Theoretical modeling of collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapy.

In previous work, we focused on the optimal therapeutic strategy with a pair of drugs which are collaterally sensitive to each other, that is, a situation in which evolution of resistance to one drug induces sensitivity to the other, and vice versa. Yoona (Bull Math Biol 8:1-34,Yoon et al. 2018) Here, we have extended this exploration to the optimal strategy with a collaterally sensitive drug sequence of an arbitrary length, N. To explore this, we have developed a dynamical model of sequential drug therapies with N drugs. In this model, tumor cells are classified as one of N subpopulations represented as [Formula: see text]. Each subpopulation, [Formula: see text], is resistant to '[Formula: see text]' and each subpopulation, [Formula: see text] (or [Formula: see text], if [Formula: see text]), is sensitive to it, so that [Formula: see text] increases under '[Formula: see text]' as it is resistant to it, and after drug-switching, decreases under '[Formula: see text]' as it is sensitive to that drug(s). Similar to our previous work examining optimal therapy with two drugs, we found that there is an initial period of time in which the tumor is 'shaped' into a specific makeup of each subpopulation, at which time all the drugs are equally effective ([Formula: see text]). After this shaping period, all the drugs are quickly switched with duration relative to their efficacy in order to maintain each subpopulation, consistent with the ideas underlying adaptive therapy. West(Canver Res 80(7):578-589Gatenby et al. 2009) and Gatenby (Cancer Res 67(11):4894-4903West et al. 2020). Additionally, we have developed methodologies to administer the optimal regimen under clinical or experimental situations in which no drug parameters and limited information of trackable populations data (all the subpopulations or only total population) are known. The therapy simulation based on these methodologies showed consistency with the theoretical effect of optimal therapy .

The 2019 mathematical oncology roadmap.

Whether the nom de guerre is Mathematical Oncology, Computational or Systems Biology, Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is no denying that mathematics continues to play an increasingly prominent role in cancer research. Mathematical Oncology-defined here simply as the use of mathematics in cancer research-complements and overlaps with a number of other fields that rely on mathematics as a core methodology. As a result, Mathematical Oncology has a broad scope, ranging from theoretical studies to clinical trials designed with mathematical models. This Roadmap differentiates Mathematical Oncology from related fields and demonstrates specific areas of focus within this unique field of research. The dominant theme of this Roadmap is the personalization of medicine through mathematics, modelling, and simulation. This is achieved through the use of patient-specific clinical data to: develop individualized screening strategies to detect cancer earlier; make predictions of response to therapy; design adaptive, patient-specific treatment plans to overcome therapy resistance; and establish domain-specific standards to share model predictions and to make models and simulations reproducible. The cover art for this Roadmap was chosen as an apt metaphor for the beautiful, strange, and evolving relationship between mathematics and cancer.

Synaptic efficacy shapes resource limitations in working memory.

Working memory (WM) is limited in its temporal length and capacity. Classic conceptions of WM capacity assume the system possesses a finite number of slots, but recent evidence suggests WM may be a continuous resource. Resource models typically assume there is no hard upper bound on the number of items that can be stored, but WM fidelity decreases with the number of items. We analyze a neural field model of multi-item WM that associates each item with the location of a bump in a finite spatial domain, considering items that span a one-dimensional continuous feature space. Our analysis relates the neural architecture of the network to accumulated errors and capacity limitations arising during the delay period of a multi-item WM task. Networks with stronger synapses support wider bumps that interact more, whereas networks with weaker synapses support narrower bumps that are more susceptible to noise perturbations. There is an optimal synaptic strength that both limits bump interaction events and the effects of noise perturbations. This optimum shifts to weaker synapses as the number of items stored in the network is increased. Our model not only provides a circuit-based explanation for WM capacity, but also speaks to how capacity relates to the arrangement of stored items in a feature space.

Crystal Structures of KPC-2 and SHV-1 ß-Lactamases in Complex with the Boronic Acid Transition State Analog S02030.

