets and ligands in the development of new drugs are introduced. This review will be helpful in the development and application of in silico aptamer screening and characterization.

Advances in Single-component inorganic nanostructures for photoacoustic imaging guided photothermal therapy

Phototheranostic based on photothermal therapy (PTT) and photoacoustic imaging (PAI), as one of avant-garde medical techniques, have sparked growing attention because it allows noninvasive, deeply penetrative, and highly selective and effective therapy. Among a variety of phototheranostic nanoagents, single-component inorganic nanostructures are found to be novel and attractive PAI and PTT combined nanotheranostic agents and received tremendous attention, which not only exhibit structural controllability, high tunability in physiochemical properties, size-dependent optical properties, high reproducibility, simple composition, easy functionalization, and simple synthesis process, but also can be endowed with multiple therapeutic and imaging functions, realizing the superior therapy result along with bringing less foreign materials into body, reducing systemic side effects and improving the bioavailability. In this review, according to their synthetic components, conventional single-component inorganic nanostructures are divided into metallic nanostructures, metal dichalcogenides, metal oxides, carbon based nanostructures, upconversion nanoparticles (UCNPs), metal organic frameworks (MOFs), MXenes, graphdiyne and other nanostructures. On the basis of this category, their detailed applications in PAI guide PTT of tumor treatment are systematically reviewed, including synthesis strategies, corresponding performances, and cancer diagnosis and therapeutic efficacy. Before these, the factors to influence on photothermal effect and the principle of in vivo PAI are briefly presented. Finally, we also comprehensively and thoroughly discussed the limitation, potential barriers, future perspectives for research and clinical translation of this single-component inorganic nanoagent in biomedical therapeutics.

In vitro anticancer and antibacterial performance of biosynthesized Ag and Ce co-doped ZnO NPs

The great potential of zinc oxide nanoparticles (ZnO NPs) for biomedical applications is attributed to their physicochemical properties. In this work, pure and Ag and Ce dual-doped ZnO NPs were synthesized through a facile and green route to examine their cytotoxicity in breast cancer and normal cells. The initial preparation of dual-doped nanoparticles was completed by the usage of taranjabin. The synthesis of Ag and Ce dual-doped ZnO NPs was started with preparing the Ce:Ag ratios of 1:1, 1:2, and 1:4. The cytotoxicity effects of synthesized nanoparticles against breast normal cells (MCF-10A) and breast cancer cells (MDA-MB-231) were examined. The hexagonal structure of synthesized nanoparticles was observed through the results of X-ray diffraction (XRD). Scanning electron microscopy (SEM) images exhibited the spherical shape and smooth surfaces of prepared particles along with the homogeneous distribution of Ag and Ce in ZnO with high-quality lattice fringes without any distortions. According to the cytotoxic results, the effects of Ag/Ce dual-doped ZnO NPs on breast cancer (MDA-MB-231) cells were significantly more than of pure ZnO NPs, while dual-doped and pure nanoparticles remained indifferent towards breast normal (MCF-10A) cells. In addition, we investigated the antimicrobial activity against harmful bacteria.

Cellular and molecular basis of therapeutic approaches to breast cancer

In recent decades, there has been a significant amount of research into breast cancer, with some important breakthroughs in the treatment of both primary and metastatic breast cancers. It's a well-known fact that treating breast cancer is still a challenging endeavour even though physicians have a fantastic toolset of the latest treatment options at their disposal. Due to limitations of current clinical treatment options, traditional chemotherapeutic drugs, and surgical options are still required to address this condition. In recent years, there have been several developments resulting in a wide range of treatment options. This review article discusses the cellular and molecular foundation of chemotherapeutic drugs, endocrine system-based treatments, biological therapies, gene therapy, and innovative techniques for treating breast cancer.

Fabrication of chitosan-gelatin films incorporated with thymol-loaded alginate microparticles for controlled drug delivery, antibacterial activity and wound healing: In-vitro and in-vivo studies

Previously, studies have demonstrated the unique characteristics of chitosan-gelatin films as wound dressings applications. However, their application has been limited due to their inadequacy of antimicrobial and anti-inflammatory characteristics. To improve the intended multifunctional characteristics of chitosan-gelatin film, in this study, we designed a novel composite film with the capability of controlled and prolonged release of thymol as a natural antioxidant and antimicrobial drug. Here, thymol-loaded ALG MPs (Thymol-ALG MPs) were prepared by electrospraying method and incorporated into the chitosan-gelatin film. The composite wound dressings of Thymol-ALG MPs incorporated in chitosan-gelatin film (CS-GEL/Thymol-ALG MPs) were characterized by in vitro and in vivo evaluations. The Thymol-ALG MPs demonstrated spherical and uniform morphology, with high encapsulation efficiency (88.9 ± 1.1 %). The CS-GEL/Thymol-ALG MPs exhibited high antibacterial activity against both Gram-positive and Gram-negative bacteria and no cytotoxicity for the L929 fibroblast cells. The release trend of thymol from CS-GEL/Thymol-ALG MPs and Thymol-ALG MPs followed a pseudo-Fickian diffusion mechanism. This wound dressing effectively accelerates the wound healing process at rats' full-thickness skin excisions. Also, the histological analysis demonstrated that the CS-GEL/Thymol-ALG MPs could significantly enhance epithelialization, collagen deposition, and induce skin regeneration. The present antibacterial composite film has promising characteristics for wound dressings applications.

