BACKGROUND: Current guidelines recommend at least two weeks duration of antibiotic therapy (DOT) for patients with uncomplicated Staphylococcus aureus bacteraemia (SAB) but the evidence for this recommendation is unclear. OBJECTIVES: To perform a systematic literature review assessing current evidence for recommended DOT for patients with SAB. METHODS: Data sources: We searched MEDLINE, ISI Web of Science, the Cochrane Database and clinicaltrials.gov from inception to March 30, 2024. References of eligible studies were screened and experts in the field contacted for additional articles. STUDY ELIGIBILITY CRITERIA: All clinical studies, regardless of design, publication status and language. PARTICIPANTS: Adult patients with uncomplicated SAB. INTERVENTIONS: Long (>14; >18; 11-16 days) vs. short (≤14; 10-18; 6-10 days, respectively) DOT with the DOT being defined as the first until the last day of antibiotic therapy. ASSESSMENT OF RISK OF BIAS: Risk of bias was assessed using the ROBINS-I-tool. METHODS OF DATA SYNTHESIS: The primary outcome was 90-day all-cause mortality. Only studies presenting results of adjusted analyses for mortality were included. Data synthesis could not be performed. RESULTS: Eleven non-randomized studies were identified that fulfilled the predefined inclusion criteria, of which three studies reported adjusted effect ratios. Only these were included in the final analysis. We did not find any RCT. Two studies with 1,230 patients reported the primary endpoint 90-day all-cause mortality. Neither found a statistically significant superiority for longer (>14; 11-16 days) or shorter DOT (≤14; 6-10 days, respectively) for patients with uncomplicated SAB. Two studies investigated the secondary endpoint 30-day all-cause mortality (>18; 11-16 days vs. 10-18; 6-10 days, respectively) and did not find a statistically significant difference. All included studies had a moderate risk of bias. CONCLUSIONS: Sound evidence that supports any duration of antibiotic treatment for patients with uncomplicated SAB is lacking.
Mg-doped copper chromite (CuCr2O4) nanocomposites were synthesised through conventional technique. The pure and doped CuCr2-xMgx O4 (x = 0.00-0.1, 0.2 and 0.3%) nanocomposites were characterized in terms of their morphology, crystal structure, surface area and catalytic performance. The chemical composition of CuCr2-xMgx O4 was confirmed via FT-IR. The formation of pure and doped catalysts was validated by XRD results. TEM/SEM confirmed the formation of CuCr2-xMgxO4 nanoparticles. Mg-doped samples possess a high specific surface area compared to pure CuCr2O4. Thus, the effects of temperature, solvent, time, oxidant and the amount of catalyst on the oxidation of veratryl alcohol were reported. Furthermore, detailed mechanisms of the catalytic oxidation of veratryl alcohol as well as the reusability and stability of the nanomaterial were investigated. The resulting composites were shown to be effective heterogeneous catalysts for the oxidation of veratryl alcohol.
Crude oil spills imperil aquatic ecosystems globally, prompting innovative solutions such as microalgae-based bioremediation. This study explores the potential of Chlorella vulgaris and Scenedesmus quadricauda, for crude oil spill phycoremediation under mixotrophic conditions and varying crude oil concentrations (0.5-2%). C. vulgaris demonstrated notable resilience, thriving up to 1% crude oil exposure, while S. quadricauda adapted to lower concentrations. Optimal growth for both was observed at 0.5% exposure. Chlorophyll a content in C. vulgaris increases at 0.5% exposure but declines above 1%, while a decline was noticeable in chlorophyll b in treatment groups above 1%. Carotenoid levels varied, displaying the highest levels at higher concentrations above 1.5%. Similarly, S. quadricauda showed increased chlorophyll a content at 0.5% exposure, with stable carotenoid levels and a decline in chlorophyll b content at higher concentrations. GC/MS analyses indicated C. vulgaris efficiently degraded aliphatic compounds like decane and tridecane, surpassing S. quadricauda in degrading both aliphatic and aromatic hydrocarbons. Growth kinetics was best represented by the modified Gompertz and logistic models. These findings highlight the species-specific adaptability and optimal concentration for microalgae to degrade crude oil effectively, advancing phycoremediation processes and strategies critical for environmental restoration.
This study marks the first exploration of both Chlorella vulgaris and the previously unexplored Scenedesmus quadricauda for crude oil phycoremediation potential under mixotrophic conditions. Additionally, it pioneers the modeling and study of algae growth kinetics in response to crude oil exposure. Notably, this research demonstrated the adaptability and efficiency of C. vulgaris in degrading crude oil components under mixotrophic conditions up to a level of 1%, while S. quadricauda showed similar capabilities at a concentration of 0.5%.
