A Quantitative Phase Analysis by Neutron Diffraction of Conventional and Advanced Aluminum Alloys Thermally Conditioned for Elevated-Temperature Applications.

As the issue of climate change becomes more prevalent, engineers have focused on developing lightweight Al alloys capable of increasing the power density of powertrains. The characterization of these alloys has been focused on mechanical properties and less on the fundamental response of microstructures to achieve these properties. Therefore, this study assesses the quality of the microstructure of two high-temperature Al alloys (A356 + 3.5RE and Al-8Ce-10Mg), comparing them to T6 A356. These alloys underwent thermal conditioning at 250 and 300 °C for 200 h. Time-of-flight neutron diffraction experiments were performed before and after conditioning. The phase evolution was quantified using Rietveld refinement. It was found that the Si phase grows significantly (13-24%) in T6 A356, A356 + 3.5RE, and T6 A356 + 3.5RE alloys, which is typically correlated with a reduction in mechanical properties. Subjecting the A356 3.5RE alloy to a T6 heat treatment stabilizes the orthorhombic Al4Ce3Si6 and monoclinic ß-Al5FeSi phases, making them resistant to thermal conditioning. These two phases are known for enhancing mechanical properties. Additionally, the T6 treatment reduced the vol.% of the cubic Al20CeTi2 and hexagonal á´¨-Al9FeSi3Mg5 phases by 13% and 23%, respectively. These phases have detrimental mechanical properties. The Al-8Ce-10Mg alloy cubic ß-Al3Mg2 phase showed significant growth (82-101%) in response to conditioning, while the orthorhombic Al11Ce3 phase remained stable. The growth of the beta phase is known to decrease the mechanical properties of this alloy. These efforts give valuable insight into how these alloys will perform and evolve in demanding high-temperature environments.

The phospholipase A of Neisseria gonorrhoeae lyses eukaryotic membranes and is necessary for survival in neutrophils and cervical epithelial cells.

Contact-dependent hemolysins are virulence factors in a number of human pathogens, including Helicobacter pylori, Rickettsia typhi, Bartonella bacilliformis, Mycobacterium tuberculosis, entero-invasive Escherichia coli, and Shigella. Here we demonstrate that Neisseria gonorrhoeae produces an outer membrane protein, phospholipase A, that exhibits contact-dependent lytic activity on host cell membranes. This enzyme can lyse human erythrocytes over a 3-day period, whereas a phospholipase A mutant cannot. We demonstrated phospholipase A activity in the parent strain but not in two, independent phospholipase A mutants. A gene for phospholipase A, pldA (hereafter referred to as pla to avoid confusion with the gene for phospholipase D, pld), is present in all sequenced gonococcal strains. Fluid phase, hemolytic activity assays showed that 25 of 29 gonococcal strains tested had hemolytic activity greater than 50% of the positive control. In support of PLA as a gonococcal outer membrane protein, supernatants from 24-, 48-, and 72-h cultures of N. gonorrhoeae strain 1291 did not contain hemolysin activity, and a monoclonal antibody specific for gonococcal phospholipase A failed to detect the enzyme in these supernatants. The organism must be viable for lysis to occur, and the inclusion of EDTA in the media removes all activity. Our studies have shown that a phospholipase A mutant has significantly reduced survival in human neutrophils and primary human cervical epithelial cells compared to the parent gonococcal strain after 3 h of incubation. Collectively, our data demonstrate that gonococcal PLA lyses host cell membranes, which is important for intracellular survival. IMPORTANCE: Intracellular survival is crucial to the success of Neisseria gonorrhoeae as a human pathogen. Multiple factors contribute to the intracellular survival of gonococci, including the ability to prohibit apoptosis of the epithelial cell the organism invades and mechanisms to evade host innate defense systems. The role of phospholipase A (PLA), an outer membrane protein, is important as it disrupts the host vacuolar and phagolysosomal membranes, preventing the effective delivery of innate immune factors that normally restrict organism growth within human cells. After cell entry, PLA disrupts the integrity of these host cell membranes, allowing the gonococcus to live free within disrupted vacuoles where it pilfers host cell nutrients that enable its survival and replication. A vaccine or drug that could neutralize PLA activity would disrupt the intracellular survival of the gonococcus.

E. coli FtsN coordinates synthesis and degradation of septal peptidoglycan by partitioning between a synthesis track and a denuded glycan track.

