Future Science OA最新文献

Background: Shoulder dystocia, a challenging condition for obstetricians, poses significant risks to both maternal and neonatal health, including maternal postpartum hemorrhage, neonatal hypoxia, and brachial plexus injury. Despite being unpredictable and unpreventable, effective management can mitigate these risks. Miscommunication and poor leadership are responsible for 72% of medical errors, which further highlights the importance of robust leadership skills in obstetric emergencies.

Research design and methods: A qualitative study involving 20 participants through structured interviews assessed preferred leadership styles in managing shoulder dystocia.

Results: Findings revealed that 55% of participants favored quantum leadership. Other preferences included laissez-faire by one anesthesiologist and democratic by two midwives. However, all participants acknowledged the efficacy of the seven quantum leadership skills in managing shoulder dystocia. Discussion emphasized that traditional leadership styles are less effective compared to quantum leadership in managing the complexities of shoulder dystocia. The quantum Ob-Wheel, consisting of 12 milestones, integrates these seven interdependent skills to guide the management process.

Conclusions: Despite the limited sample size of this study, it is worth noting that, given the unpredictable nature of shoulder dystocia, clinicians should be prepared for its occurrence during any birth, with quantum leadership providing a strategic advantage in such scenarios.

Aim: To investigate the comprehensive expression levels and possible molecular mechanisms of Anaphase Promoting Complex Subunit 1 (ANAPC1) in lung squamous cell carcinoma (LUSC).

Methods: Data from 2,031 samples were combined to evaluate ANAPC1 mRNA levels, and 118 samples were collected for immunohistochemical (IHC) analysis. High-expression co-expressed genes (HECEGs) associated with ANAPC1 were analyzed for signaling pathways. Clinical significance, immune computations, and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) validation of ANAPC1's role in LUSC were assessed. Molecular docking evaluated binding affinity with potential therapeutics.

Results: ANAPC1 mRNA was significantly upregulated in LUSC (SMD = 1.97, 95% CI [1.26-2.67]). Protein-level analysis confirmed this upregulation (p < 0.001). Most HECEGs associated with ANAPC1 were enriched in cell cycle pathways. Higher ANAPC1 expression correlated with poorer survival in LUSC patients (HR = 1.11, 95% CI: 1-1.49). ANAPC1 expression was higher in males and N1-stage vs. females and N0-stage; lower in grade I vs. II/III. Overexpression reduces immune cell infiltration and immunotherapy effectiveness, while knockdown inhibits cell proliferation. Drug sensitivity and docking analyses identified tenovin-1, carboxyatractyloside, and phycocyanobilin as potential antitumor agents targeting ANAPC1.

Conclusion: The elevated expression of ANAPC1 might play a role in LUSC advancement and progression through its participation in cell growth-related pathways.

Introduction: CHA2DS2-VASc and CHA2DS2-VA scores are often used to demonstrate thromboembolic risk in nonvalvular atrial fibrillation. Elevated whole blood viscosity is an independent risk factor for ischemic stroke.

Objective: This study aimed to ascertain the correlation between whole blood viscosity and CHA2DS2-VASc/CHA2DS2-VA scores.

Methods: This study was performed retrospectively in a tertiary cardiac facility, encompassing 150 patients.

Results: The study's results demonstrate that whole blood viscosity, concerning both high shear rate and low shear rate variables, are statistically significant in forecasting the likelihood of elevated CHA2DS2-VA and CHA2DS2-VASc scores. (AUC: 0.690, 0.693; p: <0.001; 0.647, 0.665; p: <0.05).

Conclusion: Whole blood viscosity had a substantial correlation with the CHA2DS2-VASc/CHA2DS2-VA scores in patients with atrial fibrillation and may be used to evaluate thromboembolism risk, akin to these scores.

Objectives: Global concerns were focused on the improper disposal of unwanted medications and using out-of-date medicines. This study aims to assess pharmacists' knowledge, attitudes, and practices regarding this issue, recognizing the role pharmacies can play as local collection points for the safe disposal of unwanted medications.

Methods: A cross-sectional study design including a random sample of 603 pharmacists responded to the questionnaire via face-to-face interview. Multivariate logistic regression models determined significant factors affecting the knowledge, attitudes, and practices of pharmacists.

Results: The levels of knowledge, attitudes, and practices were generally low. Only 32.8% showed good knowledge, 17.7% had positive attitudes, and 32% exhibited good practices. Certain demographic factors were positively associated with higher levels of knowledge, attitudes, and practices. These include male pharmacists, longer duration of experience, working in a chain pharmacy, working as a chief pharmacist, and receiving training about environmental impact and waste management.

Conclusion: This study illustrated serious gaps in knowledge and practices among community pharmacists in the United Arab Emirates regarding medicines waste reduction. Despite awareness, nearly half had poor knowledge, and best practices were inconsistently implemented. Proper educational campaigns and courses, comprehensive training, and policy interventions are essential to address these gaps.

