Early therapeutic drug monitoring of methotrexate and its association with acute kidney injury: A retrospective cohort study.

INTRODUCTION: High-dose methotrexate (HDMTX) use can be limited by the development of acute kidney injury (AKI). Early AKI detection is paramount to prevent further renal injury and irreversible toxicities. This study sought to determine whether early elimination patterns of MTX would be useful as a biomarker of AKI in HDMTX treatment. METHODS: This retrospective cohort study included two sites that collected ≥2 MTX levels within 16 h from completion of MTX infusion. Early levels were tagged and MTX elimination half-life (t½) were calculated from combinations of two of three different early time periods. Receiver operating characteristic (ROC) curves were synthesized for each elimination t½ (biomarker) with respect to AKI and delayed methotrexate elimination (DME); the biomarker with the highest area under the ROC curve (AUC) was tested in a multiple variable logistic regression model. RESULTS: Data from 169 patients who received a total of 556 courses of HDMTX were analyzed. ROC analysis revealed MTX elimination t½ calculated from the second and third time periods had the highest AUC for AKI at 0.62 (interquartile range [IQR] 0.56-0.69) and DME at 0.86 (IQR 0.73-1.00). After adjusting for age, sex, dose (mg/m2), infusion duration, HDMTX course, and baseline estimated glomerular filtration rate, it remained significant for AKI with an OR of 1.29 and 95% confidence interval of 1.03-1.65. CONCLUSION: Early MTX elimination t½ measured within 16 h of infusion completion was significantly associated with the development of AKI and serves as an early clearance biomarker that may identify patients who benefit from increased hydration, augmented leucovorin rescue, and glucarpidase administration.

Hypoalbuminemia in children with acute lymphoblastic leukemia: relation to asparaginase therapy and impact on high dose methotrexate elimination.

PURPOSE: High-dose methotrexate (HDMTX) therapy is an important component in treatment regimens for acute lymphoblastic leukemia (ALL). Courses are associated with a risk of renal injury, delayed elimination, and increased systemic toxicity. Recently hypoalbuminemia has been recognized as yet another risk factor. METHODS: To examine the impact of serum albumin we reviewed 325 HDMTX 5 g/m2 courses in a cohort of 51 children treated on the NOPHO ALL 2008 protocol, dividing the courses into four groups with different levels of baseline albumin (A < 25 g/L, B 25-29 g/L, C 30-34 g/L and D ≥ 35 g/L). RESULTS: Hypoalbuminemia was present in 51% of the courses, mostly in the early phases of chemotherapy while asparaginase therapy is ongoing, and especially if given less than 2 weeks after a dose (78%). Hypoalbuminemia had a significant impact on the end-of-infusion serum MTX, depending on the degree of hypoalbuminemia: MTX > 150 µM was seen in 37%, 32%, 20% and 8% in groups A to D. Serum albumin < 30 g/L was significantly associated with low MTX clearance < 10 L/h/1.73m2 (78% vs. 36%) and high AUC ≥ 1000 µM*h (44% vs. 31%). The frequency of rising creatinine or prolonged elimination was not increased, but the risk of stomatitis was significantly higher (42% vs. 19%). CONCLUSION: Low serum albumin is caused by concurrent asparaginase therapy and has a clinically significant impact on MTX disposition. Guidelines for administering HDMTX may need adjustment if serum albumin < 30 g/L, and, if possible, HDMTX courses should not be scheduled soon after asparaginase doses.

Advancements and Applications of Micro and Nanostructured Capacitive Sensors: A Review.

Capacitors are essential components in modern electrical systems, functioning primarily to store electrical charges and regulate current flow. Capacitive sensors, developed in the 20th century, have become crucial in various applications, including touchscreens and smart devices, due to their ability to detect both metallic and non-metallic objects with high sensitivity and low energy consumption. The advancement of microelectromechanical systems (MEMS) and nanotechnology has significantly enhanced the capabilities of capacitive sensors, leading to unprecedented sensitivity, dynamic range, and cost-effectiveness. These sensors are integral to modern devices, enabling precise measurements of proximity, pressure, strain, and other parameters. This review provides a comprehensive overview of the development, fabrication, and integration of micro and nanostructured capacitive sensors. In terms of an electric field, the working and detection principles are discussed with analytical equations and our numerical results. The focus extends to novel fabrication methods using advanced materials to enhance sensitivities for various parameters, such as proximity, force, pressure, strain, temperature, humidity, and liquid sensing. Their applications are demonstrated in wearable devices, human-machine interfaces, biomedical sensing, health monitoring, robotics control, industrial monitoring, and molecular detection. By consolidating existing research, this review offers insights into the advancements and future directions of capacitive sensor technology.

