Delivery Window Research Articles

Bi-modal confirmation of liposome delivery to the brain after focused ultrasound-induced blood-brain barrier opening

Focused ultrasound-mediated opening of the blood-brain barrier offers a great opportunity to deliver therapeutics into hard-to-treat brain tumors such as glioblastoma multiforme or diffuse midline glioma. However, the potential of the technique to offer a time window for efficient nanomedicine delivery has not been thoroughly studied. Non-invasive and targeted delivery of large drug-loaded nanocarriers, such as liposomes, could offer a safe and scalable method of personalized therapy for the treatment of brain pathologies. Additionally, it is essential to monitor the safety and efficacy of such treatments, tracking drug delivery in real-time through quantitative medical imaging.In this study, liposomes were modified to have an MRI contrast agent (i.e., Gd) in both lipid membrane and core, while an infrared dye (i.e., CW800) was coupled to lipids introduced in the lipid bilayer for bimodal detection and treatment verification. Targeted delivery of 110nm-in-diameter liposomes to the brain was quantified using 9.4-T MRI and near infrared fluorescence imaging. The spatiotemporal distribution of liposomes in vivo was assessed up to 4 hours post treatment using T1 weighted MRI. In vivo MRI signal co-localized with NIRF signal from excised brains ex vivo. Passive acoustic detection during treatments revealed a correlation between acoustic signal and MRI contrast, providing a scalable metric for assessing clinical treatment efficacy in real-time. In conclusion, therapeutic ultrasound exposure can enhance delivery of large trackable nanoparticles into the brain, while enabling real-time treatment monitoring and verification.

Uplift modeling and its implications for appointment date prediction in attended home delivery

Successful attended home delivery (AHD) is the most important aspect of e-commerce order fulfillment. Prior literature focuses on incentive scheme development for customers' choices of delivery windows and predictive analytics for delivery results, but it is not clear whether the effect of AHD on the appointment date set by customers increases the success rate of AHD. Therefore, we developed an uplift modeling method, PSM-NDML, as a relevant prescriptive analytic tool for AHD on an appointment date, which aims to estimate the causal effect of the by-appointment delivery on the delivery result. PSM-NDML integrates propensity score matching and double machine learning, effectively addressing sample selection bias, low predictive performance, and poor interpretability. Applied to a real-world product delivery dataset of a Chinese logistics company, PSM-NDML achieves superior performance relative to ten other state-of-the-art uplift models in terms of cumulative gain and the Qini coefficient. The predicted responses gained from PSM-NDML are also visually interpreted at the global and local levels, which reveals various managerial insights. In practice, the findings expand managers' understanding of the heterogeneous effects of AHD on appointment dates and provide decision support for logistics companies in the development of home delivery plans.

Community Recommendations for Adapting an Evidence-Based Mental Health Intervention for Racially/Ethnically Diverse Schools: A Qualitative Study

AbstractThe goal of this qualitative study was to understand the perspectives of school community members (adolescents, parents, school administrators, teachers, mental health providers) regarding the adaptation of an evidence-based transdiagnostic mental health treatment, known as the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders in Adolescents, for delivery in racially/ethnically diverse schools. Thirty-three school community members (n = 9 adolescents, n = 4 parents, n = 5 school administrators, n = 10 teachers, n = 5 mental health providers) participated in a series of focus groups or individual interviews. We used a rapid qualitative analysis to summarize their recommendations for adapting our intervention across seven themes: (1) consider social determinants of health, (2) include content related to social media and digital literacy, (3) provide teachers and staff with training on identifying and referring to mental health services and basic psychoeducation, (4) build trust and reduce stigma, (5) use qualified mental health providers to conduct culturally relevant sessions in person during school hours, (6) consider flexible format offerings and extended intervention delivery window, and (7) anticipate low parental engagement. These data were critical for informing systematic content and procedural modifications to our adapted intervention, such as scheduling sessions for school lunch hours and identifying coaches (e.g., teachers, school administrators) to support students with check-ins regarding session attendance and skill practice. These adaptations may be applied more broadly to the implementation of evidence-based mental health interventions in diverse school settings.

