Marsupialization followed by enucleation of a large maxillary dentigerous cyst in a young child: A case report and literature review.

INTRODUCTION: This report presents a rare case of a dentigerous cyst (DC) associated with the maxillary right canine in a young child, successfully treated with marsupialization followed by enucleation. PRESENTATION OF CASE: A 9-year-old girl was referred to a maxillofacial hospital after routine dental exam revealed a large lesion in maxilla. Radiograph showed a 5 × 6 cm unilocular radiolucent lesion in the right maxillary sinus, with destruction of the sinus and nasal cavity walls and displacement of the upper right canine into the floor of the right eye. Marsupialization was performed, and the patient was monitored every 6 months. Histology confirmed a dentigerous cyst lined with non-keratinized stratified cuboidal squamous epithelium. One-year post-surgery, the cyst had significantly reduced in size, and the canine had descended. A second surgery was performed to completely remove the cyst and the associated canine. DISCUSSION: This case demonstrates the successful management of a large dentigerous cyst in a 9-year-old patient through staged treatment, initially with marsupialization, followed by complete cyst removal. The conservative approach allowed for the reduction of the cyst size and facilitated the natural descent of the displaced canine. Regular follow-up and timely surgical intervention were crucial in achieving a positive outcome and preventing recurrence. CONCLUSION: This case highlights the effectiveness of marsupialization in managing maxillary dentigerous cysts in young children.

Nature-based solutions for improving food security: A systematic global review.

Nature-based solutions (NBS) have been promoted as a holistic way to solve a variety of societal issues while benefiting biodiversity at the same time. To date, applications of NBS approaches that help ensure food security have yet been systematically reviewed. In this paper, we critically review the specific NBS for food security, highlighting their limitations, to provide recommendations that promote their applications for improving global food security. We accessed and evaluated publications on four different scholastic databases, and our systematic review of relevant materials indicated that many NBS approaches can be applied to enhance food security dimensions individually or together. However, there is a strong bias towards food availability, and not enough research has been done to link NBS with improvements in food access and utilization. Over 80 % of the reviewed papers were of short-term studies or without specific timeframes, and 25 % offered no information on the economic effectiveness of NBS. Environmental benefits of NBS were explicitly described in about 60 % of these papers, and biodiversity enhancement was measured in only about 10 %. We, therefore, recommend future applications of NBS to safeguard food security be shifted to food access and utilization with careful consultation with local communities to address their specific context, using indicators that are easily measured and managed. Systematic monitoring regimes and robust and diversified financial support systems are also equally important in efforts to successfully implement NBS. Moreover, environmental and societal benefits, especially water productivity and biodiversity, must be incorporated into the planning and design of NBS.

The accuracy of deep learning models for diagnosing maxillary fungal ball rhinosinusitis.

PURPOSE: To assess the accuracy of deep learning models for the diagnosis of maxillary fungal ball rhinosinusitis (MFB) and to compare the accuracy, sensitivity, specificity, precision, and F1-score with a rhinologist. METHODS: Data from 1539 adult chronic rhinosinusitis (CRS) patients who underwent paranasal sinus computed tomography (CT) were collected. The overall dataset consisted of 254 MFB cases and 1285 non-MFB cases. The CT images were constructed and labeled to form the deep learning models. Seventy percent of the images were used for training the deep-learning models, and 30% were used for testing. Whole image analysis and instance segmentation analysis were performed using three different architectures: MobileNetv3, ResNet50, and ResNet101 for whole image analysis, and YOLOv5X-SEG, YOLOv8X-SEG, and YOLOv9-C-SEG for instance segmentation analysis. The ROC curve was assessed. Accuracy, sensitivity (recall), specificity, precision, and F1-score were compared between the models and a rhinologist. Kappa agreement was evaluated. RESULTS: Whole image analysis showed lower precision, recall, and F1-score compared to instance segmentation. The models exhibited an area under the ROC curve of 0.86 for whole image analysis and 0.88 for instance segmentation. In the testing dataset for whole images, the MobileNet V3 model showed 81.00% accuracy, 47.40% sensitivity, 87.90% specificity, 66.80% precision, and a 67.20% F1 score. Instance segmentation yielded the best evaluation with YOLOv8X-SEG showing 94.10% accuracy, 85.90% sensitivity, 95.80% specificity, 88.90% precision, and an 89.80% F1-score. The rhinologist achieved 93.5% accuracy, 84.6% sensitivity, 95.3% specificity, 78.6% precision, and an 81.5% F1-score. CONCLUSION: Utilizing paranasal sinus CT imaging with enhanced localization and constructive instance segmentation in deep learning models can be the practical promising deep learning system in assisting physicians for diagnosing maxillary fungal ball.