The E. coli cell division protein FtsN was proposed to coordinate septal peptidoglycan (sPG) synthesis and degradation to ensure robust cell wall constriction without lethal lesions. Although the precise mechanism remains unclear, previous work highlights the importance of two FtsN domains: the E domain, which interacts with and activates the sPG synthesis complex FtsWIQLB, and the SPOR domain, which binds to denuded glycan (dnG) strands, key intermediates in sPG degradation. Here, we used single-molecule tracking of FtsN and FtsW (a proxy for the sPG synthesis complex FtsWIQLB) to investigate how FtsN coordinates the two opposing processes. We observed dynamic behaviors indicating that FtsN's SPOR domain binds to dnGs cooperatively, which both sequesters the sPG synthesis complex on dnG (termed as the dnG-track) and protects dnGs from degradation by lytic transglycosylases (LTs). The release of the SPOR domain from dnGs leads to activating the sPG synthesis complex on the sPG-track and simultaneously exposing those same dnGs to degradation. Furthermore, FtsN's SPOR domain self-interacts and facilitates the formation of a multimeric sPG synthesis complex on both tracks. The cooperative self-interaction of the SPOR domain creates a sensitive switch to regulate the partitioning of FtsN between the dnG- and sPG-tracks, thereby controlling the balance between sequestered and active populations of the sPG synthesis complex. As such, FtsN coordinates sPG synthesis and degradation in space and time.

Colorectal Cancer Polygenic Risk Score Is Associated With Screening Colonoscopy Findings but Not Follow-Up Outcomes.

Background and Aims: Colorectal cancer (CRC) polygenic risk scores (PRS) may help personalize CRC prevention strategies. We investigated whether an existing PRS was associated with advanced neoplasia (AN) in a population undergoing screening and follow-up colonoscopy. Methods: We evaluated 10-year outcomes in the Cooperative Studies Program #380 screening colonoscopy cohort, which includes a biorepository of selected individuals with baseline AN (defined as CRC or adenoma ≥10 mm or villous histology, or high-grade dysplasia) and matched individuals without AN. A PRS was constructed from 136 prespecified CRC-risk single nucleotide polymorphisms. Multivariate logistic regression was used to evaluate the PRS for associations with AN prevalence at baseline screening colonoscopy or incident AN in participants with at least one follow-up colonoscopy. Results: The PRS was associated with AN risk at baseline screening colonoscopy (P = .004). Participants in the lowest PRS quintile had more than a 70% decreased risk of AN at baseline (odds ratio 0.29, 95% confidence interval 0.14-0.58; P < .001) compared to participants with a PRS in the middle quintile. Using a PRS cut-off of more than the first quintile to indicate need for colonoscopy as primary screening, the sensitivity for detecting AN at baseline is 91.8%. We did not observe a relationship between the PRS and incident AN during follow-up (P = .28). Conclusion: A PRS could identify individuals at low risk for prevalent AN. Ongoing work will determine whether this PRS can identify a subset of individuals at sufficiently low risk who could safely delay or be reassured about noninvasive screening. Otherwise, more research is needed to augment these genetic tools to predict incident AN during long-term follow-up.

Identification of a family of peptidoglycan transpeptidases reveals that Clostridioides difficile requires noncanonical cross-links for viability.

Most bacteria are surrounded by a cell wall that contains peptidoglycan (PG), a large polymer composed of glycan strands held together by short peptide cross-links. There are two major types of cross-links, termed 4-3 and 3-3 based on the amino acids involved. 4-3 cross-links are created by penicillin-binding proteins, while 3-3 cross-links are created by L,D-transpeptidases (LDTs). In most bacteria, the predominant mode of cross-linking is 4-3, and these cross-links are essential for viability, while 3-3 cross-links comprise only a minor fraction and are not essential. However, in the opportunistic intestinal pathogen Clostridioides difficile, about 70% of the cross-links are 3-3. We show here that 3-3 cross-links and LDTs are essential for viability in C. difficile. We also show that C. difficile has five LDTs, three with a YkuD catalytic domain as in all previously known LDTs and two with a VanW catalytic domain, whose function was until now unknown. The five LDTs exhibit extensive functional redundancy. VanW domain proteins are found in many gram-positive bacteria but scarce in other lineages. We tested seven non-C. difficile VanW domain proteins and confirmed LDT activity in three cases. In summary, our findings uncover a previously unrecognized family of PG cross-linking enzymes, assign a catalytic function to VanW domains, and demonstrate that 3-3 cross-linking is essential for viability in C. difficile, the first time this has been shown in any bacterial species. The essentiality of LDTs in C. difficile makes them potential targets for antibiotics that kill C. difficile selectively.

Antifungal heteroresistance causes prophylaxis failure and facilitates breakthrough Candida parapsilosis infections.