The Role of Last-Mile Delivery Quality and Satisfaction in Online Retail Experience: An Empirical Analysis

The rise of the e-commerce industry has markedly changed the global economy, providing customers with unparalleled access to goods and services. This study empirically examines online shoppers’ perceptions and preferences, focusing on their experiences with last-mile delivery (LMD) services and its impact on their shopping behaviour. This research employs machine learning classification and regression models for a large-scale analysis of customers’ responses, collected using an online survey in the main cities in Saudi Arabia, which is experiencing rapid e-commerce growth amidst a broader digital transformation. The findings highlight a strong consumer preference for timely LMD services, typically within a day of purchase, while noting dissatisfaction with exceedingly early delivery windows. The research emphasises the need to address customer dissatisfaction with delivery services to retain clientele, as many may switch retailers without informing the retailers. Additionally, a considerable trend towards preferring digital over cash-on-delivery payment methods was observed among online shoppers. Overall, this study provides valuable insights into the significant influence of LMD services on customer satisfaction and behaviour in the e-commerce sector. The use of robust machine learning models has revealed critical factors that can guide retailers and LMD providers in enhancing service delivery and customer experience, contributing to the broader discourse on e-commerce logistics efficiency and customer satisfaction.

Online Auction System with AI

An online auction is type of an auction that takes place over the Internet. It is a popular method for buying and selling products and services. Such systems give the best price to the seller as well as the buyers. The application proposed in this paper was developed with the objective of making the system reliable, easier and fast. Through this application, anyone can sell anything on the website by sitting at home. It’s as easy as browsing the app website. Even non-technical persons can easily interact with the process of buying and selling on the application. An online auction system permits a customer to submit online orders for items and/or services from a store that serves both walk-in customers and online customers. The online auction system presents an online display of an order cut off time and an associated delivery window for items selected by the customer of any 2nd hand products. The online auction system does not settle with a credit supplier of the customer until the item selected by the customer is picked from inventory. Therefore, customers can go online to modify their order. In addition, the service window is presented to the customer as a function of the order and service type selected by the customer, and also the choice is made according to the person's preference, where the order selection is correct. When ordering goods, a virtual shopping cart is also provided by many shopping systems for holding items selected for purchase. Until a customer completes their shopping trip, successive items selected for purchase are placed into the virtual shopping cart. Virtual shopping carts may be examined at any time, and their contents can be deleted and edited at the customer’s end.

Mucoadhesive Carrier-Mediated Oral Co-delivery of Bcl2 Inhibitors Improves Gastric Cancer Treatment.

Gastric cancer treatment is challenging due to the lack of early-stage diagnostic technology and targeted delivery systems. Currently, the available treatments for gastric cancer are surgery, chemotherapy, immunotherapy, and radiation. These strategies are either invasive or require systemic delivery, exerting toxicities within healthy tissues. By creation of a targeted delivery system to the stomach, gastric cancer can be treated in the early stages. Such an approach reduces the negative effects on the rest of the body by minimizing systemic absorbance and random localization. With this in mind, we developed a mucoadhesive vehicle composed of β-Glucan And Docosahexaenoic Acid (GADA) for controlled drug/gene delivery. In the current study, we investigated the therapeutic effect of codelivery Bcl2 inhibitors navitoclax (NAVI) and siRNA (Bcl2) via oral using GADA. The therapeutic efficacy of the GADA-mediated oral NAVI/siRNA was investigated in a gastric cancer mouse model. Higher Bcl2 inhibition efficacy was observed in Western blotting and TUNEL assay in mice treated with GADA/NAVI/siRNA compared to free NAVI, siRNA, and NAVI/siRNA. Histology (H&E) and immunohistochemistry (Ki67, TUNEL, and BCl2) analyses confirmed a significant reduction of the tumor region. Interaction between GADA and mucus resulted in retention for over 6 h and thereby sustained local payload release. The developed oral carrier GADA is an emerging vehicle that has promising potential in oral delivery of both small and large molecules, and their mucoadhesive property results in improved therapeutic efficacy with minimal side effects compared to conventional treatment. This study opens a new window for the effective delivery of oral medicine for the treatment of gastric cancer and other gastrointestinal diseases.