Development and Evaluation of a Web-Based Platform for Personalized Educational and Professional Assistance for Dementia Caregivers: Proposal for a Mixed Methods Study.

BACKGROUND: Alzheimer disease (AD) and AD-related dementia are prevalent concerns for aging populations. With a growing older adult population living in the United States, the number of people living with dementia is expected to grow, posing significant challenges for informal caregivers. The mental and physical burdens associated with caregiving highlight the importance of developing novel and effective resources to support caregivers. However, technology solutions designed to address their needs often face low adoption rates due to usability issues and a lack of contextual relevance. This study focuses on developing a web-based platform providing financial and legal planning information and education for dementia caregivers and evaluating the platform's usability and adoptability. OBJECTIVE: The goal of this project is to create a web-based platform that connects caregivers with personalized and easily accessible resources. This project involves industrial, academic, and community partners and focuses on two primary aims: (1) developing a digital platform using a Dementia Care Personalization Algorithm and assessing feasibility in a pilot group of caregivers, and (2) evaluating the acceptability and usability of the digital platform across different racial or ethnic populations. This work will aid in the development of technology-based interventions to reduce caregiver burden. METHODS: The phase I study follows an iterative Design Thinking approach, involving at least 25 dementia caregivers as a user feedback panel to assess the platform's functionality, aesthetics, information, and overall quality using the adapted Mobile Application Rating Scale. Phase II is a usability study with 300 dementia caregivers in Texas (100 African American, 100 Hispanic or Latinx, and 100 non-Hispanic White). Participants will use the digital platform for about 4 weeks and evaluate its usefulness and ease of use through the Technology Acceptance Survey. RESULTS: The study received funding from the National Institute on Aging on September 3, 2021. Ethical approval for phase I was obtained from the Texas A&M University Institutional Review Board on December 8, 2021, with data collection starting on January 1, 2022, and concluding on May 31, 2022. Phase I results were published on September 5, 2023, and April 17, 2024, respectively. On June 21, 2023, ethical approval for human subjects for phase II was granted, and participant recruitment began on July 1, 2023. CONCLUSIONS: Upon completing these aims, we expect to deliver a widely accessible digital platform tailored to assist dementia caregivers with financial and legal challenges by connecting them to personalized, contextually relevant information and resources in Texas. If successful, we plan to work with caregiving organizations to scale and sustain the platform, addressing the needs of the growing population living with dementia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64127.

Two New Steroidal Saponins with Potential Anti-Inflammatory Effects from the Aerial Parts of Gnetum formosum Markgr.

Gnetum formosum Markgr., a member of the Gnetaceae family, is distributed in Vietnam. This plant remains a botanical enigma with an unexplored diversity of chemical constituents and pharmacological effects. In this study, two new steroidal saponins, namely gnetumosides A (1) and B (2), were isolated from the aerial parts of G. formosum. Their chemical structures were elucidated using spectroscopic techniques, including high-resolution electrospray ionization mass spectrometry (HR-ESI-MS) and NMR, along with chemical hydrolysis and comparison with the reported literature. The potential anti-inflammatory effects of the isolated compounds were evaluated by measuring lipopolysaccharide-stimulated nitric oxide (NO) production in murine macrophage cells. Notably, compound 1 exhibited the most potent inhibitory activity (IC50 = 14.10 ± 0.75 µM), comparable to dexamethasone. Additionally, the mechanisms underlying the observed anti-inflammatory effects were investigated through molecular docking and molecular dynamics simulations on inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) proteins. This study is the first to investigate the chemical constituents and pharmacological effects of G. formosum.

