Optimal Delivery Research Articles

Blueprint for Blue Carbon: Lessons from Seychelles for Small Island States

Blue carbon has been proposed as a nature-based solution for climate change mitigation; however, a limited number of published works and data and knowledge gaps hinder the development of small island developing states’ (SIDS) national blue carbon resources globally. This paper reviews the blue carbon ecosystems of Seychelles as a case study in the context of SIDS, comparing estimations by the Blue Carbon Lab and recent blue carbon (mangrove and seagrass) evaluations submitted to the Seychelles national government. Mangroves (2195 ha, 80% in Aldabra Atoll) and seagrasses (142,065 ha) dominate in Seychelles, with coral reefs having the potential for carbon sequestration (169,000 ha). Seychelles is on track to protecting its blue carbon, but these systems are threatened by rising sea levels, coastal squeeze, erosion, severe storms, and human activities. The importance of carbon inventories, accounting institutions, and continuous monitoring of blue carbon systems is discussed. Blue accounting is necessary for accurate accounting of carbon sequestration and carbon storage, generating carbon credits, and representing impactful reductions in greenhouse gases for NDCs. Challenges and opportunities include policy legislation regarding ownership rights, accreditation and certification for carbon credits, sustainable financing mechanisms like natural asset companies and blue tokens, local engagement for long-term success, and carbon market dynamics following COP27. The restoration and regulation of blue carbon resources for optimal ecosystem services delivery, carbon inventories, and blue carbon policy are recommended development priorities. Blue carbon ecosystems have the potential to contribute to NDCs of SIDS while simultaneously offering sustainable development pathways for local communities through the multiple ecosystem services they provide.

Optimal Delivery Management for the Prevention of Early Neonatal SARS-CoV-2 Infection: Systematic Review and Meta-analysis.

Delivery management interventions (DMIs) were recommended to prevent delivery-associated transmission of maternal SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) to infants without evidence of effect on early neonatal SARS-CoV-2 infection (ENI) and neonatal death <28 days of life (ND). This systematic review describes different DMI combinations and the frequency of ENI and ND. Individual patient data were collected from articles published from January 1, 2020 to December 31, 2021 from Cochrane review databases, Medline, and Google Scholar. Article inclusion criteria were: documented maternal SARS-CoV-2 polymerase chain reaction (PCR)-positive status 10 days before delivery or symptomatic at delivery with a positive test within 48 hours, known delivery method, and known infant SARS-CoV-2 PCR result. Primary outcomes were ENI (positive PCR at 12 hours to 10 days) and ND. All characteristics were pooled using the DerSimonian-Laird inverse variance method. Primary outcome analyses were performed using logit transformation and random effect. Pooled results were expressed as percentages (95% confidence intervals). Continuity correction was applied for all pooled results if any included study has 0 event. A total of 11,075 publications were screened. 117 publications representing 244 infants and 230 mothers were included. All publications were case reports. ENI and ND were reported in 23.4% (18.2-29.18) and 2.1% (0.67-4.72) of cases, respectively. Among cases with available information, DMIs were reported for physical environment (85-100%), delivery-specific interventions (47-100%), and infant care practices (80-100%). No significant comparisons could be performed between different DMI combinations due to small sample size. The evidence supporting any DMI in SARS-CoV-2-infected mothers to prevent ENI or ND is extremely limited. Limitations of this meta-analysis include high risk of bias, small sample size, and large confidence intervals. This identifies the need for multinational database generation and specific studies designed to provide evidence of DMI guidelines best suited to prevent transmission from mother to neonate. · In this review we analyzed 2 years of maternal SARS-CoV-2 published cases.. · We assessed association of delivery management interventions with infant SARS-CoV-2 infection.. · We found no evidence supporting any DMI for that purpose..

Chitosan and Anionic Solubility Enhancer Sulfobutylether-β-Cyclodextrin-Based Nanoparticles as Dexamethasone Ophthalmic Delivery System for Anti-Inflammatory Therapy.

