Quercetin potentiates the anti-osteoporotic effects of alendronate through modulation of autophagy and apoptosis mechanisms in ovariectomy-induced bone loss rat model.

BACKGROUND: Osteoporosis is a bone disease leading to bone fracture and affects 200 million women worldwide. Autophagy and apoptosis are two fundamental mechanisms that are involved in the development of osteoporosis. In this study we aim to investigate the combined effects of quercetin and alendronate on the markers of osteoporosis, autophagy, and apoptosis in the bone of ovariectomized rats. METHODS AND RESULTS: Fifty adult female Sprague-Dawley rats were ovariectomized and treated with alendronate alone (5 µg/kg/day) or alendronate (5 µg/kg/day) in combination with quercetin (15 mg/kg/day) for 12 weeks. Then, ELISA, stereological tests, Real-time PCR analysis, and immunofluorescence assay were used to measure the markers of osteoporosis, autophagy, and apoptosis in the serum and tibia of rats. The serum osteocalcin was significantly decreased in ovariectomized rats that received quercetin and alendronate compared with alendronate only. Stereological data showed that except for osteoclasts, the total trabecular volume, bone weight, bone volume, osteocyte, and osteoblast numbers were increased in an ovariectomized group that was treated with quercetin and alendronate compared with alendronate alone. Except for Bcl2, the autophagy markers (Beclin-1 and LC3B) and Caspase-3 were significantly downregulated in ovariectomized rats that received quercetin and alendronate compared with those treated with alendronate alone. CONCLUSION: Our results show that quercetin enhances the anti-osteoporotic effects of alendronate, possibly through the regulation of autophagy and apoptosis mechanisms. These findings suggest that the combination of quercetin and alendronate could be a useful therapeutic strategy in the treatment of osteoporosis in postmenopausal women.

Formaldehyde 5% in Flexible Collodion Compared to Cryotherapy for Treatment of Female Genital Warts: A Randomized Clinical Trial.

Objectives: Genital wart is a sexually transmitted disease caused by human papillomavirus (HPV) and is responsible for discomfort, and decreased quality of life and productivity in victims with a high recurrence rate after treatments. This study aimed to compare the efficacy and safety of formaldehyde 5% with cryotherapy for the treatment of female genital warts. Methods: Eighty women with at least two similar genital warts who visited the outpatient dermatology clinic of Shahid Faghihi hospital, Shiraz, Iran, were enrolled in this study. One lesion of each patient was self-treated with formaldehyde 5% in flexible collodion gel once daily for 28 days and the other matched lesion was treated by weekly repeated cryotherapy courses. The number of eradicated lesions and the mean days needed to treat, pain scores, complications and patient satisfaction were compared between the treatment methods. Results: Complete clearance of lesions was observed in 58.7% of formaldehyde-treated lesions compared to 88.7% for cryotherapy (P value = 0.000). With formaldehyde-treated lesions, 51% complained of pain, 36.3% had pruritus, 86.3% had skin dryness, 88.8% complained of burning sensation and 93.7% showed erythema. In the cryotherapy group, 92.5% complained of pain, 15% had burning sensation, 75% showed erythema, 5% had atrophy, 80% developed post-inflammatory hyper or hypopigmentation (PIH) and 92.5% suffered from ulceration. Seventy-five (93%) found it easy to apply and (47) 58% were satisfied with their treatment results. Conclusions: Self-administration of formaldehyde 5% resulted in a lower clearance rate but had better cosmetic outcomes with lower pain scores compared to cryotherapy.

Construction of circRNA-miRNA-mRNA network in the pathogenesis of recurrent implantation failure using integrated bioinformatics study.

