Background: s/Aims: Postoperative pancreatic fistulas (POPF) remain a major cause of morbidity and mortality following pancreatoduodenectomy (PD). Pancreatogastrostomy (PG) and pancreatojejunostomy (PJ) are the two most commonly used reconstruction techniques, yet evidence favoring one over the other is inconclusive. This study evaluates postoperative outcomes following open PD at a single institution that transitioned from PG to PJ as the preferred reconstruction method. Methods: This retrospective comparative study included patients who underwent PD between April 2005 and August 2022. Of 757 patients identified, 522 met the inclusion criteria. Propensity score matching (PSM) was performed to adjust for clinically relevant covariates. Primary endpoints were clinically relevant (CR) POPF (grade B/C) and Clavien–Dindo (CD) grade ≥ 3 POPFs. Secondary outcomes included post-pancreatectomy hemorrhage (PPH), delayed gastric emptying (DGE), systemic complications, length of hospital stay, and mortality. Results: Overall, CR-POPF and CD grade ≥ 3 POPFs occurred in 21.3% and 8.0% of patients, respectively. Thirty-day and in-hospital mortality rates were 3.1% and 4.2%. After PSM, 368 patients (184 PG and 184 PJ) were analyzed. Grade B POPFs were more frequent following PJ than PG (24.5% vs. 15.8%, p < 0.001). Although CR-POPF and CD grade ≥ 3 POPFs were numerically higher in the PJ group, differences were not statistically significant. In contrast, DGE, PPH, and in-hospital mortality were significantly higher following PG (37.0% vs. 25.0%, p = 0.025; 16.3% vs. 8.7%, p = 0.025; and 7.6% vs. 2.7%, p = 0.049, respectively). Conclusions PG was associated with a lower incidence of grade B POPFs but higher rates of DGE, PPH, and in-hospital mortality.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

Objective: : Glioblastoma multiforme (GBM), particularly the isocitrate dehydrogenase (IDH)-wildtype type, represents a significant clinical challenge due to its aggressive nature and poor prognosis. Despite advancements in medical imaging and its modalities, survival rates have not improved significantly, demanding innovative treatment planning and outcome prediction approaches. Methods: : This study utilizes a support vector machine (SVM) classifier using radiomics features to predict the overall survival (OS) of GBM, IDH-wildtype patients to short (<12 months) and long (≥12 months) survivors. A dataset comprising multi-parametric magnetic resonance imaging scans from 574 patients was analyzed. Radiomic features were extracted from T1, T2, fluid-attenuated inversion recovery, and T1 with gadolinium (T1GD) sequences. Low variance features were removed, and recursive feature elimination was used to select the most informative features. The SVM model was trained using a k-fold cross-validation approach. Furthermore, clinical parameters such as age, gender, and MGMT (O6-methylguanine-DNA methyltransferase) promoter methylation status were integrated to enhance prediction accuracy. Results: : The model showed reasonable results in terms of cross-validated area under the curve of 0.84 (95% confidence interval, 0.80–0.90) with (p<0.001) effectively categorizing patients into short and long survivors. Log-rank test (chi-square statistics) analysis for the developed model was 0.00029 along with the 1.20 Cohen’s d effect size. Most importantly, clinical data integration further refined the survival estimates, providing a more fitted prediction that considers individual patient characteristics by Kaplan-Meier curve with p-value <0.0001. Conclusion : The proposed method significantly enhances the predictive accuracy of OS outcomes in GBM, IDH-wildtype patients. By integrating detailed imaging features with key clinical indicators, this model offers a robust tool for personalized treatment planning, potentially improving OS.

Objective: : Glioblastoma multiforme (GBM), particularly the isocitrate dehydrogenase (IDH)-wildtype type, represents a significant clinical challenge due to its aggressive nature and poor prognosis. Despite advancements in medical imaging and its modalities, survival rates have not improved significantly, demanding innovative treatment planning and outcome prediction approaches. Methods: : This study utilizes a support vector machine (SVM) classifier using radiomics features to predict the overall survival (OS) of GBM, IDH-wildtype patients to short (<12 months) and long (≥12 months) survivors. A dataset comprising multi-parametric magnetic resonance imaging scans from 574 patients was analyzed. Radiomic features were extracted from T1, T2, fluid-attenuated inversion recovery, and T1 with gadolinium (T1GD) sequences. Low variance features were removed, and recursive feature elimination was used to select the most informative features. The SVM model was trained using a k-fold cross-validation approach. Furthermore, clinical parameters such as age, gender, and MGMT (O6-methylguanine-DNA methyltransferase) promoter methylation status were integrated to enhance prediction accuracy. Results: : The model showed reasonable results in terms of cross-validated area under the curve of 0.84 (95% confidence interval, 0.80–0.90) with (p<0.001) effectively categorizing patients into short and long survivors. Log-rank test (chi-square statistics) analysis for the developed model was 0.00029 along with the 1.20 Cohen’s d effect size. Most importantly, clinical data integration further refined the survival estimates, providing a more fitted prediction that considers individual patient characteristics by Kaplan-Meier curve with p-value <0.0001. Conclusion : The proposed method significantly enhances the predictive accuracy of OS outcomes in GBM, IDH-wildtype patients. By integrating detailed imaging features with key clinical indicators, this model offers a robust tool for personalized treatment planning, potentially improving OS.

