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Annals of Surgical Oncology Jun 2024High-risk programs provide recommendations for surveillance/risk reduction for women at elevated risk for breast cancer development. This study evaluated the impact of...
BACKGROUND
High-risk programs provide recommendations for surveillance/risk reduction for women at elevated risk for breast cancer development. This study evaluated the impact of high-risk surveillance program participation on clinicopathologic breast cancer features at the time of diagnosis.
METHODS
Women followed in the authors' high-risk program (high-risk cohort [HRC]) with a diagnosis of breast cancer from January 2015 to June 2021 were identified and compared with the general population of women undergoing breast cancer surgery at Memorial Sloan Kettering Cancer Center (MSK; general cohort [GC]) during the same period. Patient and tumor factors were collected. Clinicopathologic features were compared between the two cohorts and in a subset of women with a family history of known BRCA mutation.
RESULTS
The study compared 255 women in the HRC with 9342 women in the GC. The HRC patients were slightly older and more likely to be white and have family history than the GC patients. The HRC patients also were more likely to present with DCIS (41 % vs 23 %; p < 0.001), to have smaller invasive tumors (pT1: 100 % vs 77 %; p < 0.001), and to be pN0 (95 % vs 81 %; p < 0.001). The HRC patients had more invasive triple-negative tumors (p = 0.01) and underwent less axillary surgery (p < 0.001), systemic therapy (p < 0.001), and radiotherapy (p = 0.002). Among those with a known BRCA mutation, significantly more women in the HRC underwent screening mammography (75 % vs 40 %; p < 0.001) or magnetic resonance imaging (MRI: 82 % vs 9.9 %; p < 0.001) in the 12 months before diagnosis.
CONCLUSIONS
Women followed in a high-risk screening program have disease diagnosed at an earlier stage and therefore require less-intensive breast cancer treatment than women presenting to a cancer center at the time of diagnosis. Identification of high-risk women and implementation of increased surveillance protocols are vital to improving outcomes.
PubMed: 38949720
DOI: 10.1245/s10434-024-15633-x -
Methods in Molecular Biology (Clifton,... 2024Whole genome sequencing of Mycobacterium tuberculosis complex (MTBC) isolates has been shown to provide accurate predictions for resistance and susceptibility for many...
Whole genome sequencing of Mycobacterium tuberculosis complex (MTBC) isolates has been shown to provide accurate predictions for resistance and susceptibility for many first- and second-line anti-tuberculosis drugs. However, bioinformatic pipelines and mutation catalogs to predict antimicrobial resistances in MTBC isolates are often customized and detailed protocols are difficult to access. Here, we provide a step-by-step workflow for the processing and interpretation of short-read sequencing data and give an overview of available analysis pipelines.
Topics: Mycobacterium tuberculosis; Whole Genome Sequencing; Microbial Sensitivity Tests; Humans; Antitubercular Agents; Computational Biology; Genome, Bacterial; Drug Resistance, Bacterial; Mutation; Tuberculosis
PubMed: 38949712
DOI: 10.1007/978-1-0716-3981-8_18 -
Methods in Molecular Biology (Clifton,... 2024To model complex systems, individual-based models (IBMs), sometimes called "agent-based models" (ABMs), describe a simplification of the system through an adequate...
To model complex systems, individual-based models (IBMs), sometimes called "agent-based models" (ABMs), describe a simplification of the system through an adequate representation of the elements. IBMs simulate the actions and interaction of discrete individuals/agents within a system in order to discover the pattern of behavior that comes from these interactions. Examples of individuals/agents in biological systems are individual immune cells and bacteria that act independently with their own unique attributes defined by behavioral rules. In IBMs, each of these agents resides in a spatial environment and interactions are guided by predefined rules. These rules are often simple and can be easily implemented. It is expected that following the interaction guided by these rules we will have a better understanding of agent-agent interaction as well as agent-environment interaction. Stochasticity described by probability distributions must be accounted for. Events that seldom occur such as the accumulation of rare mutations can be easily modeled.Thus, IBMs are able to track the behavior of each individual/agent within the model while also obtaining information on the results of their collective behaviors. The influence of impact of one agent with another can be captured, thus allowing a full representation of both direct and indirect causation on the aggregate results. This means that important new insights can be gained and hypotheses tested.
