Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles.

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson-Boltzmann theory to capture these phenomena.

Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation.

Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here, we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-κB as a primary regulator of acutely induced histone 3 lysine 27 acetylation (H3K27ac). Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data support clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.

A saturation mutagenesis screen uncovers resistant and sensitizing secondary KRAS mutations to clinical KRASG12C inhibitors.

Mutant-specific inhibitors of KRASG12C, such as AMG510 (sotorasib) and MRTX849 (adagrasib), offer the unprecedented opportunity to inhibit KRAS, the most frequently mutated and heretofore undruggable oncoprotein. While clinical data are still limited, on-target mutations in KRASG12C at position 12 and other sites are emerging as major drivers of clinical relapse. We identified additional mutations in KRASG12C that impact inhibitor sensitivity through a saturation mutagenesis screen in the KRASG12C NCI-H358 non­small-cell lung cancer (NSCLC) cell line. We also identified individuals in population genetic databases harboring these resistance mutations in their germline and in tumors, including a subset that co-occur with KRASG12C, indicating that these mutations may preexist in patients treated with KRASG12C inhibitors. Notably, through structural modeling, we found that one such mutation (R68L) interferes with the critical protein­drug interface, conferring resistance to both inhibitors. Finally, we uncovered a mutant (S17E) that demonstrated a strong sensitizing phenotype to both inhibitors. Functional studies suggest that S17E sensitizes KRASG12C cells to KRASG12C inhibition by impacting signaling through PI3K/AKT/mTOR but not the MAPK signaling pathway. Our studies highlight the utility of unbiased mutation profiling to understand the functional consequences of all variants of a disease-causing genetic mutant and predict acquired resistant mutations in the targeted therapeutics.

Frailty in patients with IDH-mutant gliomas: experience from a high-volume tumor center.

PURPOSE: Gliomas are increasingly diagnosed in an aging population, with treatment outcomes influenced by factors like tumor genetics and patient frailty. This study focused on IDH-mutant gliomas and assessed how frailty affects 30-day readmission and overall survival (OS). We aimed to address a gap in understanding the impact of frailty on this specific glioma subtype. METHODS: 136 patients with an IDH-mutant glioma between 2007 and 2021 were identified at our institution. High frailty was classified by scores ≥ 1 on the 5-factor modified frailty index (mFI-5) and ≥ 3 on the Charlson Comorbidity Index (CCI). Patient and tumor characteristics including age, sex, race, Karnofsky Performance Status (KPS), Body Mass Index (BMI), tumor type and location, type of operation, and therapy course were recorded. Outcomes measured included 30-day readmission and overall survival (OS). Analysis was conducted utilizing logistic regression and Kaplan-Meier curves. RESULTS: Of the 136 patients, 52 (38%) had high frailty: 18 with CCI ≥ 3, 34 with mFI-5 ≥ 1. High frailty correlated with increased BMI (CCI: 30.2, mFI-5: 30.1 kg/m2), more neurological deficits (CCI: 61%, mFI-5: 56%), and older age at surgery (CCI: 63, mFI-5: 48 years). Hospital readmission within 30 days occurred in 8 (5.9%) patients. Logistic regression indicated no significant difference in 30-day readmission rates (CCI: p = 0.30, mFI-5: p = 0.62) or median OS between high and low frailty groups. However, patients treated at our institution with newly diagnosed tumors with high mFI-5 had a 6.79 times higher adjusted death hazard than those with low mFI-5 (p = .049). CONCLUSION: Our analysis revealed that CCI and mFI-5 were not significantly associated with 30-day nor OS. However, in patients with non-recurrent tumors, there was a significant association of mFI-5 with OS. Further study of frailty with larger cohorts is warranted to enhance prognostication of outcome after neurosurgical treatment.

Structure adaptation in Omicron SARS-CoV-2/hACE2: Biophysical origins of evolutionary driving forces.