Anti-diabetic Activity of Brucine in Streptozotocin-Induced Rats: In Silico, In Vitro, and In Vivo Studies

Diabetes mellitus (DM) is a complex and multiple group of disorders, and understanding the molecular mechanisms is a key role in identifying various markers involved in the diagnosis of the disease. Brucine is derived from the seeds of Strychnos nux-vomica L. (Loganiaceae), which has been used in traditional medicine to cure a variety of ailments, such as chronic rheumatism, nervous system diseases, dyspepsia, gonorrhea, anemia, and bronchitis, and has analgesic, anti-inflammatory, anti-oxidant, anti-snake venom, and anti-diabetic properties. The anti-diabetic potential of brucine was studied utilizing in vitro, in silico, in vivo, and molecular methods, including streptozotocin-induced diabetic rat models, α-glucosidase and α-amylase inhibitory assays, and via Auto-DocVina software. Brucine exhibits binding affinities of -5.0 to -10.1 Kcal/mol against chosen protein targets, according to an in silico investigation. In vitro studies revealed that brucine inhibited the enzymes α-amylase and α-glucosidase, and brucine (20 mg/kg) reduced blood glucose levels, oral glucose tolerance overload, body weight, glycosylated hemoglobin levels, total cholesterol, triglycerides, low-density lipoprotein, alanine transaminase, aspartate aminotransferase, total bilirubin, and alkaline phosphatase and elevated high-density lipoprotein levels in in vivo studies. The brucine binding energy against certain protein targets ranges from -5.0 to -10.1 Kcal/mol. It has anti-diabetic, anti-hyperlipidemic, hepatoprotective, anti-oxidant, and anti-inflammatory properties, which are mediated via inhibition of α-glucosidase and α-amylase.

The role and therapeutic applications of exosomes in multiple sclerosis disease

A range of the central nervous system (CNS) and immune cells are affected by multiple sclerosis (MS), a complex autoimmune disease of the CNS. Chronic neuroinflammation, demyelination, and neuronal death are all features of MS, but the disease's molecular mechanisms are unknown. Exosomes are small, membrane-bound extracellular vesicles with a crucial role in cell communication. They are stable in biological fluids and emerge from the cell membrane during endocytic internalization. It might be possible to recognize better the mechanisms involved in the development and progress of illnesses by understanding the variety of exosomal contents and their associated targets, like neurologic disorders. In this review, we sought to bring together important data on the biology of exosomes in MS and highlight discoveries on these nanoparticles' prognostic, diagnostic and therapeutic potential.

Metals-triggered compound CDPDP exhibits anti-arthritic behavior by downregulating the inflammatory cytokines, and modulating the oxidative storm in mice models with extensive ADMET, docking and simulation studies

Triggering through abiotic stress, including chemical triggers like heavy metals, is a new technique for drug discovery. In this research, the effect of heavy metal Nickel on actinobacteria Streptomyces sp. SH-1327 to obtain a stress-derived compound was firstly investigated. A new compound cyclo-(D)-Pro-(D)-Phe (CDPDP) was triggered from the actinobacteria strain SH-1327 with the addition of nickel ions 1 mM. The stress compound was further evaluated for its anti-oxidant, analgesic, and anti-inflammatory activity against rheumatoid arthritis through in-vitro and in-vivo assays in albino mice. A remarkable in-vitro anti-oxidant potential of CDPDP was recorded with the IC₅₀ value of 30.06 ± 5.11 μg/ml in DPPH, IC₅₀ of 18.98 ± 2.91 against NO free radicals, the IC₅₀ value of 27.15 ± 3.12 against scavenging ability and IC₅₀ value of 28.40 ± 3.14 μg/ml for iron chelation capacity. Downregulation of pro-inflammatory mediators (NO and MDA), suppressed levels of pro-inflammatory cytokines (TNF-α, IL-6, IL-Iβ) and upregulation of expressions of anti-oxidant enzymes (GSH, catalase, and GST) unveiled its anti-inflammatory potential. CDPDP was analyzed in human chondrocyte cell line CHON-001 and the results demonstrated that CDPDP significantly increased cell survival, and inhibited apoptosis of IL-1β treated chondrocytes and IL-1β induced matrix degrading markers. In addition, to evaluate the mitochondrial fitness of CHON-001 cells, CDPDP significantly upregulated pgc1-α, the master regulator of mitochondrial biogenesis, indicating that CDPDP provides protective effects in CHON-001 cells. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile of the CDPDP showed that CDPDP is safe in cases of hepatotoxicity, cardiotoxicity, and cytochrome inhibition. Furthermore, docking results showed good binding of CDPDP with IL-6-17.4 kcal/mol, and the simulation studies proved the stability between ligand and protein. Therefore, the findings of the current study prospect CDPDP as a potent anti-oxidant and a plausible anti-arthritic agent with a strong pharmacokinetic and pharmacological profile.