Chemically Tagging Cargo for Specific Packaging inside and on the Surface of Virus-like Particles.

Virus-like particles (VLPs) have untapped potential for packaging and delivery of macromolecular cargo. To be a broadly useful platform, there needs to be a strategy for attaching macromolecules to the inside or the outside of the VLP with minimal modification of the platform or cargo. Here, we repurpose antiviral compounds that bind to hepatitis B virus (HBV) capsids to create a chemical tag to noncovalently attach cargo to the VLP. Our tag consists of a capsid assembly modulator, HAP13, connected to a linker terminating in maleimide. Our cargo is a green fluorescent protein (GFP) with a single addressable cysteine, a feature that can be engineered in many proteins. The HAP-GFP construct maintained HAP's intrinsic ability to bind HBV capsids and accelerate assembly. We investigated the capacity of HAP-GFP to coassemble with HBV capsid protein and bind to preassembled capsids. HAP-GFP binding was concentration-dependent, sensitive to capsid stability, and dependent on linker length. Long linkers had the greatest activity to bind capsids, while short linkers impeded assembly and damaged intact capsids. In coassembly reactions, >20 HAP-GFP molecules were presented on the outside and inside of the capsid, concentrating the cargo by more than 100-fold compared to bulk solution. We also tested an HAP-GFP with a cleavable linker so that external GFP molecules could be removed, resulting in exclusive internal packaging. These results demonstrate a generalizable strategy for attaching cargo to a VLP, supporting development of HBV as a modular VLP platform.

Glycerol metabolism contributes to competition by oral streptococci through production of hydrogen peroxide.

As a biological byproduct from both humans and microbes, glycerol's contribution to microbial homeostasis in the oral cavity remains understudied. In this study, we examined glycerol metabolism by Streptococcus sanguinis, a commensal associated with oral health. Genetic mutants of glucose-PTS enzyme II (manL), glycerol metabolism (glp and dha pathways), and transcriptional regulators were characterized with regard to glycerol catabolism, growth, production of hydrogen peroxide (H2O2), transcription, and competition with Streptococcus mutans. Biochemical assays identified the glp pathway as a novel source for H2O2 production by S. sanguinis that is independent of pyruvate oxidase (SpxB). Genetic analysis indicated that the glp pathway requires glycerol and a transcriptional regulator, GlpR, for expression and is negatively regulated by PTS, but not the catabolite control protein, CcpA. Conversely, deletion of either manL or ccpA increased the expression of spxB and a second, H2O2-non-producing glycerol metabolic pathway (dha), indicative of a mode of regulation consistent with conventional carbon catabolite repression (CCR). In a plate-based antagonism assay and competition assays performed with planktonic and biofilm-grown cells, glycerol greatly benefited the competitive fitness of S. sanguinis against S. mutans. The glp pathway appears to be conserved in several commensal streptococci and actively expressed in caries-free plaque samples. Our study suggests that glycerol metabolism plays a more significant role in the ecology of the oral cavity than previously understood. Commensal streptococci, though not able to use glycerol as a sole carbohydrate source for growth, benefit from the catabolism of glycerol through production of both ATP and H2O2. IMPORTANCE: Glycerol is an abundant carbohydrate in the oral cavity. However, little is understood regarding the metabolism of glycerol by commensal streptococci, some of the most abundant oral bacteria. This was in part because most streptococci cannot grow on glycerol as the sole carbon source. In this study, we show that Streptococcus sanguinis, a commensal associated with dental health, can degrade glycerol for persistence and competition through two pathways, one of which generates hydrogen peroxide at levels capable of inhibiting Streptococcus mutans. Preliminary studies suggest that several additional commensal streptococci are also able to catabolize glycerol, and glycerol-related genes are actively expressed in human dental plaque samples. Our findings reveal the potential of glycerol to significantly impact microbial homeostasis, which warrants further exploration.