Since its emergence, the COVID-19 threat has been sustained by a series of transmission waves initiated by new variants of the SARS-CoV-2 virus. Some of these arise with higher transmissivity and/or increased disease severity. Here, we use molecular dynamics simulations to examine the modulation of the fundamental interactions between the receptor binding domain (RBD) of the spike glycoprotein and the host cell receptor (human angiotensin-converting enzyme 2 [hACE2]) arising from Omicron variant mutations (BA.1 and BA.2) relative to the original wild-type strain. Our key findings are that glycans play a vital role at the RBD···hACE2 interface for the Omicrons, and the interplay between glycans and sequence mutations leads to enhanced binding. We find significant structural differences in the complexes, which overall bring the spike protein and its receptor into closer proximity. These are consistent with and attributed to the higher positive charge on the RBD conferred by BA.1 and BA.2 mutations relative to the wild-type. However, further differences between subvariants BA.1 and BA.2 (which have equivalent RBD charges) are also evident: mutations reduce interdomain interactions between the up chain and its clockwise neighbor chain in particular for the latter, resulting in enhanced flexibility for BA.2. Consequently, we see occurrence of additional close contacts in one replica of BA.2, which include binding to hACE2 by a second RBD in addition to the up chain. Although this motif is not seen in BA.1, we find that the Omicrons can directly/indirectly bind a down-RBD to hACE2 through glycans: the role of the glycan on N90 of hACE2 switches from inhibiting to facilitating the binding to Omicron spike protein via glycan-protein lateral interactions. These structural and electrostatic differences offer further insight into the mechanisms by which viral mutations modulate host cell binding and provide a biophysical basis for evolutionary driving forces.

State of pediatric liver transplantation in the United States and achieving zero wait list mortality with ideal outcomes: A statement from the Starzl Network for Excellence in Pediatric Transplant Surgeon's Working Group.

BACKGROUND: Liver transplant is a life-saving therapy that can restore quality life for several pediatric liver diseases. However, it is not available to all children who need one. Expertise in medical and surgical management is heterogeneous, and allocation policies are not optimally serving children. Technical variant grafts from both living and deceased donors are underutilized. METHODS: Several national efforts in pediatric liver transplant to improve access to and outcomes from liver transplant for children have been instituted and include adjustments to allocation policies, UNOS-sponsored collaborative improvement projects, and the emergence of national learning networks to study ongoing challenges in the field the Surgical Working group of the Starzl Network for Excellence in Pediatric Transplantation (SNEPT) discusses key issues and proposes potential solutions to eliminate the persistent wait list mortality that pediatric patients face. RESULTS: A discussion of the factors impacting pediatric patients' access to liver transplant is undertaken, along with a proposal of several measures to ensure equitable access to life-saving liver transplant. CONCLUSIONS: Pediatric liver transplant wait list mortality can and should be eliminated. Several measures, including collaborative efforts among centers, could be leveraged to acheive this goal.

Purely nasal floor mucosa-free graft for reconstruction after endoscopic endonasal transellar approach: an anatomical and clinical analysis.

BACKGROUND/OBJECTIVE: In this radioanatomical study with clinical correlate, we study a variation of the 'extended nasal floor mucosa' (ENFM) free-graft, the purely nasal floor mucosa (PuNFM) free-graft. The objectives of this study are to evaluate the coverage surface area provided by the PuNFM, study the adequacy of the PuNFM in the reconstruction of endoscopic endonasal approach (EEA) transsellar postoperative defects and compare and evaluate this reconstructive technique with current sellar region reconstruction practices. METHODS: Dissections were performed on five cadaveric specimens. PuNFM were harvested bilaterally and the area provided for reconstruction was calculated. Twenty-five consecutive cases of pituitary adenomas resected through an EEA were analyzed to estimate the sellar defect surface area (SDSA) after a transsellar EEA and calculate the area of PuNFM bilaterally. RESULTS: The median cadaveric SDSA was 4.77 cm2, with a median left and right side PuNFM area of 5.09 and 5.19 cm2, respectively. Clinically, the median SDSA was 5.36 cm2, and the total radiological PuNFM surface area was 5.46 cm2, with modified Knosp grade >2 tumors having larger SDSA than that of Knosp grade <2 tumors. The PuNFM graft proved to be most effective for covering modified Knosp <2 tumor defects. CONCLUSIONS: The PuNFM represents a variation of the ENFM free-graft sellar defect reconstruction technique that provides sufficient surface area to reconstruct the majority of the sellar defects related to transsellar EAA for pituitary adenomas. This technique may positively impact sinonasal function and quality of life. Future prospective clinical studies are needed to verify these findings.

Clinical and radiographic characteristics of diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma: a single institution review.