Breakthrough fungal infections in patients on antimicrobial prophylaxis during allogeneic hematopoietic cell transplantation (allo-HCT) represent a major and often unexplained cause of morbidity and mortality. Candida parapsilosis is a common cause of invasive candidiasis and has been classified as a high-priority fungal pathogen by the World Health Organization. In high-risk allo-HCT recipients on micafungin prophylaxis, we show that heteroresistance (the presence of a phenotypically unstable, low-frequency subpopulation of resistant cells (~1 in 10,000)) underlies breakthrough bloodstream infections by C. parapsilosis. By analyzing 219 clinical isolates from North America, Europe and Asia, we demonstrate widespread micafungin heteroresistance in C. parapsilosis. Standard antimicrobial susceptibility tests, such as broth microdilution or gradient diffusion assays, which guide drug selection for invasive infections, fail to detect micafungin heteroresistance in C. parapsilosis. To facilitate rapid detection of micafungin heteroresistance in C. parapsilosis, we constructed a predictive machine learning framework that classifies isolates as heteroresistant or susceptible using a maximum of ten genomic features. These results connect heteroresistance to unexplained antifungal prophylaxis failure in allo-HCT recipients and demonstrate a proof-of-principle diagnostic approach with the potential to guide clinical decisions and improve patient care.

Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity.

Objective. Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable better therapy. However, it is challenging to understand which irregular patterns are most effective for different therapeutic applications given the massively high-dimensional parameter space.Approach. Here we applied many irregular stimulation patterns in a single neural circuit to demonstrate how they can enable new dimensions of neural control compared to conventional stimulation, to guide future exploration of novel stimulation patterns in translational settings. We optogenetically excited the septohippocampal circuit with constant-frequency, nested pulse, sinusoidal, and randomized stimulation waveforms, systematically varying their amplitude and frequency parameters.Main results.We first found equal entrainment of hippocampal oscillations: all waveforms provided similar gamma-power increase, whereas no parameters increased theta-band power above baseline (despite the mechanistic role of the medial septum in driving hippocampal theta oscillations). We then compared each of the effects of each waveform on high-dimensional multi-band activity states using dimensionality reduction methods. Strikingly, we found that conventional stimulation drove predominantly 'artificial' (different from behavioral activity) effects, whereas all irregular waveforms induced activity patterns that more closely resembled behavioral activity.Significance. Our findings suggest that irregular stimulation patterns are not useful when the desired mechanism is to suppress or enhance a single frequency band. However, novel stimulation patterns may provide the greatest benefit for neural control applications where entraining a particular mixture of bands (e.g. if they are associated with different symptoms) or behaviorally-relevant activity is desired.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Aluminothermic reduction of CeO2: mechanism of an economical route to aluminum-cerium alloys.

Cerium oxide is a low-value byproduct of rare-earth mining yet constitutes the largest fraction of the rare earth elements. The reduction of cerium oxide by liquid aluminum is proposed as an energy- and cost-efficient route to produce high-strength Al-Ce alloys. This work investigated the mechanism of a multi-step reduction reaction to facilitate the industrial adaptation of the process. Differential scanning calorimetry in combination with time-resolved synchrotron diffraction data uncovered the rate-limiting reaction step as the origin of the reported temperature dependence of reduction efficiency. This is the first in situ study of a metallothermic reaction mechanism and will serve as guidance for cost- and energy efficient industrial process control.

Heteroresistance to piperacillin/tazobactam in Klebsiella pneumoniae is mediated by increased copy number of multiple ß-lactamase genes.

Background: Piperacillin/tazobactam is a ß-lactam/ß-lactamase inhibitor combination with a broad spectrum of activity that is often used as empirical and/or targeted therapy among hospitalized patients. Heteroresistance (HR) is a form of antibiotic resistance in which a minority population of resistant cells coexists with a majority susceptible population that has been found to be a cause of antibiotic treatment failure in murine models. Objectives: To determine the prevalence of HR and mechanisms of HR to piperacillin/tazobactam among Klebsiella pneumoniae bloodstream infection (BSI) isolates. Materials: From July 2018 to June 2021, K. pneumoniae piperacillin/tazobactam-susceptible BSI isolates were collected from two tertiary hospitals in Atlanta, GA, USA. Only first isolates from each patient per calendar year were included. Population analysis profiling (PAP) and WGS were performed to identify HR and its mechanisms. Results: Among 423 K. pneumoniae BSI isolates collected during the study period, 6% (25/423) were found to be HR with a subpopulation surviving above the breakpoint. WGS of HR isolates grown in the presence of piperacillin/tazobactam at concentrations 8-fold that of the MIC revealed copy number changes of plasmid-located ß-lactamase genes blaCTX-M-15, blaSHV33, blaOXA-1 and blaTEM-1 by tandem gene amplification or plasmid copy number increase. Conclusions: Prevalence of HR to piperacillin/tazobactam among bloodstream isolates was substantial. The HR phenotype appears to be caused by tandem amplification of ß-lactamase genes found on plasmids or plasmid copy number increase. This raises the possibility of dissemination of HR through horizontal gene transfer and requires further study.

