A microbial supply chain for production of the anti-cancer drug vinblastine.

Monoterpene indole alkaloids (MIAs) are a diverse family of complex plant secondary metabolites with many medicinal properties, including the essential anti-cancer therapeutics vinblastine and vincristine1. As MIAs are difficult to chemically synthesize, the world's supply chain for vinblastine relies on low-yielding extraction and purification of the precursors vindoline and catharanthine from the plant Catharanthus roseus, which is then followed by simple in vitro chemical coupling and reduction to form vinblastine at an industrial scale2,3. Here, we demonstrate the de novo microbial biosynthesis of vindoline and catharanthine using a highly engineered yeast, and in vitro chemical coupling to vinblastine. The study showcases a very long biosynthetic pathway refactored into a microbial cell factory, including 30 enzymatic steps beyond the yeast native metabolites geranyl pyrophosphate and tryptophan to catharanthine and vindoline. In total, 56 genetic edits were performed, including expression of 34 heterologous genes from plants, as well as deletions, knock-downs and overexpression of ten yeast genes to improve precursor supplies towards de novo production of catharanthine and vindoline, from which semisynthesis to vinblastine occurs. As the vinblastine pathway is one of the longest MIA biosynthetic pathways, this study positions yeast as a scalable platform to produce more than 3,000 natural MIAs and a virtually infinite number of new-to-nature analogues.

Mechanical theory of nonequilibrium coexistence and motility-induced phase separation.

Nonequilibrium phase transitions are routinely observed in both natural and synthetic systems. The ubiquity of these transitions highlights the conspicuous absence of a general theory of phase coexistence that is broadly applicable to both nonequilibrium and equilibrium systems. Here, we present a general mechanical theory for phase separation rooted in ideas explored nearly a half-century ago in the study of inhomogeneous fluids. The core idea is that the mechanical forces within the interface separating two coexisting phases uniquely determine coexistence criteria, regardless of whether a system is in equilibrium or not. We demonstrate the power and utility of this theory by applying it to active Brownian particles, predicting a quantitative phase diagram for motility-induced phase separation in both two and three dimensions. This formulation additionally allows for the prediction of novel interfacial phenomena, such as an increasing interface width while moving deeper into the two-phase region, a uniquely nonequilibrium effect confirmed by computer simulations. The self-consistent determination of bulk phase behavior and interfacial phenomena offered by this mechanical perspective provide a concrete path forward toward a general theory for nonequilibrium phase transitions.

Biosynthesis of natural and halogenated plant monoterpene indole alkaloids in yeast.

Monoterpenoid indole alkaloids (MIAs) represent a large class of plant natural products with marketed pharmaceutical activities against a wide range of indications, including cancer, malaria and hypertension. Halogenated MIAs have shown improved pharmaceutical properties; however, synthesis of new-to-nature halogenated MIAs remains a challenge. Here we demonstrate a platform for de novo biosynthesis of two MIAs, serpentine and alstonine, in baker's yeast Saccharomyces cerevisiae and deploy it to systematically explore the biocatalytic potential of refactored MIA pathways for the production of halogenated MIAs. From this, we demonstrate conversion of individual haloindole derivatives to a total of 19 different new-to-nature haloserpentine and haloalstonine analogs. Furthermore, by process optimization and heterologous expression of a modified halogenase in the microbial MIA platform, we document de novo halogenation and biosynthesis of chloroalstonine. Together, this study highlights a microbial platform for enzymatic exploration and production of complex natural and new-to-nature MIAs with therapeutic potential.

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering.

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

The influence of molecular design on structure-property relationships of a supramolecular polymer prodrug.

Supramolecular self-assemblies of hydrophilic macromolecules functionalized with hydrophobic, structure-directing components have long been used for drug delivery. In these systems, loading of poorly soluble compounds is typically achieved through physical encapsulation during or after formation of the supramolecular assembly, resulting in low encapsulation efficiencies and limited control over release kinetics, which are predominately governed by diffusion and carrier degradation. To overcome these limitations, amphiphilic prodrugs that leverage a hydrophobic drug as both the therapeutic and structure-directing component can be used to create supramolecular materials with higher loading and controlled-release kinetics using biodegradable or enzymatically cleavable linkers. Here, we report the design, synthesis, and characterization of a library of supramolecular polymer prodrugs based on poly(ethylene glycol) (PEG) and the proregenerative drug 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (DPCA). Structure-property relationships were elucidated through experimental characterization of prodrug behavior in both the wet and dry states using scattering techniques and electron microscopy and corroborated by coarse-grained modeling. Molecular architecture and the hydrophobic-to-hydrophilic ratio of PEG-DPCA conjugates strongly influenced their physical state in water, ranging from fully soluble to supramolecular spherical assemblies and nanofibers. Molecular design and supramolecular structure, in turn, were shown to dramatically alter hydrolytic and enzymatic release and cellular transport of DPCA. In addition to potentially expanding therapeutic options for DPCA through control of supramolecular assemblies, the design principles elaborated here may inform the development of other supramolecular prodrugs based on hydrophobic small-molecule compounds.