PURPOSE: Genetic analyses of gliomas have identified key molecular features that impact treatment paradigms beyond conventional histomorphology. Despite at-times lower grade histopathologic appearances, IDH-wildtype infiltrating gliomas expressing certain molecular markers behave like higher-grade tumors. For IDH-wildtype infiltrating gliomas lacking traditional features of glioblastoma, these markers form the basis for the novel diagnosis of diffuse astrocytic glioma, IDH-wildtype (wt), with molecular features of glioblastoma (GBM), WHO grade-IV (DAG-G). However, given the novelty of this approach to diagnosis, literature detailing the exact clinical, radiographic, and histopathologic findings associated with these tumors remain in development. METHODS: Data for 25 patients matching the DAG-G diagnosis were obtained from our institution's retrospective database. Information regarding patient demographics, treatment regimens, radiographic imaging, and genetic pathology were analyzed to determine association with clinical outcomes. RESULTS: The initial radiographic findings, histopathology, and symptomatology of patients with DAG-G were similar to lower-grade astrocytomas (WHO grade 2/3). Overall survival (OS) and progression free survival (PFS) associated with our cohort, however, were similar to that of IDH-wt GBM, indicating a more severe clinical course than expected from other associated features (15.1 and 5.39 months respectively). CONCLUSION: Despite multiple features similar to lower-grade gliomas, patients with DAG-G experience clinical courses similar to GBM. Such findings reinforce the need for biopsy and subsequent analysis of molecular features associated with any astrocytoma regardless of presenting characteristics.

A Learning Health System for Pediatric Liver Transplant: The Starzl Network for Excellence in Pediatric Transplantation.

OBJECTIVE: Learning health systems (LHS) integrate research, improvement, management, and patient care, such that every child receives "the right care at the right time...every time," that is, evidence-based, personalized medicine. Here, we report our efforts to establish a sustainable, productive, multicenter LHS focused on pediatric liver transplantation. METHODS: The Starzl Network for Excellence in Pediatric Transplantation (SNEPT) is the first multicenter effort by pediatric liver transplant families and providers to develop shared priorities and a shared agenda for innovation in clinical care. This report outlines SNEPT's structure, accomplishments, and challenges as an LHS. RESULTS: We prioritized 4 initial projects: immunosuppression, perioperative anticoagulation, quality of life, and transition of care. We shared center protocols/management to identify areas of practice variability between centers. We prioritized actionable items that address barriers to providing "the right care at the right time" to every pediatric liver transplant recipient: facilitating transparency of practice variation and the connection of practices to patient outcomes, harnessing existing datasets to reduce the burden of tracking outcomes, incorporating patient-reported outcomes into outcome metrics, and accelerating the implementation of knowledge into clinical practice. This has allowed us to strengthen collaborative relationships, design quality improvement projects, and collect pilot data for each of our priority projects. CONCLUSIONS: The field of pediatric liver transplantation can be advanced through application of LHS principles. Going forward, SNEPT will continue to unite patient advocacy, big data, technology, and transplant thought leaders to deliver the best care, while developing new, scalable solutions to pediatric transplantation's most challenging problems.

NextPBM: a platform to study cell-specific transcription factor binding and cooperativity.

High-throughput (HT) in vitro methods for measuring protein-DNA binding have become invaluable for characterizing transcription factor (TF) complexes and modeling gene regulation. However, current methods do not utilize endogenous proteins and, therefore, do not quantify the impact of cell-specific post-translational modifications (PTMs) and cooperative cofactors. We introduce the HT nextPBM (nuclear extract protein-binding microarray) approach to study DNA binding of native cellular TFs that accounts for PTMs and cell-specific cofactors. We integrate immune-depletion and phosphatase treatment steps into our nextPBM pipeline to characterize the impact of cofactors and phosphorylation on TF binding. We analyze binding of PU.1/SPI1 and IRF8 from human monocytes, delineate DNA-sequence determinants for their cooperativity, and show how PU.1 affinity correlates with enhancer status and the presence of cooperative and collaborative cofactors. We describe how nextPBMs, and our accompanying computational framework, can be used to discover cell-specific cofactors, screen for synthetic cooperative DNA elements, and characterize TF cooperativity.

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.

We present a machine learning approach to automated force field development in dissipative particle dynamics (DPD). The approach employs Bayesian optimization to parametrize a DPD force field against experimentally determined partition coefficients. The optimization process covers a discrete space of over 40 000 000 points, where each point represents the set of potentials that jointly forms a force field. We find that Bayesian optimization is capable of reaching a force field of comparable performance to the current state-of-the-art within 40 iterations. The best iteration during the optimization achieves an R2 of 0.78 and an RMSE of 0.63 log units on the training set of data, these metrics are maintained when a validation set is included, giving R2 of 0.8 and an RMSE of 0.65 log units. This work hence provides a proof-of-concept, expounding the utility of coupling automated and efficient global optimization with a top down data driven approach to force field parametrization. Compared to commonly employed alternative methods, Bayesian optimization offers global parameter searching and a low time to solution.

