Patient cancer care education aims to inform and empower patients by providing clear, relevant information about cancer, including its mechanisms, treatment options, and management strategies. This study evaluated the effectiveness and accuracy of existing patient cancer care education materials in Malaysia, specifically assessing patients’ understanding of treatment, side effects, and their management. Method: A descriptive, correlational study was conducted involving 20 cancer patients at Gleneagles Penang Medical Center, using the Patient Cancer Education Needs Assessment questionnaire. Data analysis was performed using SPSS version 21.0 and Microsoft Excel 2013. Result: Patient age, education level, occupation, and socioeconomic status were not significant factors influencing understanding. Findings highlight the need to improve existing educational materials to enhance patient comprehension and ensure materials are comprehensive, culturally appropriate, and innovative. Conclusion: Patient cancer care education materials should be comprehensive, interactive, and patient is friendly. Current materials require revision and enhancement to keep pace with technological developments, ensuring they are accessible, understandable, and effective in supporting patients’ knowledge of cancer treatment, side effects, management strategies, and psychosocial aspects.

In this study, an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process. Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved. Drug content increases with pellet size; therefore, particle size monitoring can ensure product safety and quality. The direct imaging system, consisting of a rigid endoscope, a light source, and a high-speed camera, provides real-time information about pellet size and layer uniformity, enabling timely intervention in the case of out-of-spec products. A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus, ensuring that pellet size could be accurately determined despite the dense flow of the particles. After training the model, the performance of the developed system was assessed by analysing the particle size distribution of pellet cores with variable sizes within the 250-850 μm size range. The endoscopic system was tested in-line at a larger scale during the drug layering of inert pellet cores. The particle size data acquired in real time with the endoscopic imaging system corresponded with the reference methods, demonstrating the feasibility of the proposed machine vision-based method as a process analytical technology tool for in-line process monitoring.

Background: and Purpose Neurocysticercosis is a parasitic infection caused by Taenia solium larvae that leads to various neurological symptoms, including vision loss. This systematic review analyzed cases of vision loss associated with neurocysticercosis to assess its etiology and vision outcomes. Methods: Following PRISMA guidelines, the review included reports on human subjects with vision loss due to neurocysticercosis and is registered with PROSPERO (CRD42024556278).The PubMed, Scopus, Embase, and Google Scholar databases were searched. Results: This review included 149 records from 176 patients with a mean age of 27.5 years, comprising 40.3% females, 59.1% males, and 0.6% subjects of unknown sex. Most cases were from Asia, predominantly India. The illness duration varied, but was mostly between 1 and 6 months.In addition to vision loss, common symptoms were headache or orbital pain (30.7%), seizures (12.5%), and altered consciousness (5.7%). Vision loss was mainly unilateral (72.7%). Imaging abnormalities included multiple cystic brain lesions (16.5%), enhanced lesions (4.0%), and calcified lesions (2.3%). Intravitreal and retinal regions were most affected (52.3%), followed by the anterior chamber (6.2%), orbital apex (5.1%), and optic nerve (6.2%). Anticysticercal drugs were the primary treatment, with 57.4% of cases showing improvement. Surgical excision was performed in 40.9% of cases with intravitreal or retinal cysts. Conclusions Vision loss in neurocysticercosis is mainly due to intravitreal and retinal involvement, and is frequently associated with multiple cystic brain lesions. Anticysticercal drugs can produce improvements, though surgical intervention is often needed for intravitreal or retinal cysts. Most of the patients in this review improved, though severe outcomes such as eye loss were reported.

Metabolic dysfunction-associated steatotic liver disease (MASLD), is the most common cause of liver disease, and its burden on health systems worldwide continues to rise at an alarming rate. MASLD is a complex disease in which the interactions between susceptible genes and the environment influence the disease phenotype and severity. Advances in human genetics over the past few decades have provided new opportunities to improve our understanding of the multiple pathways involved in the pathogenesis of MASLD. Notably, the PNPLA3, TM6SF2, GCKR, MBOAT7 and HSD17B13 single nucleotide polymorphisms have been demonstrated to be robustly associated with MASLD development and disease progression. These genetic variants play crucial roles in lipid droplet remodeling, secretion of hepatic very low-density lipoprotein and lipogenesis, and understanding the biology has brought new insights to this field. This review discusses the current body of knowledge regarding these genetic drivers and how they can lead to development of MASLD, the complex interplay with metabolic factors such as obesity, and how this information has translated clinically into the development of risk prediction models and possible treatment targets.

Background/Aims: Multi-society experts proposed the adoption of new terminology, metabolic dysfunctionassociated steatotic liver disease (MASLD) and steatotic liver disease (SLD). We studied the current prevalence of SLD and its subcategories in the US. Methods: Using the recent National Health and Nutrition Examination Survey from 2017 to 2023, we analyzed data from 12,199 participants (≥18 years) who completed transient elastography. SLD and its subcategories, including MASLD, metabolic and alcohol-related liver disease (MetALD), and alcohol-related liver disease (ALD), were categorized according to consensus nomenclature. Results: The age-adjusted prevalence of SLD (cut-off: 285 dB/m) was 35.0% (95% confidence interval [CI] 33.4–36.7). Within this category, the age-adjusted prevalence for MASLD was 31.9% (95% CI 30.4–33.4), MetALD 2.2% (95% CI 1.8–2.6), and ALD 0.8% (95% CI 0.6–1.1). The prevalence of SLD and MASLD showed a statistically insignificant decrease during COVID-19, while ALD increased without significance. In contrast, the prevalence of advanced fibrosis in SLD was significantly higher during the COVID-19 era, at 9.8% for 285 dB/m and 7.8% for 263 dB/m, compared to 7.4% (P=0.039) and 6% (P=0.041) in the pre-COVID-19 era. The proportion of advanced fibrosis and cirrhosis in individuals with ALD was two-fold higher than MASLD and MetALD, largely due to increases during the COVID-19 era. Conclusions While the prevalence of SLD and its subcategories remained stable, there was a significant increase in advanced fibrosis among SLD individuals during the COVID-19 era, with ALD having a proportion of advanced fibrosis and cirrhosis that was twice as high as MASLD and MetALD.