Tuning the Emulsion Properties Influences the Size of Poly(Caprolactone) Particles for Drug Delivery Applications.

Advances in drug delivery have been accelerated with the addition of polymeric drug carriers. Direct delivery to a target site is a promising step in developing effective drug and gene therapies to treat disease. The efficacy of these drug carriers heavily relies on cell uptake without compromising critical cellular processes that promote cell viability. Drug release from biodegradable polymers is mediated largely by polymer degradation, and therefore the rate of polymer degradation dictates the feasibility of drug delivery applications. Traditionally, poly(caprolactone) (PCL) has only been used in long-term biomedical applications because the degradation time is much slower than other polymers. However, the biocompatibility of this polymer and the potential for longer delivery windows renders it a promising polymer candidate for drug delivery. In this work, we outline sixteen emulsion solvent evaporation preparation methods for PCL nanoparticles and microparticles to develop particles between 300nm and 1.7μm and with zeta potentials of -1.8mV. We further investigated particles in a size range suitable for systemic tumor delivery and inhaled aerosol delivery to determine cell biocompatibility with the polymer in lung adenocarcinoma, endometrial adenocarcinoma, and human embryonic kidney cells. We determined these particles aren't detrimental to cell viability below particle monolayer coverage atop cells and therefore these formulations hold promise for the next stage of development as sustained-release drug delivery carriers.

A large-scale last-mile consolidation model for e-commerce home delivery

E-commerce's rapid growth, combined with customer demand for fast shipping, has significantly escalated last-mile transportation, particularly home deliveries. This surge calls for novel strategies to optimize vehicle utilization while maintaining timely delivery. In response, many online retailers are incentivizing customers to embrace delayed home deliveries by offering economic incentives. Nonetheless, current transportation systems fall short in accommodating orders with extended delivery windows, primarily adhering to the First-In-First-Out rule and distance minimization via the Vehicle Routing Problem (VRP). In this paper, we introduce a new consolidation-based delivery methodology that addresses these challenges. Our approach accounts for orders with daily-based time windows and also anticipates future demand realizations (i.e., expected incoming orders). We characterize this consolidation problem using a Mixed Integer Linear Programming model and propose a custom metaheuristic approach that can tackle the problem on a large-scale setting, introducing a significant novelty approach in last-mile delivery research. We applied our methodology to one of Mexico's largest retailers and compared its performance against the company's existing transportation systems. Our approach substantially improves vehicle utilization and yields considerable reductions in distance traveled, time, and overall transportation costs, achieving cost savings of up to 52%. These savings represent tangible benefits, enabling potential revenue enhancements for businesses and cost-effective, timely deliveries for consumers. Additionally, the increased vehicle utilization implies fewer vehicles are needed for the same volume of deliveries, thereby enhancing operational efficiency. This innovative approach, therefore, presents a practical and highly effective solution for managing large-scale last-mile delivery scenarios.

A New Hybrid Algorithm for Vehicle Routing Optimization

To solve the vehicle routing problem with simultaneous pickup–delivery and time windows (VRPSDPTW), a sine cosine and firefly perturbed sparrow search algorithm (SFSSA) is presented. Based on the standard sparrow search algorithm, the initial population uses tent chaotic mapping to change the population diversity; then, the discoverer location is updated using the sine cosine fluctuation range of the random weight factor, and finally the global population location is updated using the firefly perturbation strategy. In this study, SFSSA was compared with a genetic algorithm (GA), parallel simulated annealing algorithm (p-SA), discrete cuckoo search algorithm (DCS), and novel mimetic algorithm with efficient local search and extended neighborhood (MATE) adopting improved Solomon’s benchmark test cases. The computational results showed that the proposed SFSSA was able to achieve the current optimal solutions for 100% of the nine small-to-medium instances. For large-scale instances, SFSSA obtained the current optimal solutions for 25 out of 56 instances. The experimental findings demonstrated that SFSSA was an effective method for solving the VRPSPDTW problem.