Dissipative particle dynamics: Systematic parametrization using water-octanol partition coefficients.

We present a systematic, top-down, thermodynamic parametrization scheme for dissipative particle dynamics (DPD) using water-octanol partition coefficients, supplemented by water-octanol phase equilibria and pure liquid phase density data. We demonstrate the feasibility of computing the required partition coefficients in DPD using brute-force simulation, within an adaptive semi-automatic staged optimization scheme. We test the methodology by fitting to experimental partition coefficient data for twenty one small molecules in five classes comprising alcohols and poly-alcohols, amines, ethers and simple aromatics, and alkanes (i.e., hexane). Finally, we illustrate the transferability of a subset of the determined parameters by calculating the critical micelle concentrations and mean aggregation numbers of selected alkyl ethoxylate surfactants, in good agreement with reported experimental values.

Mini-open anterior approach for cervicothoracic junction fracture: technical note.

Elderly patients with diffuse idiopathic skeletal hyperostosis are at high risk for falls, and 3-column unstable fractures present multiple challenges. Unstable fractures across the cervicothoracic junction are associated with significant morbidity and require fixation, which is commonly performed through a posterior open or percutaneous approach. The authors describe a novel, navigated, mini-open anterior approach using intraoperative cone-beam CT scanning to place lag screws followed by an anterior plate in a 97-year-old patient. This approach is less invasive and faster than an open posterior approach and can be considered as an option for management of cervicothoracic junction fractures in elderly patients with high perioperative risk profile who cannot tolerate being placed prone during surgery.

Suvorexant, a dual orexin receptor antagonist for the management of insomnia.

Suvorexant, a dual orexin receptor antagonist for the management of insomnia.

Characterizing the association between CSF biomarkers and risk for ventriculoperitoneal shunt following posterior fossa tumor resection in a case-control study.

BACKGROUND: Recalcitrant hydrocephalus necessitating permanent cerebrospinal fluid (CSF) diversion is a known complication after resection of a posterior fossa tumor (PFT). Various CSF contents, such as protein and other markers, have been variably correlated with the need for permanent CSF diversion. This study aims to evaluate which CSF laboratory values are associated with permanent CSF diversion following PFT resection in adults. METHODS: This study queried our multi-institutional database (Central Nervous System Tumor Outcome Registry at Emory; CTORE) consisting of 617 adult patients with PFT resections from 2006 to 2021. Retrospective data was collected from the 89 patients of this cohort that required EVD placement. Patients were stratified into two groups: those that required a shunt following EVD removal (n = 30) and those that did not (n = 40). CSF variables collected included glucose, protein, nucleated cell count, and presence of infection. An unadjusted logistic regression was performed to assess exposures associated with shunt requirement and unadjusted odds ratios (ORs) and their associated 95 % confidence intervals (CIs) were obtained. RESULTS: Immediately following surgery, no CSF variables were significantly associated with shunt placement. Except for post-operative CSF being not-clear (OR: 4.15 (1.47-12.56), p = 0.009) and CSF glucose (OR: 0.97 (1.03-1.07), p = 0.031) all other variables were not significantly associated with shunt at time point 2. CONCLUSION: In our retrospective analysis, most routinely collected CSF values were not associated with permanent CSF diversion via a ventriculoperitoneal shunt following PFT resection. Further research is needed to identify other potential predictive markers.

An Artificial Neural Network Model for Predicting Postoperative Facial Nerve Outcomes After Vestibular Schwannoma Surgery.