Herein, we synthesized hydrogel films from crosslinked polyethylene oxide (PEO) and guar gum (GG) which can offer hydrophilicity, antibacterial efficacy, and neovascularization. This study focuses on synthesis and material/biological characterization of rosemary (RM) and citric acid (CA) loaded PEO/GG hydrogel films. Scanning Electron Microscopy images confirmed the porous structure of the developed hydrogel film matrix (PEO/GG) and the dispersion of RM and CA within it. This porous structure promotes moisture adsorption, cell attachment, proliferation, and tissue layer formation. Fourier Transform Infrared Spectroscopy (FTIR) further validated the crosslinking of the PEO/GG matrix, as evidenced by the appearance of C-O-C linkage in the FTIR spectrum. PEO/GG and PEO/GG/RM/CA revealed similar degradation and release kinetics in Dulbecco's Modified Eagle Medium, Simulated Body Fluid, and Phosphate Buffer Saline (degradation of ~55â¯% and release of ~60â¯% RM in 168â¯h.). The developed hydrogel film exhibited a zone of inhibition against Escherichia. coli (2â¯mm) and Staphylococcus. aureus (9â¯mm), which can be attributed to the presence of RM in the hydrogel film. Furthermore, incorporating CA in the hydrogel film promoted neovascularization, as confirmed by the Chorioallantoic Membrane Assay. The developed RM and CA-loaded PEO/GG-based hydrogel film offered suitable in-vitro properties that may aid in potential wound healing applications.
Gangliosides represent glycolipids containing sialic acid residues, present on the cell membrane with glycan residues exposed to the extracellular matrix (ECM), while the ceramides are anchored within the membrane. These molecules play a critical role in pathophysiological processes such as host-pathogen interactions, cell-cell recognition, signal transduction, cell adhesion, motility, and immunomodulation. Accumulated evidence suggests the overexpression of gangliosides on tumor tissues in comparison to healthy human tissues. These tumor-associated gangliosides have been implicated in various facets of tumor biology, including cell motility, differentiation, signaling, immunosuppression, angiogenesis, and metastasis. Consequently, these entities emerge as attractive targets for immunotherapeutic interventions. Notably, the administration of antibodies targeting gangliosides has demonstrated cytotoxic effects on cancer cells that exhibit an overexpression of these glycolipids. Passive immunotherapy approaches utilizing murine or murine/human chimeric anti-ganglioside antibodies have been explored as potential treatments for diverse cancer types. Additionally, vaccination strategies employing tumor-associated gangliosides in conjunction with adjuvants have entered the realm of promising techniques currently undergoing clinical trials. The present comprehensive review encapsulates the multifaceted roles of gangliosides in tumor initiation, progression, immunosuppression, and metastasis. Further, an overview is provided of the correlation between the expression status of gangliosides in normal and tumor cells and its impact on cancer patient survival. Furthermore, the discussion extends to ongoing and completed clinical trials employing diverse strategies to target gangliosides, elucidating their effectiveness in treating cancers. This emerging discipline is expected to supply substantial impetus for the establishment of novel therapeutic strategies.
Despite considerable progress in cancer treatment options, resistance to chemotherapeutic drugs remains a significant challenge. This review focuses on Berberine (BBR), an isoquinoline alkaloid found in various medicinal plants, which has garnered attention in the field of oncology for its anticancer potential either alone or in combination with other compounds and its ability to modulate chemoresistance, acting as a natural chemosensitizer. BBR's ability to modulate chemoresistance is attributed to its diverse mechanisms of action, including inducing DNA breaks, inhibition of drug efflux pumps, modulation of apoptosis and necroptosis, downregulating multidrug resistance genes, enhancing immune response, suppressing angiogenesis and targeting multiple pathways within cancer cells, including protein kinase B/mammalian target of rapamycin (Akt/mTOR), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase (MAPK), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), poly(ADP-ribose) polymerase (PARP1), janus kinase/signal transducers and activators of transcription (JAK-STAT), Wnt/ß-catenin etc. Moreover, BBR, in combination with other compounds, also offers a promising approach to cancer therapy, enforcing its broad-spectrum anticancer effects. Therefore, this review aims to elucidate the intricate mechanism of action of BBR in combinatorial therapy as a potential chemosensitizer to increase the efficiency of several drugs, including cisplatin, doxorubicin, lapatinib, tamoxifen, irinotecan, niraparib, etc. in various cancers. Additionally, this review briefly covers the origin and biological activities of BBR, exploring the specific actions underlying its anticancer effects. Further, pharmacokinetic properties of BBR are also discussed, providing insight into its therapeutic potential and optimization of its use in cancer treatment.