Standardised definitions and diagnostic criteria for extranodal extension detected on histopathological examination in head and neck cancer: Head and Neck Cancer International Group consensus recommendations.

Detection of extranodal extension on histopathology in surgically treated head and neck squamous cell carcinoma indicates poor prognosis. However, there is no consensus on the diagnostic criteria, interpretation, and reporting of histology detected extranodal extension, which has contributed to conflicting evidence in the literature, and likely clinical inconsistency. The Head and Neck Cancer International Group conducted a three-round modified Delphi process with a group of 19 international pathology experts representing 15 national clinical research groups to generate consensus recommendations for histology detected extranodal extension diagnostic criteria. The expert panel strongly agreed on terminology and diagnostic features for histology detected extranodal extension and soft tissue metastasis. Moreover, the panel reached consensus on reporting of histology detected extranodal extension and on nodal sampling. These consensus recommendations, endorsed by 19 organisations representing 34 countries, are a crucial development towards standardised diagnosis and reporting of histology detected extranodal extension, and more accurate data collection and analysis.

Criteria for the diagnosis of extranodal extension detected on radiological imaging in head and neck cancer: Head and Neck Cancer International Group consensus recommendations.

Extranodal extension of tumour on histopathology is known to be a negative prognostic factor in head and neck cancer. Compelling evidence suggests that extranodal extension detected on radiological imaging is also a negative prognostic factor. Furthermore, if imaging detected extranodal extension could be identified reliably before the start of treatment, it could be used to guide treatment selection, as patients might be better managed with non-surgical approaches to avoid the toxicity and cost of trimodality therapy (surgery, chemotherapy, and radiotherapy together). There are many aspects of imaging detected extranodal extension that remain unresolved or are without consensus, such as the criteria to best diagnose them and the associated terminology. The Head and Neck Cancer International Group conducted a five-round modified Delphi process with a group of 18 international radiology experts, representing 14 national clinical research groups. We generated consensus recommendations on the terminology and diagnostic criteria for imaging detected extranodal extension to harmonise clinical practice and research. These recommendations have been endorsed by 19 national and international organisations, representing 34 countries. We propose a new classification system to aid diagnosis, which was supported by most of the participating experts over existing systems, and which will require validation in the future. Additionally, we have created an online educational resource for grading imaging detected extranodal extensions.

Remembering the Work of Phillip L. Geissler: A Coda to His Scientific Trajectory.

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers.

Lessons learnt from an aggressive tumour masquerading as a neuropathic heel ulcer: a case report.

Cutaneous malignant melanoma (cMM) can develop at any site, but one-third of cases primarily affect the lower extremities, with ankle and foot lesions representing 3-15% of all cases. However, cMM may become a clinical conundrum when it presents as chronic ulceration that is clinically indiscernible from other lower extremity ulcers in patients with diabetes. We present the case of a 71-year-old female patient with a longstanding history of diabetes, hypertension, obesity, chronic kidney disease and heart failure who presented to our hospital with a fungating heel ulcer. The lesion was initially managed in another hospital as a neuropathic diabetic foot ulcer (DFU), treated by multiple local wound debridement. However, the ulcer progressed into a fungating heel lesion that interfered with the patient's mobility and quality of life. Consequently, the patient was referred to our specialist diabetic foot service for further management. Excisional biopsy of the lesion disclosed a cMM. Positron emission tomography/computed-tomography scanning revealed hypermetabolic ipsilateral inguinal lymphadenopathy, and a right cerebral metastasis for which palliative chemotherapy was initiated. Immunotherapy was considered, but the patient died before it was started. Atypical foot ulcers in patients with diabetes warrant a careful diagnostic approach, especially for recalcitrant cutaneous lesions not responding to standard therapies. Conscientious management, without undue delay in obtaining a histopathological diagnosis, might lead to early diagnosis of melanoma and potentially more favourable outcomes. This case highlights the importance of consideration of atypical foot lesions, in general practice in addition to referral centres, to try to identify alarming features and act accordingly.

Non-Repetitive Scanning LiDAR Sensor for Robust 3D Point Cloud Registration in Localization and Mapping Applications.