Evaluating the impact of tubular retractors in glioma surgery: A systematic review and meta-analysis.

BACKGROUND: Achieving safe, maximal tumor resection in gliomas can be challenging due to the tumor's intricate relationship with surrounding structures. Tubular retractors offer a minimally invasive approach, preserving functional pathways and reducing complications. To assess their efficacy and safety, we conducted a systematic review and meta-analysis. METHODS: A search across databases identified 26 studies meeting inclusion criteria, encompassing 106 patients with various glioma types and tumor locations. RESULTS: Among 26 eligible studies, 15 provided sufficient data on 106 patients (median age: 50.5 years). Glioblastoma multiforme constituted 52.4 % of tumors, followed by IDH-mutant astrocytomas at 31.0 %. Tumor locations varied, with intraventricular and thalamic involvement in 16.3 % (16/98) of cases, followed by temporal (12.2 %), frontal and occipital (each 8.16 %), basal ganglia (8.16 %), parietal (7.14 %), optic pathway (2.04 %), and caudate nucleus (1.02 %) involvement. VyCor and Brainpath retractors were most used (22.6 % and 21.7 %, respectively). Tubular retractors were often combined with the exoscope (35.9 %). Gross total resection (GTR) was achieved in 69.4 % of cases, near-total resection (NTR) in 5.1 %, and subtotal resection/partial resection (STR/PR) in 25.5 %. Mean extent of resection (EOR) significantly differed between GTR and STR/NTR/PR groups (p<0.001). Postoperative complications included visual deficits (6.38 %), hemiparesis or weakness (2.13 %), multiple complications (1.06 %), and other unspecified complications (3.19 %). CONCLUSION: Tubular retractors are a valuable intraoperative adjunct and component of the surgical armamentarium for glioma surgery allowing bimanual operative techniques to manage hemostasis directly with excellent surgical outcomes and an acceptable complication profile.

Toxicity profile of high-dose methotrexate in young children with central nervous system tumors.

High-dose methotrexate (HD-MTX) is used in the treatment of children with central nervous system (CNS) tumors; however, toxicity information is limited. We characterized toxicities following 102 administrations of HD-MTX (4.6-13.5 g/m2) infused over 4 or 24 h in 38 children with a CNS tumor before 6 years of age (2010-2020). Delayed clearance of methotrexate occurred following 24% of infusions. Common Terminology Criteria for Adverse Events v5 grade 2-3 mucositis was observed in 47% of individuals, Grade 4 neutropenia in 76%, and grade 3-4 thrombocytopenia in 58%. No neurotoxicity was observed. HD-MTX can be safely used with supportive care and monitoring.

Glycerol Metabolism Contributes to Competition by Oral Streptococci through Production of Hydrogen Peroxide.