Cataract surgery interventions are constantly increasing, particularly among adult and elderly patients. This type of surgery can lead to inflammatory states of the ocular anterior segment (AS), usually healed via postoperative treatment with dexamethasone (DEX)-containing eye drops. The application of eye drops is challenging due to the high number of daily administrations. In this study, mucoadhesive nanoparticles (NPs) were formulated to improve the residence time of DEX on the corneal mucosa, enhancing the drug's solubility and bioavailability. The NPs were generated using an ionotropic gelation technique, exploiting the interaction between the cationic group of chitosan (CS) and the anionic group of sulfobutylether-β-cyclodextrin (SBE-β-CD). The formation of the inclusion complex and its stoichiometry were studied through phase solubility studies, Job's plot method, and Bi-directional transport studies on MDCKII-MDR1. The obtained NPs showed good chemical and physical characteristics suitable for drug loading and subsequent testing on animal mucosa. The DEX-loaded CS/SBE-β-CD NPs exhibited a prolonged residence time on animal mucosa and demonstrated enhanced drug permeability through the corneal membrane, showing a sustained release profile. The developed NPs posed no irritation or toxicity concerns upon local administration, making them an optimal and innovative drug delivery system for inflammatory AS diseases treatment.

Design, Evaluation and Optimization of Albuterol Sulphate and Theophylline Pulsincap drug delivery system for chronotherapy of Asthma

The aim of the current study was to design and develop and evaluate pulsatile drug delivery system of Albuterol Sulphate and Theophylline for the treatment of Asthma. The capsule body was made water insoluble by cross linked with formaldehyde vaopur. The treatment of Formalin was adopted to modify the gelatin capsule solubility. The formalin residue was carried out by quantitative test. The drug-excipient compatibility is done by FTIR and UV . The pulsincap formulation were prepared by using hydrogel plug of various components. The drug content of the formulation of pulsincap was found to be in the general range. The invitro drug release studies in ph1.2 .6.2 and 7.4 buffern was noticed to be zero percent and capsule was stable for 2 hours drug the studyF5 formulation batch was selected which was best and good formulation and promoted maximum drug release of 96.29% percentage at phosphate buffers when compared with other formulation. Pulsincap formulation can be adopted for optimum delivery of pellets in the treatment as per chronotherapy&#x0D; Keywords: Theophylline, quantitative test, invitro drug release studies, phosphate buffers6.2 and 7.4.

Usability of simplified audiometry and electrocardiogram during treatment of drug-resistant tuberculosis in Mozambique: a qualitative study

BackgroundIn 2021, there were approximately 450,000 cases of drug-resistant tuberculosis (DR-TB) worldwide. The treatment of DR-TB historically included expensive and toxic injectable drugs leading to adverse effects including ototoxicity and Electrocardiogram (ECG) abnormalities. This study described the perspectives of healthcare providers and people with DR-TB on the usability of simplified audiometry and ECG for monitoring treatment adverse effects.MethodsA qualitative study was conducted in December 2019 across four provinces in Mozambique, namely Maputo, Gaza, Zambézia, and Nampula. Sixteen outpatient primary care health facilities equipped with simplified Audiometry and/or ECG devices (specifically, SHOEBOX Audiometer® and/or SmartHeart Pro ECG®) installed for at least 6 months before the study initiation were selected. The data was collected using in-depth interviews (IDI) and Focus Group Discussions (FGD) techniques. Interviews were audio-recorded, transcribed verbatim in Portuguese, coded, and analyzed using Nvivo 12 software®. We generated two themes and fit our results into a conceptual framework consisting of three domains in the implementation of technological innovations in health.ResultsA total of 16 healthcare providers and 91 people undergoing treatment for DR-TB were enrolled in the study. Most people with DR-TB had experienced audiometry testing and demonstrated a good understanding of the assessments. Conversely, while most healthcare providers demonstrated robust knowledge of the importance of both audiometry and ECG assessments, they were not confident in managing ECG devices and interpreting the results.ConclusionsWhile healthcare providers demonstrated a consolidated understanding of the importance of audiometry, the limited number of devices and lack of training were constraints, impeding optimal usage and service delivery.