A Curcumin‐Based MOF Embedded Ag NPs and Modified with Polydopamine for Dual‐Drug Delivery and Dual Biological Window Responsive Synergetic Cancer Therapy

AbstractA dual‐drug delivery, pH‐responsive composite nanoplatform (MAPD NPs) that can respond to two biological windows is developed to improve the efficacy of synergetic chemotherapic/photothermal/chemodynamic therapy (CDT) against tumors. This nanoplatform is surface‐modified polydopamine (PDA) with excellent biocompatibility as the shell and Ag NPs as the catalyst for CDT. The curcumin (Cur) acts as an organic ligand to be encapsulated in metal−biomolecule frameworks (Bio‐MOFs) by self‐assembly, and Bio‐MOF acts as a delivery carrier to deliver of DOX•HCl and then releases the Cur when it degrades in vivo. Moreover, Bio‐MOF can be taken up by cells faster and accelerate cell death compared to free Cur. PDA modification enables MAP (PDA@MOF‐Ag) to have photothermal properties under 808 and 1064 nm light irradiation, which not only improves the biocompatibility of MAP but also makes it produce high heat and abundant ·OH. The photothermal performance of MAP is stable after irradiation at 808 or 1064 nm, and the photothermal conversion efficiency reaches 63.57% and 26.25%. The survival rate of HeLa cells co‐incubation with MAPD NPs after irradiation at 808 and 1064 nm decreases to 19.52 ± 0.69% and 30.48 ± 0.49%, respectively, providing a feasible scheme for the realization of deep tumor killing.

Assessment of gestational age at antenatal care visits among Kenyan women to inform delivery of a maternal respiratory syncytial virus (RSV) vaccine in low- and middle-income countries.

Background: Maternal respiratory syncytial virus (RSV) vaccines that are likely to be implementable in low- and middle-income countries (LMICs) are in final stages of clinical trials. Data on the number of women presenting for antenatal care (ANC) per day and proportion attending within the proposed gestational window for vaccine delivery, is a prerequisite to guide development of vaccine vial size and inform vaccine uptake in this setting. Methods: We undertook administrative review and abstraction of ANC attendance records from 2019 registers of 24 selected health facilities, stratified by the level of care, from Kilifi, Siaya and Nairobi counties in Kenya. Additional data were obtained from Mother and Child Health (MCH) booklets of women in each of the Health and Demographic Surveillance System (HDSS) areas of Kilifi, Nairobi and Siaya. Data analysis involved descriptive summaries of the number (mean, median) and proportion of women attending ANC within the gestational window period of 28-32 weeks and 24-36 weeks. Results: A total of 62,153 ANC records were abstracted, 33,872 from Kilifi, 19,438 from Siaya and 8,943 from Nairobi Counties. The median (Interquartile range, IQR) number of women attending ANC per day at a gestational age window of 28-32 and 24-36 weeks, respectively, were: 4 (2-6) and 7 (4-12) in dispensaries, 5 (2-9) and 10 (4-19) in health centres and 6 (4-11) and 16 (10-26) in county referral hospitals. In the HDSS areas of Kilifi, Siaya and Nairobi, pregnant women attending at least one ANC visit, within a window of 28-32 weeks, were: 77% (360/470), 75% (590/791) and 67% (547/821), respectively. Conclusions: About 70% of pregnant women across three distinct geographical regions in Kenya, attend ANC within 28-32 weeks of gestation. A multidose vial size with about five doses per vial, approximates daily ANC attendance and would not incur possible wastage in similar settings.

Efficacy and selectivity of tumor-treating field therapy for triple-negative breast cancer cells via in-house delivery device

PurposeTriple-negative breast cancer continues to be one of the leading causes of death in women, making up 7% of all cancer deaths. Tumor-treating electric fields are low-energy, low-frequency oscillating electric fields that induce an anti-proliferative effect on mitotic cells in glioblastoma multiforme, non-small cell lung cancer, and ovarian cancer. Little is known about effects of tumor-treating fields on triple-negative breast cancer and known research for tumor-treating fields only utilizes low (< 3 V/cm) electric field intensities.MethodsWe have developed an in-house field delivery device capable of high levels of customization to explore a much wider variety of electric field and treatment parameters. Furthermore, we investigated the selectivity of tumor-treating field treatment between triple-negative breast cancer and human breast epithelial cells.ResultsTumor-treating fields show greatest efficacy against triple-negative breast cancer cell lines between 1 and 3 V/cm electric field intensities while having little effect on epithelial cells.ConclusionThese results provide a clear therapeutic window for tumor-treating field delivery to triple-negative breast cancer.