An investigation into patterns of Alcohol drinking in Scotland after the introduction of minimum unit pricing.

BACKGROUND: In 2018, Scotland became the second country to implement minimum unit pricing (MUP) for all types of alcoholic beverages. The aim of this study was to examine the effect of the policy. METHOD: Three national household-level surveys were used: Scottish Health Surveys (2008-2021), Health Surveys in England (2011-2019), and Northern Ireland Continuous Household Survey (2011-2015). First, a generalized ordered logistic model examined patterns of drinking solely in Scotland from 2008-2021 covering current drinking, drinking categories and the weekly consumption (in alcohol units). Secondly, difference-in-difference (DID) analysis was employed to examine changes in "social drinking" behaviours in Scotland after the announcement in 2012 (2011-2015, Northern Ireland and England as comparators) and after the adoption of the policy in 2018 (England as a comparator, with two timeframes 2016-2019 and 2013-2019). RESULTS: Overall, drinking in Scotland began to decline prior to 2012 and dropped further with the enactment of MUP in 2018. In response to MUP, the likelihood of abstention increased along with a slight decrease in the prevalence of heavy drinking. The overall amount of drinking fell by about 8% after 2012 and 12% after 2018 (as compared to 2008-2011 level), with a significant decline seen in moderate drinkers but not of those who drank at hazardous or harmful levels. The DID analyses confirmed the reduction in current drinking in Scotland starting since 2012 and continued post-MUP in 2018. CONCLUSION: This study points to the impact of MUP in Scotland with a potential role for 'policy signalling' by the Scottish Government's with a multiple-buy discount ban and MUP's announcement since 2011-2012. Indications of impact include a clear decline in alcohol consumption levels and a small but noteworthy change in prevalence of overall drinking and heavy drinking.

Precision-engineered metal and metal-oxide nanoparticles for biomedical imaging and healthcare applications.

The growing field of nanotechnology has witnessed numerous advancements over the past few years, particularly in the development of engineered nanoparticles. Compared with bulk materials, metal nanoparticles possess more favorable properties, such as increased chemical activity and toxicity, owing to their smaller size and larger surface area. Metal nanoparticles exhibit exceptional stability, specificity, sensitivity, and effectiveness, making them highly useful in the biomedical field. Metal nanoparticles are in high demand in biomedical nanotechnology, including Au, Ag, Pt, Cu, Zn, Co, Gd, Eu, and Er. These particles exhibit excellent physicochemical properties, including amenable functionalization, non-corrosiveness, and varying optical and electronic properties based on their size and shape. Metal nanoparticles can be modified with different targeting agents such as antibodies, liposomes, transferrin, folic acid, and carbohydrates. Thus, metal nanoparticles hold great promise for various biomedical applications such as photoacoustic imaging, magnetic resonance imaging, computed tomography (CT), photothermal, and photodynamic therapy (PDT). Despite their potential, safety considerations, and regulatory hurdles must be addressed for safe clinical applications. This review highlights advancements in metal nanoparticle surface engineering and explores their integration with emerging technologies such as bioimaging, cancer therapeutics and nanomedicine. By offering valuable insights, this comprehensive review offers a deep understanding of the potential of metal nanoparticles in biomedical research.

A pre-post evaluation of a digital intervention to improve psychosocial outcomes of caregivers of people living with cancer in Vietnam.