Topics: Humans; Drug Resistance, Microbial; Anti-Bacterial Agents; Models, Theoretical; Bacteria; Host-Pathogen Interactions; Drug Resistance, Bacterial; Models, Biological; Computer Simulation
PubMed: 38949704
DOI: 10.1007/978-1-0716-3981-8_10 -
Methods in Molecular Biology (Clifton,... 2024Mathematical models have been used to study the spread of infectious diseases from person to person. More recently studies are developing within-host modeling which...
Mathematical models have been used to study the spread of infectious diseases from person to person. More recently studies are developing within-host modeling which provides an understanding of how pathogens-bacteria, fungi, parasites, or viruses-develop, spread, and evolve inside a single individual and their interaction with the host's immune system.Such models have the potential to provide a more detailed and complete description of the pathogenesis of diseases within-host and identify other influencing factors that may not be detected otherwise. Mathematical models can be used to aid understanding of the global antibiotic resistance (ABR) crisis and identify new ways of combating this threat.ABR occurs when bacteria respond to random or selective pressures and adapt to new environments through the acquisition of new genetic traits. This is usually through the acquisition of a piece of DNA from other bacteria, a process called horizontal gene transfer (HGT), the modification of a piece of DNA within a bacterium, or through. Bacteria have evolved mechanisms that enable them to respond to environmental threats by mutation, and horizontal gene transfer (HGT): conjugation; transduction; and transformation. A frequent mechanism of HGT responsible for spreading antibiotic resistance on the global scale is conjugation, as it allows the direct transfer of mobile genetic elements (MGEs). Although there are several MGEs, the most important MGEs which promote the development and rapid spread of antimicrobial resistance genes in bacterial populations are plasmids and transposons. Each of the resistance-spread-mechanisms mentioned above can be modeled allowing us to understand the process better and to define strategies to reduce resistance.
Topics: Bacteria; Humans; Gene Transfer, Horizontal; Drug Resistance, Microbial; Models, Theoretical; Drug Resistance, Bacterial; Anti-Bacterial Agents; Host-Pathogen Interactions
PubMed: 38949703
DOI: 10.1007/978-1-0716-3981-8_9 -
ELife Jul 2024Tubulin posttranslational modifications (PTMs) modulate the dynamic properties of microtubules and their interactions with other proteins. However, the effects of...
Tubulin posttranslational modifications (PTMs) modulate the dynamic properties of microtubules and their interactions with other proteins. However, the effects of tubulin PTMs were often revealed indirectly through the deletion of modifying enzymes or the overexpression of tubulin mutants. In this study, we directly edited the endogenous tubulin loci to install PTM-mimicking or -disabling mutations and studied their effects on microtubule stability, neurite outgrowth, axonal regeneration, cargo transport, and sensory functions in the touch receptor neurons of . We found that the status of β-tubulin S172 phosphorylation and K252 acetylation strongly affected microtubule dynamics, neurite growth, and regeneration, whereas α-tubulin K40 acetylation had little influence. Polyglutamylation and detyrosination in the tubulin C-terminal tail had more subtle effects on microtubule stability likely by modulating the interaction with kinesin-13. Overall, our study systematically assessed and compared several tubulin PTMs for their impacts on neuronal differentiation and regeneration and established an in vivo platform to test the function of tubulin PTMs in neurons.
Topics: Animals; Tubulin; Protein Processing, Post-Translational; Caenorhabditis elegans; Microtubules; Caenorhabditis elegans Proteins; Acetylation; Axons; Phosphorylation; Nerve Regeneration; Kinesins
PubMed: 38949652
DOI: 10.7554/eLife.94583 -
The Journal of Experimental Medicine Aug 2024Germline activating mutations in STAT3 cause a multi-systemic autoimmune and autoinflammatory condition. By studying a mouse model, Toth et al....
Germline activating mutations in STAT3 cause a multi-systemic autoimmune and autoinflammatory condition. By studying a mouse model, Toth et al. (https://doi.org/10.1084/jem.20232091) propose a role for dysregulated IL-22 production by Th17 cells in causing some aspects of immune-mediated skin inflammation in human STAT3 GOF syndrome.
Topics: STAT3 Transcription Factor; Animals; Humans; Th17 Cells; Skin; Interleukin-22; Interleukins; Gain of Function Mutation; Mice; Inflammation
PubMed: 38949650
DOI: 10.1084/jem.20240849 -
The Journal of Cell Biology Oct 2024The diverse roles of the dynein motor in shaping microtubule networks and cargo transport complicate in vivo analysis of its functions significantly. To address this...