Three-dimensional point cloud registration is a fundamental task for localization and mapping in autonomous navigation applications. Over the years, registration algorithms have evolved; nevertheless, several challenges still remain. Recently, non-repetitive scanning LiDAR sensors have emerged as a promising 3D data acquisition tool. However, the feasibility of this type of sensor to leverage robust point cloud registration still needs to be ascertained. In this paper, we explore the feasibility of one such LiDAR sensor with a Spirograph-type non-repetitive scanning pattern for robust 3D point cloud registration. We first characterize the data of this unique sensor; then, utilizing these results, we propose a new 3D point cloud registration method that exploits the unique scanning pattern of the sensor to register successive 3D scans. The characteristic equations of the unique scanning pattern, determined during the characterization phase, are used to reconstruct a perfect scan at the target distance. The real scan is then compared with this reconstructed scan to extract objects in the scene. The displacement of these extracted objects with respect to the center of the unique scanning pattern is compared in successive scans to determine the transformations that are then used to register these scans. The proposed method is evaluated on two real and different datasets and compared with other state-of-the-art registration methods. After analysis, the performance (localization and mapping results) of the proposed method is further improved by adding constraints like loop closure and employing a Curve Fitting Derivative Filter (CFDT) to better estimate the trajectory. The results clearly demonstrate the suitability of the sensor for such applications. The proposed method is found to be comparable with other methods in terms of accuracy but surpasses them in performance in terms of processing time.

Buds and Bugs: A Fascinating Tale of Gut Microbiota and Cannabis in the Fight against Cancer.

Emerging research has revealed a complex bidirectional interaction between the gut microbiome and cannabis. Preclinical studies have demonstrated that the gut microbiota can significantly influence the pharmacological effects of cannabinoids. One notable finding is the ability of the gut microbiota to metabolise cannabinoids, including Δ9-tetrahydrocannabinol (THC). This metabolic transformation can alter the potency and duration of cannabinoid effects, potentially impacting their efficacy in cancer treatment. Additionally, the capacity of gut microbiota to activate cannabinoid receptors through the production of secondary bile acids underscores its role in directly influencing the pharmacological activity of cannabinoids. While the literature reveals promising avenues for leveraging the gut microbiome-cannabis axis in cancer therapy, several critical considerations must be accounted for. Firstly, the variability in gut microbiota composition among individuals presents a challenge in developing universal treatment strategies. The diversity in gut microbiota may lead to variations in cannabinoid metabolism and treatment responses, emphasising the need for personalised medicine approaches. The growing interest in understanding how the gut microbiome and cannabis may impact cancer has created a demand for up-to-date, comprehensive reviews to inform researchers and healthcare practitioners. This review provides a timely and invaluable resource by synthesizing the most recent research findings and spotlighting emerging trends. A thorough examination of the literature on the interplay between the gut microbiome and cannabis, specifically focusing on their potential implications for cancer, is presented in this review to devise innovative and effective therapeutic strategies for managing cancer.

The Neurotherapeutic Arsenal in Cannabis sativa: Insights into Anti-Neuroinflammatory and Neuroprotective Activity and Potential Entourage Effects.

Cannabis, renowned for its historical medicinal use, harbours various bioactive compounds-cannabinoids, terpenes, and flavonoids. While major cannabinoids like delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) have received extensive scrutiny for their pharmacological properties, emerging evidence underscores the collaborative interactions among these constituents, suggesting a collective therapeutic potential. This comprehensive review explores the intricate relationships and synergies between cannabinoids, terpenes, and flavonoids in cannabis. Cannabinoids, pivotal in cannabis's bioactivity, exhibit well-documented analgesic, anti-inflammatory, and neuroprotective effects. Terpenes, aromatic compounds imbuing distinct flavours, not only contribute to cannabis's sensory profile but also modulate cannabinoid effects through diverse molecular mechanisms. Flavonoids, another cannabis component, demonstrate anti-inflammatory, antioxidant, and neuroprotective properties, particularly relevant to neuroinflammation. The entourage hypothesis posits that combined cannabinoid, terpene, and flavonoid action yields synergistic or additive effects, surpassing individual compound efficacy. Recognizing the nuanced interactions is crucial for unravelling cannabis's complete therapeutic potential. Tailoring treatments based on the holistic composition of cannabis strains allows optimization of therapeutic outcomes while minimizing potential side effects. This review underscores the imperative to delve into the intricate roles of cannabinoids, terpenes, and flavonoids, offering promising prospects for innovative therapeutic interventions and advocating continued research to unlock cannabis's full therapeutic potential within the realm of natural plant-based medicine.

