Bioactive coating provides antimicrobial protection through immunomodulation and phage therapeutics.

Medical implant-associated infections (IAI) is a growing threat to patients undergoing implantation surgery. IAI prevention typically relies on medical implants endowed with bactericidal properties achieved through surface modifications with antibiotics. However, the clinical efficacy of this traditional paradigm remains suboptimal, often necessitating revision surgery and posing potentially lethal consequences for patients. To bolster the existing anti-IAI arsenal, we propose herein a chitosan-based bioactive coating, i.e., ChitoAntibac, which exerts bacteria-inhibitory effects either through immune modulation or phage-directed microbial clearance, without relying on conventional antibiotics. The immuno-stimulating effects and phage-induced bactericidal properties can be tailored by engineering the loading dynamic of macrophage migration inhibitory factor (MIF), which polarizes macrophages towards the proinflammatory subtype (M1) with enhanced bacterial phagocytosis, and Staphylococcal Phage K, resulting in rapid and targeted pathogenic clearance (>99.99%) in less than 8 h. Our innovative antibacterial coating opens a new avenue in the pursuit of effective IAI prevention through immuno-stimulation and phage therapeutics.

Bioengineered hydrogels enhance ex vivo preservation of patient-derived tumor explants for drug evaluation.

Ex vivo patient-derived tumor slices (PDTS) are currently limited by short-term viability in culture. Here, we show how bioengineered hydrogels enable the identification of key matrix parameters that significantly enhance PDTS viability compared to conventional culture systems. As demonstrated using single-cell RNA sequencing and high-dimensional flow cytometry, hydrogel-embedded PDTS tightly preserved cancer, cancer-associated fibroblast, and various immune cell populations and subpopulations in the corresponding original tumor. Cell-cell communication networks within the tumor microenvironment, including immune checkpoint ligand-receptor interactions, were also maintained. Remarkably, our results from a co-clinical trial suggest hydrogel-embedded PDTS may predict sensitivity to immune checkpoint inhibitors (ICIs) in head and neck cancer patients. Further, we show how these longer term-cultured tumor explants uniquely enable the sampling and detection of temporal evolution in molecular readouts when treated with ICIs. By preserving the compositional heterogeneity and complexity of patient tumors, hydrogel-embedded PDTS provide a valuable tool to facilitate experiments targeting the tumor microenvironment.

Mechano-Activated Cell Therapy for Accelerated Diabetic Wound Healing.

Chronic diabetic wounds are a significant global healthcare challenge. Current strategies, such as biomaterials, cell therapies, and medical devices, however, only target a few pathological features and have limited efficacy. A powerful platform technology combining magneto-responsive hydrogel, cells, and wireless magneto-induced dynamic mechanical stimulation (MDMS) is developed to accelerate diabetic wound healing. The hydrogel encapsulates U.S. Food and Drug Administration (FDA)-approved fibroblasts and keratinocytes to achieve ∼3-fold better wound closure in a diabetic mouse model. MDMS acts as a nongenetic mechano-rheostat to activate fibroblasts, resulting in ∼240% better proliferation, ∼220% more collagen deposition, and improved keratinocyte paracrine profiles via the Ras/MEK/ERK pathway to boost angiogenesis. The magneto-responsive property also enables on-demand insulin release for spatiotemporal glucose regulation through increasing network deformation and interstitial flow. By mining scRNAseq data, a mechanosensitive fibroblast subpopulation is identified that can be mechanically tuned for enhanced proliferation and collagen production, maximizing therapeutic impact. The "all-in-one" system addresses major pathological factors associated with diabetic wounds in a single platform, with potential applications for other challenging wound types.

Kappa opioid receptor activation increases thermogenic energy expenditure which drives increased feeding.

Opioid receptors, including the kappa opioid receptor (KOR), exert control over thermoregulation and feeding behavior. Notably, activation of KOR stimulates food intake, leading to postulation that KOR signaling plays a central role in managing energy intake. KOR has also been proposed as a target for treating obesity. Herein, we report studies examining how roles for KOR signaling in regulating thermogenesis, feeding, and energy balance may be interrelated using pharmacological interventions, genetic tools, quantitative thermal imaging, and metabolic profiling. Our findings demonstrate that activation of KOR in the central nervous system causes increased energy expenditure via brown adipose tissue activation. Importantly, pharmacologic, or genetic inhibition of brown adipose tissue thermogenesis prevented the elevated food intake triggered by KOR activation. Furthermore, our data reveal that KOR-mediated thermogenesis elevation is reversibly disrupted by chronic high-fat diet, implicating KOR signaling as a potential mediator in high-fat diet-induced weight gain.