Aims: Ficus vasta Forssk. is a valuable but relatively less explored medicinal and edible plant. This study focused on analyzing the biochemical properties, molecular docking, and ADMET profiling of its n-hexane extract (NHFV).

Materials and methods: Phytochemical screening was performed using GC-MS and total bioactive content assays (TPC, TFC, and TTC). Antioxidant potential (NOS and TAC), antiurease, antityrosinase, and hemolytic activities were also assayed. Molecular docking was performed for GC-MS identified ligands against urease and tyrosinase. ADMET investigation was performed to assess drug-likeness and safety profiles.

Results: NHFV showed significant concentration of TPC (48.01 ± 0.73 mg GA.Eq.g^-1), TFC (65.33 ± 0.67 mg QU.Eq.g^-1), and TTC (3.45 ± 0.31 mg TA.Eq.g^-1). GC-MS analysis identified 43 phytochemicals. Antioxidant assays revealed 91.34 ± 0.86 mg AA.Eq.g^-1 NOS and 72.90 ± 0.10 mg AA.Eq.g^-1 TAC activity. The extract showed 4.64 ± 0.08% hemolysis, 60.20 ± 1.39% urease, and 75.61 ± 0.64% tyrosinase inhibition. Docking results revealed Cycloartenol (-8.2 kcal/mol) and Lupeol acetate (-8.3 kcal/mol) as potent inhibitors, surpassing standard agents.

Conclusion: NHFV possesses prominent antioxidant, antiulcer, and skin-whitening potential. Molecular docking and ADMET data support its therapeutic relevance and potential for future drug design.

Artificial intelligence (AI) has demonstrated remarkable potential in transforming medical diagnostics across various healthcare domains. This paper explores AI applications in cancer detection, dental medicine, brain tumor database management, and personalized treatment planning. AI technologies such as machine learning and deep learning have enhanced diagnostic accuracy, improved data management, and facilitated personalized treatment strategies. In cancer detection, AI-driven imaging analysis aids in early diagnosis and precise treatment decisions. In dental healthcare, AI applications improve oral disease detection, treatment planning, and workflow efficiency. AI-powered brain tumor databases streamline medical data management, enhancing diagnostic precision and research outcomes. Personalized treatment planning benefits from AI algorithms that analyze genetic, clinical, and lifestyle data to recommend tailored interventions. Despite these advancements, AI integration faces challenges related to data privacy, algorithm bias, and regulatory concerns. Addressing these issues requires improved data governance, ethical frameworks, and interdisciplinary collaboration among healthcare professionals, researchers, and policymakers. Through comprehensive validation, educational initiatives, and standardized protocols, AI adoption in healthcare can enhance patient outcomes and optimize clinical decision-making, advancing the future of precision medicine and personalized care.

Background: This study incorporates Fitbit wearable sensor technology into a mobile application named Cancer Wellness Program (CWP) for patient monitoring. The objective of this study is to explore the experiences of healthcare providers in using the CWP application for managing symptoms of people with cancer and in delivering health education programs. Methods: A qualitative study design with a purposive sampling approach was employed, using a structured, in-depth interview method to involve 15 healthcare workers. Results: Key features of the CWP application include a patient education platform, a dashboard to monitor patient health data and learning progress, and interactive communication between the two parties. Multiple advantages of this application were identified by healthcare providers, namely user-friendliness, data aggregation and personalization. Conclusion: Despite minor technical drawbacks, the CWP application proves to be a powerful assistant for healthcare providers to optimize patient care.

Objective: This study assesses the cost-effectiveness of carfilzomib plus lenalidomide and dexamethasone (KRd) versus ixazomib plus lenalidomide and dexamethasone for relapsed and refractory multiple myeloma (RRMM) in China.

Methods: A survival model was used to analyze health states and costs over a lifetime, with a 4-week cycle. Treatment effects on progression-free survival (PFS) and overall survival (OS) were modeled using hazard ratios (HRs) derived from the network meta-analysis (NMA). Health state utility values and disutility values for adverse events were obtained from published literature. Direct medical costs included drug costs, disease management costs, and costs associated with adverse event management. Costs and utilities were discounted by 5% annually. Both one-way and probabilistic sensitivity analyses were conducted.

Results: The carfilzomib combination was found to be cost-effective, saving $127,513.22 per additional quality-adjusted life year (QALY) gained compared to the ixazomib combination. Sensitivity analysis showed that ixazomib's price, progression state utility, and carfilzomib's price significantly affected the results. At a $40,023.27 willingness-to-pay (WTP) threshold, the carfilzomib combination has a 100% probability of being cost-effective.

Conclusions: The study shows that, based on evidence from indirect comparisons, KRd is a cost-effective treatment option for RRMM patients in China.