Lung cancer stands as one of the most lethal diseases and is the foremost cause of cancer-related mortalities worldwide. The pathophysiology of lung cancer is multifaceted, and it includes multiple cell signaling pathways and other complex factors such as oxidative stress and genetics. The association of HPV with lung carcinogenesis was first proposed in 1979, and since then, scientists worldwide have been putting forward several hypotheses to establish a relationship between this virus and lung cancer. Although studies have reported the presence of HPV in lung cancer, the exact mechanism of entry and the route of transmission have not been elucidated clearly till now. Numerous studies across the globe have detected differentially expressed HPV oncoproteins in lung cancer patients and found their association with the critical cell signaling pathways that leads to the development and progression of lung cancer. Many reports have also provided evidence stating the involvement of HPV in determining the survival status of lung cancer patients. The present review recapitulates the studies evincing the association of HPV and lung cancer, its route of transmission and mechanism of action; the detection of the virus and treatment opportunities for HPV-positive lung cancer; and the severity associated with this disease. Therefore, this will provide an explicit idea and would help to develop preventive measures and specific as well as effective treatment for HPV-associated lung carcinogenesis.
The study of thermal therapy to tumors and the response of living cells to this therapy used to treat tumor is very important due to the complexity of heat transfer in biological tissues. In the past few years, there has been a growing interest among clinicians, mathematicians, and engineers regarding the use of computational and mathematical methods to simulate biological systems. Numerous medical proceedings also employ mathematical modeling and engineering techniques as a means to guarantee their safety and evaluate the associated risks effectively. This manuscript provides an analytical solution used for the first time to study the mechanism of biological thermal response during heat therapy on spheroidal skin tumor. The proposed method used a generalized thermoelasticity model with one relaxation time. The influence of relaxation times on the responses of diseased and healthy tissues is studied and interpreted graphically. Also, the impact of different laser irradiance on the thermal profile of the malignant tumor cells over a period of 2 minutes is interpreted graphically. To investigate the transfer of heat within biological tissues during the thermal therapy, the Laplace transform and inverse Laplace transform methods were applied. A comparison of the present generalized thermoelasticity model and different models based on Pennes bioheat transfer PBT shows that our proposed model yields more realistic and accurate predictions. The current model can be used to explain various therapeutic methods.
Hot Temperature , Hyperthermia, Induced , Skin Neoplasms , Humans , Skin Neoplasms/therapy , Skin Neoplasms/pathology , Hyperthermia, Induced/methods , Hot Temperature/therapeutic use , Models, Biological , Models, Theoretical
Universities and colleges play a pivotal role in the pursuit of a future that is sustainable through their pedagogical efforts and the execution of state-of-the-art research endeavors aimed at mitigating the effects of climate change. Higher Education Institutions (HEIs) serve as crucial catalysts in advancing sustainable development. HEIs are increasingly embracing precise measures to reduce their carbon footprint (CF) while also educating students on global sustainability. These nano-methods provide a quantitative framework for assessing a campus's sustainability efforts in line with Green Campus (GC) initiatives to lower carbon emissions align with GC goals. This study employs K-means clustering to analyze the integration of green and low-carbon principles in higher education political and ideological studies. Its goal is to identify patterns, assess teaching effectiveness, and improve sustainability education, aligning with Green Campus initiatives to enhance institutional contributions to sustainable growth through informed pedagogical strategies. Input data includes curriculum content, teaching methods, student engagement, and institutional goals related to sustainability. Seeking to improve sustainability education align with Green Campus initiatives, higher education can strategically enhance their contributions to long-term sustainability and growth through effective pedagogical approaches. Cluster 3 has the lowest WCSS value of 1200, indicating tighter cohesion and less variability within this cluster compared to Cluster 1 (1500) and Cluster 2 (1800). Cluster 3 stands out with the highest silhouette score of 0.7, suggesting well-defined and distinct clusters, while Cluster 2 has the lowest score of 0.4, indicating some overlap or ambiguity in data points. Cluster 1 has the lowest Davies-Bouldin Index of 0.4, implying better separation between clusters compared to Cluster 2 (0.6) and Cluster 3 (0.5). Cluster 3 is well-defined and cohesive, showing strong integration of green practices. Cluster 1 displays good separation and cohesion, while Cluster 2 requires refinement due to potential overlap in sustainability integration.