Автоматизація побудови, порівняння та вибору маршрутів та схем доставки в системі мультимодальних перевезень

&#x0D; The article proposes the application of a methodical approach to choosing the optimal route of multimodal transportation based on a module integrated into the information system of a freight forwarding company. The functions of the module are to build an optimal delivery scheme and meet all customer requirements, both domestic and international multimodal transportation, taking into account the changing circumstances in the conditions of instability caused by the state of war and the need to reorient the usual delivery routes.&#x0D; In the conditions of military operations, this method of automated search and comparison of alternative routes allows taking into account changing conditions that develop in real time, while the cargo flow should be accompanied by an information flow that would also be available in real time. The proposed structure of the database, the structures of requests for development routes., developed forms of source documents. The criteria for comparing routes of different dimensions are defined: the difference in the distance of cargo transportation, the costs of changing the existing system of cargo transportation, increasing the level of transportation safety, delivery time, reducing the cost of delivering a batch of goods, the difference in delivery time. A solution to the multi-criteria decision-making problem by normalizing the criteria and the additive optimization method is proposed. The method of determining the best route and supply scheme is implemented in the "decision-making" module, which is integrated into the information system of the transport forwarding company.&#x0D; The result of the practical implementation of the proposed method of construction, comparison and selection of routes and delivery schemes in the system of multimodal transportation based on the integrated module in the information system of the transport and forwarding company is the possibility of quick response to changes in external circumstances, warnings of emergency and conflict situations, control of the transportation process along the entire route and , if necessary, making adjustments to the route and delivery scheme, choosing a safe and effective option by the operator of multimodal transportation.

Institutional capacity assessment in the lens of implementation research: Capacity of the local institutions in delivering WASH services at Cox's Bazar district, Bangladesh.

The influx of Forcibly Displaced Myanmar Nationals (FDMNs) has left the Southwest coastal district of Cox's Bazar with one of the greatest contemporary humanitarian crises, stressing the existing water, sanitation, and hygiene (WASH) resources and services. This study aimed to assess the existing capacity of local institutions involved in delivering WASH services and identify relevant recommendations for intervention strategies. We used a qualitative approach, including interviews and capacity assessment workshops with institutions engaged in WASH service delivery. We conducted five key informant interviews (KII) with sub-district level officials of the Department of Public Health Engineering (DPHE), Directorate General of Health Services (DGHS), Directorate of Primary Education (DPE) and Bangladesh Rural Advancement Committee (BRAC) to have a general idea of WASH service mechanisms. Seven capacity assessment workshops were organized with the relevant district and sub-district level stakeholders from August 2019 to September 2019. These workshops followed three key areas: i) knowledge of policy, organizational strategy, guidelines, and framework; ii) institutional arrangements for service delivery such as planning, implementation, coordination, monitoring, and reporting; and iii) availability and management of human, financial and infrastructural resources. Data were categorized using thematic content analysis. The majority of stakeholders lacked awareness of national WASH policies. Furthermore, the top-down planning approaches resulted in activities that were not context-specific, and lack of coordination between multiple institutions compromised the optimal WASH service delivery at the local level. Shortage of human resources in delivering sustainable WASH services, inadequate supervision, and inadequate evaluation of activities also required further improvement, as identified by WASH stakeholders. Research evidence suggests that decision-makers, donors, and development partners should consider learning from the WASH implementers and stakeholders about their existing capacity, gaps, and opportunities before planning for any WASH intervention in any particular area.

An Observational Study of Dialogue about Uncertainty in Clinician-Family Counseling Conversations Following Prenatal Diagnosis of Complex Congenital Heart Disease

ObjectiveFamilies who receive a prenatal diagnosis of complex congenital heart disease (cCHD) often experience severe psychological distress and identify uncertainty as a key source of that distress. This study examined clinician-family conversations during initial fetal cardiology consultations to identify the topics of uncertainty discussed. MethodsIn this observational, qualitative study, initial fetal cardiology consultations were audio-recorded, transcribed verbatim, and coded by two independent coders. A codebook was inductively and deductively developed and applied. This content analysis focused on uncertainty-related codes and associated themes. ResultsDuring 19 consultations including five clinicians, 13 different cardiac diagnoses were discussed (seven with high mortality risk). Median consultation length was 37 min (IQR: 26–51), with only 11% of words spoken by families. On average, 51% of total words spoken focused on uncertainty in relation to cardiac diagnosis, etiology, comorbidities, prognosis, childbirth, therapeutics, and logistics. Family-initiated discussion on uncertainty largely focused on childbirth and pregnancy and postpartum logistics. ConclusionsHalf of dialogue within initial fetal cardiology encounters discussed uncertainty surrounding prenatally diagnosed cCHD. Parent and clinician perspectives should be gathered on the essential content and optimal delivery of uncertainty-related topics. InnovationThis study is conceptually and methodologically innovative as one of the first to examine audio-recorded dialogue between fetal cardiology clinicians and families.