Pharmacological basis of bergapten in gastrointestinal diseases focusing on H+/K+ ATPase and voltage-gated calcium channel inhibition: A toxicological evaluation on vital organs

Aim and objectives: This study aimed to establish a pharmacological basis for evaluating the effects of bergapten (5-methoxypsoralen) in gastrointestinal diseases and assessment of its toxicological profile.

Methods: The pharmacokinetic profile was evaluated using the SwissADME tool. AUTODOCK and PyRx were used for evaluating the binding affinities. The obtained results were further investigated for a post-dock analysis using Discovery Studio Visualizer 2016. The Desmond software package was used to conduct molecular dynamic simulations of best bound poses. Bergapten was further investigated for antidiarrheal, anti-secretory, charcoal meal transit time, anti-ulcer, anti-H. pylori activity.

Results: Bergapten at a dose of 50, 100, and 200 mg/kg was proved effective in reducing diarrheal secretions, intestinal secretions, and distance moved by charcoal meal. Bergapten at the aforementioned doses acts as a gastroprotective agent in the ethanol-induced ulcer model that can be attributed to its effectiveness against H. pylori. Bergapten shows concentration-dependent relaxation of both spontaneous and K+ (80 mM)-induced contractions in the isolated rabbit jejunum model; the Ca2+ concentration–response curves (CRCs) were shifted to the right showing potentiating effect similar to papaverine. For molecular investigation, the H+/K+ ATPase inhibitory assay indicated inhibition of the pump comparable to omeprazole. Oxidative stress markers GST, GSH, and catalase showed increased expression, whereas the expression of LPO (lipid peroxidation) was reduced. Histopathological examination indicated marked improvement in cellular morphology. ELISA and western blot confirmed the reduction in inflammatory mediator expression. RT-PCR reduced the mRNA expression level of H+/K+ ATPase, confirming inhibition of the pump. The toxicological profile of bergapten was evaluated by an acute toxicity assay and evaluated for behavioral analysis, and the vital organs were used to analyze biochemical, hematological, and histopathological examination.

Conclusion: Bergapten at the tested doses proved to be an antioxidant, anti-inflammatory, anti-ulcer, and antidiarrheal agent and relatively safe in acute toxicity assay.

Does green finance and energy policy paradox demonstrate green economic recovery: Role of social capital and public health

Green economy development has become a mainstream value orientation in social and global economic development to protect and improve the ecological environment. Multiple stakeholders are needed to address complex issues, such as climate change and its impact on the ecological environment and public health. This study investigates the impact of energy policy and green finance on green economic recovery via the controlling role of social capital and public health. An entropy approach was used to measure the green economic index in addition to an econometric approximation for interpreting the longitudinal dataset for the scenarios for E7 countries between 2010 and 2020. The findings show that the development of green finance significantly improves green productivity. Higher levels of economic and social conditions, a lower level of public involvement in environmental protection, and a higher level of pollution amplify this positive effect. On the other hand, energy policy can enhance the impact of green finance development. The findings suggest that the empirical findings benefit green finance planning and energy policy.

The influence and mechanism of health expenditures on investment of financial assets decisions: A case study of China's economy

Policymakers worldwide have been actively involved in the past few decades to ensure that human diseases are kept to a minimum. A new econometric technique, dynamic ARDL simulations, was used in this study to estimate and model the influence of health expenditures on investment in non-financial assets in China from 1990 to 2019. An economic growth framework, gross capital formation, information and communication technologies, foreign direct investment, and carbon emissions are all considered in the empirical model-the analysis produced interesting results. First, the estimates show that health expenditures and foreign direct investment have a significant long-run decreasing impact on non-financial assets in China by 0.451 and 0.234%. Second, economic growth and gross capital formation significantly affect the economy's non-financial assets. Likewise, ICT and carbon emissions also positively correlate with an explained variable in China. The findings show that the economy is becoming less investment-intensive as health spending and foreign direct investment rise. The study develops important policy implications for the selected country to achieve desired targets based on the empirical results.