Resistance to expanded-spectrum cephalosporins and carbapenems has rendered certain strains of Klebsiella pneumoniae the most problematic pathogens infecting patients in the hospital and community. This broad-spectrum resistance to ß-lactamases emerges in part via the expression of KPC-2 and SHV-1 ß-lactamases and variants thereof. KPC-2 carbapenemase is particularly worrisome, as the genetic determinant encoding this ß-lactamase is rapidly spread via plasmids. Moreover, KPC-2, a class A enzyme, is difficult to inhibit with mechanism-based inactivators (e.g., clavulanate). In order to develop new ß-lactamase inhibitors (BLIs) to add to the limited available armamentarium that can inhibit KPC-2, we have structurally probed the boronic acid transition state analog S02030 for its inhibition of KPC-2 and SHV-1. S02030 contains a boronic acid, a thiophene, and a carboxyl triazole moiety. We present here the 1.54- and 1.87-Å resolution crystal structures of S02030 bound to SHV-1 and KPC-2 ß-lactamases, respectively, as well as a comparative analysis of the S02030 binding modes, including a previously determined S02030 class C ADC-7 ß-lactamase complex. S02030 is able to inhibit vastly different serine ß-lactamases by interacting with the conserved features of these active sites, which includes (i) forming the bond with catalytic serine via the boron atom, (ii) positioning one of the boronic acid oxygens in the oxyanion hole, and (iii) utilizing its amide moiety to make conserved interactions across the width of the active site. In addition, S02030 is able to overcome more distantly located structural differences between the ß-lactamases. This unique feature is achieved by repositioning the more polar carboxyl-triazole moiety, generated by click chemistry, to create polar interactions as well as reorient the more hydrophobic thiophene moiety. The former is aided by the unusual polar nature of the triazole ring, allowing it to potentially form a unique C-H…O 2.9-Å hydrogen bond with S130 in KPC-2.

Chitosan bioactive glass scaffolds for in vivo subcutaneous implantation, toxicity assessment, and diabetic wound healing upon animal model.

This study aims to develop chitosan-bioactive glass (BG) scaffolds for diabetic wound healing, toxicity valuation, and subcutaneous implantation in animals for biocompatibility assessment. The scaffolds were prepared by lyophilization technique. In specific BG without sodium (Na), composited with chitosan for better biological activities. The equipped scaffolds were studied for their physiochemical, biological, in vitro and in vivo performances. The chitosan and chitosan-BG (Na free) scaffolds show reliable biocompatibility, cytocompatibility, anti-oxidant, and tissue regeneration. The biocompatibility, toxicity assessments, and diabetic skin wound healing experiments were examined through in vivo studies using Sprague Dawley rats. The extracted tissue samples were analyzed using hematoxylin-eosin- (H and E) and Masson's trichrome staining. Further, tissue excised after scaffold implantation declared non-toxic, non-allergic, and anti-inflammatory nature of chitosan scaffolds. Moreover, the total ribonucleic acid (RNA) expression levels were measured using reverse transcription-polymerase chain reaction (RT-PCR) for the scaffolds against vascular endothelial growth factor (VEGF), and collagen type one (Col-1) primers. Admirably, the scaffolds achieved the best level of skin wound healing via tissue regeneration by increasing epithetical cell formation and collagen deposition. Thus, the biocompatibility, non-toxicity, anti-inflammatory, and wound healing efficiency proved that the chitosan-BG (Na free) scaffold can be readily substantial for wound healing.

A low-cost, open-source evolutionary bioreactor and its educational use.

A morbidostat is a bioreactor that uses antibiotics to control the growth of bacteria, making it well-suited for studying the evolution of antibiotic resistance. However, morbidostats are often too expensive to be used in educational settings. Here we present a low-cost morbidostat called the EVolutionary biorEactor (EVE) that can be built by students with minimal engineering and programming experience. We describe how we validated EVE in a real classroom setting by evolving replicate Escherichia coli populations under chloramphenicol challenge, thereby enabling students to learn about bacterial growth and antibiotic resistance.

Genomic heterogeneity underlies multidrug resistance in Pseudomonas aeruginosa: A population-level analysis beyond susceptibility testing.