An ant colony optimization based on local search for the vehicle routing problem with simultaneous pickup–delivery and time window

The Vehicle Routing Problem with Simultaneous Pickup–Delivery and Time Window (VRPSPDTW) is an important logistics distribution problem. Due to the complexity of this problem, there are few researches on it and lack of relevant solutions. To solve this problem, this paper proposes to use the ant colony optimization (ACO) for the first time, which a swarm intelligence optimization algorithm. An ant colony optimization algorithm with destory and repair strategies (ACO–DR) is proposed on the basis of ACO. Firstly, ACO–DR designs a random transition rule with direction to improve the probability of the algorithm to search the target and to enhance the global search ability of the algorithm. Secondly, because the positive feedback property of ACO, it is easy for the algorithm to fall into the local optimum. Therefore, two local operators, the destory operator and the repair operator, are added to avoid this phenomenon. Finally, to verify the performance of the proposed ACO-DR algorithm, it is tested on Solomon benchmark and Gehring–Homberge benchmark and compared with the state-of-the-art algorithms. The experimental results show that the ACO-DR algorithm is feasible and provides a new effective algorithm for solving VRPSPDTW problem. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

Contestability between Road and Rail Transport for Dry Cargo in Malawi: Cost and Service Reliability Issues. The Never Ending Race

For several years, a modal shift from road to rail transport has been promoted by policymakers and industry experts as it is believed that this move would provide a basis for achieving lower transportation costs. Malawi’s main goal is to reduce transportation costs and ensure that transport does not constrain its economy and the achievement of this strategic objective would be by facilitating a modal shift from road to rail transport. While all these efforts are being made, there is still not much to trigger the modal shift. This study therefore, focused on understanding the freight modal split between road and rail and went further to establish the reasons why shippers choose a particular mode of transport for their shipments. A descriptive research design within quantitative methodology was employed. Using a simple random sampling technique, 84 participants were recruited for this study. The finding of the study revealed that 87 percent of shippers use road transport because it provides a shorter shipment delivery window, reliable transport service, and availability. It is therefore recommended that the government should invest to revitalize rail transportation to make it more efficient.

Optimization of Vehicle Routing Problem Using Particle Swarm Optimization: A Case Study Watering Plants in Yogyakarta City

Dinas Lingkungan Hidup (DLH) Yogyakarta City always tries to monitor, control, and control activities regarding all aspects of the environment, one of which is watering plants. The right path must be selected so as not to exceed the time limit set. This study aims to determine the direction of watering plants in Sector 3 for Vehicle Route Problem (VRP) using the Particle Swarm Optimization (PSO) and compare the performance results of the PSO method with the Genetic Algorithm (GA) in previous studies. The VRP criteria are heterogeneous fleet, intermediated facility, multi-trip, split delivery, and times window (VRPHFIFMTSDTW). The results of the comparison between the two methods, namely, the GA method, are better than the PSO method in terms of computational time efficiency and fitness value. The total travel time for the GA method is 22 minutes, or 2.1% faster than the PSO method. In contrast, the total distance traveled by the PSO method is 345 meters shorter than the GA method. These two methods' results are also excellent compared to the current watering route. The difference in total mileage is about 20.4%, and total travel time is about 11.7% between the two methods.

Sustainable Operations of Last Mile Logistics Based on Machine Learning Processes

The last-mile logistics is regarded as one of the least efficient, most expensive, and polluting part of the entire supply chain and has a significant impact and consequences on sustainable delivery operations. The leading business model in e-commerce called Attended Home Delivery is the most expensive and demanding when a short delivery window is mutually agreed upon with the customer, decreasing possible optimizing flexibility. On the other hand, last-mile logistics is changing as decisions should be made in real time. This paper is focused on the proposed solution of sustainability opportunities in Attended Home Delivery, where we use a new approach to achieve more sustainable deliveries with machine learning forecasts based on real-time data, different dynamic route planning algorithms, tracking logistics events, fleet capacities and other relevant data. The developed model proposes to influence customers to choose a more sustainable delivery time window with important sustainability benefits based on machine learning to predict accurate time windows with real-time data influence. At the same time, better utilization of vehicles, less congestion, and fewer failures at home delivery are achieved. More sustainable routes are selected in the preplanning process due to predicted traffic or other circumstances. Increasing time slots from 2 to 4 h makes it possible to improve travel distance by about 5.5% and decrease cost by 11% if we assume that only 20% of customers agree to larger time slots.