Objective: : Glioblastoma multiforme (GBM), particularly the isocitrate dehydrogenase (IDH)-wildtype type, represents a significant clinical challenge due to its aggressive nature and poor prognosis. Despite advancements in medical imaging and its modalities, survival rates have not improved significantly, demanding innovative treatment planning and outcome prediction approaches. Methods: : This study utilizes a support vector machine (SVM) classifier using radiomics features to predict the overall survival (OS) of GBM, IDH-wildtype patients to short (<12 months) and long (≥12 months) survivors. A dataset comprising multi-parametric magnetic resonance imaging scans from 574 patients was analyzed. Radiomic features were extracted from T1, T2, fluid-attenuated inversion recovery, and T1 with gadolinium (T1GD) sequences. Low variance features were removed, and recursive feature elimination was used to select the most informative features. The SVM model was trained using a k-fold cross-validation approach. Furthermore, clinical parameters such as age, gender, and MGMT (O6-methylguanine-DNA methyltransferase) promoter methylation status were integrated to enhance prediction accuracy. Results: : The model showed reasonable results in terms of cross-validated area under the curve of 0.84 (95% confidence interval, 0.80–0.90) with (p<0.001) effectively categorizing patients into short and long survivors. Log-rank test (chi-square statistics) analysis for the developed model was 0.00029 along with the 1.20 Cohen’s d effect size. Most importantly, clinical data integration further refined the survival estimates, providing a more fitted prediction that considers individual patient characteristics by Kaplan-Meier curve with p-value <0.0001. Conclusion : The proposed method significantly enhances the predictive accuracy of OS outcomes in GBM, IDH-wildtype patients. By integrating detailed imaging features with key clinical indicators, this model offers a robust tool for personalized treatment planning, potentially improving OS.

INTRODUCTION: Acute severe ulcerative colitis (ASUC) is a significant cause of disease morbidity. One-third of patients with ASUC are steroid refractory. Rescue therapy may not successfully induce remission, necessitating colectomy. We aimed to identify predictors of rescue therapy and colectomy in ASUC assessed within 24 h of admission for early risk stratification. METHODS: We conducted a retrospective cohort study of 58 admissions for ASUC among 47 patients from August 2002 to January 2022. Serum biomarkers assessed were measured on admission. Primary outcomes were the need for rescue therapy during the same admission and colectomy within 1 year of admission. RESULTS: Rescue therapy (all with infliximab) was given in 20 (34.5%) of the admissions. Colectomy was done within 1 year for nine (15.5%) of the admissions. An elevated C-reactive protein (CRP) of >30 mg/L (relative risk [RR] 1.63), a CRP-albumin ratio of >0.85 (RR 1.63), and a composite factor of both CRP > 30 mg/L and age ≥60 years (RR 2.37) were significantly associated with the need for rescue therapy. Hypoalbuminaemia ≤ 25 g/L (RR 4.35) and the use of biologics at presentation (RR 1.54) were significantly associated with colectomy within 1 year of admission, while a CRP of ≥ 80 mg/L was a significant protective factor (RR 0.70). CONCLUSION Patients with ASUC who have elevated CRP or CRP-albumin ratio on admission should be considered at risk for steroid-refractory disease. Those with hypoalbuminaemia on admission and using biologics at presentation are more likely to require colectomy in the first year after admission for ASUC.
Humans ; Colitis, Ulcerative/therapy* ; Colectomy ; Retrospective Studies ; Male ; Female ; Middle Aged ; Adult ; C-Reactive Protein/metabolism* ; Infliximab/therapeutic use* ; Biomarkers/blood* ; Acute Disease ; Aged ; Severity of Illness Index ; Treatment Outcome