Influence of the coiling porosity on the risk reduction of the cerebral aneurysm rupture: computational study

The formation and progress of cerebral aneurysm is highly associated with hemodynamic factors and blood flow feature. In this study, comprehensive efforts are done to investigate the blood hemodynamic effects on the creation and growth of the Internal Carotid Artery. The computational fluid dynamic method is used for the visualization of the bloodstream inside the aneurysm. Transitional, non-Newtonian and incompressible conditions are considered for solving the Navier-Stokes equation to achieve the high-risk region on the aneurysm wall. OSI and WSS of the aneurysm wall are compared within different blood flow stages. The effects of blood viscosity and coiling treatment on these factors are presented in this work. Our study shows that in male patients (HCT = 0.45), changing the porosity of coiling from 0.89 with 0.79 would decreases maximum OSI up to 75% (in maximum acceleration). However, this effect is limited to about 45% for female patients (HCT = 0.35).

The effect of disease-modifying antirheumatic drugs (DMARDs) on bone homeostasis in rheumatoid arthritis (RA) patients

The autoimmune disease known as rheumatoid arthritis (RA) has been linked to the deterioration of bone. Bone erosion is a hallmark of RA and is linked to the severity of the disease as well as a poor functional result. Erosion of periarticular cortical bone is a common feature seen on plain radiographs of patients with RA. This characteristic feature is the result of excessive bone resorption and inadequate formation of bone. It has been determined that there is a complex interaction between the inflammatory condition seen in RA and bone destruction. Increased knowledge of the pathways and other mechanisms involved in osteoclastogenesis has resulted from advances in both animal and clinical investigations. Also, Biological and targeted medicines have modified RA's bone metabolism. Here, we provide a narrative overview of the literature on the pathomechanisms of bone structure involved in biological and targeted treatments for RA and also, the clinical implications of disease-modifying antirheumatic drugs (DMARDs) are discussed. In light of the fact that these newer treatments present patients with RA with new possibilities for disease improvement and symptom control, it is imperative that additional rigorous evidence be gathered to provide a clinical reference for both patients and their treating physicians.

DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

Alzheimer’s Disease (AD) is a neurological brain disorder that causes dementia and neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a kind of Artificial Intelligence (AI), has paved the way for new AD detection and automation methods. The DL model’s prediction accuracy depends on the dataset’s size. The DL models lose their accuracy when the dataset has an imbalanced class problem. This study aims to use the deep Convolutional Neural Network (CNN) to develop a reliable and efficient method for identifying Alzheimer’s disease using MRI. In this study, we offer a new CNN architecture for diagnosing Alzheimer’s disease with a modest number of parameters, making it perfect for training a smaller dataset. This proposed model correctly separates the early stages of Alzheimer’s disease and displays class activation patterns on the brain as a heat map. The proposed Detection of Alzheimer’s Disease Network (DAD-Net) is developed from scratch to correctly classify the phases of Alzheimer’s disease while reducing parameters and computation costs. The Kaggle MRI image dataset has a severe problem with class imbalance. Therefore, we used a synthetic oversampling technique to distribute the image throughout the classes and avoid the problem. Precision, recall, F1-score, Area Under the Curve (AUC), and loss are all used to compare the proposed DAD-Net against DEMENET and CNN Model. For accuracy, AUC, F1-score, precision, and recall, the DAD-Net achieved the following values for evaluation metrics: 99.22%, 99.91%, 99.19%, 99.30%, and 99.14%, respectively. The presented DAD-Net outperforms other state-of-the-art models in all evaluation metrics, according to the simulation results.

Classification of Marine Mammals Using the Trained Multilayer Perceptron Neural Network with the Whale Algorithm Developed with the Fuzzy System

The existence of various sounds from different natural and unnatural sources in the deep sea has caused the classification and identification of marine mammals intending to identify different endangered species to become one of the topics of interest for researchers and activist fields. In this paper, first, an experimental data set was created using a designed scenario. The whale optimization algorithm (WOA) is then used to train the multilayer perceptron neural network (MLP-NN). However, due to the large size of the data, the algorithm has not determined a clear boundary between the exploration and extraction phases. Next, to support this shortcoming, the fuzzy inference is used as a new approach to developing and upgrading WOA called FWOA. Fuzzy inference by setting FWOA control parameters can well define the boundary between the two phases of exploration and extraction. To measure the performance of the designed categorizer, in addition to using it to categorize benchmark datasets, five benchmarking algorithms CVOA, WOA, ChOA, BWO, and PGO were also used for MLPNN training. The measured criteria are concurrency speed, ability to avoid local optimization, and the classification rate. The simulation results on the obtained data set showed that, respectively, the classification rate in MLPFWOA, MLP-CVOA, MLP-WOA, MLP-ChOA, MLP-BWO, and MLP-PGO classifiers is equal to 94.98, 92.80, 91.34, 90.24, 89.04, and 88.10. As a result, MLP-FWOA performed better than other algorithms.