Dynamic Stimulations with Bioengineered Extracellular Matrix-Mimicking Hydrogels for Mechano Cell Reprogramming and Therapy.

Cells interact with their surrounding environment through a combination of static and dynamic mechanical signals that vary over stimulus types, intensity, space, and time. Compared to static mechanical signals such as stiffness, porosity, and topography, the current understanding on the effects of dynamic mechanical stimulations on cells remains limited, attributing to a lack of access to devices, the complexity of experimental set-up, and data interpretation. Yet, in the pursuit of emerging translational applications (e.g., cell manufacturing for clinical treatment), it is crucial to understand how cells respond to a variety of dynamic forces that are omnipresent in vivo so that they can be exploited to enhance manufacturing and therapeutic outcomes. With a rising appreciation of the extracellular matrix (ECM) as a key regulator of biofunctions, researchers have bioengineered a suite of ECM-mimicking hydrogels, which can be fine-tuned with spatiotemporal mechanical cues to model complex static and dynamic mechanical profiles. This review first discusses how mechanical stimuli may impact different cellular components and the various mechanobiology pathways involved. Then, how hydrogels can be designed to incorporate static and dynamic mechanical parameters to influence cell behaviors are described. The Scopus database is also used to analyze the relative strength in evidence, ranging from strong to weak, based on number of published literatures, associated citations, and treatment significance. Additionally, the impacts of static and dynamic mechanical stimulations on clinically relevant cell types including mesenchymal stem cells, fibroblasts, and immune cells, are evaluated. The aim is to draw attention to the paucity of studies on the effects of dynamic mechanical stimuli on cells, as well as to highlight the potential of using a cocktail of various types and intensities of mechanical stimulations to influence cell fates (similar to the concept of biochemical cocktail to direct cell fate). It is envisioned that this progress report will inspire more exciting translational development of mechanoresponsive hydrogels for biomedical applications.

Making In Vitro Tumor Models Whole Again.

As a reductionist approach, patient-derived in vitro tumor models are inherently still too simplistic for personalized drug testing as they do not capture many characteristics of the tumor microenvironment (TME), such as tumor architecture and stromal heterogeneity. This is especially problematic for assessing stromal-targeting drugs such as immunotherapies in which the density and distribution of immune and other stromal cells determine drug efficacy. On the other end, in vivo models are typically costly, low-throughput, and time-consuming to establish. Ex vivo patient-derived tumor explant (PDE) cultures involve the culture of resected tumor fragments that potentially retain the intact  TME of the original tumor. Although developed decades ago, PDE cultures have not been widely adopted likely because of their low-throughput and poor long-term viability. However, with growing recognition of the importance of patient-specific TME in mediating drug response, especially in the field of immune-oncology, there is an urgent need to resurrect these holistic cultures. In this Review, the key limitations of patient-derived tumor explant cultures are outlined and technologies that have been developed or could be employed to address these limitations are discussed. Engineered holistic tumor explant cultures may truly realize the concept of personalized medicine for cancer patients.

Evaluating the utility of knowledge-based planning for clinical trials using the TROG 08.03 post prostatectomy radiation therapy planning data.

Background and purpose: Poor quality radiotherapy can detrimentally affect outcomes in clinical trials. Our purpose was to explore the potential of knowledge-based planning (KBP) for quality assurance (QA) in clinical trials. Materials and methods: Using 30 in-house post-prostatectomy radiation treatment (PPRT) plans, an iterative KBP model was created according to the multicentre clinical trial protocol, delivering 64 Gy in 32 fractions. KBP was used to replan 137 plans. The KB (knowledge based) plans were evaluated for their ability to fulfil the trial constraints and were compared against their corresponding original treatment plans (OTP). A second analysis between only the 72 inversely planned OTPs (IP-OTPs) and their corresponding KB plans was performed. Results: All dose constraints were met in 100% of KB plans versus 69% of OTPs. KB plans demonstrated significantly less variation in PTV coverage (Mean dose range: KB plans 64.1 Gy-65.1 Gy vs OTP 63.1 Gy-67.3 Gy, p < 0.01). KBP resulted in significantly lower doses to OARs. Rectal V60Gy and V40Gy were 17.7% vs 27.7% (p < 0.01) and 40.5% vs 53.9% (p < 0.01) for KB plans and OTP respectively. Left femoral head (FH) V45Gy and V35Gy were 0.4% vs 7.4% (p < 0.01) and 7.9% vs 34.9% (p < 0.01) respectively. In the second analysis plan improvements were maintained. Conclusions: KBP created high quality PPRT plans using the data from a multicentre clinical trial in a single optimisation. It is a powerful tool for utilisation in clinical trials for patient specific QA, to reduce dose to surrounding OARs and variations in plan quality which could impact on clinical trial outcomes.