OBJECTIVES: To evaluate a co-designed intervention using digital resources "Vietnam Cancer Caring Coping" (V-CCC) on the health literacy, depression, and quality of life of caregivers supporting a cancer patient in oncology hospitals in Vietnam. METHODS: A pre-post quantitative evaluation with adult cancer caregivers across regional Oncology hospitals in Vietnam (Ho Chi Minh City, Da Nang, Can Tho, and Hue). Participants completed baseline and follow-up measures of health literacy (HLS-SF12) depression (PHQ-9) and Health-related Quality of Life (5Q-5D-5L). Participants accessed and reviewed V-CCC for a 2-week period. RESULTS: Two hundred and thirty-four caregivers completed pre and post-tests. Most participants were female (n = 143, 61%), married (n = 165, 70%), aged 18-44 (n = 155, 66%), lived rurally (n = 157, 67%). All health literacy scores of participants in post-intervention were significantly higher than that in pre-intervention across all domain's healthcare, disease prevention, and health promotion as well as the total score (p < 0.001). A significant reduction in the proportion of caregivers reporting PHQ-9 moderately severe/severe depression post-intervention was demonstrated (10.2 vs. 6.1%, respectively (p ≤ 0.001). No significant differences were observed pre and post-intervention across four 5Q-5D-5L health dimensions: mobility, self-care, usual activities, and pain/discomfort. Regarding anxiety/depression as measured by 5Q-5D-5L the proportion of participants who reported having moderate, severe, and extreme problems in pre- and post-intervention was statistically significant (32 vs. 24%), respectively (p = 0.0028). CONCLUSION: Co-designed digital resources can reduce health literacy inequities and improve psychological outcomes for cancer caregivers.

Impact of ligand fields on Kubas interaction of open copper sites in MOFs with hydrogen molecules: an electronic structural insight.

We investigate hydrogen sorption on open copper sites in various ligand coordinations of metal-organic frameworks (MOFs), including the triangular T(CuL3) in MFU-4l, the linear L(CuL2) in NU2100, and the paddlewheel P(CuL4)2 in HKUST-1 from an electronic structure perspective using DFT calculations. The ligand-field-induced splitting of d states and spd hybridizations in copper are thoroughly examined. The hybridization between Cu s, p, and d orbitals occurs in various forms to optimize the Coulomb repulsion of different ligand fields. Despite the Cu+ oxidation state, which is typically conducive to strong Kubas interactions with hydrogen molecules, the vacant spd z 2 hybrid orbitals of the open copper site in the L(CuL2) coordination are unsuitable for facilitating electron forward donation, thereby preventing effective hydrogen adsorption. In contrast, the vacant spd z 2 hybrid orbitals in the T(CuL3) and P(CuL4)2 coordinations can engage in electron forward donations, forming bonding states between the Cu spd z 2 and H2 σ bonding orbitals. The forward donation in the T(CuL3) configuration is significantly stronger than in the P(CuL4)2 configuration due to both the lower energy of the vacant orbitals and the larger contributions of p and d z 2 characters to the hybrid orbital. Additionally, the occupied Cu pd xz/yz and pd x 2-y 2 hybrid orbitals in the T(CuL3) configuration promote electron back donation to the H2 σ* antibonding orbital, leading to the formation of π bonding states. In the P(CuL4)2 coordination, the repulsion from the electron density distributed over the surrounding ligands prevents the H2 molecule from approaching the copper center closely enough for the back donation to occur. The complete Kubas interaction, involving both forward and back electron donations, results in a large dihydrogen-copper binding energy of 37.6 kJ mol-1 in the T(CuL3) coordination. In contrast, the binding energy of 10.6 kJ mol-1 in the P(CuL4)2 coordination is primarily driven by electrostatic interactions with a minor contribution of the Kubas-like forward donation interaction. This analysis highlights the pivotal role of coordination environments in determining the hydrogen sorption properties of MOFs.

Temporal Trends in Tobacco Smoking Prevalence During the Period 2010-2020 in Vietnam: A Repeated Cross-Sectional Study.

Objectives: This study used repeated cross-sectional data from three national surveys in Vietnam to determine tobacco smoking prevalence from 2010 to 2020 and disparities among demographic and socioeconomic groups. Methods: Tobacco smoking temporal trends were estimated for individuals aged 15 and over and stratified by demographic and socioeconomic status (SES). Prevalence estimates used survey weights and 95% confidence intervals. Logistic regression models adjusted for survey sample characteristics across time were used to examine trends. Results: Tobacco smoking prevalence dropped from 23.8% in 2010 to 22.5% in 2015 and 20.8% in 2020. The adjusted OR for 2015 compared to 2010 was 0.87, and for 2020 compared to 2010 was 0.69. Smoking decreased less for employed individuals than unemployed individuals in 2020 compared to 2010. Smoking was higher in the lower SES group in all 3 years. Higher-SES households have seen a decade-long drop in tobacco use. Conclusion: This prevalence remained constant in lower SES households. This highlights the need for targeted interventions to address the specific challenges faced by lower-SES smokers and emphasizes the importance of further research to inform effective policies.