As a biological byproduct from both humans and microbes, glycerol's contribution to microbial homeostasis in the oral cavity remains understudied. Here we examined glycerol metabolism by Streptococcus sanguinis, a commensal associated with oral health. Genetic mutants of glucose-PTS enzyme II ( manL ), glycerol metabolism ( glp and dha pathways), and transcriptional regulators were characterized with regard to glycerol catabolism, growth, production of hydrogen peroxide (H 2 O 2 ), transcription, and competition with Streptococcus mutans . Biochemical assays identified the glp pathway as a novel source of H 2 O 2 production by S. sanguinis that is independent of pyruvate oxidase (SpxB). Genetic analysis indicated that the glp pathway requires glycerol and a transcriptional regulator, GlpR, for expression and is negatively regulated by PTS, but not the catabolite control protein, CcpA. Conversely, deletion of either manL or ccpA increased expression of spxB and a second, H 2 O 2 -non-producing glycerol metabolic pathway ( dha ), indicative of a mode of regulation consistent with conventional carbon catabolite repression (CCR). In a plate-based antagonism assay and competition assays performed with planktonic and biofilm-grown cells, glycerol greatly benefited the competitive fitness of S. sanguinis against S. mutans. The glp pathway appears to be conserved in several commensal streptococci and actively expressed in caries-free plaque samples. Our study suggests that glycerol metabolism plays a more significant role in the ecology of the oral cavity than previously understood. Commensal streptococci, though not able to use glycerol as a sole carbohydrate for growth, benefit from catabolism of glycerol through production of both ATP and H 2 O 2 . Importance: Glycerol is an abundant carbohydrate found in oral cavity, both due to biological activities of humans and microbes, and as a common ingredient of foods and health care products. However, very little is understood regarding the metabolism of glycerol by some of the most abundant oral bacteria, commensal streptococci. This was in part because most streptococci cannot grow on glycerol as the sole carbon source. Here we show that Streptococcus sanguinis , an oral commensal associated with dental health, can degrade glycerol for persistence and competition through two independent pathways, one of which generates hydrogen peroxide at levels capable of inhibiting a dental pathobiont, Streptococcus mutans . Preliminary studies suggest that several other commensal streptococci are also able to catabolize glycerol, and glycerol-related genes are being actively expressed in human dental plaque samples. Our findings reveal the potential of glycerol to significantly impact microbial homeostasis which warrants further exploration.

Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.

BACKGROUND. Deep learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. OBJECTIVE. The purpose of this article is to develop and validate deep learning models for liver, spleen, and pancreas segmentation on pediatric CT examinations. METHODS. This retrospective study developed and validated deep learning models for liver, spleen, and pancreas segmentation using 1731 CT examinations (1504 training, 221 testing), derived from three internal institutional pediatric (age ≤ 18 years) datasets (n = 483) and three public datasets comprising pediatric and adult examinations with various pathologies (n = 1248). Three deep learning model architectures (SegResNet, DynUNet, and SwinUNETR) from the Medical Open Network for Artificial Intelligence (MONAI) framework underwent training using native training (NT), relying solely on institutional datasets, and transfer learning (TL), incorporating pretraining on public datasets. For comparison, TotalSegmentator, a publicly available segmentation model, was applied to test data without further training. Segmentation performance was evaluated using mean Dice similarity coefficient (DSC), with manual segmentations as reference. RESULTS. For internal pediatric data, the DSC for TotalSegmentator, NT models, and TL models for normal liver was 0.953, 0.964-0.965, and 0.965-0.966, respectively; for normal spleen, 0.914, 0.942-0.945, and 0.937-0.945; for normal pancreas, 0.733, 0.774-0.785, and 0.775-0.786; and for pancreas with pancreatitis, 0.703, 0.590-0.640, and 0.667-0.711. For public pediatric data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.952, 0.871-0.908, and 0.941-0.946, respectively; for spleen, 0.905, 0.771-0.827, and 0.897-0.926; and for pancreas, 0.700, 0.577-0.648, and 0.693-0.736. For public primarily adult data, the DSC for TotalSegmentator, NT models, and TL models for liver was 0.991, 0.633-0.750, and 0.926-0.952, respectively; for spleen, 0.983, 0.569-0.604, and 0.923-0.947; and for pancreas, 0.909, 0.148-0.241, and 0.699-0.775. The DynUNet TL model was selected as the best-performing NT or TL model considering DSC values across organs and test datasets and was made available as an open-source MONAI bundle (https://github.com/cchmc-dll/pediatric_abdominal_segmentation_bundle.git). CONCLUSION. TL models trained on heterogeneous public datasets and fine-tuned using institutional pediatric data outperformed internal NT models and Total-Segmentator across internal and external pediatric test data. Segmentation performance was better in liver and spleen than in pancreas. CLINICAL IMPACT. The selected model may be used for various volumetry applications in pediatric imaging.

Time Delay in Motor Vehicle Accident Arrival: A Critical Analysis of Trauma Team Activation.