The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.
The need to explore the abundance of natural products cannot be overemphasized particularly in the management of various disease conditions. In traditional medical practice, Vernonia amygdalina has been widely adopted in the management of various inflammatory disorders. The objective of this investigation was to isolate the bioactive principles from the stem-bark and root of V. amygdalina and assess the anti-inflammatory (in vitro) activity of both the crude extracts and the isolated compounds. Following extraction with the methanol, the extract was subjected to gravity column chromatography and the resultant fractions was further purified to obtained pure compounds. The structural elucidation of the compounds were based on data obtained from 1H to 13C nuclear magnetic resonance (NMR) spectroscopies as well as fourier transform infrared (FT-IR). Using diclofenac as a control drug, the albumin denaturation assay was used to determine the in vitro anti-inflammatory activity of the extracts and isolates. Three distinct compounds characterized are vernoamyoside D, luteolin-7-α-o-glucuronide, and vernotolaside, a new glycoside. When compared to diclofenac, which has an IC50 of 167.8 µg/mL, luteolin-7-α-o-glucuronide, vernoamyoside D, and vernotolaside all showed significant inhibitions with respective IC50 values 549.8, 379.5, and 201.7 µg/mL. Vernotolaside is reported for the first time from the root. The assertion that the plant is used in traditional medicine for the management of inflammatory disorder is somewhat validated by the confirmation of the existence of the compounds with the biochemical actions. Further validation of the isolated compounds would be required in animal studies.
BACKGROUND: In agricultural pest management, especially in combatting the invasive red imported fire ant (RIFA, Solenopsis invicta), significant challenges emerge as a consequence of the constraints of solely depending on chemical insecticides or entomopathogenic nematodes (EPNs). The utilization of chemical insecticides carries environmental and ecological hazards, whereas EPNs, when applied independently, might not offer the immediate effectiveness necessary for adequate RIFA suppression. Acknowledging these hurdles, our study investigates a synergistic method that integrates EPNs with chemical insecticides, aiming to fulfill the urgent demand for more efficient and environmentally friendly pest control solutions. RESULTS: Our evaluation focused on the interaction between the highly pathogenic Steinernema riobrave 7-12 EPN strain and prevalent insecticides, specifically beta-cypermethrin and a mixture of bifenthrin and clothianidin, applied at highly diluted recommended concentrations. The findings revealed a notable increase in RIFA mortality rates when EPNs and these insecticides were used together, outperforming the results achieved with each method individually. Remarkably, this enhanced efficacy was especially evident at lower concentrations of the bifenthrin-clothianidin mixture, indicating a valuable approach to minimizing reliance on chemical insecticides in agriculture. Furthermore, the high survival rates of EPNs alongside the tested insecticides indicate their compatibility and potential for sustained use in integrated pest management programs. CONCLUSION: Our research underscores the effectiveness of merging EPNs with chemical insecticides as a powerful and sustainable strategy for RIFA management. This combined approach not only meets the immediate challenges of pest control in agricultural settings, but also supports wider environmental objectives by reducing the dependency on chemical insecticides. © 2024 Society of Chemical Industry.
Cancer has become a burgeoning global healthcare concern marked by its exponential growth and significant economic ramifications. Though advancements in the treatment modalities have increased the overall survival and quality of life, there are no definite treatments for the advanced stages of this malady. Hence, understanding the diseases etiologies and the underlying molecular complexities, will usher in the development of innovative therapeutics. Recently, YAP/TAZ transcriptional regulation has been of immense interest due to their role in development, tissue homeostasis and oncogenic transformations. YAP/TAZ axis functions as coactivators within the Hippo signaling cascade, exerting pivotal influence on processes such as proliferation, regeneration, development, and tissue renewal. In cancer, YAP is overexpressed in multiple tumor types and is associated with cancer stem cell attributes, chemoresistance, and metastasis. Activation of YAP/TAZ mirrors the cellular "social" behavior, encompassing factors such as cell adhesion and the mechanical signals transmitted to the cell from tissue structure and the surrounding extracellular matrix. Therefore, it presents a significant vulnerability in the clogs of tumors that could provide a wide window of therapeutic effectiveness. Natural compounds have been utilized extensively as successful interventions in the management of diverse chronic illnesses, including cancer. Owing to their capacity to influence multiple genes and pathways, natural compounds exhibit significant potential either as adjuvant therapy or in combination with conventional treatment options. In this review, we delineate the signaling nexus of YAP/TAZ axis, and present natural compounds as an alternate strategy to target cancer.