Comprehensive nodal breast VMAT: solving the low-dose wash dilemma using an iterative knowledge-based radiotherapy planning solution.

INTRODUCTION: Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low-dose wash. METHODS: Forty CLN-breast patient data sets were utilised to develop a knowledge-based planning (KBP) VMAT model, which limits low-dose wash using iterative learning and base-tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP-generated ipsilateral VMAT (ipsi-VMAT) plans against the benchmarked hybrid (h)-VMAT (departmental standard) and bowtie-VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ-at-risk (OAR), remaining-volume-at-risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. RESULTS: Ipsi- and bowtie-VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P < 0.05) compared to h-VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral-lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low-dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient-specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review. CONCLUSIONS: A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low-dose wash associated with increased second malignancy risk.

Improving efficiency in the radiation management of multiple brain metastases using a knowledge-based planning solution for single-isocentre volumetric modulated arc therapy (VMAT) technique.

INTRODUCTION: This study aimed to develop a single-isocentre volumetric modulated arc therapy (si-VMAT) technique for multiple brain metastases using knowledge-based planning software, comparing it with a multiple-isocentre stereotactic radiosurgery (mi-SRS) planning approach. METHODS: Twenty-six si-VMAT plans were created and uploaded into RapidPlanTM (RP) to create a si-VMAT model. Ten patients, with 2 to 6 metastases (mets), were planned with a si-VMAT technique utilising RP, and a mi-SRS technique on Brainlab iPlan. Paddick Conformity Index (PCI) was used to compare conformity. The volumes of the brain receiving 15Gy, 12Gy, 10Gy, 7.5Gy and 3Gy were also compared. Retrospective treatment times from the last eight patients treated were averaged for pre-imaging and beam on time to calculate treatment times for both techniques. RESULTS: There was a significant difference in the PCI scores for the mi-SRS plans (M = 0.667, SD = 0.114) and si-VMAT plans (M = 0.728, SD = 0.088), with PCI values suggesting better prescription dose conformity with the si-VMAT technique (P = 0.014). Percentage of total brain volume receiving low-dose wash at four of the five different dose levels was significantly less (P < 0.05) with mi-SRS. Average time to treat a single met with current mi-SRS technique is 25.7 min, with each additional met requiring this same amount of time. The average time to treat 2-3 mets using si-VMAT would be 25.3 min and 4+ metastases 33.5 min. CONCLUSION: A knowledge-based si-VMAT approach was efficient in planning and treating multi metastases while achieving clinically acceptable dosimetry with respect to dose conformity and low-dose fall off.

Rolling out RapidPlan: What we've learnt.

INTRODUCTION: RapidPlan (RP), a knowledge-based planning system, aims to consistently improve plan quality and efficiency in radiotherapy. During the early stages of implementation, some of the challenges include knowing how to optimally train a model and how to integrate RP into a department. We discuss our experience with the implementation of RP into our institution. METHODS: We reviewed all patients planned using RP over a 7-month period following inception in our department. Our primary outcome was clinically acceptable plans (used for treatment) with secondary outcomes including model performance and a comparison of efficiency and plan quality between RP and manual planning (MP). RESULTS: Between November 2017 and May 2018, 496 patients were simulated, of which 217 (43.8%) had an available model. RP successfully created a clinically acceptable plan in 87.2% of eligible patients. The individual success of the 24 models ranged from 50% to 100%, with more than 90% success in 15 (62.5%) of the models. In 40% of plans, success was achieved on the 1st optimisation. The overall planning time with RP was reduced by up to 95% compared with MP times. The quality of the RP plans was at least equivalent to historical MP plans in terms of target coverage and organ at risk constraints. CONCLUSION: While initially time-consuming and resource-intensive to implement, plans optimised with RP demonstrate clinically acceptable plan quality, while significantly improving the efficiency of a department, suggesting RP and its application is a highly effective tool in clinical practice.

Parotid sparing in RapidPlan Oropharynx models: To split or not to split.