Introduction This research aims to investigate the role of time since trauma (TST) in refining trauma team activation (TTA) criteria within a level I trauma center. We analyze the association between TST and post-emergency department (ED) disposition, proposing new insights for the enhancement of TTA criteria. Methods A retrospective analysis was conducted on a dataset comprising 3,693 patients presenting to a level I trauma center following motor vehicle accidents (MVAs) from 2016 to 2021. Data from a trauma registry, encompassing time of injury, time of ED arrival, TTA status, and post-ED disposition, were utilized. TST was calculated as the difference between the time of injury and the time of ED arrival. Patients that received TTA, full or partial, were categorized based on TST (less than one hour, one to two hours, and two or more hours). Statistical analyses, including chi-square tests, were performed using the Statistical Analysis System (SAS) (version 3.8, SAS Institute Inc., Cary, NC). Results Of the 1,261 patients meeting the criteria, 98.3% received TTA, with decreasing TTA rates observed with increasing TST (p = 0.0076). A significant association was found between TST and post-ED disposition for patients who received TTA (p = 0.0007). Compared to the other TST groups, a higher proportion of patients with a TST of two or more hours were admitted, sent to the intensive care unit (ICU), and sent to the operating room (OR).  Conclusion The study indicates a statistically significant relationship between TST and TTA rates, challenging our assumptions about the decreased need for TTA over time. While a longer TST was associated with a lower percentage of TTA, patients with a TST of two or more hours demonstrated increased rates of admission, ICU utilization, and surgical interventions. This suggests that TTA criteria may benefit from refinement to include patients with longer TST. Acknowledging study limitations, such as a small sample size and retrospective design, this research contributes valuable insights into potential considerations for optimizing trauma care protocols.

Assessment of Dosing Strategies for Pediatric Drug Products.

Pediatric drug dosing is challenged by the heterogeneity of developing physiology and ethical considerations surrounding a vulnerable population. Often, pediatric drug dosing leverages findings from the adult population; however, recent regulatory efforts have motivated drug sponsors to pursue pediatric-specific programs to meet an unmet medical need and improve pediatric drug labeling. This paradigm is further complicated by the pathophysiological implications of obesity on drug distribution and metabolism and the roles that body composition and body size play in drug dosing. Therefore, we sought to understand the landscape of pediatric drug dosing by characterizing the dosing strategies from drug products recently approved for pediatric indications identified using FDA Drug Databases and analyze the impact of body size descriptors (age, body surface area, weight) on drug pharmacokinetics for several selected antipsychotics approved in pediatric patients. Our review of these pediatric databases revealed a dependence on body size-guided dosing, with 68% of dosing in pediatric drug labelings being dependent on knowing either the age, body surface area, or weight of the patient to guide dosing for pediatric patients. This dependence on body size-guided dosing drives the need for special consideration when dosing a drug in overweight and obese patients. Exploratory pharmacokinetic analyses in antipsychotics illustrate possible effects of drug exposure when applying different dosing strategies for this class of drugs. Future efforts should aim to further understand the pediatric drug dosing and obesity paradigm across pediatric age ranges and drug classes to optimize drug development and clinical care for this patient population.

Injury Patterns in Vehicle Crashes: The Significance of Occupant Seating Position.

OBJECTIVES:  Investigating patterns among the outcomes of patients involved in motor vehicle accidents (MVAs) can provide information necessary to guide targeted interventions to improve road traffic safety. Our purpose is to identify any differences between passenger and driver injury severity and overall clinical course after MVAs. METHODS:  We performed a retrospective review and analysis of 3,693 patients involved in MVAs from 2016 to 2021. We divided the data into two groups, drivers and passengers, and compared the Injury Severity Score (ISS), Revised Trauma Score (RTS) on admission, days in the Intensive Care Unit (ICU), length of hospital stay (LOS), post Emergency Department (ED) disposition, discharge (DC) disposition, and signs of life on arrival (SOLA) to the ED. We compared mean ISS, New Injury Severity Score (NISS), RTS, length in ICU and LOS using a student's T-test and SOLA, post-ED and DC disposition using Chi-square analysis. RESULTS:  We did not find any statistically significant difference in ISS, RTS, days in ICU, LOS, or SOLA between the drivers and passengers. However, we did find a statistically significant difference in the post-ED (X2= 113.743, p=<0.0001) and DC disposition (X2=41.172, p=<0.0001) of drivers and passengers. After the ED and DC, more passengers were transferred to a higher level of care than expected, while the inverse was true for drivers. The number of drivers discharged to Skilled Nursing Facilities (SNFs) was also higher than expected, further contributing to the observed difference in DC disposition.  Conclusion: Our study found no statistically significant difference between driver and passenger injury severity, length of hospital stay, days in ICU, and SOLA after an MVA. The clinical courses of the two groups were found to be significantly different based on post-ED and DC disposition data. We identified limitations, such as a relatively small sample size and insufficient data on specific car seat locations for passengers, underscoring the need for a more nuanced exploration. Future research must broaden its scope to encompass diverse crash scenarios, vehicle design and safety technologies, seat belt dynamics, and age- and gender-specific vulnerabilities.