A molecular modeling on the potential application of beryllium oxide nanotube for delivery of hydroxyurea anticancer drug

Within this work, we scrutinized the use of BeO nanotube (BeONT) as a nanocarrier for the anticancer drug hydroxyurea (HU) through density functional theory (DFT) calculations. We utilized the functional ꞷB97XD and the basis set 6-31G**. Based on a detailed surface analysis, HU was adsorbed on the surface of the nanotube through 4 different orientations. Also, no vibrational spectra exhibited imaginary frequencies, showing the minimum energy of the relaxed structures. The maximum adsorption energy and the minimum adsorption energy are in strong physical adsorption. The BeONT exhibited p-type semiconducting characteristics in all orientations since it received electronic charge from HU. The results demonstrate the possibility of using the BeONT as a promising carrier for HU drugs.

The neuroprotective effects of fisetin, a natural flavonoid in neurodegenerative diseases: Focus on the role of oxidative stress

Oxidative stress (OS) disrupts the chemical integrity of macromolecules and increases the risk of neurodegenerative diseases. Fisetin is a flavonoid that exhibits potent antioxidant properties and protects the cells against OS. We have viewed the NCBI database, PubMed, Science Direct (Elsevier), Springer-Nature, ResearchGate, and Google Scholar databases to search and collect relevant articles during the preparation of this review. The search keywords are OS, neurodegenerative diseases, fisetin, etc. High level of ROS in the brain tissue decreases ATP levels, and mitochondrial membrane potential and induces lipid peroxidation, chronic inflammation, DNA damage, and apoptosis. The subsequent results are various neuronal diseases. Fisetin is a polyphenolic compound, commonly present in dietary ingredients. The antioxidant properties of this flavonoid diminish oxidative stress, ROS production, neurotoxicity, neuro-inflammation, and neurological disorders. Moreover, it maintains the redox profiles, and mitochondrial functions and inhibits NO production. At the molecular level, fisetin regulates the activity of PI3K/Akt, Nrf2, NF-κB, protein kinase C, and MAPK pathways to prevent OS, inflammatory response, and cytotoxicity. The antioxidant properties of fisetin protect the neural cells from inflammation and apoptotic degeneration. Thus, it can be used in the prevention of neurodegenerative disorders.

Phytochemical and toxicological evaluation of Zephyranthes citrina

Drugs obtained from medicinal plants have always played a pivotal role in the field of medicine and to identify novel compounds. Safety profiling of plant extracts is of utmost importance during the discovery of new biologically active compounds and the determination of their efficacy. It is imperative to conduct toxicity studies before exploring the pharmacological properties and perspectives of any plant. The present work aims to provide a detailed insight into the phytochemical and toxicological profiling of methanolic extract of Zephyranthes citrina (MEZ). Guidelines to perform subacute toxicity study (407) and acute toxicity study (425) provided by the organization of economic cooperation and development (OECD) were followed. A single orally administered dose of 2000 mg/kg to albino mice was used for acute oral toxicity testing. In the subacute toxicity study, MEZ in doses of 100, 200, and 400 mg/kg was administered orally, consecutive for 28 days. Results of each parameter were compared to the control group. In both studies, the weight of animals and their selected organs showed consistency with that of the control group. No major toxicity or organ damage was recorded except for some minor alterations in a few parameters such as in the acute study, leukocyte count was increased and decreased platelet count, while in the subacute study platelet count increased in all doses. In the acute toxicity profile liver enzymes Alanine aminotransferase (ALT), as well as, aspartate aminotransferase (AST) were found to be slightly raised while alkaline phosphatase (ALP) was decreased. In subacute toxicity profiling, AST and ALT were not affected by any dose while ALP was decreased only at doses of 200 and 400 mg/kg. Uric acid was raised at a dose of 100 mg/kg. In acute toxicity, at 2000 mg/kg, creatinine and uric acid increased while urea levels decreased. Therefore, it is concluded that the LD₅₀ of MEZ is more than 2000 mg/kg and the toxicity profile of MEZ was generally found to be safe.