Oversaturating Liquid Interfaces with Nanoparticle-Surfactants.

Assemblies of nanoparticles at liquid interfaces hold promise as dynamic "active" systems when there are convenient methods to drive the system out of equilibrium via crowding. To this end, we show that oversaturated assemblies of charged nanoparticles can be realized and held in that state with an external electric field. Upon removal of the field, strong interparticle repulsive forces cause a high in-plane electrostatic pressure that is released in an explosive emulsification. We quantify the packing of the assembly as it is driven into the oversaturated state under an applied electric field. Physiochemical conditions substantially affect the intensity of the induced explosive emulsification, underscoring the crucial role of interparticle electrostatic repulsion.

Addressing the impact of high glucose microenvironment on the immunosuppressive characteristics of human mesenchymal stem cells.

Mesenchymal stem cells (MSCs) are a therapeutically efficient type of stem cells validated by their ability to treat many inflammatory and chronic conditions. The biological and therapeutic characteristics of MSCs can be modified depending on the type of microenvironment at the site of transplantation. Diabetes mellitus (DM) is a commonly diagnosed metabolic disease characterized by hyperglycemia, which alters over time the cellular and molecular functions of many cells and causes their damage. Hyperglycemia can also impact the success rate of MSCs transplantation; therefore, it is extremely significant to investigate the effect of high glucose on the biological and therapeutic attributes of MSCs, particularly their immunomodulatory abilities. Thus, in this study, we explored the effect of high glucose on the immunosuppressive characteristics of human adipose tissue-derived mesenchymal stem cells (hAD-MSCs). We found that hAD-MSCs cultured in high glucose lost their immunomodulatory abilities and became detectable by immune cells. The decline in the immunosuppressive capabilities of hAD-MSCs was mediated by significant decrease in the levels of IDO, IL-10, and complement factor H and substantial increase in the activity of immunoproteasome. The protein levels of AMP-activated protein kinase (AMPK) and phosphofructokinase-1 (PFK-1), which are integral regulators of glycolysis, revealed a marked decline in high glucose exposed MSCs. The findings of our study indicated the possibility of immunomodulatory shift in MSCs after being cultured in high glucose, which can be translationally employed to explain their poor survival and short-lived therapeutic outcomes in diabetic patients.

Boundary design regulates the diffusion of active matter in heterogeneous environments.

Physical boundaries play a key role in governing the overall transport properties of nearby self-propelled particles. In this work, we develop dispersion theories and conduct Brownian dynamics simulations to predict the coupling between surface accumulation and effective diffusivity of active particles in boundary-rich media. We focus on three models that are well-understood for passive systems: particle transport in (i) an array of fixed volume-excluding obstacles; (ii) a pore with spatially heterogeneous width; and (iii) a tortuous path with kinks and corners. While the impact of these entropic barriers on passive particle transport is well established, we find that these classical models of porous media flows break down due to the unique interplay between activity and the microstructure of the internal geometry. We study the activity-induced slowdown of effective diffusivity by formulating a Smoluchowski description of long-time self diffusivity which contains contributions from the density and fluctuation fields of the active particles. Particle-based and finite element simulations corroborate this perspective and reveal important nonequilibrium considerations of active transport.

Development and validation of a predictive models for predicting the cardiac events within one year for patients underwent percutaneous coronary intervention procedure at IJN.

PURPOSE: Percutaneous coronary intervention (PCI) is a common treatment modality for coronary artery disease. Accurate prediction of patients at risk for complications and hospital readmission after PCI could improve the overall clinical management. We aimed to develop and validate predictive models to predict any cardiac event within a year post PCI procedure. METHODS: This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared. RESULTS: The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720). CONCLUSIONS: This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.

Outcomes of Pediatric Patients With Metastatic Ewing Sarcoma Treated With Interval Compression.

BACKGROUND: Interval compression (IC), a regimen of alternating vincristine/doxorubicin/cyclophosphamide and ifosfamide/etoposide every 2 weeks, improves survival for localized Ewing sarcoma (ES), with uncertain effect on metastatic disease. MATERIALS AND METHODS: We reviewed the charts of pediatric patients with metastatic ES treated with IC at our center between January 2013 and March 2020. We calculated event-free survival and overall survival (OS) and used log-rank tests for univariate comparisons. RESULTS: We identified 34 patients 2.7 to 17.1 years of age (median: 11.6 y). Twenty-six patients (76%) had pulmonary metastases, and 14 (41%) had extrapulmonary metastases. All patients received local control therapy: surgery only (n=7, 21%), radiotherapy only (n=18, 53%), or both (n=9, 26%). The estimated 3-year OS and event-free survival were 62%±9% and 39%±9%, respectively. Patients with pulmonary-only and extrapulmonary metastasis had a 3-year OS of 88%±8% and 27%±13%, respectively ( P =0.0074). Age group (above vs. below 12 y), or primary tumor site did not affect survival, but local control therapy did (surgery only, 83%±15%; combined surgery and radiation, 30%±18%; radiation only, 15%±10%; P =0.048). CONCLUSION: IC yielded similar outcomes for patients with metastatic ES to other reported regimens. We suggest including this approach to other blocks of therapy.