Transcellular Barriers to Glucose Delivery in the Body.

Glucose is the universal fuel of most mammalian cells, and it is largely replenished through dietary intake. Glucose availability to tissues is paramount for the maintenance of homeostatic energetics and, hence, supply should match demand by the consuming organs. In its journey through the body, glucose encounters cellular barriers for transit at the levels of the absorbing intestinal epithelial wall, the renal epithelium mediating glucose reabsorption, and the tight capillary endothelia (especially in the brain). Glucose transiting through these cellular barriers must escape degradation to ensure optimal glucose delivery to the bloodstream or tissues. The liver, which stores glycogen and generates glucose de novo, must similarly be able to release it intact to the circulation. We present the most up-to-date knowledge on glucose handling by the gut, liver, brain endothelium, and kidney, and discuss underlying molecular mechanisms and open questions. Diseases associated with defects in glucose delivery and homeostasis are also briefly addressed. We propose that the universal problem of sparing glucose from catabolism in favor of translocation across the barriers posed by epithelia and endothelia is resolved through common mechanisms involving glucose transfer to the endoplasmic reticulum, from where glucose exits the cells via unconventional cellular mechanisms.

Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study

We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computed Z values were compared and the robustness of the approach based on the materials’ composition was confirmed. Finally, the calibration method was compared with a previous method by Bourque et al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.

Telerehabilitation: lessons from the COVID-19 pandemic and future perspectives.

The coronavirus disease 2019 (COVID-19) pandemic has had an enormous effect on healthcare, notably rehabilitation for neurological, rheumatological, musculoskeletal, and cognitive diseases. Telerehabilitation provides rehabilitation services via multiple modalities,such as real-time chats, computerized consultations, and distant evaluations, emphasizingassessment, diagnosis, and intervention. While the use of telerehabilitation had restrictions beforeCOVID-19, regulatory changes have accelerated its adoption, broadening therapy provision beyond traditional healthcare settings. Telerehabilitation has been examined for its effectiveness in a variety of health concerns, including stroke, traumatic brain injury, Parkinson's disease, musculoskeletal disorders, and rheumatic diseases. Despite the constraints of the COVID-19 environment, telerehabilitation settings, which include patient and therapist aspects, have emerged to ensure optimal treatment delivery. Key themes include home-based rehabilitation initiatives, wearable gadgets, and the integration of analytics and artificial intelligence. The growing acceptance of telehealth and telerehabilitation is expected to drive further progress in this discipline.

The improvement of tyrosol bioavailability by encapsulation into liposomes using pH-driven method

To improve the poor water solubility and oral bioavailability of tyrosol, novel tyrosol liposomes (Tyr-LPs) were prepared by pH-driven method. Fourier transform infrared (FTIR) absorption spectra and X-ray diffraction (XRD) analysis indicated that Tyr-LPs were successfully encapsulated and tyrosol was in an amorphous state in liposomes. When tyrosol content in Tyr-LP was 1.33 mg/ml and the Tyr:LP (mass ratio) = 1:2, favorable dispersibility of Tyr-LP was exhibited, with an instability index of 0.049 ± 0.004, PDI of 0.274 ± 0.003, and the EE of 94.8 ± 2.5 %. In vivo pharmacokinetic studies showed that after oral administration of tyrosol or Tyr-LP (Tyr:LP = 1:2), concentration-versus-time curve (AUC0–720mins) and maximum concentration (Cmax) values of Tyr-LP was respectively 1.5-fold (P < 0.01) and 2.25-fold (P < 0.01) higher than tyrosol, which indicated that the oral bioavailability of tyrosol was effectively improved in Tyr-LPs. Our study thereby provides theoretical support for the application of Tyr-LP for optimal delivery of tryosol.