COVID-19 Vaccine Related Cervical Radiculitis and Parsonage-Turner Syndrome: Case Report and Review of the Literature.

Parsonage-Turner Syndrome, or neuralgic amyotrophy, is an acute-onset upper limb and shoulder girdle palsy that can occur in a post-viral, post-surgical or idiopathic setting. There have also been some reported cases of the syndrome occurring following vaccinations. The pathophysiology of neuralgic amyotrophy is not completely understood and many of the commonly used diagnostic imaging modalities we use to try and diagnose this syndrome are inaccurate and misleading. We present the case of a 40-year-old gentleman who presented with acute onset burning pain and fasciculations in his right upper extremity following vaccination with the second dose of the Pfizer-BioNTech COVID-19 vaccine. His symptoms progressed to weakness in isolated muscle groups with electromyographic evidence of decreased nerve conduction. MRI of the cervical spine demonstrated multilevel central and foraminal stenosis, suggesting a diagnosis of cervical radiculopathy. The patient underwent a C4-5/C5-6 and C6-7 laminoforaminotomy and tolerated the procedure well. Post-operatively, the patient has experienced gradual symptom improvement with residual right triceps and pectoralis muscle weakness as well as paresthesias of the right elbow and forearm. Parsonage-Turner Syndrome is a brachial plexus palsy that can affect one or multiple branches of the brachial plexus. It causes acute-onset pain and weakness, and the diagnosis can be difficult to make with the commonly used diagnostic imaging methods. We reviewed other case reports about neuralgic amyotrophy following vaccinations as well as the current literature on more accurate diagnostic imaging modalities that may help our diagnosis and understanding of the pathophysiology of this condition.

CYP2D6 Phenotype Influences Pharmacokinetic Parameters of Venlafaxine: Results from a Population Pharmacokinetic Model in Older Adults with Depression.

In this study, we aimed to improve upon a published population pharmacokinetic (PK) model for venlafaxine (VEN) in the treatment of depression in older adults, then investigate whether CYP2D6 metabolizer status affected model-estimated PK parameters of VEN and its active metabolite O-desmethylvenlafaxine. The model included 325 participants from a clinical trial in which older adults with depression were treated with open-label VEN (maximum 300 mg/day) for 12 weeks and plasma levels of VEN and O-desmethylvenlafaxine were assessed at weeks 4 and 12. We fitted a nonlinear mixed-effect PK model using NONMEM to estimate PK parameters for VEN and O-desmethylvenlafaxine adjusted for CYP2D6 metabolizer status and age. At both lower doses (up to 150 mg/day) and higher doses (up to 300 mg/day), CYP2D6 metabolizers impacted PK model-estimated VEN clearance, VEN exposure, and active moiety (VEN + O-desmethylvenlafaxine) exposure. Specifically, compared with CYP2D6 normal metabolizers, (i) CYP2D6 ultra-rapid metabolizers had higher VEN clearance; (ii) CYP2D6 intermediate metabolizers had lower VEN clearance; (iii) CYP2D6 poor metabolizers had lower VEN clearance, higher VEN exposure, and higher active moiety exposure. Overall, our study showed that including a pharmacogenetic factor in a population PK model could increase model fit, and this improved model demonstrated how CYP2D6 metabolizer status affected VEN-related PK parameters, highlighting the importance of genetic factors in personalized medicine.