An intelligent DNA nanorobot for detection of MiRNAs cancer biomarkers using molecular programming to fabricate a logic-responsive hybrid nanostructure

Herein, we designed a DNA framework-based intelligent nanorobot using toehold-mediated strand displacement reaction-based molecular programming and logic gate operation for the selective and synchronous detection of miR21 and miR125b, which are known as significant cancer biomarkers. Moreover, to investigate the applicability of our design, DNA nanorobots were implemented as capping agents onto the pores of MSNs. These agents can develop a logic-responsive hybrid nanostructure capable of specific drug release in the presence of both targets. The prosperous synthesis steps were verified by FTIR, XRD, BET, UV-visible, FESEM-EDX mapping, and HRTEM analyses. Finally, the proper release of the drug in the presence of both target microRNAs was studied. This Hybrid DNA Nanostructure was designed with the possibility to respond to any target oligonucleotides with 22 nucleotides length.

Define the Two Molecular Subtypes of Epithelioid Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a fatal disease of respiratory system. Despite the availability of invasive biomarkers with promising results, there are still significant diagnostic and therapeutic challenges in the treatment of MPM. One of three main mesothelioma cell types, epithelioid mesothelioma makes up approximately 70% of all mesothelioma cases. Different observational findings are under process, but the molecular heterogeneity and pathogenesis of epithelioid malignant pleural mesothelioma (eMPM) are still not well understood. Through molecular analysis, expression profiling data were used to determine the possibility and optimal number of eMPM molecular subtypes. Next, clinicopathological characteristics and different molecular pathways of each subtype were analyzed to prospect the clinical applications and advanced mechanisms of eMPM. In this study, we identified two distinct epithelioid malignant pleural mesothelioma subtypes with distinct gene expression patterns. Subtype I eMPMs were involved in steroid hormone biosynthesis, porphyrin and chlorophyll metabolism, and drug metabolism, while subtype II eMPMs were involved in rational metabolism, tyrosine metabolism, and chemical carcinogenesis pathways. Additionally, we identified potential subtype-specific therapeutic targets, including CCNE1, EPHA3, RNF43, ROS1, and RSPO2 for subtype I and CDKN2A and RET for subtype II. Considering the need for potent diagnostic and therapeutic biomarkers for eMPM, we are anticipating that our findings will help both in exploring underlying mechanisms in the development of eMPM and in designing targeted therapy for eMPM.

Metal-organic frameworks for pharmaceutical and biomedical applications

Metal-organic framework (MOF) materials provide unprecedented opportunities for evaluating valuable compounds for various medical applications. MOFs merged with biomolecules, used as novel biomaterials, have become particularly useful in biological environments. Bio-MOFs can be promising materials in the global to avoid utilization above toxicological substances. Bio-MOFs with crystallin and porosity nature offer flexible structure via bio-linker and metal node variation, which improves their wide applicability in medical science.

Multiple Cell Cultures for MRI Analysis

Magnetic resonance imaging (MRI) is an imaging method that enables diagnostics. In recent years, this technique has been widely used for research using cell cultures used in pharmaceutical science to understand the distribution of various drugs in a variety of biological samples, from cellular models to tissues. MRI's dynamic development in recent years, in addition to diagnostics, has allowed the method to be implemented to assess response to applied therapies. Conventional MRI imaging provides anatomical and pathological information. Due to advanced technology, MRI provides physiological information. The use of cell cultures is very important in the process of testing new synthesized drugs, cancer research, and stem cell research, among others. Two-dimensional (2D) cell cultures conducted under laboratory conditions, although they provide a lot of information, do not reflect the basic characteristics of the tumor. To replicate the tumor microenvironment in science, a three-dimensional (3D) culture of tumor cells was developed. This makes it possible to reproduce in vivo conditions where, in addition, there is a complex and dynamic process of cell-to-cell communication and cell-matrix interaction. In this work, we reviewed current research in 2D and 3D cultures and their use in MRI studies. Articles for each section were collected from PubMed, ScienceDirect, Web of Science, and Google Scholar.

Synergistic effect of Si-doping and Fe2O3-encapsulation on drug delivery and sensor applications of γ-graphyne nanotube toward favipiravir as an antiviral for COVID-19: A DFT study

In this work, the behavior of favipiravir (FAV) adsorption on the pristine (2,2) graphyne-based γ-nanotube (GYNT) was theoretically studied. Also, the Si-doped form (Si-GYNT) and its composite with encapsulated Fe₂O₃ (Fe₂O₃@Si-GYNT) were investigated within density functional theory (DFT) calculations, using M05 functionals and B3LYP. It was found that FAV is weakly to moderately adsorb on the bare GYNT and Si-GYNT tube, releasing the energy of 2.2 to 19.8 kcal/mol. After FAV adsorption, the bare tube's electronic properties are changed. Localized impurity is induced at the valence and conduction levels by encapsulating a tiny Fe₂O₃ cluster. As such, the target composite becomes a magnetic material. The binding energy between the Fe₂O₃@Si-GYNT and the FAV molecule becomes substantially stronger (E_ad = -25.2 kcal/mol). We developed a drug release system in target parts of body, during protonation in the low pH of injured cells, detaching the FAV from the tube surface. The drug's reaction mechanism with Fe₂O₃@Si-GYNT shifts from covalence in the normal environment to hydrogen bonding in an acidic matrix. The optimized structure's natural bond orbital, quantum molecular descriptors, LUMO, HOMO and energy gap were also investigated. The recovery time can be reduced to less than 10 s by increasing the working temperature properly during the experimental test.