The comparison of adipose-derived stromal cells (ADSCs) delivery method in a murine model of hindlimb ischemia

BackgroundAdipose-derived stromal cells (ADSCs) demonstrate ability to promote tissue healing and down-regulate excessive inflammation. ADSCs have been used to treat critical limb ischemia in preclinical and clinical trials, but still, there is little known about their optimal delivery strategy. To date, no direct analysis of different methods of ADSCs delivery has been performed in the hindlimb ischemia model. Therefore, in this study we focused on the therapeutic efficacy of different ADSCs delivery methods in a murine model of hindlimb ischemia.MethodsFor the hADSCs isolation, we used the subcutaneous adipose tissue collected during the surgery. The murine hindlimb ischemia was used as a model. The unilateral femoral artery ligation was performed on 10–12-week-old male C57BL/6. ADSCs were delivered directly into ischemic muscle, into the contralateral muscle or intravenously. 7 and 14 days after the surgery, the gastrocnemius and quadriceps muscles were collected for the immunohistochemical analysis. The results were analyzed with relevant tests using the Statistica software.ResultsOur research revealed that muscle regeneration, angiogenesis, arteriogenesis and macrophage infiltration in murine model of hindlimb ischemia differ depending on ADSCs delivery method. We have demonstrated that intramuscular method (directly into ischemic limb) of ADSCs delivery is more efficient in functional recovery after critical limb ischemia than intravenous or contralateral route.ConclusionsWe have noticed that injection of ADSCs directly into ischemic limb is the optimal delivery strategy because it increases: (1) muscle fiber regeneration, (2) the number of capillaries and (3) the influx of macrophages F4/80+/CD206+.

Spotlight on Leadership: What Nurse Leaders Need to Know About Artificial Intelligence.

Artificial intelligence (AI) is not a new concept. Since the 2022 release of a popular large language model, AI has become readily accessible to the general population, brought transformational shifts in healthcare, and created significant implications for nurse leaders. Specifically, AI has major indications in the area of evidence-based practice. Historically, new evidence takes years to reach the bedside. Nurse leaders are instrumental in closing the research-to-practice gap and, in doing so, promote optimal patient safety and care delivery methods. This article provides an overview of using AI in the context of nursing leadership in healthcare settings, including appropriate case use. In addition, this article covers the ethical challenges of using AI in clinical settings.

A user-centered smart inhaler algorithm for targeted drug delivery in juvenile onset recurrent respiratory papillomatosis treatment integrating computational fluid particle dynamics and machine learning

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates targeted drug delivery (TDD) to ensure that inhaled aerosolized drugs reach specific sites, such as the larynx and glottis, without harming healthy tissues. Using computational fluid particle dynamics (CFPD) and machine learning (ML), this study (1) investigated how drug properties and individual factors influence TDD efficiency for JORRP treatment and (2) developed personalized inhalation therapy using an ML-empowered smart inhaler control algorithm for precise medication release. This algorithm optimizes the inhaler nozzle position and diameter based on drug and patient-specific data, enhancing drug delivery to the larynx and glottis. CFPD simulations show that particle size significantly affects deposition fractions in the upper airway, emphasizing the importance of particle size selection. Additionally, optimal nozzle diameter and delivery efficiency depend on particle size, inhalation flow rate, and release time. The ML-based TDD strategy, employing a classification and regression tree model, outperforms conventional inhalation therapy by achieving a higher delivery efficiency to the larynx and glottis. This innovative concept of an ML-empowered smart inhaler represents a promising step toward personalized and precise pulmonary healthcare through inhalation therapy. It demonstrates the potential of AI-driven smart inhalers for improving the treatment outcomes of lung diseases that require TDD at designated lung sites.

PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction.