Neoplasms , Transcription Factors , Transcriptional Coactivator with PDZ-Binding Motif Proteins , YAP-Signaling Proteins , Animals , Humans , Antineoplastic Agents/therapeutic use , Antineoplastic Agents/pharmacology , Biological Products/therapeutic use , Biological Products/pharmacology , Neoplasms/drug therapy , Neoplasms/metabolism , Neoplasms/pathology , Signal Transduction/drug effects , Trans-Activators/metabolism , Transcription Factors/metabolism , Transcriptional Coactivator with PDZ-Binding Motif Proteins/metabolism , YAP-Signaling Proteins/metabolism
BACKGROUND: Most surveillance systems for catheter-related bloodstream infections (CRBSI) and central line-associated bloodstream infections (CLABSI) are based on manual chart review. Our objective was to validate a fully automated algorithm for CRBSI and CLABSI surveillance in intensive care units (ICU). METHODS: We developed a fully automated algorithm to detect CRBSI, CLABSI and ICU-onset bloodstream infections (ICU-BSI) in patients admitted to the ICU of a tertiary care hospital in Switzerland. The parameters included in the algorithm were based on a recently performed systematic review. Structured data on demographics, administrative data, central vascular catheter and microbiological results (blood cultures and other clinical cultures) obtained from the hospital's data warehouse were processed by the algorithm. Validation for CRBSI was performed by comparing results with prospective manual BSI surveillance data over a 6-year period. CLABSI were retrospectively assessed over a 2-year period. RESULTS: From January 2016 to December 2021, 854 positive blood cultures were identified in 346 ICU patients. The median age was 61.7 years [IQR 50-70]; 205 (24%) positive samples were collected from female patients. The algorithm detected 5 CRBSI, 109 CLABSI and 280 ICU-BSI. The overall CRBSI and CLABSI incidence rates determined by automated surveillance for the period 2016 to 2021 were 0.18/1000 catheter-days (95% CI 0.06-0.41) and 3.86/1000 catheter days (95% CI: 3.17-4.65). The sensitivity, specificity, positive predictive and negative predictive values of the algorithm for CRBSI, were 83% (95% CI 43.7-96.9), 100% (95% CI 99.5-100), 100% (95% CI 56.5-100), and 99.9% (95% CI 99.2-100), respectively. One CRBSI was misclassified as an ICU-BSI by the algorithm because the same bacterium was identified in the blood culture and in a lower respiratory tract specimen. Manual review of CLABSI from January 2020 to December 2021 (n = 51) did not identify any errors in the algorithm. CONCLUSIONS: A fully automated algorithm for CRBSI and CLABSI detection in critically-ill patients using only structured data provided valid results. The next step will be to assess the feasibility and external validity of implementing it in several hospitals with different electronic health record systems.
Catheter-Related Infections , Catheterization, Central Venous , Cross Infection , Sepsis , Humans , Female , Middle Aged , Cross Infection/epidemiology , Cross Infection/microbiology , Prospective Studies , Retrospective Studies , Catheter-Related Infections/diagnosis , Catheter-Related Infections/epidemiology , Catheter-Related Infections/microbiology , Catheters , Algorithms
Majority of the existing SARS-CoV-2 vaccines work by presenting the whole pathogen in the attenuated form to immune system to invoke an immune response. On the other hand, the concept of a peptide based vaccine (PBV) is based on the identification and chemical synthesis of only immunodominant peptides known as T-cell epitopes (TCEs) to induce a specific immune response against a particular pathogen. However PBVs have received less attention despite holding huge untapped potential for boosting vaccine safety and immunogenicity. To identify these TCEs for designing PBV, wet-lab experiments are difficult, expensive, and time-consuming. Machine learning (ML) techniques can accurately predict TCEs, saving time and cost for speedy vaccine development. This work proposes novel hybrid ML techniques based on the physicochemical properties of peptides to predict SARS-CoV-2 TCEs. The proposed hybrid ML technique was evaluated using various ML model evaluation metrics and demonstrated promising results. The hybrid technique of decision tree classifier with chi-squared feature weighting technique and forward search optimal feature searching algorithm has been identified as the best model with an accuracy of 98.19%. Furthermore, K-fold cross-validation (KFCV) was performed to ensure that the model is reliable and the results indicate that the hybrid random forest model performs consistently well in terms of accuracy with respect to other hybrid approaches. The predicted TCEs are highly likely to serve as promising vaccine targets, subject to evaluations both in-vivo and in-vitro. This development could potentially save countless lives globally, prevent future epidemic-scale outbreaks, and reduce the risk of mutation escape.