Elongated Cargo Dwell Time in Nigeria Ports, the Root-Source and Economic Implications

The study investigated the root-source of elongated cargo dwell time in Nigerian ports and estimated the economic implications. It also compared the cargo dwell time among the ports in the West African sub-Saharan African regions. The study used exploratory research design combined with an ex-post factor research design in which secondary data was employed and analyzed using mathematical models to determine the root-source of elongated cargo dwell time in Nigerian ports, in comparison with those of other ports in the West and sub-Saharan African region. It was found that transactional dwell time constitutes the bulk of the time cargo stays in Nigerian ports after arrival. While transactional dwell time took about 73% of the total cargo dwell time in Nigerian ports, operational dwell time took about 20.5% and storage dwell time took the least, about 4.8% of the entire cargo dwell time of the time average shipper’s consignment spends in port. The Nigerian ports were also found to have the highest cargo dwell time in the West and Sub-Saharan African regions, being 475% times higher than the global average benchmark of 4 days and that of the port of Durban in South-African, 64% higher than that of Cotonou port in Benin, 53% higher than that of Tema port in Ghana, 156% higher than that of Lome port in Togo, and 109% higher than the of Mombasa port in Kenya. At an average storage rental charge rate of 7533.33 naira per TEU per day after the 3 to 4 days free cargo delivery window is closed, the estimated mean amount paid by shippers to terminal operators in Apapa port and Tin-can Island port as storage rental charges per day each year between 2014 and 2017 is 2,714,985,000 naira and 3423242500 naira respectively in each of the ports. These figures represent the daily economic implications of elongated cargo dwell time in Nigerian ports borne by shippers.

Successive cytotoxicity control by evolutionary surface decorated electronic push-pull green ZnCr-LDH nanostructures: Drug delivery enlargement for targeted breast cancer chemotherapy

The reason for the increasing bioavailability and biocompatibility of the porous nanomaterials in the presence of different (bio)molecules is still unknown. The role of difference functional groups and their interactions with the potential bioavailability and biocompatibility is of great importance. To investigate the potential contribution of the electronic effects (especially on the surface of the porous nanomaterials) on their biomedical behavior, a series of surface-decorated green ZnCr-layered double hydroxide (LDH) porous nanocarriers is developed as a non-viral vector. Different conjugations investigated these porous LDHs for optimizing and minimizing the cytotoxicity for targeted breast cancer therapy. Quick low-temperature synthesized ZnCr-LDH nanocarriers method with enlarged drug delivery windows decorated with leaf extracts and benzamide-like molecules revealed a push-pull electronic synergistic effect on cytotoxicity and enhanced cell viability, biocompatibility, aggregations, and interactions with the cell membranes. The pre-defined model drug, doxorubicin (DOX), unraveled chemotherapy performance in response to MCF-7 cell lines, with ≈ 60% drug payload contributed from functional groups of leaf extracts. Moreover, electron-poor and electron-rich benzamide-like molecules attached to the ZnCr-LDH surface enhanced the relative cell viability up to 29% and 32%, respectively. The in vivo experiments on breast cancer of treated mice (H&E) revealed unaggregated cellular arrays and antibacterial activity against E. coli (gram-negative) and S. aureus (gram-positive) bacteria. Benzamide-like ZnCr-LDH nanocarriers showed a suitable zone of inhibition beyond 10 mm, compared to the standard. Cytotoxicity control achieved herein seems promising for the future ahead of nanomedicine.