BACKGROUND: Pseudomonas aeruginosa is a persistent and difficult-to-treat pathogen in many patients, especially those with Cystic Fibrosis (CF). Herein, we describe a longitudinal analysis of a series of multidrug resistant (MDR) P. aeruginosa isolates recovered in a 17-month period, from a young female CF patient who underwent double lung transplantation. Our goal was to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence evolution over time. METHODS: Twenty-two sequential P. aeruginosa isolates were obtained within a 17-month period, before and after a double-lung transplant. At the end of the study period, antimicrobial susceptibility testing, whole genome sequencing (WGS), phylogenetic analyses and RNAseq were performed in order to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence changes over time. RESULTS: The majority of isolates were resistant to almost all tested antibiotics. A phylogenetic reconstruction revealed 3 major clades representing a genotypically and phenotypically heterogeneous population. The pattern of mutation accumulation and variation of gene expression suggested that a group of closely related strains was present in the patient prior to transplantation and continued to change throughout the course of treatment. A trend toward accumulation of mutations over time was observed. Different mutations in the DNA mismatch repair gene mutL consistent with a hypermutator phenotype were observed in two clades. RNAseq performed on 12 representative isolates revealed substantial differences in the expression of genes associated with antibiotic resistance and virulence traits. CONCLUSIONS: The overwhelming current practice in the clinical laboratories setting relies on obtaining a pure culture and reporting the antibiogram from a few isolated colonies to inform therapy decisions. Our analyses revealed significant underlying genomic heterogeneity and unpredictable evolutionary patterns that were independent of prior antibiotic treatment, highlighting the need for comprehensive sampling and population-level analysis when gathering microbiological data in the context of CF P. aeruginosa chronic infection. Our findings challenge the applicability of antimicrobial stewardship programs based on single-isolate resistance profiles for the selection of antibiotic regimens in chronic infections such as CF.

UV-C tower for point-of-care decontamination of filtering facepiece respirators.

BACKGROUND: Filtering facepiece respirators (FFR) are critical for protecting essential personnel and limiting the spread of disease. Due to the current COVID-19 pandemic, FFR supplies are dwindling in many health systems, necessitating re-use of potentially contaminated FFR. Multiple decontamination solutions have been developed to meet this pressing need, including systems designed for bulk decontamination of FFR using vaporous hydrogen peroxide or ultraviolet-C (UV-C) radiation. However, the large scale on which these devices operate may not be logistically practical for small or rural health care settings or for ad hoc use at points-of-care. METHODS: Here, we present the Synchronous UV Decontamination System, a novel device for rapidly deployable, point-of-care decontamination using UV-C germicidal irradiation. We designed a compact, easy-to-use device capable of delivering over 2 J cm2 of UV-C radiation in one minute. RESULTS: We experimentally tested Synchronous UV Decontamination System' microbicidal capacity and found that it eliminates near all virus from the surface of tested FFRs, with less efficacy against pathogens embedded in the inner layers of the masks. CONCLUSIONS: This short decontamination time should enable care-providers to incorporate decontamination of FFR into a normal donning and doffing routine following patient encounters.

UV decontamination of personal protective equipment with idle laboratory biosafety cabinets during the COVID-19 pandemic.

Personal protective equipment (PPE) is crucially important to the safety of both patients and medical personnel, particularly in the event of an infectious pandemic. As the incidence of Coronavirus Disease 2019 (COVID-19) increases exponentially in the United States and many parts of the world, healthcare provider demand for these necessities is currently outpacing supply. In the midst of the current pandemic, there has been a concerted effort to identify viable ways to conserve PPE, including decontamination after use. In this study, we outline a procedure by which PPE may be decontaminated using ultraviolet (UV) radiation in biosafety cabinets (BSCs), a common element of many academic, public health, and hospital laboratories. According to the literature, effective decontamination of N95 respirator masks or surgical masks requires UV-C doses of greater than 1 Jcm-2, which was achieved after 4.3 hours per side when placing the N95 at the bottom of the BSCs tested in this study. We then demonstrated complete inactivation of the human coronavirus NL63 on N95 mask material after 15 minutes of UV-C exposure at 61 cm (232 µWcm-2). Our results provide support to healthcare organizations looking for methods to extend their reserves of PPE.