Identification of a new family of peptidoglycan transpeptidases reveals atypical crosslinking is essential for viability in Clostridioides difficile.

Clostridioides difficile, the leading cause of antibiotic-associated diarrhea, relies primarily on 3-3 crosslinks created by L,D-transpeptidases (LDTs) to fortify its peptidoglycan (PG) cell wall. This is unusual, as in most bacteria the vast majority of PG crosslinks are 4-3 crosslinks, which are created by penicillin-binding proteins (PBPs). Here we report the unprecedented observation that 3-3 crosslinking is essential for viability in C. difficile. We also report the discovery of a new family of LDTs that use a VanW domain to catalyze 3-3 crosslinking rather than a YkuD domain as in all previously known LDTs. Bioinformatic analyses indicate VanW domain LDTs are less common than YkuD domain LDTs and are largely restricted to Gram-positive bacteria. Our findings suggest that LDTs might be exploited as targets for antibiotics that kill C. difficile without disrupting the intestinal microbiota that is important for keeping C. difficile in check.

Theoretical considerations and empirical predictions of the pharmaco- and population dynamics of heteroresistance.

Antibiotics are considered one of the most important contributions to clinical medicine in the last century. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulation models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend that the definition of heteroresistance should include a consideration of the rate of return to susceptibility.

Identification of Clostridioides difficile mutants with increased daptomycin resistance.

Daptomycin is a cyclic lipopeptide antibiotic used to treat infections caused by some Gram-positive bacteria. Daptomycin disrupts synthesis of the peptidoglycan (PG) cell wall by inserting into the cytoplasmic membrane and binding multiple forms of the undecaprenyl carrier lipid required for PG synthesis. Membrane insertion requires phosphatidylglycerol, so studies of daptomycin can provide insight into assembly and maintenance of the cytoplasmic membrane. Here, we studied the effects of daptomycin on Clostridioides difficile, the leading cause of healthcare-associated diarrhea. We observed that growth of C. difficile strain R20291 in the presence of sub-MIC levels of daptomycin resulted in a chaining phenotype, minicell formation, and lysis-phenotypes broadly consistent with perturbation of membranes and PG synthesis. We also selected for and characterized eight mutants with elevated daptomycin resistance. The mutations in these mutants were mapped to four genes: cdsA (cdr20291_2041), ftsH2 (cdr20291_3396), esrR (cdr20291_1187), and draS (cdr20291_2456). Of these four genes, only draS has been characterized previously. Follow-up studies indicate these mutations confer daptomycin resistance by two general mechanisms: reducing the amount of phosphatidylglycerol in the cytoplasmic membrane (cdsA) or altering the regulation of membrane processes (ftsH2, esrR, and draS). Thus, the mutants described here provide insights into phospholipid synthesis and identify signal transduction systems involved in cell envelope biogenesis and stress response in C. difficile. IMPORTANCE: C. difficile is the leading cause of healthcare-associated diarrhea and is a threat to public health due to the risk of recurrent infections. Understanding biosynthesis of the atypical cell envelope of C. difficile may provide insight into novel drug targets to selectively inhibit C. difficile. Here, we identified mutations that increased daptomycin resistance and allowed us to better understand phospholipid synthesis, cell envelope biogenesis, and stress response in C. difficile.

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset.

Supplemental material is available for this article.

Color constancy in real-world settings.

Color constancy denotes the ability to assign a particular and stable color percept to an object, irrespective of its surroundings and illumination. The light reaching the eye confounds illumination and spectral reflectance of the object, making the recovery of constant object color an ill-posed problem. How good the visual system is at accomplishing this task is still a matter of heated debate, despite more than a 100 years of research. Depending on the laboratory task and the specific cues available to observers, color constancy was found to be at levels ranging between 15% and 80%, which seems incompatible with the relatively stable color appearance of objects around us and the consistent usage of color names in real life. Here, we show close-to-perfect color constancy using real objects in a natural task and natural environmental conditions, chosen to mimic the role of color constancy in everyday life. Participants had to identify the color of a (non-present) item familiar to them in an office room under five different experimental illuminations. They mostly selected the same colored Munsell chip as their match to the absent object, even though the light reaching the eye in each case differed substantially. Our results demonstrate that color constancy under ideal conditions in the real world can indeed be exceptionally good. We found it to be as good as visual memory permits and not generally compromised by sensory uncertainty.