This research attempted to elucidate the molecular components are involved in the pathogenesis of recurrent implantation failure (RIF). We initially identified that 386 mRNAs, 144 miRNAs and 2548 circRNAs were differentially expressed (DE) in RIF and then investigated the genetic cause of the observed abnormal expression by constructing a circRNA-miRNA-mRNA network considering the competing endogenous RNA theory. We further analysed the upstream transcription factors and related kinases of DEmRNAs (DEMs) and demonstrated that SUZ12, AR, TP63, NANOG, and TCF3 were the top five TFs binding to these DEMs. Besides, protein-protein interaction analysis disclosed that ACTB, CXCL10, PTGS2, CXCL12, GNG4, AGT, CXCL11, SST, PENK, and FOXM1 were the top 10 hub genes in the acquired network. Finally, we performed the functional enrichment analysis and found that arrhythmogenic right ventricular cardiomyopathy (ARVC), hypertrophic cardiomyopathy (HCM), pathways in cancer, TNF signalling pathway and steroid hormone biosynthesis were the potentially disrupted pathways in RIF patients. Optimistically, our findings may deepen our apprehensions about the underlying molecular and biological causes of RIF and provide vital clues for future laboratory and clinical experiments that will ultimately bring a better outcome for patients with RIF.

Exploring the dysregulated mRNAs-miRNAs-lncRNAs interactions associated to idiopathic non-obstructive azoospermia.

Non-obstructive azoospermia (NOA) is the most clinical problem in case of infertility. About 70% of NOA patients are idiopathic with uncharacterized molecular mechanisms. This study aimed to analyze the possible pathogenic miRNA-target gene interaction and lncRNA-miRNA association involved in NOA. In the current study, differentially expressed (DE) nRNAs, miRNAs and lncRNAs were determined using the microarray dataset and statistical software R. miRNAs-mRNA and miRNA-lncRNA interactions were identified and the base-pair binding between the seed region of miRNAs and complementary nucleotides in 3' UTR of mRNAs were analyzed. The influence of the validated single nucleotide polymorphisms (SNPs) was described by calculating the minimum free energy (MFE) of the interaction. A total of 74 mRNAs, 14 miRNAs, and 10 lncRNAs were identified to have significant differential expression in testicular tissue between patients and the fertile group. Four of the DE-mRNAs and all of the reported DE-miRNAs were upregulated. In addition, all of the represented DE-lncRNAs were showed to be downregulated. miR-509-5p and miR-27b-3p were found to interact with target gene polo-like kinase 1 (PLK1) and Cysteine-rich secretory protein2 (CRISP2), respectively. Rs550967205 (A > G) positioned at 3' UTR CRISP2 and rs544604911 (T > C) located at 3' UTR PLK1, with lowest MFE in miRNA-mRNA interaction, were assumed to have possible pathogenic roles linked to spermatogenesis arrest. The results of the study provide new clues to understand the regulatory roles of miRNAs and lncRNAs in the pathogenesis and diagnosis of idiopathic azoospermia. Communicated by Ramaswamy H. Sarma.

The Effect of Oral Vitamin E on Semen Parameters and IVF Outcome: A Double-Blinded Randomized Placebo-Controlled Clinical Trial.

BACKGROUND: Male infertility is a main clinical problem that affects about 7% of all men worldwide. Many patients with male infertility are caused by a reduced antioxidant capacity of semen. Several antioxidant supplements, especially vitamin E, are proposed to help male infertility treatment. This project was goaled to study the effects of oral synthetic vitamin E (400 IU/day) for eight weeks on betterment of semen parameters and pregnancy rate. METHODS: After dropping the cases, 124 infertile couples with a male factor who were admitted to the IVF program were included. The male patients with idiopathic abnormal motility and/or morphology were randomized into two groups: 61 receiving vitamin E and 63 as the control group receiving placebo for eight weeks. The pretreatment semen parameters of both groups were compared with those of posttreatment. The pregnancy outcomes were considered between the two groups. RESULTS: There were no significant differences statistically between before and after treatment in the term of sperm volume, count, motility, and morphology. Furthermore, the IVF outcomes of the two groups were not different significantly, either. Interestingly, the percent of normal sperm in the placebo group was significantly decreased after eight weeks. CONCLUSION: Vitamin E supplementation might neutralize free radical activity to keep sperm from more oxidative damages. Further studies regarding the influence of higher acceptable doses of vitamin E on semen characteristics and fertility rates are needed. This study was registered as a two-arm, blinded, randomized, placebo-controlled clinical trial (IRCTID: IRCT2014020616506N1, 2014-03-18).