Human Responses in Public Health Emergencies for Infectious Disease Control: An Overview of Controlled Topologies for Biomedical Applications

COVID-19 originated in Wuhan city of Hubei Province in China in December three years ago. Since then, it has spread to more than 210 countries and territories. This disease is caused by Severe Acute Respiratory Syndrome Coronavirus 2. The virus has a size of one to two nanometers and a single-stranded positive RNA. Droplets spread the virus from coughing and sneezing. This condition causes coughing, fever, acute respiratory problems, and even death. According to the WHO, the virus can survive outside the body for several hours. This research aimed to determine how environmental factors influenced the COVID-19 virus's survival and behavior, as well as its transmission, in a complex environment. Based on the results, virus transmissions are influenced by various human and environmental factors such as population distribution, travel, social behavior, and climate change. Environmental factors have not been adequately examined concerning the transmission of this epidemic. Thus, it is necessary to examine various aspects of prevention and control of this disease, including its effects on climate and other environmental factors.

Analysis of COVID-19 severity from the perspective of coagulation index using evolutionary machine learning with enhanced brain storm optimization

Coronavirus 2019 (COVID-19) is an extreme acute respiratory syndrome. Early diagnosis and accurate assessment of COVID-19 are not available, resulting in ineffective therapeutic therapy. This study designs an effective intelligence framework to early recognition and discrimination of COVID-19 severity from the perspective of coagulation indexes. The framework is proposed by integrating an enhanced new stochastic optimizer, a brain storm optimizing algorithm (EBSO), with an evolutionary machine learning algorithm called EBSO-SVM. Fast convergence and low risk of the local stagnant can be guaranteed for EBSO with added by Harris hawks optimization (HHO), and its property is verified on 23 benchmarks. Then, the EBSO is utilized to perform parameter optimization and feature selection simultaneously for support vector machine (SVM), and the presented EBSO-SVM early recognition and discrimination of COVID-19 severity in terms of coagulation indexes using COVID-19 clinical data. The classification performance of the EBSO-SVM is very promising, reaching 91.9195% accuracy, 90.529% Matthews correlation coefficient, 90.9912% Sensitivity and 88.5705% Specificity on COVID-19. Compared with other existing state-of-the-art methods, the EBSO-SVM in this paper still shows obvious advantages in multiple metrics. The statistical results demonstrate that the proposed EBSO-SVM shows predictive properties for all metrics and higher stability, which can be treated as a computer-aided technique for analysis of COVID-19 severity from the perspective of coagulation.

Study the nature of interaction between 5-Fluorouracil anti-cancer drug and borospherene

This study employs density functional theory (DFT) to evaluate pristine C₄B₃₂ borospherene and borospherenes functionalized by amino acid in drug delivery efficiency. The results showed that pristine and alanine-modified C₄B₃₂ clusters demonstrated high efficiency in drug delivery when borospherenes were designed using the quadruple carbon atom doping of C₄B₃₂. The main goal of this study was to evaluate the interaction between the 5-Fluorouracil drug (FU) and borospherenes (both alanine-modified variants and pristine). According to the findings, the bio-drug delivery function enabled by the amino acid led to enhanced FU adsorption onto C₄B₃₂, and in the ultraviolet-visible (UV-Vis) spectroscopy, a redshift was found in the drug@cluster electronic spectra. Therefore, it can be concluded that the borospherene modified by alanine offers drug delivery efficiency.

Nutritional Management Mode of Early Cardiac Rehabilitation in Patients with Stanford Type A Aortic Dissection

Malnutrition and metabolic disorders are common problems faced by patients with Stanford type A aortic dissection after surgery. Some patients have dietary problems such as malnutrition, unbalanced diet, and poor eating habits before surgery. Therefore, the nutritional management of early heart health can improve the nutritional support for perioperative recovery, to improve the pertinence. Therefore, active nutritional support after surgery will help to change malnutrition and metabolism and is of great significance to postoperative recovery and quality of life. This paper is aimed at studying the nutritional management mode of early cardiac rehabilitation in patients with Stanford type A aortic dissection. Based on the analysis of the pathogenesis of aortic dissection and the diagnosis of aortic dissection, two groups of patients were given individualized nutritional management scheme and routine nutritional scheme, respectively, and the nutritional risk differences between the two groups under different schemes were compared. The results showed that there was a statistical difference between the two groups at discharge. The NRS-2002 score of 14 cases in the observation group was less than 3 after nutritional intervention, indicating that there was no nutritional risk at discharge.