Wavefront-modified vector beams for THz cornea spectroscopy.

Terahertz spectroscopy is a promising method to diagnose ocular diseases, where the cornea is typically imaged by Gaussian beams. However, the beam's mismatch with the cornea's spherical surface produces a 5-10 % error in analysis. We investigate cornea spectroscopy with wavefront-modified vector beams, reducing the original analysis error to less than 0.5 %. Vector beams are synthesized by our developed 3D Angular Spectrum Method expanded to vector spherical harmonic presentation, allowing wavefront modification and scattering analysis from 100-layer cornea models. We show that wavefront-modified spherical vector beams possess increased accuracy and non-sensitive focusing on cornea spectroscopy compared to the Gaussian beams. Additionally, we investigate wavefront-modified cylindrical vector beams, which show frequency-dependent scattering power arising from s- and p-polarizations. As a result, these beams are unsuitable for cornea spectroscopy, although they have potential for optical force applications. Wavefront-modified vector beams can be applied to spherical target spectroscopy and optical force applications, such as medicine, medical imaging, and optical tweezers.

Mie scattering with 3D angular spectrum method.

Mie theory is a powerful method to model electromagnetic scattering from a multilayered sphere. Usually, the incident beam is expanded to its vector spherical harmonic representation defined by beam shape coefficients, and the multilayer sphere scattering is obtained by the T-matrix method. However, obtaining the beam shape coefficients for arbitrarily shaped incident beams has limitations on source locations and requires different methods when the incident beam is defined inside or outside the computational domain or at the scatterer surface. We propose a 3D angular spectrum method for defining beam shape coefficients from arbitrary source field distributions. This method enables the placement of the sources freely within the computational domain without singularities, allowing flexibility in beam design. We demonstrate incident field synthesis and spherical scattering by comparing morphology-dependent resonances to known values, achieving excellent matching and high accuracy. The proposed method has significant benefits for optical systems and inverse beam design. It allows for the analysis of electromagnetic forward/backward propagation between optical elements and spherical targets using a single method. It is also valuable for optical force beam design and analysis.

S100a9 Protects Against the Effects of Repeated Social Defeat Stress.

Background: Posttraumatic stress disorder, a consequence of psychological trauma, is associated with increased inflammation and an elevated risk of developing comorbid inflammatory diseases. However, the mechanistic link between this mental health disorder and inflammation remains elusive. We previously found that S100a8 and S100a9 messenger RNA, genes that encode the protein calprotectin, were significantly upregulated in T lymphocytes and positively correlated with inflammatory gene expression and the mitochondrial redox environment in these cells. Therefore, we hypothesized that genetic deletion of calprotectin would attenuate the inflammatory and redox phenotype displayed after psychological trauma. Methods: We used a preclinical mouse model of posttraumatic stress disorder known as repeated social defeat stress (RSDS) combined with pharmacological and genetic manipulation of S100a9 (which functionally eliminates calprotectin). A total of 186 animals (93 control, 93 RSDS) were used in these studies. Results: Unexpectedly, we observed worsening of behavioral pathology, inflammation, and the mitochondrial redox environment in mice after RSDS compared with wild-type animals. Furthermore, loss of calprotectin significantly enhanced the metabolic demand on T lymphocytes, suggesting that this protein may play an undescribed role in mitochondrial regulation. This was further supported by single-cell RNA sequencing analysis demonstrating that RSDS and loss of S100a9 primarily altered genes associated with mitochondrial function and oxidative phosphorylation. Conclusions: These data demonstrate that the loss of calprotectin potentiates the RSDS-induced phenotype, which suggests that its observed upregulation after psychological trauma may provide previously unexplored protective functions.

Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018-2022.

Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, Streptococcus equi subspecies equi, can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environmental conditions. The purpose of this study was to analyze strangles case numbers across the United States of America from 2018 to 2022 to investigate potential temporal or weather patterns associated with outbreaks. Diagnosed case records were obtained from the Equine Disease Communication Center, university databases, government agencies, or veterinary diagnostic labs, and geographic information systems (GISs) were used to map cases and to acquire relevant meteorological data from outbreak areas. These data were analyzed using logistic regression to explore trends that occur between outbreaks and changes in temperature and precipitation. Initial review of weather data suggested monthly changes in strangles case numbers corresponded with changing seasons. Logistic regression indicated that changes in monthly average temperature and minimum temperature were significantly associated with increased or decreased odds of strangles outbreaks, respectively. Future analyses should focus on weather data isolated within a smaller region or state to better resolve trends in strangles outbreaks throughout the continental USA.

Tutorial on model selection and validation of model input into precision dosing software for model-informed precision dosing.

There has been rising interest in using model-informed precision dosing to provide personalized medicine to patients at the bedside. This methodology utilizes population pharmacokinetic models, measured drug concentrations from individual patients, pharmacodynamic biomarkers, and Bayesian estimation to estimate pharmacokinetic parameters and predict concentration-time profiles in individual patients. Using these individualized parameter estimates and simulated drug exposure, dosing recommendations can be generated to maximize target attainment to improve beneficial effect and minimize toxicity. However, the accuracy of the output from this evaluation is highly dependent on the population pharmacokinetic model selected. This tutorial provides a comprehensive approach to evaluating, selecting, and validating a model for input and implementation into a model-informed precision dosing program. A step-by-step outline to validate successful implementation into a precision dosing tool is described using the clinical software platforms Edsim++ and MwPharm++ as examples.

Escitalopram and Sertraline Population Pharmacokinetic Analysis in Pediatric Patients.

BACKGROUND AND OBJECTIVE: Escitalopram and sertraline are commonly prescribed for anxiety and depressive disorders in children and adolescents. The pharmacokinetics (PK) of these medications have been evaluated in adults and demonstrate extensive variability, but studies in pediatric patients are limited. Therefore, we performed a population PK analysis for escitalopram and sertraline in children and adolescents to characterize the effects of demographic, clinical, and pharmacogenetic factors on drug exposure. METHODS: A PK dataset was generated by extracting data from the electronic health record and opportunistic sampling of escitalopram- and sertraline-treated psychiatrically hospitalized pediatric patients aged 5-18 years. A population PK analysis of escitalopram and sertraline was performed using NONMEM. Concentration-time profiles were simulated using MwPharm++ to evaluate how covariates included in the final models influence medication exposure and compared to adult therapeutic reference ranges. RESULTS: The final escitalopram cohort consisted of 315 samples from 288 patients, and the sertraline cohort consisted of 265 samples from 255 patients. A one-compartment model with a proportional residual error model best described the data for both medications. For escitalopram, CYP2C19 phenotype and concomitant CYP2C19 inhibitors affected apparent clearance (CL/F), and normalizing CL/F and apparent volume of distribution (V/F) to body surface area (BSA) improved estimations. The final escitalopram model estimated CL/F and V/F at 14.2 L/h/1.73 m2 and 428 L/1.73 m2, respectively. For sertraline, CYP2C19 phenotype and concomitant CYP2C19 inhibitors influenced CL/F, and empirical allometric scaling of patient body weight on CL/F and V/F was significant. The final sertraline model estimated CL/F and V/F at 124 L/h/70 kg and 4320 L/70 kg, respectively. Normalized trough concentrations (Ctrough) for CYP2C19 poor metabolizers taking escitalopram were 3.98-fold higher compared to normal metabolizers (151.1 ng/mL vs 38.0 ng/mL, p < 0.0001), and normalized Ctrough for CYP2C19 poor metabolizers taking sertraline were 3.23-fold higher compared to normal, rapid, and ultrarapid metabolizers combined (121.7 ng/mL vs 37.68 ng/mL, p < 0.0001). Escitalopram- and sertraline-treated poor metabolizers may benefit from a dose reduction of 50-75% and 25-50%, respectively, to normalize exposure to other phenotypes. CONCLUSION: To our knowledge, this is the largest population PK analysis of escitalopram and sertraline in pediatric patients. Significant PK variability for both medications was observed and was largely explained by CYP2C19 phenotype. Slower CYP2C19 metabolizers taking escitalopram or sertraline may benefit from dose reductions given increased exposure.