BACKGROUND AND OBJECTIVES: The emergence of machine learning models has significantly improved the accuracy of surgical outcome predictions. This study aims to develop and validate an artificial neural network (ANN) model for predicting facial nerve (FN) outcomes after vestibular schwannoma (VS) surgery using the proximal-to-distal amplitude ratio (P/D) along with clinical variables. METHODS: This retrospective study included 71 patients who underwent VS resection between 2018 and 2022. At the end of surgery, the FN was stimulated at the brainstem (proximal) and internal acoustic meatus (distal) and the P/D was calculated. Postoperative FN function was assessed using the House-Brackmann grading system at discharge (short-term) and after 9-12 months (long-term). House-Brackmann grades I-II were considered good outcome, whereas grades III-VI were considered fair/poor. An ANN model was constructed, and the performance of the model was evaluated using the area under the ROC curve for internal validation and accuracy, sensitivity, specificity, and positive and negative predictive values for external validation. RESULTS: The short-term FN outcome was grades I-II in 57.7% and grades III-VI in 42.3% of patients. Initially, a model using P/D had an area under the curve of 0.906 (internal validation) and an accuracy of 89.1% (95% CI: 68.3%-98.8%) (external validation) for predicting good vs fair/poor short-term FN outcomes. The model was then refined to include only muscles with a P/D with a proximal latency between 6 and 8 ms. This improved the accuracy to 100% (95% CI: 79%-100%). Integrating clinical variables (patient's age, tumor size, and preoperative HB grade) in addition to P/D into the model did not significantly improve the predative value. A model was then created to predict the long-term FN outcome using P/D with latencies between 6 and 8 ms and had an accuracy of 90.9% (95% CI: 58.7%-99.8%). CONCLUSION: ANN models incorporating P/D can be a valuable tool for predicting FN outcomes after VS surgery. Refining the model to include P/D with latencies between 6 and 8 ms further improves the model's prediction. A user-friendly interface is provided to facilitate the implementation of this model.

Smartphone Applications for Remote Monitoring of Patients After Transsphenoidal Pituitary Surgery: A Narrative Review of Emerging Technologies.

OBJECTIVE: Almost all postoperative assessments for pituitary patients are performed in clinical settings under the supervision of medical providers. With the emergence of telemedicine, however, there are opportunities to monitor these patients remotely. The potential for use of such technologies is inconsistently described in the brain tumor literature, especially for patients with pituitary adenomas. METHODS: In this comprehensive narrative review, we present the literature for the use of mobile applications (apps) for monitoring of postoperative symptomatology that is specific to patients undergoing pituitary surgery. Our primary research question was: "Which smartphone apps exist in the literature to monitor parameters associated with common complications of pituitary surgery?" Specifically, we search for apps in the literature that facilitate the measurement of parameters associated with adrenal insufficiency, disorders of water imbalance, and visual changes-3 common complications of pituitary surgery. RESULTS: Twenty-six apps were identified. Fourteen apps pertained to monitoring of visual changes, followed by 9 apps for monitoring water and electrolyte imbalances and 3 apps for monitoring adrenal dysfunction. Novel technologies that were integrated into these apps included digital image-based colorimetry, sonouroflowmetry, visual contrast sensitivity, and lateral flow immunoassays, among others. CONCLUSIONS: Due to advancing capabilities of smartphone apps, the potential of telemedicine may extend beyond patient appointments. We show that by integrating novel advances in medical technologies from a variety of specialties, it is possible to develop smartphone-based protocols for remote monitoring of patients after pituitary surgery.

The Impact of Social Determinants on Receipt of Adjuvant Radiation Nationally Following Atypical Meningioma Surgery.

OBJECTIVE: We aimed to identify socioeconomic gaps in the administration of adjuvant radiotherapy (RT) for patients with atypical meningioma (AM) and secondarily to determine differences in survival between patients receiving radiation and those not receiving radiation at 12 and 60 months. METHODS: The National Cancer Database was queried for patients receiving AM surgery between 2004 and 2019. Statistical analyses were performed to assess the association between receipt of adjuvant radiation and social determinants. Secondarily, Kaplan-Meir curves were used to compare overall patient survival between those that received radiation and those that did not. RESULTS: Adjuvant radiation was less likely to be administered to patients over 65 (95% confidence interval [CI] = 0.53-22 0.77) and more likely to be administered to males (95% CI = 1.07-1.38). Compared to the Southern USA, patients were more likely to receive RT in the Northeastern (95% CI 24 = 1.40-2.05), Midwestern (95% CI = 1.06-1.54), and Western parts of the USA (95% 25 CI = 1.31-2.00). Patients residing furthest from their facility were less likely to receive radiation (95% CI = 0.65-0.98). Insured patients were more likely to receive radiation (P = 0.048) than uninsured patients. On multivariate analysis, no differences were found between racial groups regarding adjuvant radiation. For patients unstratified, radiation was shown to improve survival at 12 and 60 months. CONCLUSIONS: Disparities exist in the administration of adjuvant RT for AM. Patients over 65, women, those residing in the Southern USA, those living further from their facilities and uninsured patients are less likely to receive radiation than their counterparts.