The cost of delivering COVID-19 vaccines in Vietnam.

BACKGROUND: The COVID-19 pandemic affected hundreds of millions of people and lives, and vaccination was the safest and most effective strategy to prevent and mitigate the burden of this disease. The implementation of COVID-19 vaccination in Vietnam in 2021 was unprecedentedly challenging in scale and complexity, yet economic evidence on the cost of delivery vaccines thought the program was lacking. METHODS: This retrospective costing study utilized a bottom-up, ingredient-based approach to estimate the cost of delivering COVID-19 vaccines in Vietnam in 2021, from a payer perspective. The study included 38 study sites across all administrative and implementation level, including three geographic areas and two delivery strategies, in two provinces, Hanoi and Dak Lak. The study findings were complemented with qualitative interviews with health staff and stakeholders. RESULTS: The economic cost to deliver one COVID-19 vaccine dose was $1.73, mostly comprised of opportunity costs ($1.14 per dose) which were driven by labor costs ($1.12 per dose). The delivery cost in urban areas was the highest ($2.02), followed by peri-urban areas ($1.45) and remote areas ($1.37). Delivery costs were higher at temporary sites ($1.78) when compared to facility-based delivery ($1.63). Comparing low-volume and high-volume periods showed that the delivery cost decreased significantly as volume increased, from $5.24 per dose to $1.65 per dose. CONCLUSIONS: The study estimates the cost of delivering COVID-19 vaccines in Vietnam in 2021. Enabling factors and challenges during the implementation of the program were explored. Study limitations may lead to underestimation of results and reduce generalizability.

Prevalence and Phage-Based Biocontrol of Methicillin-Resistant Staphylococcus aureus Isolated from Raw Milk of Cows with Subclinical Mastitis in Vietnam.

S. aureus, particularly methicillin-resistant S. aureus, has been recognized as a main cause of bovine mastitis and food poisoning. This study investigated the prevalence, antibiotic resistance, and phage-based biocontrol of S. aureus and methicillin-resistant S. aureus isolated from raw milk of cows with subclinical mastitis. The results showed that the prevalence of S. aureus and methicillin-resistant S. aureus was 12% (48/400) and 1.5% (6/400), respectively. The S. aureus isolates were highly resistant to penicillin (72.92%), erythromycin (43.75%), and tetracycline (39.58%). Out of 48 S. aureus isolates, 6 were identified as methicillin-resistant strains. Among them, one isolate was found to harbor the sea gene. A total of 5 phages were recovered from 50 pork and 50 chicken meat samples, 1 from pork and 4 from chicken meat samples. Phage PSA2 capable of lysing all 6 methicillin-resistant isolates was selected for characterization. The use of phage PSA2 completely inactivated methicillin-resistant S. aureus SA33 in raw milk at both 24 °C and 4 °C, indicating its potential as a promising antibacterial agent in controlling methicillin-resistant S. aureus in raw milk and treating bovine mastitis.

Fcg-Former: Identification of Functional Groups in FTIR Spectra Using Enhanced Transformer-Based Model.

Deep learning (DL) is becoming more popular as a useful tool in various scientific domains, especially in chemistry applications. In the infrared spectroscopy field, where identifying functional groups in unknown compounds poses a significant challenge, there is a growing need for innovative approaches to streamline and enhance analysis processes. This study introduces a transformative approach leveraging a DL methodology based on transformer attention models. With a data set containing approximately 8677 spectra, our model utilizes self-attention mechanisms to capture complex spectral features and precisely predict 17 functional groups, outperforming conventional architectures in both functional group prediction accuracy and compound-level precision. The success of our approach underscores the potential of transformer-based methodologies in enhancing spectral analysis techniques.