Adsorption of thiotepa anticancer drugs on the C3N nanotube as promising nanocarriers for drug delivery

This paper focused on the efficiency of carbon nitride nanotubes functionalized with alanine amino acid (f-C₃NNTs) in thiotepa (TPA) anti-cancerous drug delivery via density functional theory (DFT). Pristine C₃NNTs were incorporated for comparison. TPA was found to spontaneously undergo exothermic adsorption onto the nanostructures. The f-C₃NNT/TPA complexes showed the highest interaction strength. The adsorption distance of TPA was found to be smaller, with a greater adsorption capacity and solubility on the f-C₃NNT surface than on the pristine C₃NNT surface. As they were polar, all the complexes were concluded to be insoluble within an aqueous phase. The quantum molecular descriptors revealed the f-C₃NNT nanocarriers to be more reactive than the C₃NNT carrier. The drug was found to spontaneously and exothermically interact with f-C₃NNT. As a result, f-C₃NNT would be promising for TPA adsorption in drug delivery applications.

Engineered 3D-Printed Polyvinyl Alcohol Scaffolds Incorporating β-Tricalcium Phosphate and Icariin Induce Bone Regeneration in Rat Skull Defect Model

The skull defects are challenging to self-heal, and autologous bone graft repair has numerous drawbacks. The scaffolds for the rapid and effective repair of skull defects have become an important research topic. In this study, polyvinyl alcohol (PVA)/β-tricalcium phosphate(β-TCP) composite scaffolds containing icariin (ICA) were prepared through direct-ink three-dimensional (3D) printing technology. β-TCP in the composite scaffold had osteoconductive capability, and the ICA molecule had osteoinductive capacity. The β-TCP and ICA components in the composite scaffold can enhance the capability to repair skull defects. We show that ICA exhibited a slow-release behaviour within 80 days. This behaviour helped the scaffold to continuously stimulate the formation of new bone. The results of in vitro cell compatibility experiments showed that the addition of ICA molecules contributed to the adhesion and proliferation of MC-3T3-E1 cells. The level of alkaline phosphatase secretion demonstrated that the slow release of ICA can promote the osteogenic differentiation of MC-3T3-E1 cells. The introduction of ICA molecules accelerated the in situ bone regeneration in in vivo. It is concluded that the 3D-printed PVA scaffold with β-TCP and ICA has a wide range of potential applications in the field of skull defect treatment.

Research Advances of Injectable Functional Hydrogel Materials in the Treatment of Myocardial Infarction

Myocardial infarction (MI) has become one of the serious diseases threatening human life and health. However, traditional treatment methods for MI have some limitations, such as irreversible myocardial necrosis and cardiac dysfunction. Fortunately, recent endeavors have shown that hydrogel materials can effectively prevent negative remodeling of the heart and improve the heart function and long-term prognosis of patients with MI due to their good biocompatibility, mechanical properties, and electrical conductivity. Therefore, this review aims to summarize the research progress of injectable hydrogel in the treatment of MI in recent years and to introduce the rational design of injectable hydrogels in myocardial repair. Finally, the potential challenges and perspectives of injectable hydrogel in this field will be discussed, in order to provide theoretical guidance for the development of new and effective treatment strategies for MI.

Drug discovery of sclerostin inhibitors

Sclerostin, a protein secreted from osteocytes, negatively regulates the WNT signaling pathway by binding to the LRP5/6 co-receptors and further inhibits bone formation and promotes bone resorption. Sclerostin contributes to musculoskeletal system-related diseases, making it a promising therapeutic target for the treatment of WNT-related bone diseases. Additionally, emerging evidence indicates that sclerostin contributes to the development of cancers, obesity, and diabetes, suggesting that it may be a promising therapeutic target for these diseases. Notably, cardiovascular diseases are related to the protective role of sclerostin. In this review, we summarize three distinct types of inhibitors targeting sclerostin, monoclonal antibodies, aptamers, and small-molecule inhibitors, from which monoclonal antibodies have been developed. As the first-in-class sclerostin inhibitor approved by the U.S. FDA, the monoclonal antibody romosozumab has demonstrated excellent effectiveness in the treatment of postmenopausal osteoporosis; however, it conferred high cardiovascular risk in clinical trials. Furthermore, romosozumab could only be administered by injection, which may cause compliance issues for patients who prefer oral therapy. Considering these above safety and compliance concerns, we therefore present relevant discussion and offer perspectives on the development of next-generation sclerostin inhibitors by following several ways, such as concomitant medication, artificial intelligence-based strategy, druggable modification, and bispecific inhibitors strategy.