Timing of delivery for placenta accreta spectrum: the Pan-American Society for the Placenta Accreta Spectrum experience

The Society for Maternal-Fetal Medicine recommends cesarean delivery with potential hysterectomy scheduled in the late preterm period between 34 0/7 and 35 6/7 weeks of gestation for prenatally suspected placenta accreta spectrum. We aimed to investigate clinical compliance with the recommended delivery timing window for placenta accreta spectrum and its impact on maternal and neonatal outcomes. We performed a retrospective multicenter review of data from referral centers within the Pan-American Society for Placenta Accreta Spectrum. Patients with placenta accreta spectrum with both antenatal diagnosis and confirmed histopathologic findings were included. We investigated adherence to the Society for Maternal-Fetal Medicine-recommended gestational age window for delivery, and compliance was further stratified by scheduled and unscheduled delivery. We compared the outcomes for patients with scheduled delivery within vs immediately 2 weeks outside the recommended window. Among 744 patients with a prenatal diagnosis of placenta accreta spectrum and placental histopathologic confirmation, 488 (66%) had scheduled delivery. Among all prenatally diagnosed placenta accreta spectrum patients, 252 (39%) delivered within the recommended window of 34 0/7 and 35 6/7 weeks gestation. For the subgroup of patients who underwent scheduled delivery (n=426), 209 (49%) had delivery in this window, 120 (28%) delivered before 34 weeks, and 97 (23%) delivered at or later than 36 weeks. In the patients with scheduled delivery, 27% of placenta accreta spectrum patients with accreta delivered in the 2 weeks immediately after the recommended window (36 0/7-37 6/7 weeks), and 22% of placenta accreta spectrum pregnancies with increta/percreta delivered in the 2 weeks immediately before the recommended delivery (32 0/7-33 6/7 weeks). The maternal outcomes among those who delivered within the recommended range vs those delivering 2 weeks before and after the recommended range were similar, regardless of placenta accreta spectrum severity. Less than half of placenta accreta spectrum patients had scheduled delivery within the recommended gestational age of 34 0/7 to 35 6/7 weeks. The reasons for deviation from recommendations and the risks and benefits of individualized timing of delivery on the basis of risk factors and predicted outcomes warrant further investigation.

21-LB: Transdermal Microneedle Device Delivery of Adipocyte-Specific AAVs to Overexpress Adipose Tissue Neurotrophic Factors in the Treatment of Diabetic Peripheral Neuropathy

Diabetes is the leading cause of peripheral neuropathy (PN) , which results in loss of nerve supply in tissues like skin, adipose and muscle. While there are currently few treatments for PN, early mitigation in the pre-diabetic state with tissue neurotrophic factors may improve nerve function in metabolically important tissues like adipose. We used an adipocyte-tropic adeno-associated virus (AAV; serotype Rec2) to deliver neurotrophic factors directly to scWAT using a transdermal microneedle device that we developed. This approach avoids potential off-target effects and aberrant axon outgrowth in skin that may increase pain. Using both the BTBRob/ob and C57BL/6J diet-induced neuropathy mouse models, we have demonstrated that AAVRec2-BDNF (brain derived neurotrophic factor, which we have implicated in controlling adipose innervation) delivery to scWAT with our device increased tissue innervation 14 days after treatment, marked by increased protein expression of pan-neuronal marker PGP9.5 and sympathetic nerve marker tyrosine hydroxylase (TH) . Longer periods of dietary obesity (25+ wks vs 16 wks) blunted the ability of AAVRec2-BDNF to increase innervation in scWAT, despite these mice showing an initial decrease in body weight compared to controls. This indicates there may be a critical window for therapy delivery during the progression to diabetic neuropathy during which interventions are more advantageous. Treatment with AAVRec2-NGF (nerve growth factor) also increased scWAT innervation in obese mice at 8 weeks post-treatment, as evidenced by increased protein expression of PGP9.5, TH and markers of axon outgrowth (Gap43, Vasp) . Thermal imaging above inguinal scWAT revealed an increase in temperature only in AAVRec2-NGF treated mice, supporting the idea that NGF-responsive nerves drive tissue browning and/or thermogenesis. Taken together, we have developed a novel treatment approach for delivering adipocyte-tropic AAVs to overexpress neurotrophic factors as a means to mitigate diabetes-associated PN. Disclosure M. Blaszkiewicz: None. K. L. Townsend: Other Relationship; Neuright, Inc.