Oncology pharmacy practice in the United States: Results of a comprehensive, nationwide survey.

Introduction: This study was designed to describe the landscape of oncology pharmacy practice at patient facing institutional healthcare organizations throughout the United States. Methods: The Hematology/Oncology Pharmacy Association (HOPA) Practice Outcomes and Professional Benchmarking Committee conducted a multi-organization, voluntary survey of HOPA members between March 2021 and January 2022. Four overarching domains were targeted: institutional description, job function, staffing, and training/certification. Data were evaluated using descriptive statistics. Results: A total of 68 responses were analyzed including 59% and 41% who self-identified their organization as academic and community centers, respectively. The median number of infusion chairs and annual infusion visits were 49 (interquartile range (IQR): 32-92) and 23,500 (IQR: 8300-300,000), respectively. Pharmacy departments reported to a business leader, physician leader, and nursing leader 57%, 24%, and 10% of the time, respectively. The median oncology pharmacy full-time equivalents was 16 (IQR: 5-60). At academic centers, 50% (IQR: 26-60) of inpatient and 30% (IQR: 21-38) of ambulatory pharmacist FTEs were dedicated to clinical activities. At community centers, 45% (IQR: 26-65) of inpatient and 50% (IQR: 42-58) of ambulatory pharmacist FTEs were dedicated to clinical activities. As many as 18% and 65% of organizations required or encouraged certification for oncology pharmacists, respectively. The median number of Board-Certified Oncology Pharmacists was 4 (IQR: 2-15). Conclusion: As the number of patients with cancer rises, the oncology workforce must grow to support this expanding population. These results describe the practice landscape of oncology pharmacy at US healthcare institutions to serve as a foundation for future research evaluating metrics and benchmarks.

Direct Observation of the Pressure-Induced Structural Variation in Gold Nanoclusters and the Correlated Optical Response.

The ability to gradually modify the atomic structures of nanomaterials and directly identify such structural variation is important in nanoscience research. Here, we present the first example of a high-pressure single-crystal X-ray diffraction analysis of atomically precise metal nanoclusters. The pressure-dependent, subangstrom structural evolution of an ultrasmall gold nanoparticle, Au25S18, has been directly identified. We found that a 0.1 Å decrease of the Au-Au bond length could induce a blue-shift of 30 nm in the photoluminescence spectra of gold nanoclusters. From theoretical calculations, the origins of the blue-shift and enhanced photoluminescence under pressure are investigated, which are ascribed to molecular orbital symmetry and conformational locking, respectively. The combination of the high-pressure in situ X-ray results with both theoretical and experimental optical spectra provides a direct and generalizable avenue to unveil the underlying structure-property relations for nanoclusters and nanoparticles which cannot be obtained through traditional physical chemistry measurements.

Machine learning analysis of self-assembled colloidal cones.

Optical and confocal microscopy is used to image the self-assembly of microscale colloidal particles. The density and size of self-assembled structures is typically quantified by hand, but this is extremely tedious. Here, we investigate whether machine learning can be used to improve the speed and accuracy of identification. This method is applied to confocal images of dense arrays of two-photon lithographed colloidal cones. RetinaNet, a deep learning implementation that uses a convolutional neural network, is used to identify self-assembled stacks of cones. Synthetic data is generated using Blender to supplement experimental training data for the machine learning model. This synthetic data captures key characteristics of confocal images, including slicing in the z-direction and Gaussian noise. We find that the best performance is achieved with a model trained on a mixture of synthetic data and experimental data. This model achieves a mean Average Precision (mAP) of ∼85%, and accurately measures the degree of assembly and distribution of self-assembled stack sizes for different cone diameters. Minor discrepancies between machine learning and hand labeled data is discussed in terms of the quality of synthetic data, and differences in cones of different sizes.

Ductile Metallic Glass Nanoparticles via Colloidal Synthesis.