The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined. In addition, the influencing parameters and their contributing percentages to the performance of the Pelton wheel were calculated using different optimisation techniques such as Taguchi Design of Experiments (DoE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA) and Criteria Importance Through Intercriteria Correlation (CRITIC). The effect of input factors on the output response was examined with DoE, and the results show that the inlet pressure had the most significant impact (97.38%, 99.18%, and 97.38%, respectively, for all different spear sites with a 99% confidence level). In terms of preference values, the TOPSIS and GRA results are comparable (best ranks for simulation runs #24 and #25 and least ranks for simulations #2 and #3, respectively). The CRITIC results for the pressure parameter are in good agreement with the Taguchi ANOVA analysis. The last spear location (5 mm after the nozzle outlet), with an inlet pressure of 413685 Pa generated the best result when employing the TOPSIS and GRA techniques. The outlet pressure of the nozzle was found to have a significant impact on the flow pattern of the Pelton Wheel based on the analysis of the CRITIC, Taguchi, and CFD results.
Background: To evaluate the effect of dimethyl sulfoxide (DMSO) primer on microtensile bond strength (µTBS) and the micromorphological pattern of a hydroxyethyl methacrylate (HEMA)-free universal adhesive (UA) applied on wet/dry dentin in etch and rinse (E&R) mode before/after thermomechanical aging. Material and Methods: For the µTBS test, the mid-coronal dentin of 80 human mandibular first molars was exposed and etched with 35% phosphoric acid. Teeth were randomly divided into two equal groups: dry and wet dentin (n = 40). Then, each group was subdivided according to dentin pretreatment by DMSO before UA (Gluma Bond Universal, Heraeus Kulzer, Hanau, Germany) application into unpretreated and 10% DMSO/water (OT Primer S100, OT Oy Dent, Turku, Finland) pretreated (n = 20). Resin composite blocks were built up using a specially designed Teflon mold. In every subgroup, both the µTBS test and failure analysis by stereomicroscope were evaluated immediately after 24 h and after thermomechanical aging (n = 10). The data were statistically analyzed using a three-way analysis of variance (ANOVA) (p = 0.05). For the micromorphological pattern, 16 maxillary first premolars were distributed as mentioned in the µTBS test, prepared, and buccolingually sectioned. The dentin-resin interface was examined using an environmental scanning electron microscope (ESEM) (n = 2). Results: Three-way ANOVA revealed that the main effects and interactions between dentin wetness, dentin pretreatment, and evaluation time (thermomechanical aging) were not significant for µTBS (p> 0.05). Adhesive failure was the predominant type in all immediate and delayed specimens. Longer and more prominent resin tags were observed at dentin-resin interfaces after DMSO application. Conclusions: Neither the initial dentin wetness condition, dentin pretreatment, nor thermomechanical aging could affect the dentin bond strength. No correlation was found between the bond strength and the micromorphology findings. Key words:Wet/dry dentin bonding, Microtensile bond strength, Micromorphology, Universal adhesive, Dimethyl sulfoxide, Thermomechanical aging.
SKP2 (S-phase kinase-associated protein 2) is a member of the F-box family of substrate-recognition subunits in the SCF ubiquitin-protein ligase complexes. It is associated with ubiquitin-mediated degradation in the mammalian cell cycle components and other target proteins involved in cell cycle progression, signal transduction, and transcription. Being an oncogene in solid tumors and hematological malignancies, it is frequently associated with drug resistance and poor disease outcomes. In the current review, we discussed the novel role of SKP2 in different hematological malignancies. Further, we performed a limited in-silico analysis to establish the involvement of SKP2 in a few publicly available cancer datasets. Interestingly, our study identified Skp2 expression to be altered in a cancer-specific manner. While it was found to be overexpressed in several cancer types, few cancer showed a down-regulation in SKP2. Our review provides evidence for developing novel SKP2 inhibitors in hematological malignancies. We also investigated the effect of SKP2 status on survival and disease progression. In addition, the role of miRNA and its associated families in regulating Skp2 expression was explored. Subsequently, we predicted common miRNAs against Skp2 genes by using miRNA-predication tools. Finally, we discussed current approaches and future prospective approaches to target the Skp2 gene by using different drugs and miRNA-based therapeutics applications in translational research.