A screening life cycle metric to benchmark the environmental sustainability of waste management systems.

The disposal of municipal solid waste (MSW) can lead to significant environmental burdens. The implementation of effective waste management practices, however, requires the ability to benchmark alternative systems from an environmental sustainability perspective. Existing metrics--such as recycling and generation rates, or the emissions of individual pollutants--often are not goal-oriented, are not readily comparable, and may not provide insight into the most effective options for improvement. Life cycle assessment (LCA) is an effective approach to quantify and compare systems, but full LCA comparisons typically involve significant expenditure of resources and time. In this work we develop a metric called the Resource Conservation Efficiency (RCE) that is based on a screening-LCA approach, and that can be used to rapidly and effectively benchmark (on a screening level) the ecological sustainability of waste management practices across multiple locations. We first demonstrate that this measure is an effective proxy by comparing RCE results with existing LCA inventory and impact assessment methods. We then demonstrate the use of the RCE metric by benchmarking the sustainability of waste management practices in two U.S. cities: San Francisco and Honolulu. The results show that while San Francisco does an excellent job recovering recyclable materials, adding a waste to energy (WTE) facility to their infrastructure would most beneficially impact the environmental performance of their waste management system. Honolulu would achieve the greatest gains by increasing the capture of easily recycled materials not currently being recovered. Overall results also highlight how the RCE metric may be used to provide insight into effective actions cities can take to boost the environmental performance of their waste management practices.

Structural studies and molecular dynamics simulations suggest a processive mechanism of exolytic lytic transglycosylase from Campylobacter jejuni.

The bacterial soluble lytic transglycosylase (LT) breaks down the peptidoglycan (PG) layer during processes such as cell division. We present here crystal structures of the soluble LT Cj0843 from Campylobacter jejuni with and without bulgecin A inhibitor in the active site. Cj0843 has a doughnut shape similar but not identical to that of E. coli SLT70. The C-terminal catalytic domain is preceded by an L-domain, a large helical U-domain, a flexible linker, and a small N-terminal NU-domain. The flexible linker allows the NU-domain to reach over and complete the circular shape, using residues conserved in the Epsilonproteobacteria LT family. The inner surface of the Cj0843 doughnut is mostly positively charged including a pocket that has 8 Arg/Lys residues. Molecular dynamics simulations with PG strands revealed a potential functional role for this pocket in anchoring the negatively charged terminal tetrapeptide of the PG during several steps in the reaction including homing and aligning the PG strand for exolytic cleavage, and subsequent ratcheting of the PG strand to enhance processivity in degrading PG strands.

Inhibition of Klebsiella ß-Lactamases (SHV-1 and KPC-2) by Avibactam: A Structural Study.

ß-Lactamase inhibition is an important clinical strategy in overcoming ß-lactamase-mediated resistance to ß-lactam antibiotics in Gram negative bacteria. A new ß-lactamase inhibitor, avibactam, is entering the clinical arena and promising to be a major step forward in our antibiotic armamentarium. Avibactam has remarkable broad-spectrum activity in being able to inhibit classes A, C, and some class D ß-lactamases. We present here structural investigations into class A ß-lactamase inhibition by avibactam as we report the crystal structures of SHV-1, the chromosomal penicillinase of Klebsiella pneumoniae, and KPC-2, an acquired carbapenemase found in the same pathogen, complexed with avibactam. The 1.80 Å KPC-2 and 1.42 Å resolution SHV-1 ß-lactamase avibactam complex structures reveal avibactam covalently bonded to the catalytic S70 residue. Analysis of the interactions and chair-shaped conformation of avibactam bound to the active sites of KPC-2 and SHV-1 provides structural insights into recently laboratory-generated amino acid substitutions that result in resistance to avibactam in KPC-2 and SHV-1. Furthermore, we observed several important differences in the interactions with amino acid residues, in particular that avibactam forms hydrogen bonds to S130 in KPC-2 but not in SHV-1, that can possibly explain some of the different kinetic constants of inhibition. Our observations provide a possible reason for the ability of KPC-2 ß-lactamase to slowly desulfate avibactam with a potential role for the stereochemistry around the N1 atom of avibactam and/or the presence of an active site water molecule that could aid in avibactam desulfation, an unexpected consequence of novel inhibition chemistry.