The design of ductile metallic glasses has been a longstanding challenge. Here, we use colloidal synthesis to fabricate nickel-boron metallic glass nanoparticles that exhibit homogeneous deformation at room temperature and moderate strain rates. In situ compression testing is used to characterize the mechanical behavior of 90-260 nm diameter nanoparticles. The force-displacement curves consist of two regimes separated by a slowly propagating shear band in small, 90 nm particles. The propensity for shear banding decreases with increasing particle size, such that large particles are more likely to deform homogeneously through gradual shape change. We relate this behavior to differences in composition and atomic bonding between particles of different size using mass spectroscopy and XPS. We propose that the ductility of the nanoparticles is related to their internal structure, which consists of atomic clusters made of a metalloid core and a metallic shell that are connected to neighboring clusters by metal-metal bonds.

Stress-Induced Structural Transformations in Au Nanocrystals.

Nanocrystals can exist in multiply twinned structures like icosahedron or single crystalline structures like cuboctahedron. Transformations between these structures can proceed through diffusion or displacive motion. Experimental studies on nanocrystal structural transformations have focused on high-temperature diffusion-mediated processes. Limited experimental evidence of displacive motion exists. We report structural transformation of 6 nm Au nanocrystals under nonhydrostatic pressure of 7.7 GPa in a diamond anvil cell that is driven by displacive motion. X-ray diffraction and transmission electron microscopy were used to detect the structural transformation from multiply twinned to single crystalline. Single crystalline nanocrystals were recovered after unloading, then quickly reverted to the multiply twinned state after dispersion in toluene. The dynamics of recovery was captured using TEM which showed surface recrystallization and rapid twin boundary motion. Molecular dynamics simulations showed that twin boundaries are unstable due to defects nucleated from the interior of the nanocrystal.

Nucleation of Dislocations in 3.9 nm Nanocrystals at High Pressure.

As circuitry approaches single nanometer length scales, it has become important to predict the stability of single nanometer-sized metals. The behavior of metals at larger scales can be predicted based on the behavior of dislocations, but it is unclear if dislocations can form and be sustained at single nanometer dimensions. Here, we report the formation of dislocations within individual 3.9 nm Au nanocrystals under nonhydrostatic pressure in a diamond anvil cell. We used a combination of x-ray diffraction, optical absorbance spectroscopy, and molecular dynamics simulation to characterize the defects that are formed, which were found to be surface-nucleated partial dislocations. These results indicate that dislocations are still active at single nanometer length scales and can lead to permanent plasticity.

Direct observation of phase transitions in truncated tetrahedral microparticles under quasi-2D confinement.

Colloidal crystals are used to understand fundamentals of atomic rearrangements in condensed matter and build complex metamaterials with unique functionalities. Simulations predict a multitude of self-assembled crystal structures from anisotropic colloids, but these shapes have been challenging to fabricate. Here, we use two-photon lithography to fabricate Archimedean truncated tetrahedrons and self-assemble them under quasi-2D confinement. These particles self-assemble into a hexagonal phase under an in-plane gravitational potential. Under additional gravitational potential, the hexagonal phase transitions into a quasi-diamond two-unit basis. In-situ imaging reveal this phase transition is initiated by an out-of-plane rotation of a particle at a crystalline defect and causes a chain reaction of neighboring particle rotations. Our results provide a framework of studying different structures from hard-particle self-assembly and demonstrates the ability to use confinement to induce unusual phases.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields.

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aß42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aß42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aß42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aß42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aß42α-helix or Aß42ß-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse ß-strand secondary structures; in contrast, ff14SB favored helicity during the Aß42α-helix simulations. The conformations obtained from Aß42ß-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and ß-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel ß-strand (ß-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aß42 peptides. Communicated by Ramaswamy H. Sarma.

Mechanical nanolattices printed using nanocluster-based photoresists.

Natural materials exhibit emergent mechanical properties as a result of their nanoarchitected, nanocomposite structures with optimized hierarchy, anisotropy, and nanoporosity. Fabrication of such complex systems is currently challenging because high-quality three-dimensional (3D) nanoprinting is mostly limited to simple, homogeneous materials. We report a strategy for the rapid nanoprinting of complex structural nanocomposites using metal nanoclusters. These ultrasmall, quantum-confined nanoclusters function as highly sensitive two-photon activators and simultaneously serve as precursors for mechanical reinforcements and nanoscale porogens. Nanocomposites with complex 3D architectures are printed, as well as structures with tunable, hierarchical, and anisotropic nanoporosity. Nanocluster-polymer nanolattices exhibit high specific strength, energy absorption, deformability, and recoverability. This framework provides a generalizable, versatile approach for the use of photoactive nanomaterials in additive manufacturing of complex systems with emergent mechanical properties.