CapNet: An Automatic Attention-Based with Mixer Model for Cardiovascular Magnetic Resonance Image Segmentation.

Deep neural networks have shown excellent performance in medical image segmentation, especially for cardiac images. Transformer-based models, though having advantages over convolutional neural networks due to the ability of long-range dependence learning, still have shortcomings such as having a large number of parameters and and high computational cost. Additionally, for better results, they are often pretrained on a larger data, thus requiring large memory size and increasing resource expenses. In this study, we propose a new lightweight but efficient model, namely CapNet, based on convolutions and mixing modules for cardiac segmentation from magnetic resonance images (MRI) that can be trained from scratch with a small amount of parameters. To handle varying sizes and shapes which often occur in cardiac systolic and diastolic phases, we propose attention modules for pooling, spatial, and channel information. We also propose a novel loss called the Tversky Shape Power Distance function based on the shape dissimilarity between labels and predictions that shows promising performances compared to other losses. Experiments on three public datasets including ACDC benchmark, Sunnybrook data, and MS-CMR challenge are conducted and compared with other state of the arts (SOTA). For binary segmentation, the proposed CapNet obtained the Dice similarity coefficient (DSC) of 94% and 95.93% for respectively the Endocardium and Epicardium regions with Sunnybrook dataset, 94.49% for Endocardium, and 96.82% for Epicardium with the ACDC data. Regarding the multiclass case, the average DSC by CapNet is 93.05% for the ACDC data; and the DSC scores for the MS-CMR are 94.59%, 92.22%, and 93.99% for respectively the bSSFP, T2-SPAIR, and LGE sequences of the MS-CMR. Moreover, the statistical significance analysis tests with p-value < 0.05 compared with transformer-based methods and some CNN-based approaches demonstrated that the CapNet, though having fewer training parameters, is statistically significant. The promising evaluation metrics show comparative results in both Dice and IoU indices compared to SOTA CNN-based and Transformer-based architectures.

Prevalence, Molecular Characterization, and Antimicrobial Resistance Profiles of Shiga Toxin-Producing Escherichia coli Isolated from Raw Beef, Pork, and Chicken Meat in Vietnam.

Shiga toxin-producing Escherichia coli (STEC) is one of the most important foodborne pathogens, and the rise of antibiotic resistance to it is a significant threat to global public health. The purpose of this study is to investigate the prevalence, molecular characterization, and antibiotic resistance of STEC isolated from raw meat in Vietnam. The findings in this study showed that the prevalence of STEC in raw beef, pork, and chicken meat was 9.72% (7/72), 5.56% (4/72), and 1.39% (1/72), respectively. The STEC isolates were highly resistant to ampicillin (91.67%) and tetracycline (91.67%), followed by trimethoprim/sulfamethoxazole (83.33%), streptomycin (75%), and florfenicol (66.67%). The incidence of STEC virulence-associated genes, including stx1, stx2, eae, and ehxA, was 8.33% (1/12), 91.67% (11/12), 33.33% (4/12), and 58.33% (7/12), respectively. STEC serogroups O157, O26, and O111 were detected in 3 out of 12 STEC isolates. Two isolates were found to be ESBL producers carrying the blaCTX-M-55 gene, and three isolates were colistin-resistant strains harboring the mcr-1 gene. Notably, a STEC O111 isolate from chicken meat harbored both the blaCTX-M-55 and mcr-1 genes.

First Report on the Occurrence and Antibiotic Resistance Profile of Colistin-Resistant Escherichia coli in Raw Beef and Cow Feces in Vietnam.