Effective drug delivery systems are paramount in enhancing pharmaceutical outcomes, particularly through the use of cell-penetrating peptides (CPPs). These peptides are gaining prominence due to their ability to penetrate eukaryotic cells efficiently without inflicting significant damage to the cellular membrane, thereby ensuring optimal drug delivery. However, the identification and characterization of CPPs remain a challenge due to the laborious and time-consuming nature of conventional methods, despite advances in proteomics. Current computational models, however, are predominantly tailored for balanced datasets, an approach that falls short in real-world applications characterized by a scarcity of known positive CPP instances. To navigate this shortfall, we introduce PractiCPP, a novel deep-learning framework tailored for CPP prediction in highly imbalanced data scenarios. Uniquely designed with the integration of hard negative sampling and a sophisticated feature extraction and prediction module, PractiCPP facilitates an intricate understanding and learning from imbalanced data. Our extensive computational validations highlight PractiCPP's exceptional ability to outperform existing state-of-the-art methods, demonstrating remarkable accuracy, even in datasets with an extreme positive-to-negative ratio of 1:1000. Furthermore, through methodical embedding visualizations, we have established that models trained on balanced datasets are not conducive to practical, large-scale CPP identification, as they do not accurately reflect real-world complexities. In summary, PractiCPP potentially offers new perspectives in CPP prediction methodologies. Its design and validation, informed by real-world dataset constraints, suggest its utility as a valuable tool in supporting the acceleration of drug delivery advancements. The source code of PractiCPP is available on Figshare at https://doi.org/10.6084/m9.figshare.25053878.v1.

Carbon footprint of hospital laundry: a life-cycle assessment

ObjectivesTo assess greenhouse gas (GHG) emissions from a regional hospital laundry unit, and model ways in which these can be reduced.DesignA cradle to grave process-based attributional life-cycle assessment.SettingA large hospital...

The next-generation DNA vaccine platforms and delivery systems: advances, challenges and prospects.

Vaccines have proven effective in the treatment and prevention of numerous diseases. However, traditional attenuated and inactivated vaccines suffer from certain drawbacks such as complex preparation, limited efficacy, potential risks and others. These limitations restrict their widespread use, especially in the face of an increasingly diverse range of diseases. With the ongoing advancements in genetic engineering vaccines, DNA vaccines have emerged as a highly promising approach in the treatment of both genetic diseases and acquired diseases. While several DNA vaccines have demonstrated substantial success in animal models of diseases, certain challenges need to be addressed before application in human subjects. The primary obstacle lies in the absence of an optimal delivery system, which significantly hampers the immunogenicity of DNA vaccines. We conduct a comprehensive analysis of the current status and limitations of DNA vaccines by focusing on both viral and non-viral DNA delivery systems, as they play crucial roles in the exploration of novel DNA vaccines. We provide an evaluation of their strengths and weaknesses based on our critical assessment. Additionally, the review summarizes the most recent advancements and breakthroughs in pre-clinical and clinical studies, highlighting the need for further clinical trials in this rapidly evolving field.

Early delivery of human umbilical cord mesenchymal stem cells improves healing in a rat model of Achilles tendinopathy.

Objective: This study aimed to explore the efficacy and optimal delivery time of human umbilical cord mesenchymal stem cells (hUC-MSCs) in treating collagenase-induced Achilles tendinopathy. Methods: Achilles tendinopathy in rats at early or advanced stages was induced by injecting collagenase I into bilateral Achilles tendons. A total of28 injured rats were injected with a hUC-MSCsolution or normal saline into bilateral tendons twice andsampled after 4weeks for histological staining, gene expression analysis, transmission electron microscope assayand biomechanical testing analysis. Results: The results revealed better histological performance and a larger collagen fiber diameter in theMSC group. mRNA expressionof TNF-α, IL-1βand MMP-3 was lower after MSC transplantation. Early MSC delivery promoted collagen I and TIMP-3 synthesis, and strengthened tendon toughness. Conclusion: hUC-MSCs demonstrated atherapeutic effect in treating collagenase-induced Achilles tendinopathy, particularly in the early stage of tendinopathy.

Integrated palliative care in oncology: a protocol for a realist synthesis

IntroductionEmerging evidence suggests improved quality of life, reduced symptom burden and lower health services costs when integrated palliative care and cancer care are implemented. Integrated palliative care aims to achieve...