INTRODUCTION: Differences in knowledge and experience, patient anatomy and tumour location and manipulation of inverse planning objectives and priorities will lead to a variability in the quality of radiation planning. The aim of this study was to investigate whether parotid glands should be treated as separate or combined structures when using knowledge-based planning (KBP) to create oropharyngeal plans, based on the dose they receive. METHOD: Two separate RapidPlan (RP) models were created using the same 70 radical oropharyngeal patients. The 'separated model' divided the parotids into ipsilateral and contralateral structures. The 'combined model' did not separate the parotids. The models were independently validated using 20 patients not included in the models. The same dose constraints and priorities were applied to planning target volumes (PTVs) and organs at risk (OARs) for all plans. An auto-generated line objective and priority was applied in both models, with parotid mean dose and V50 doses evaluated and compared. RESULTS: Plans optimised using the combined model resulted in lower ipsilateral mean doses and lower V50 doses in 80% and 75% of cases, respectively. Fifty-five per cent of plans produced lower mean doses for the contralateral parotid when optimised using the combined model, while lower V50 doses were evenly split between the models. CONCLUSION: Combining the data for both parotids into one RP model resulted in better ipsilateral parotid sparing. Results also suggest that a combined parotid model will spare dose to the contralateral parotid; however, further investigation is required to confirm these results.

Results of a Prospective Dose Escalation Study of Linear Accelerator-Based Virtual Brachytherapy (BOOSTER) for Prostate Cancer; Virtual HDR Brachytherapy for Prostate Cancer.

PURPOSE: To demonstrate feasibility and toxicity of linear accelerator-based stereotactic radiation therapy boost (SBRT) for prostate cancer, mimicking a high-dose-rate brachytherapy boost. METHODS AND MATERIALS: A phase 1 sequential dose escalation study of SBRT compared 20 Gy, 22 Gy, and 24 Gy to the prostate and 25 Gy, 27.5 Gy, and 30 Gy to the gross tumor volume in 2 fractions, combined with 46 Gy in 23 fractions of external beam radiation. Feasibility of dose escalation (volume receiving 125% and 150% of the dose) while meeting organ-at-risk dose constraints, grade 2 acute and late gastrointestinal and genitourinary toxicity, and freedom from biochemical failure were secondary endpoints. RESULTS: Thirty-six men with intermediate- and high-risk prostate cancer were enrolled with a median follow-up of 24 months. Sixty-four percent of patients had high-risk features. Nine men were enrolled to dose level 1, 6 to level 2, and 6 to level 3. Another 15 patients were treated at dose level 3 on the continuation study. Dose level 3 achieved superior 125% (23.75 Gy) and 150% (28.5 Gy) dose compared to dose levels 1 and 2, with minimal differences in organ-at-risk doses. Kaplan-Meier estimate of freedom from biochemical failure at 3 years was 93.3%. There were no late grade 2 or 3 gastrointestinal events. The late grade 2 genitourinary toxicity at 2 years was 19.3%. Prostate-specific membrane antigen positron emission tomography was performed at 2 years with no local recurrences. CONCLUSIONS: We have shown that a linear accelerator-based SBRT boost for prostate cancer is feasible and can achieve doses comparable to high-dose-rate boost up to the 150% isodose volumes. Rectal, bladder, and urethral doses remained low, and long-term toxicity was the same as or better than previous reports from high-dose-rate or low-dose-rate boost protocols.

WikiPathways for plants: a community pathway curation portal and a case study in rice and arabidopsis seed development networks.

BACKGROUND: Next-generation sequencing and 'omics' platforms are used extensively in plant biology research to unravel new genomes and study their interactions with abiotic and biotic agents in the growth environment. Despite the availability of a large and growing number of genomic data sets, there are only limited resources providing highly-curated and up-to-date metabolic and regulatory networks for plant pathways. RESULTS: Using PathVisio, a pathway editor tool associated with WikiPathways, we created a gene interaction network of 430 rice (Oryza sativa) genes involved in the seed development process by curating interactions reported in the published literature. We then applied an InParanoid-based homology search to these genes and used the resulting gene clusters to identify 351 Arabidopsis thaliana genes. Using this list of homologous genes, we constructed a seed development network in Arabidopsis by processing the gene list and the rice network through a Perl utility software called Pathway GeneSWAPPER developed by us. In order to demonstrate the utility of these networks in generating testable hypotheses and preliminary analysis prior to more in-depth downstream analysis, we used the expression viewer and statistical analysis features of PathVisio to analyze publicly-available and published microarray gene expression data sets on diurnal photoperiod response and the seed development time course to discover patterns of coexpressed genes found in the rice and Arabidopsis seed development networks. These seed development networks described herein, along with other plant pathways and networks, are freely available on the plant pathways portal at WikiPathways (http://plants.wikipathways.org). CONCLUSION: In collaboration with the WikiPathways project we present a community curation and analysis platform for plant biologists where registered users can freely create, edit, share and monitor pathways supported by published literature. We describe the curation and annotation of a seed development network in rice, and the projection of a similar, gene homology-based network in Arabidopsis. We also demonstrate the utility of the Pathway GeneSWAPPER (PGS) application in saving valuable time and labor when a reference network in one species compiled in GPML format is used to project a similar network in another species based on gene homology.