Associations of insulin resistance, sex hormone-binding globulin, triglyceride, and hormonal profiles in polycystic ovary syndrome: A cross-sectional study.

BACKGROUND: Insulin resistance (IR) occurs in 50-70% of women with polycystic ovary syndrome (PCOS) and can be applied as a prediabetic feature in PCOS. OBJECTIVE: In this study, indirect methods including fasting blood sugar (FBS), fasting insulin (FI), FBS/FI ratio, and quantitative insulin sensitivity check index (QUICKI) were compared with the homeostasis model assessment of insulin resistance (HOMA-IR) as a standard technique. The association of IR to sex hormone-binding globulin (SHBG) and several hormones was also analyzed. MATERIALS AND METHODS: This cross-sectional study was performed on 74 PCOS women. Sensitivity and specificity of each IR method was calculated based on HOMA-IR. Hormonal profiles of the patients were compared between the groups with defined normal and abnormal values of IR. RESULTS: Triglyceride levels had a positive association with FBS and HOMA-IR (p = 0.002 and p = 0.01, respectively) with a negative association to QUICKI and SHBG (p = 0.02 and p = 0.02, respectively). SHBG showed a significant negative association with FBS (p = 0.001). Dehydroepiandrosterone sulfate showed a positive association with FI (p = 0.002). Seven PCOS women showed abnormal SHBG levels ( < 36 nmol/L) while expressed normal values of the rest of the studied variables. FI and QUICKI had the highest sensitivity while FBS/FI and QUICKI had the highest specificity when HOMA-IR was applied as a standard test. CONCLUSION: SHBG and triglyceride had a significant negative and positive association with IR, respectively. HOMA-IR followed by FI and QUICKI is the most sensitive test for the detection of IR. SHBG levels can be a helpful biomarker for the diagnosis of PCOS.

In Silico Identification of miRNA-lncRNA Interactions in Male Reproductive Disorder Associated with COVID-19 Infection.

Coronavirus disease 2019 (COVID-19), a global pandemic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and transmembrane serine protease 2 (TMPRSS2) facilitates ACE2-mediated virus entry. Moreover, the expression of ACE2 in the testes of infertile men is higher than normal, which indicates that infertile men may be susceptible to be infected and SARS-CoV-2 may cause reproductive disorder through the pathway induced by ACE2 and TMPRSS2. Little is known about the pathway regulation of ACE2 and TMPRSS2 expression in male reproductive disorder. Since the regulation of gene expression is mediated by microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) at the post-transcriptional level, the aim of this study was to analyze the dysregulated miRNA-lncRNA interactions of ACE2 and TMPRSS2 in male reproductive disorder. Using bioinformatics analysis, we speculate that the predicted miRNAs including miR-125a-5p, miR-125b-5p, miR-574-5p, and miR-936 as regulators of ACE2 and miR-204-5p as a modulator of TMPRSS2 are associated with male infertility. The lncRNAs with a tissue-specific expression for testis including GRM7-AS3, ARHGAP26-AS1, BSN-AS1, KRBOX1-AS1, CACNA1C-IT3, AC012361.1, FGF14-IT1, AC012494.1, and GS1-24F4.2 were predicted. The identified miRNAs and lncRNAs are proposed as potential biomarkers to study the possible association between COVID-19 and male infertility. This study encourages further studies of miRNA-lncRNA interactions to explain the molecular mechanisms of male infertility in COVID-19 patients.

Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data.

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein-protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug-protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

Comparing four different methods for the management of ectopic pregnancy: A cross-sectional study.