Options for management of municipal solid waste in New York City: a preliminary comparison of health risks and policy implications.

Landfill disposal and waste-to-energy (WTE) incineration remain the two principal options for managing municipal solid waste (MSW). One critical determinant of the acceptability of these options is the different health risks associated with each. In this analysis relying on published data and exposure modeling, we have performed health risk assessments for landfill disposal versus WTE treatment options for the management of New York City's MSW. These are based on the realistic scenario of using a waste transfer station (WTS) in Brooklyn and then transporting the untreated MSW by truck to a landfill in Pennsylvania or using a WTE facility in Brooklyn and then transporting the resultant ash by truck to a landfill in Pennsylvania. The overall results indicate that the individual cancer risks for both options would be considered generally acceptable, although the risk from landfilling is approximately 5 times greater than from WTE treatment; the individual non-cancer health risks for both options would be considered generally unacceptable, although once again the risk from landfilling is approximately 5 times greater than from WTE treatment. If one considers only the population in Brooklyn that would be directly affected by the siting of either a WTS or a WTE facility in their immediate neighborhood, individual cancer and non-cancer health risks for both options would be considered generally acceptable, but risks for the former remain considerably higher than for the latter. These results should be considered preliminary due to several limitations of this study such as: consideration of risks only from inhalation exposures; assumption that only volume and not composition of the waste stream is altered by WTE treatment; reliance on data from the literature rather than actual measurements of the sites considered, assuming comparability of the sites. However, the results of studies such as this, in conjunction with ecological, socioeconomic and equity considerations, should prove useful to environmental managers, regulators, policy makers, community representatives and other stakeholders in making sound and acceptable decisions regarding the optimal handling of MSW.

A hybrid life cycle inventory of nano-scale semiconductor manufacturing.

The manufacturing of modern semiconductor devices involves a complex set of nanoscale fabrication processes that are energy and resource intensive, and generate significant waste. It is important to understand and reduce the environmental impacts of semiconductor manufacturing because these devices are ubiquitous components in electronics. Furthermore, the fabrication processes used in the semiconductor industry are finding increasing application in other products, such as microelectromechanical systems (MEMS), flat panel displays, and photovoltaics. In this work we develop a library of typical gate-to-gate materials and energy requirements, as well as emissions associated with a complete set of fabrication process models used in manufacturing a modern microprocessor. In addition, we evaluate upstream energy requirements associated with chemicals and materials using both existing process life cycle assessment (LCA) databases and an economic input-output (EIO) model. The result is a comprehensive data set and methodology that may be used to estimate and improve the environmental performance of a broad range of electronics and other emerging applications that involve nano and micro fabrication.

Examination of the fate of carbon in waste management systems through statistical entropy and life cycle analysis.

The statistical entropy (SE) function has been developed as a methodology to rapidly benchmark he effectiveness of different waste management systems by determining the level to which specific substances are either concentrated or diluted. Past usage of SE has been confined to metals. In this paper, this method is extended to account for carbon--a key substance of interest Accounting for carbon is complicated by the fact that reactions involving this substance are complex and their products are numerous. Through experiments on carbon-containing emissions from styrene-butadiene rubber (SBR), natural rubber (polyisoprene, IR), and waste tires we demonstrate that a knowledge of carbon-containing species accounting for 90% (by mass) of gaseous emissions is sufficient. Next, we develop an extended SE calculation methodology and apply it to compare carbon flows through two different systems for municipal solid waste (MSW) management (landfills) and waste-to-energy (WTE) facilities. Our results indicate that while landfills perform better on a cursory analysis, they are roughly equal to WTE when carbon flows related to energy generation are accounted for, and underperform by a factor of 3 when considering global warming potential.