Germline Genetics of Prostate Cancer: Prevalence of Risk Variants and Clinical Implications for Disease Management.

Prostate cancer has entered into the era of precision medicine with the recent approvals of targeted therapeutics (olaparib and rucaparib). The presence of germline mutations has important hereditary cancer implications for patients with prostate cancer, and germline testing is increasingly important in cancer screening, risk assessment, and the overall treatment and management of the disease. In this review, we discuss germline variants associated with inherited predisposition, prostate cancer risk and outcomes. We review recommendations for germline testing, available testing platforms, genetic counseling as well as discuss the therapeutic implications of germline variants relevant to prostate cancer treatments. Understanding the role of germline (heritable) mutations that affect prostate cancer biology and risk as well as the subsequent effect of these alterations on potential therapies is critical as the treatment paradigm shifts towards precision medicine. Furthermore, enhancing patient education tactics and healthcare system infrastructure is essential for the utilization of relevant predictive biomarkers and the improvement of clinical outcomes of patients with prostate cancer or at high risk of developing the disease.

Hardening in Au-Ag nanoboxes from stacking fault-dislocation interactions.

Porous, nano-architected metals with dimensions down to ~10 nm are predicted to have extraordinarily high strength and stiffness per weight, but have been challenging to fabricate and test experimentally. Here, we use colloidal synthesis to make ~140 nm length and ~15 nm wall thickness hollow Au-Ag nanoboxes with smooth and rough surfaces. In situ scanning electron microscope and transmission electron microscope testing of the smooth and rough nanoboxes show them to yield at 130 ± 45 MPa and 96 ± 31 MPa respectively, with significant strain hardening. A higher strain hardening rate is seen in rough nanoboxes than smooth nanoboxes. Finite element modeling is used to show that the structure of the nanoboxes is not responsible for the hardening behavior suggesting that material mechanisms are the source of observed hardening. Molecular dynamics simulations indicate that hardening is a result of interactions between dislocations and the associated increase in dislocation density.

Detecting direct oral anticoagulants in trauma patients using liquid chromatography-mass spectrometry: A novel approach to medication reconciliation.

BACKGROUND: Accurate medication reconciliation in trauma patients is essential but difficult. Currently, there is no established clinical method of detecting direct oral anticoagulants (DOACs) in trauma patients. We hypothesized that a liquid chromatography-mass spectrometry (LCMS)-based assay can be used to accurately detect DOACs in trauma patients upon hospital arrival. METHODS: Plasma samples were collected from 356 patients who provided informed consent including 10 healthy controls, 19 known positive or negative controls, and 327 trauma patients older than 65 years who were evaluated at our large, urban level 1 trauma center. The assay methodology was developed in healthy and known controls to detect apixaban, rivaroxaban, and dabigatran using LCMS and then applied to 327 samples from trauma patients. Standard medication reconciliation processes in the electronic medical record documenting DOAC usage were compared with LCMS results to determine overall accuracy, sensitivity, specificity, and positive and negative predictive values (PPV, NPV) of the assay. RESULTS: Of 356 patients, 39 (10.96%) were on DOACs: 21 were on apixaban, 14 on rivaroxaban, and 4 on dabigatran. The overall accuracy of the assay for detecting any DOAC was 98.60%, with a sensitivity of 94.87% and specificity of 99.05% (PPV, 92.50%; NPV, 99.37%). The assay detected apixaban with a sensitivity of 90.48% and specificity of 99.10% (PPV, 86.36%; NPV 99.40%). There were three false-positive results and two false-negative LCMS results for apixaban. Dabigatran and rivaroxaban were detected with 100% sensitivity and specificity. CONCLUSION: This LCMS-based assay was highly accurate in detecting DOACs in trauma patients. Further studies need to confirm the clinical efficacy of this LCMS assay and its value for medication reconciliation in trauma patients. LEVEL OF EVIDENCE: Diagnostic Test, level III.