Background: Ectopic pregnancy (EP) is one of the major causes of maternal mortality during the first trimester of pregnancy. Objective: Four treatment methods for EP including single-dose methotrexate (SD-MTX), double-dose methotrexate, expectant and surgical management were considered. Materials and Methods: In this cross-sectional study, the clinical characteristics of 365 women aged 15-44 yr who had been diagnosed with EP were reviewed from March 2017 to March 2019 in hospitals affiliated to Shiraz University of Medical Sciences, Shiraz, Iran. Receiver operating characteristics curves were plotted to determine the cut-off points for size of ectopic mass and beta-human chorionic gonadotropin (ß-hCG) that suitably discriminated between double-dose methotrexate and surgery management. Results: The most common site of EP was adnexa. According to the receiver operating characteristics analysis, surgery was the best plan for the women with an ectopic mass > 34.50 mm in diameter or with an initial ß-hCG level > 6419 mIU/ml. The ß-hCG levels in the women successfully treated with SD-MTX were significantly lower than in those with failed treatment (p = 0.02). The SD-MTX group had a higher success rate and significantly shorter duration of hospitalization, and so this was a more effective medical treatment in comparison with the double-dose protocol. Conclusion: Surgery is proposed as the best option for the cases with large ectopic mass or high ß-hCG level. SD-MTX had a higher success rate and shorter hospital stay than the double-dose protocol, and so was found to be an efficient and safe alternative. Further randomized clinical trials with larger sample sizes are recommended to validate the current results.

Computer aided analysis of disease linked protein networks.

Proteins can interact in various ways, ranging from direct physical relationships to indirect interactions in a formation of protein-protein interaction network. Diagnosis of the protein connections is critical to identify various cellular pathways. Today constructing and analyzing the protein interaction network is being developed as a powerful approach to create network pharmacology toward detecting unknown genes and proteins associated with diseases. Discovery drug targets regarding therapeutic decisions are exciting outcomes of studying disease networks. Protein connections may be identified by experimental and recent new computational approaches. Due to difficulties in analyzing in-vivo proteins interactions, many researchers have encouraged improving computational methods to design protein interaction network. In this review, the experimental and computational approaches and also advantages and disadvantages of these methods regarding the identification of new interactions in a molecular mechanism have been reviewed. Systematic analysis of complex biological systems including network pharmacology and disease network has also been discussed in this review.

Selected application of peptide molecules as pharmaceutical agents and in cosmeceuticals.

Introduction: Peptide molecules are being vastly investigated as an emerging class of therapeutic molecules in recent years. Currently, 60 peptides have been approved by the US Food and Drug Administration (FDA), and more would enter the market in near future. Peptides have already opened their ways into cosmeceutical and food industries as well.Areas covered: Antibodies, vaccines, and antimicrobial agents are the major classes of therapeutic peptides. Additionally, peptides may be employed in drug development to support cell penetration or targeting. The interest in antimicrobial peptides is surging due to the increasing risk of antibiotic-resistant pathogens. Peptide vaccines with their significant advantages compared with traditional vaccines, are expected to find their place in coming years, especially for cancer, microbial and allergen-specific immunotherapy. The usage of peptides in cosmeceuticals is also growing rapidly.Expert opinion: Peptide synthesis has become accessible, and advances in peptide engineering, sequencing technologies, and structural bioinformatics have resulted in the rational designing of novel peptides. All these advancements would lead to the more prominent roles of peptides in the mentioned areas. In this review, we discuss applications of peptides in different fields including pharmaceuticals, cosmeceuticals, besides the critical factors in designing efficient peptide molecules.

Decreasing the immunogenicity of arginine deiminase enzyme via structure-based computational analysis.