INTRODUCTION: The primary objective of this guideline is to establish evidence-based recommendations for the clinical use of parenteral nutrition (PN) in adult patients within the acute hospital setting in Singapore. METHOD: An expert workgroup, consisting of healthcare practitioners actively involved in clinical nutrition support across all public health institutions, systematically evaluated existing evidence and addressed clinical questions relating to PN therapy. RESULTS: This clinical practice guideline developed 30 recommendations for PN therapy, which cover these key aspects related to PN use: indications, patient assess-ment, titration and formulation of PN bags, access routes and devices, and monitoring and management of PN-related complications. CONCLUSION This guideline provides recommendations to ensure appropriate and safe clinical practice of PN therapy in adult patients within the acute hospital setting.
Humans ; Singapore ; Parenteral Nutrition/adverse effects* ; Adult

INTRODUCTION: Paediatric sexual assault (SA) victims should be assessed for post-exposure prophylaxis (PEP) to mitigate the risk of sexually transmitted infections (STIs). We describe the clinical characteristics of children and young persons (CYPs) presenting with SA at KK Women's and Children's Hospital in Singapore, viral PEP (human immunodeficiency virus [HIV] and hepatitis B virus [HBV]) prescribing practices, and STI evaluation at follow-up. METHOD: Medical records of CYPs ≤16 years who presented with SA between January 2022 and August 2023 were reviewed, including assault and assailant characteristics, baseline and follow-up STI screening, PEP prescription, adherence and follow-up attendance. CYPs with SA in the preceding 72 hours by HIV-positive or HIV-status unknown assailants with high-risk characteris-tics were eligible for HIV PEP. RESULTS: We analysed 278 CYPs who made 292 SA visits. There were 40 (13.7%) CYPs eligible for HIV PEP, of whom 29 (82.9%) received it. Among those tested at baseline, 9% and 34.9% of CYPs tested positive for Chlamydia trachomatis and Gardnerella vaginalis, respectively. None tested positive for Neisseria gonorrhoeae, Trichomonas vaginalis, HIV, HBV or hepatitis C. Majority of CYPs tested were HBV non-immune (n=167, 67.6%); only 77 (46.1%) received the vaccine. Out of 27 CYPs eligible for HBV PEP with immunoglobulin, only 21 (77.7%) received immunoglobulin. A total of 37 CYPs received HIV PEP, including 8 who were retrospectively deemed ineligible. Only 10 (27%) completed the course. Overall, 153 (57.7%) CYPs attended follow-up, and none seroconverted for HIV or HBV. CONCLUSION We report suboptimal rates of HBV post-exposure vaccination, and low compliance to HIV PEP and follow-up among paediatric SA victims. Factors contri-buting to poor compliance should be examined to optimise care for this vulnerable population.
Humans ; Post-Exposure Prophylaxis/methods* ; Female ; Child ; Adolescent ; Singapore/epidemiology* ; HIV Infections/prevention & control* ; Male ; Sexually Transmitted Diseases/epidemiology* ; Retrospective Studies ; Hepatitis B/prevention & control* ; Follow-Up Studies ; Child, Preschool ; Sex Offenses/statistics & numerical data* ; Child Abuse, Sexual

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Nicotinamide adenine dinucleotide (NAD⁺) is a central and pleiotropic metabolite involved in multiple cellular energy metabolism, such as cell signaling, DNA repair, protein modifications, and so on. Evidence suggests that NAD⁺ levels decline with age, obesity, and hypertension, which are all significant CVD risk factors. In addition, the therapeutic elevation of NAD⁺ levels reduces chronic low-grade inflammation, reactivates autophagy and mitochondrial biogenesis, and enhances antioxidation and metabolism in vascular cells of humans with vascular disorders. In preclinical animal models, NAD⁺ boosting also extends the health span, prevents metabolic syndrome, and decreases blood pressure. Moreover, NAD⁺ storage by genetic, pharmacological, or natural dietary NAD⁺-increasing strategies has recently been shown to be effective in improving the pathophysiology of cardiac and vascular health in different animal models and humans. Here, we discuss NAD⁺-related mechanisms pivotal for vascular health and summarize recent research on NAD⁺ and its association with vascular health and disease, including hypertension, atherosclerosis, and coronary artery disease. This review also assesses various NAD⁺ precursors for their clinical efficacy and the efficiency of NAD⁺ elevation in the prevention or treatment of major CVDs, potentially guiding new therapeutic strategies.
Humans ; Cardiovascular Diseases/physiopathology* ; NAD/metabolism* ; Animals ; Hypertension/metabolism*