The diverse roles of the dynein motor in shaping microtubule networks and cargo transport complicate in vivo analysis of its functions significantly. To address this issue, we have generated a series of missense mutations in Drosophila Dynein heavy chain. We show that mutations associated with human neurological disease cause a range of defects, including impaired cargo trafficking in neurons. We also describe a novel microtubule-binding domain mutation that specifically blocks the metaphase-anaphase transition during mitosis in the embryo. This effect is independent from dynein's canonical role in silencing the spindle assembly checkpoint. Optical trapping of purified dynein complexes reveals that this mutation only compromises motor performance under load, a finding rationalized by the results of all-atom molecular dynamics simulations. We propose that dynein has a novel function in anaphase progression that depends on it operating in a specific load regime. More broadly, our work illustrates how in vivo functions of motors can be dissected by manipulating their mechanical properties.
Topics: Animals; Dyneins; Anaphase; Drosophila melanogaster; Drosophila Proteins; Microtubules; Molecular Dynamics Simulation; Mutation; Spindle Apparatus; Humans; Mutation, Missense
PubMed: 38949648
DOI: 10.1083/jcb.202310022 -
Molecular Pharmaceutics Jul 2024The plasma protein α-acid glycoprotein (AGP) primarily affects the pharmacokinetics of basic drugs. There are two AGP variants in humans, A and F1*S, exhibiting...
The plasma protein α-acid glycoprotein (AGP) primarily affects the pharmacokinetics of basic drugs. There are two AGP variants in humans, A and F1*S, exhibiting distinct drug-binding selectivity. Elucidation of the drug-binding selectivity of human AGP variants is essential for drug development and personalized drug therapy. Herein, we aimed to establish the contribution of amino acids 112 and 114 of human AGP to drug-binding selectively. Both amino acids are located in the drug-binding region and differ between the variants. Phe112/Ser114 of the A variant and its equivalent residues in the F1*S variant (Leu112/Phe114) were swapped with each other. Binding experiments were then conducted using the antiarrhythmic drug disopyramide, which selectively binds to the A variant. A significant decrease in the bound fraction was observed in each singly mutated A protein (Phe112Leu or Ser114Phe). Moreover, the bound fraction of the double A mutant (Phe112Leu/Ser114Phe) was decreased to that of wild-type F1*S. Intriguingly, the double F1*S mutant (Leu112Phe/Phe114Ser), in which residues were swapped with those of the A variant, showed only partial restoration in binding. The triple F1*S mutant (Leu112Phe/Phe114Ser/Asp115Tyr), where position 115 is thought to contribute to the difference in pocket size between variants, showed a further recovery in binding to 70% of that of wild-type A. These results were supported by thermodynamic analysis and acridine orange binding, which selectively binds the A variant. Together, these data indicate that, in addition to direct interaction with Phe112 and Ser114, the binding pocket size contributed by Tyr115 is important for the drug-binding selectivity of the A variant.
PubMed: 38949624
DOI: 10.1021/acs.molpharmaceut.4c00428 -
ACS Macro Letters Jul 2024The frequent mutations of influenza A virus (IAV) have led to an urgent need for the development of innovative antiviral drugs. Glycopolymers offer significant...
The frequent mutations of influenza A virus (IAV) have led to an urgent need for the development of innovative antiviral drugs. Glycopolymers offer significant advantages in biomedical applications owing to their biocompatibility and structural diversity. However, the primary challenge lies in the design and synthesis of well-defined glycopolymers to precisely control their biological functionalities. In this study, functional glycopolymers with sulfated fucose and 6'-sialyllactose were successfully synthesized through ring-opening metathesis polymerization and a postmodification strategy. The optimized heteropolymer exhibited simultaneous targeting of hemagglutinin and neuraminidase on the surface of IAV, as evidenced by MU-NANA assay and hemagglutination inhibition data. Antiviral experiments demonstrated that the glycopolymer displayed broad and efficient inhibitory activity against wild-type and mutant strains of H1N1 and H3N2 subtypes , thereby establishing its potential as a dual-targeted inhibitor for combating IAV resistance.
PubMed: 38949618
DOI: 10.1021/acsmacrolett.4c00221 -
Medical Physics Jul 2024Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular...
BACKGROUND
Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes.
PURPOSE
We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas.
METHODS
An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions ( ) and diffusivities of the maximum peaks ( ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation.
RESULTS
The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis). showed a positive and negative correlation with MIB-1 respectively ( , all ). The AUC of for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model ( ) was 0.873 (95% CI, 0.802-0.944).
CONCLUSION
The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.
PubMed: 38949565
DOI: 10.1002/mp.17280