A machine learning approach for real-time cortical state estimation.

Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.

Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement.

Multidrug-resistant organism (MDRO) colonization is a fundamental challenge in antimicrobial resistance. Limited studies have shown that fecal microbiota transplantation (FMT) can reduce MDRO colonization, but its mechanisms are poorly understood. We conducted a randomized, controlled trial of FMT for MDRO decolonization in renal transplant recipients called PREMIX (NCT02922816). Eleven participants were enrolled and randomized 1:1 to FMT or an observation period followed by delayed FMT if stool cultures were MDRO positive at day 36. Participants who were MDRO positive after one FMT were treated with a second FMT. At last visit, eight of nine patients who completed all treatments were MDRO culture negative. FMT-treated participants had longer time to recurrent MDRO infection versus PREMIX-eligible controls who were not treated with FMT. Key taxa (Akkermansia muciniphila, Alistipes putredinis, Phocaeicola dorei, Phascolarctobacterium faecium, Alistipes species, Mesosutterella massiliensis, Barnesiella intestinihominis, and Faecalibacterium prausnitzii) from the single feces donor used in the study that engrafted in recipients and metabolites such as short-chain fatty acids and bile acids in FMT-responding participants uncovered leads for rational microbiome therapeutic and diagnostic development. Metagenomic analyses revealed a previously unobserved mechanism of MDRO eradication by conspecific strain competition in an FMT-treated subset. Susceptible Enterobacterales strains that replaced baseline extended-spectrum ß-lactamase-producing strains were not detectable in donor microbiota manufactured as FMT doses but in one case were detectable in the recipient before FMT. These data suggest that FMT may provide a path to exploit strain competition to reduce MDRO colonization.

3D U-Net for automated detection of multiple sclerosis lesions: utility of transfer learning from other pathologies.

Background and purpose: Deep learning algorithms for segmentation of multiple sclerosis (MS) plaques generally require training on large datasets. This manuscript evaluates the effect of transfer learning from segmentation of another pathology to facilitate use of smaller MS-specific training datasets. That is, a model trained for detection of one type of pathology was re-trained to identify MS lesions and active demyelination. Materials and methods: In this retrospective study using MRI exams from 149 patients spanning 4/18/2014 to 7/8/2021, 3D convolutional neural networks were trained with a variable number of manually-segmented MS studies. Models were trained for FLAIR lesion segmentation at a single timepoint, new FLAIR lesion segmentation comparing two timepoints, and enhancing (actively demyelinating) lesion segmentation on T1 post-contrast imaging. Models were trained either de-novo or fine-tuned with transfer learning applied to a pre-existing model initially trained on non-MS data. Performance was evaluated with lesionwise sensitivity and positive predictive value (PPV). Results: For single timepoint FLAIR lesion segmentation with 10 training studies, a fine-tuned model demonstrated improved performance [lesionwise sensitivity 0.55 ± 0.02 (mean ± standard error), PPV 0.66 ± 0.02] compared to a de-novo model (sensitivity 0.49 ± 0.02, p = 0.001; PPV 0.32 ± 0.02, p < 0.001). For new lesion segmentation with 30 training studies and their prior comparisons, a fine-tuned model demonstrated similar sensitivity (0.49 ± 0.05) and significantly improved PPV (0.60 ± 0.05) compared to a de-novo model (sensitivity 0.51 ± 0.04, p = 0.437; PPV 0.43 ± 0.04, p = 0.002). For enhancement segmentation with 20 training studies, a fine-tuned model demonstrated significantly improved overall performance (sensitivity 0.74 ± 0.06, PPV 0.69 ± 0.05) compared to a de-novo model (sensitivity 0.44 ± 0.09, p = 0.001; PPV 0.37 ± 0.05, p = 0.001). Conclusion: By fine-tuning models trained for other disease pathologies with MS-specific data, competitive models identifying existing MS plaques, new MS plaques, and active demyelination can be built with substantially smaller datasets than would otherwise be required to train new models.

Theoretical Considerations and Empirical Predictions of the Pharmaco- and Population Dynamics of Heteroresistance.

Antibiotics are considered one of the most important contributions to clinical medicine in the last 100 years. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulations models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend the definition of heteroresistance should include a consideration of the rate of return to susceptibility.