Colistin-resistant Escherichia coli (COE) has been recently recognized as a serious threat to animal and human health. This study aimed to determine the prevalence and antibiotic resistance profile of COE isolated from raw beef and cow feces in Vietnam. Our results showed that 16% (16/100) and 32% (32/100) of raw beef and cow feces samples were positive for COE, respectively. A total of 48 COE strains were isolated, with 16 originating from raw beef and 32 from cow feces samples. The antibiotic susceptibility test revealed that the COE isolates were highly resistant to ampicillin, tetracycline, florfenicol, trimethoprim/sulfamethoxazole, streptomycin, and nalidixic acid, with resistance rates ranging from 66.67% to 87.5%. In addition, 87.5% of the isolates were identified to be multidrug-resistant strains. Further molecular characterization indicated that all COE isolates carried the mcr-1 gene, with 16 of them also harboring blaCTX-M-55 genes. Taken together, the findings in this study demonstrate that raw beef and cow feces are important sources of COE, which can be potentially transmitted to humans through the food chain.

Cost analysis of establishing and operating the first human milk bank at Da Nang Hospital for Women and Children in Vietnam: an activity-based costing ingredients study.

BACKGROUND: Breastfeeding is the biological norm for feeding infants and young children. When mothers' breastmilk is unavailable, donor human milk (DHM) from a human milk bank (HMB) becomes the next option for small vulnerable newborns. A comprehensive cost analysis is essential for understanding the investments needed to establish, operate, and scale up HMBs. This study aims to estimate and analyze such costs at the first facility established in Vietnam. METHODS: An activity-based costing ingredients (ABC-I) approach was employed, with the cost perspective from service provision agencies (specifically, the project conducted at Da Nang Hospital for Women and Children and Development Partners). Estimated financial costs, based on actual expenditures, were measured in 2023 local currency and then converted to 2023 US dollars (USD). We examined three scenarios: 1) direct start-up costs + indirect start-up costs + implementation costs, 2) direct start-up costs + implementation costs, and 3) capital costs + implementation costs over the 6.5 years of operation. RESULTS: The total start-up cost was USD 616,263, with total expenditure on direct activities at USD 228,131 and indirect activities at USD 388,132. Investment in equipment accounted for the largest proportion (USD 84,213). The monthly costs of Da Nang HMB were USD 25,217, 14,565, and 9,326, corresponding to scenarios 1, 2, and 3, respectively. Over HMB's 6.5 years of operation, on average, the unit costs were USD 166, USD 96, and USD 62 for DHM received and USD 201, USD 116, and USD 74 for pasteurized DHM meeting specified criteria in the corresponding scenarios. Unit costs were highest in the initial six months, decreased, and reached their lowest levels after a year. Then, the unit costs experienced an increase in late 2020 and early 2021. CONCLUSION: Although the unit cost of DHM in Da Nang HMB is comparable to that in certain neighboring countries, intentional measures to reduce disposal rates, improve HMB efficiency, motivate more community-based donors, and establish an HMB service network should be implemented to lower costs.

Water-Based Recycling Process of FTO/SnO2 Substrate for Sustainable Perovskite Solar Cell Technology.

Fluorine-doped tin oxide (FTO) substrate is an important and expensive component in perovskite solar cells (PSCs), which accounts for up to 40% of a typical PSC raw material cost. In this study, we investigated the recyclability of SnO2/FTO in PSCs by washing the spent PSCs using different solvent such as dimethylformamide (DMF), dimethylsulfoxide (DMSO), acetone, water, and acetone/water mixture. Characterisation of properties of the SnO2/FTO substrates recovered from the PSC show the surface wettability of SnO2/FTO is largely unchanged with water washing while a higher hydrophobicity is obtained with organic solvent washing. Comparison of electronic properties of the SnO2/FTO substrate shows a downward shift of the conduction band by 180 meV with water washing, creating favourable energy alignment with adjacent perovskite for efficient interfacial charge injection. Consequently, PSCs using the water-based recycled SnO2/FTO substrates produced a high power conversion efficiency (PCE) of 19.33% which is comparable to the device using fresh SnO2/FTO substrate (PCE = 19.85%). Furthermore, we demonstrated that the water washing process could retain property of SnO2/FTO substrate for decent PSC performance up to four recycling cycles. This study opens new avenues towards recycling of valuable FTO substrates in PSCs for increased sustainability and cost-effectiveness.