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The carrot plant (Daucus carota) and its components are traditionally reported for the management of gastric ulcers. This study was performed to evaluate the role of carrot when administered concurrently with a conventional antiulcer treatment, pantoprazole, in alleviating gastric and duodenal ulcers in female experimental animals. The study involved standard animal models to determine the ulcer preventive effect using pylorus ligation, ethanol, and stress induced acute gastric ulcer models and duodenal ulcer models involving cysteamine. Acetic acid-induced chronic gastric ulcer and indomethacin-induced gastric ulcer models were used to evaluate the ulcer healing effect. Carrot fruit (500 mg/kg) and its co-administration with pantoprazole produced significant protection in an ethanol- and stress-induced acute gastric ulcer and cysteamine-induced duodenal ulcer. The healing of the acetic acid-induced chronic gastric ulcer was also augmented with this combination. Both total proteins and mucin contents were significantly increased in indomethacin-induced gastric ulcers. Similarly, in pylorus ligation, the pepsin content of gastric juice, total acidity, and free acidity were reduced. Overall, both ulcer preventive effects and ulcer healing properties of the pantoprazole were significantly enhanced in animals who received the co-administration of carrot fruit (500 mg/kg).

Automated dispensing cabinets (ADCs) represent a critical innovation in modern healthcare, revolutionizing medication management by improving efficiency, accuracy, and security. With the increasing reliance on these technologies, optimizing their performance is paramount. This study aims to apply conventional, hybrid time series, and machine learning models to forecast three key performance indicators of ADCs: items dispensation, override occurrences, and error integration. Using monthly data from the MICU at Almoosa Hospital between January 2023 and December 2024, we employed both traditional linear time series models (e.g., autoregressive models, simple exponential smoothing, autoregressive moving average, and theta models) and advanced non-linear machine learning models (e.g., NPAR, Artificial Neural Networks (ANN)) in various hybrid configurations (ARIMA-ANN, EMS-ANN, NPAR-ANN). Model accuracy was assessed using key metrics such as RMSE, MAE, MAPE, and RMSLE, with a bootstrap 95% CI to ensure the best performance for predicting future trends. The study demonstrated that the NPAR-ANN, a hybrid model combining nonparametric ARIMA and artificial neural networks, showed superior performance. The model demonstrated the best performance, achieving the lowest RMSE values. Specifically, for the number of items issued, it attained an RMSE of 71.50, for overrides an RMSE of 15.43, while for error integration, and an RMSE of 20.92 lowest among all competing models. This novel study modeled key parameters of ADCs, providing data-driven insights that can inform hospital decision-making and optimize medication management. The study showcased the application of hybrid machine learning models in forecasting critical ADC parameters, offering valuable data-driven insights for hospital administrators.

Background The Automated Dispensing Cabinets (ADCs) represent one of the most widely deployed forms of technology integrated with today’s medication-use systems. Despite the rise of ADC use and subsequent benefits, research exploring the impacts of ADCs on staff acceptance and satisfaction is still relatively limited and not thoroughly investigated. The present study aims to address this by assessing the impact of ADC implementation on healthcare staff satisfaction. Methods This cross-sectional study was conducted in Almoosa Specialist hospital, Al-Ahsa, KSA, involving 203 healthcare staff participants selected through a convenience sampling approach considering the busy and tough schedule of staff. The questionnaire, named ADC User Acceptance Survey (ADC-UAS), was developed using a 10-item scale designed to measure Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Behavioral Intention to Use ADCs. This instrument employed a 7-point Likert scale and was based on the Modified Technology Acceptance Model (TAM). Pearson’s correlation was computed to investigate the correlation between demographic and TAM factors. The Artificial Neural Network (ANN) model was applied to assess the influential factors, and results were declared statistically significant if p  < 0.05. Results Out of 203 healthcare professionals, the majority were nurses (82.8%) and females (86.7%), with a mean age of 31.94 ± 5.96 years. The findings demonstrated high ADC acceptance and satisfaction, with 87.2% of participants reporting improved efficiency and 92.1% acknowledging enhanced patient safety. The strong positive relationship between current unit experience and acceptance ( r  = 0.304, p  = 0.000) showed that individuals with more experience in their current unit are more likely to accept the system. Acceptance of ADC was significantly correlated with its usefulness ( r  = 0.820, p  = 0.000). Positive correlation was also observed between professional experience and the perceived usefulness of the system ( r  = 0.144, p  = 0.040). The result of the ANN model identified professional experience (100%), current unit experience (99.9%), and automation experience (97.8%) as the strongest predictors of ADC acceptance. Conclusion The study revealed high acceptance and satisfaction with ADCs among Almoosa healthcare staff, emphasizing that these systems make work more manageable and efficient. Given the high levels of acceptance and satisfaction among healthcare professionals regarding ADCs, it is recommended that healthcare facilities continue to invest in and expand the use of ADC systems.