The clinical applications of therapeutic enzymes are often limited due to their immunogenicity. B-cell epitope removal is an effective approach to solve this obstacle. The identification of hot spot epitopic residues is a critical step in the removal of protein B-cell epitope. Hereof, computational approaches are a suitable alternative to costly and labor-intensive experimental approaches. Arginine deiminase, a Mycoplasma arginine-catabolizing enzyme, is in the clinical trial for treating arginine auxotrophic cancers, especially hepatocellular carcinomas and melanomas through depleting plasma arginine and causing cell starvation. In this study, arginine deiminase from Mycoplasma hominis (MhADI) was computationally analyzed for recognizing and locating its immune-reactive regions. The 3D structure of the bioactive form of MhADI was modeled. The B-cell epitope mapping of protein was performed using various servers with different algorithms. Six segments: 31-40, 48-55, 131-140, 196-206, 294-314, and 331-344 were predicted to be the consensus immunogenic regions. The modification of epitopic hot spot residue was performed to reduce immune-reactiveness. The hot spot residue was selected considering a high B-cell epitope score, convexity index, surface accessibility, flexibility, and hydrophilicity. The structure stability of native and mutant proteins was evaluated through molecular dynamics simulation. The E304L mutein was suggested as a lower antigenic and stable enzyme derivative.

Exploring dengue proteome to design an effective epitope-based vaccine against dengue virus.

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models. Communicated by Ramaswamy H. Sarma.

Deficiency in Sperm-Egg Protein Interaction as a Major Cause of Fertilization Failure.

Complete elucidation of fertilization process at molecular level is one of the unresolved challenges in sexual reproduction studies, and understanding the molecular mechanism is crucial in overcoming difficulties in infertility and unsuccessful in vitro fertilization. Sperm-oocyte interaction is one of the most remarkable events in fertilization process, and deficiency in protein-protein interactions which mediate this interaction is a major cause of unexplained infertility. Due to detection of how the various defects of sperm-oocyte interaction can affect fertilization failure, different experimental methods have been applied. This review summarizes the current understanding of sperm-egg interaction mechanism during fertilization and also accumulates the different types of sperm-egg interaction abnormalities and their association with infertility. Several detection approaches regarding sperm-egg protein interactions and the associated defects are reviewed in this paper.

Systematic Analysis of Protein Interaction Network Associated with Azoospermia.

Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Using Online Mendelian Inheritance in Man, the Human Protein Reference Database and Cytoscape, we created a novel network consisting of 209 protein nodes and 737 interactions. Mathematical analysis identified three proteins, ar, dazap2, and esr1, as hub nodes and a bottleneck protein within the network. We also identified new candidate genes, CREBBP and BCAR1, which may play a role in azoospermia. The gene ontology analysis suggests a genetic link between azoospermia and liver disease. The KEGG analysis also showed 45 statistically important pathways with 31 proteins associated with colorectal, pancreatic, chronic myeloid leukemia and prostate cancer. Two new genes and associated diseases are promising for further experimental validation.

Identification of putative drug targets for human sperm-egg interaction defect using protein network approach.

BACKGROUND: Sperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis. RESULTS: We have created human sperm-egg protein interaction networks with high confidence, including 106 nodes and 415 interactions. Through topological analysis of the network with calculation of some metrics, such as connectivity and betweenness centrality, we have identified 13 essential proteins as putative drug targets. The potential drug targets are from integrins, fibronectins, epidermal growth factor receptors, collagens and tetraspanins protein families. We evaluated these targets by ingenuity pathway analysis, and the known drugs for the targets have been detected, and the possible effective role of the drugs on sperm-egg interaction defect has been considered. These results showed that the drugs ocriplasmin (Jetrea©), gefitinib (Iressa©), erlotinib hydrochloride (Tarceva©), clingitide, cetuximab (Erbitux©) and panitumumab (Vectibix©) are possible candidates for efficacy testing for the treatment of sperm-egg interaction deficiency. Further experimental validation can be carried out to confirm these results. CONCLUSION: We have identified the first potential list of drug targets for human sperm-egg interaction defect using the protein interaction network approach. The essential proteins or potential drug targets were found using topological analysis of the protein network. These putative targets are promising for further experimental validation. These study results, if validated, may develop drug discovery techniques for sperm-egg interaction defect and also improve assisted reproductive technologies to avoid in-vitro fertilization failure.

Functional features and protein network of human sperm-egg interaction.

Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new computationally resolved interactions and the genetic links between sperm-egg interaction abnormalities and the associated disease.