Phase coexistence implications of violating Newton's third law.

Newton's third law, action = reaction, is a foundational statement of classical mechanics. However, in natural and living systems, this law appears to be routinely violated for constituents interacting in a nonequilibrium environment. Here, we use computer simulations to explore the macroscopic phase behavior implications of breaking microscopic interaction reciprocity for a simple model system. We consider a binary mixture of attractive particles and introduce a parameter that is a continuous measure of the degree to which interaction reciprocity is broken. In the reciprocal limit, the species are indistinguishable, and the system phase separates into domains with distinct densities and identical compositions. Increasing nonreciprocity is found to drive the system to explore a rich assortment of phases, including phases with strong composition asymmetries and three-phase coexistence. Many of the states induced by these forces, including traveling crystals and liquids, have no equilibrium analogs. By mapping the complete phase diagram for this model system and characterizing these unique phases, our findings offer a concrete path forward toward understanding how nonreciprocity shapes the structures found in living systems and how this might be leveraged in the design of synthetic materials.

Tuning nonequilibrium phase transitions with inertia.

In striking contrast to equilibrium systems, inertia can profoundly alter the structure of active systems. Here, we demonstrate that driven systems can exhibit effective equilibrium-like states with increasing particle inertia, despite rigorously violating the fluctuation-dissipation theorem. Increasing inertia progressively eliminates motility-induced phase separation and restores equilibrium crystallization for active Brownian spheres. This effect appears to be general for a wide class of active systems, including those driven by deterministic time-dependent external fields, whose nonequilibrium patterns ultimately disappear with increasing inertia. The path to this effective equilibrium limit can be complex, with finite inertia sometimes acting to accentuate nonequilibrium transitions. The restoration of near equilibrium statistics can be understood through the conversion of active momentum sources to passive-like stresses. Unlike truly equilibrium systems, the effective temperature is now density dependent, the only remnant of the nonequilibrium dynamics. This density-dependent temperature can in principle introduce departures from equilibrium expectations, particularly in response to strong gradients. Our results provide additional insight into the effective temperature ansatz while revealing a mechanism to tune nonequilibrium phase transitions.

Comparison of acetaminophen, ketamine, or ketorolac versus morphine in the treatment of acute renal colic: A network meta-analysis.

BACKGROUND: Renal colic is a disease in which a calculus obstructs the urinary tract, resulting in severe pain do ureteric peristaltic movements. Other symptoms, such as hematuria, nausea, and vomiting, may accompany the pain. This network meta-analysis aimed to compare the efficacy and safety of different analgesic agents for the treatment of acute renal colic. METHODS: Medline, Embase, and CENTRAL databases were searched. Randomized controlled trials (RCTs) that compared different analgesic agents, either alone or in combination were included. For the management of acute renal colic, analgesic agents were selected based on the current standard medical practice. The medications included intravenous acetaminophen, ketamine, ketorolac, and morphine. This study sought to evaluate the pain score on the visual analog scale (VAS) at 15, 30, and 60 min; adverse events; and the utilization of rescue therapy. The efficacy of different analgesic agents was explored through a frequentist network meta-analysis using the Netmeta statistical package in R software. All treatments were ranked using the Netrank function, yielding P-scores. RESULTS: Twelve RCTs were deemed eligible. As per the P-scores, acetaminophen was the most effective in reducing pain score at 15 min (P-score = 0.74). Ketorolac was the most effective in reducing the pain score at 30 and 60 min (P-score = 0.84) (P-score = 0.99), whereas morphine was the least effective (P-score = 0.07). Moreover, morphine was correlated with the highest odds of adverse events after treatment (P-score = 0.89). Morphine was the most frequently required rescue therapy in cases of suboptimal pain relief (P-score = 0.96). CONCLUSION: This network meta-analysis demonstrated that ketorolac and acetaminophen were the most effective analgesic agents according to the pain score. Morphine showed the highest adverse event profile and the highest rate at which rescue therapy was required for the management of acute renal colic.