Technology has increasingly influenced the provision of healthcare services by enhancing patient safety, optimising workflows, and improving efficiency. Large healthcare facilities have adopted automated dispensing cabinets (ADCs) as an advanced technological solution. A key gap exists in understanding the ADC implementation experience in different contexts. Therefore, this study seeks to fill this literature gap by exploring key stakeholders’ perspectives on the benefits, barriers, and improvement opportunities related to ADCs, offering valuable insights to support their effective integration across various healthcare settings. This qualitative study was conducted in Saudi Arabia. The implementation of ADCs generally has positive outcomes for all staff. The system has brought about enhanced medication tracking, greater time efficiency, along with reduced workload and medication errors. However, there are barriers to their implementation, including changes in workflow and workload distribution, cabinet design, technical medication management challenges, and the need for staff training. To maximise the effectiveness of ADCs, healthcare organisations should focus on improving operational workflows, providing ongoing staff training, and maintaining robust system monitoring. Additionally, manufacturers should focus on advancing technology to further enhance the efficiency and functionality of ADCs.

There has been an increase in the prevalence of gram-positive bacteremia in neonates in the last two decades. However, as a consequence of better care, there has been an increase in the survival of premature neonates. Coagulase-negative staphylococci (CoNS) is the most prevalent bacteria, responsible for up to 60% of late-onset sepsis (LOS). Daptomycin, a lipopeptide antimicrobial agent, is active against CoNS. This was an observational, retrospective case series study carried out in the Pediatric Hospital of King Saud Medical City, Riyadh, Saudi Arabia. The medical records of 21 neonates, aged 0–28 days, who were treated in Neonatal Intensive Care Unit (NICU) with intravenous daptomycin as monotherapy or combination therapy for at least 4 days for proven gram-positive infection between June 2019 to July 2020, were included. The median gestational and chronological age were 27 weeks and 5 days, respectively. The most frequent diagnosis in neonates was infective endocarditis (42.9%). Of the 21 patients who received daptomycin therapy, 13 (62%) recovered and 8 died. The clinical cure rate was higher in Staphylococcus hominis (100%) and in patients who received 6 mg/kg/dose twice daily (62.5%). The mean of aspartate aminotransferase significantly elevated after starting daptomycin (p = 0.048). However, no muscular or neurological toxicity of daptomycin was documented in any of the cases. Overall, daptomycin was well tolerated, even with long-term treatment.

Maintaining a sterile environment in operative theatres is crucial for minimizing the risk of healthcare-associated infections (HAIs), which can lead to prolonged recovery, increased healthcare costs, and significant morbidity or mortality. This study explores the historical evolution of sterilization methods, assesses current standards and guidelines, and identifies challenges faced in sterilization processes. Historically, sterilization techniques have transitioned from rudimentary practices, such as boiling water used by ancient civilizations, to the introduction of steam sterilization, which revolutionized infection control in surgical settings. Pioneers like Louis Pasteur and Joseph Lister laid the groundwork for modern aseptic techniques, significantly reducing postoperative infection rates. Today, sterilization practices are guided by authoritative organizations such as the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO), which advocate for standardized protocols to ensure patient safety. The most prevalent sterilization methods include steam sterilization, ethylene oxide gas sterilization, and hydrogen peroxide vapor sterilization, each with specific applications and limitations. Steam sterilization remains the gold standard due to its efficacy and cost-effectiveness, but the complexity of modern surgical instruments presents ongoing challenges. Innovative heat-based sterilization techniques, particularly moist heat methods, have emerged as effective solutions for pathogen elimination. Recent advancements, such as pulsating vacuum technology, enhance steam penetration and improve sterilization outcomes for porous materials. However, challenges persist, including the variability in microbial resistance, the impact of biofilms on sterilization efficacy, and the compatibility of materials with various sterilization methods. The growing trend towards minimally invasive surgery further complicates sterilization efforts due to the intricate designs of instruments used. This study underscores the need for continuous updates to sterilization protocols, informed by the latest research and technological advancements, to ensure optimal patient outcomes and mitigate the risks associated with surgical procedures.

Antibiotics used in dentistry are frequently used and abused. Antibiotic prescriptions in dentistry can be either preventative or therapeutic. Because of their selective toxicity, which allows them to injure or destroy microorganisms without harming the host cells, they are useful against infections. Eliminating antibiotic misuse has received a lot of attention since it may be achieved by choosing antimicrobial agents wisely, being well-informed about the location of infections, patient characteristics, and the microorganism's resistance to a particular antibiotic. Finding the reasons behind the use of antibiotics in dentistry is necessary for a complete comprehension of the dentist's role in this worldwide health concern. This study emphasizes antibiotic prescription strategies, identifies factors linked to dental patients' appropriate and inappropriate use of antibiotics, offers insights into the importance of antibiotic indications in the dental field, and encourages dentists to reevaluate the prescriptions they write. Antibiotic-resistant infections are a major danger to world health because they make it more difficult to treat common infections and perform intricate medical procedures. Misuse of antibiotics, especially in low- and middle-income nations, is making the issue worse. Aim: The aim of this study is to investigate the use and misuse of antibiotics in dentistry. To describe antibiotic prescribing behaviors in dentistry, including clinical and nonclinical indications for their use, the type and regimen of antibiotics prescribed, and factors influencing their prescription.