Imprinting reversible deformations on a compressed soft rod network.

We present emergent behaviour of storing mechanical deformation in compressed soft cellular materials (a network of soft polymeric rods). Under an applied compressive strain field, the soft cellular material transits from an elastic regime to a 'pseudo-plastic' regime (not to be confused with pseudoplasticity in fluids). In the elastic phase, it is capable of forgetting (or relaxing) any applied indentation once the applied indentation is removed. This relaxation will be determined by the visco-elasticity and internal relaxation timescales in polymeric hyperelastic cellular materials. In the pseudo-plastic phase, however, the material is capable of storing local indentation (or deformation) indefinitely. This deformation can be erased via removal of the external strain field and is therefore reversible. We characterise this behaviour experimentally and present a simple model that makes use of friction for understanding this behavior.

Connecting Agent-Based Models with High-Dimensional Parameter Spaces to Multidimensional Data Using SMoRe ParS: A Surrogate Modeling Approach.

Across a broad range of disciplines, agent-based models (ABMs) are increasingly utilized for replicating, predicting, and understanding complex systems and their emergent behavior. In the biological and biomedical sciences, researchers employ ABMs to elucidate complex cellular and molecular interactions across multiple scales under varying conditions. Data generated at these multiple scales, however, presents a computational challenge for robust analysis with ABMs. Indeed, calibrating ABMs remains an open topic of research due to their own high-dimensional parameter spaces. In response to these challenges, we extend and validate our novel methodology, Surrogate Modeling for Reconstructing Parameter Surfaces (SMoRe ParS), arriving at a computationally efficient framework for connecting high dimensional ABM parameter spaces with multidimensional data. Specifically, we modify SMoRe ParS to initially confine high dimensional ABM parameter spaces using unidimensional data, namely, single time-course information of in vitro cancer cell growth assays. Subsequently, we broaden the scope of our approach to encompass more complex ABMs and constrain parameter spaces using multidimensional data. We explore this extension with in vitro cancer cell inhibition assays involving the chemotherapeutic agent oxaliplatin. For each scenario, we validate and evaluate the effectiveness of our approach by comparing how well ABM simulations match the experimental data when using SMoRe ParS-inferred parameters versus parameters inferred by a commonly used direct method. In so doing, we show that our approach of using an explicitly formulated surrogate model as an interlocutor between the ABM and the experimental data effectively calibrates the ABM parameter space to multidimensional data. Our method thus provides a robust and scalable strategy for leveraging multidimensional data to inform multiscale ABMs and explore the uncertainty in their parameters.

Quality improvement initiative approach to increase the duration of Kangaroo Mother Care in a neonatal intensive care unit of a tertiary care institute in South India during the COVID-19 pandemic.

INTRODUCTION: Kangaroo mother care (KMC) provided to stable babies in hospitals is associated with 40% relative risk reduction in death, 65% risk reduction in nosocomial infections. Despite clear existing evidence of advantages of KMC, its implementation remains limited.This study aimed to improve the median KMC practice hours in eligible preterm and low birth weight (LBW) neonates by 50% from the baseline practice. METHODS: This was a Quality Improvement study conducted at Neonatal unit of a tertiary care institute in South India. All stable preterm and LBW neonates were included after obtaining written informed consent from mother. Those who needed interruption in KMC due to medical reason were excluded. A team comprising of 2 principal investigators (UG students), 2 consultants and 2 in-charge nurses was formed. Baseline data were collected between January and February 2021 to find out the median duration of KMC practice and to identify limiting factors (barriers) and the facilitating ones through in-depth interviews and team meetings. The study was conducted over a 10 month period. Steps were taken to tackle these in two PDSA cycles, each lasting for 3 weeks (1st PDSA: Education of Mothers and Nurses; 2nd PDSA: KMC technique, orders by residents). The PDSA was followed by monitoring for 10 weeks for sustenance. RESULTS: The baseline data showed that the median duration (in hours) of KMC practice was 2.6 which increased to 5.0 and 5.5 h by the end of first and second PDSA cycle, respectively and showed a lasting change, peaking at a median value of 6.1 h during the sustenance phase over the next 10 weeks. CONCLUSION: Through simple measures and closing the communication gap between health care workers and mothers, we were able to increase the duration of KMC, which remained high during the 10 week follow up period.

Synthetic Approaches to Halogen Bonded Ternary Cocrystals.

Higher cocrystal synthesis depends acutely on a knowledge of supramolecular synthons. We report three synthetic approaches towards ternary halogen bonded cocrystals that illustrate specificity and generality. Electrophilicity/nucleophilicity differences are needed among alternative sites of halogen bond formation. The two halogen bonds A⋅⋅⋅B and B⋅⋅⋅C in a halogen bonded ternary cocrystal ABC need to be of different strength. Interaction mimicry of hydrogen bonds by halogen bonds is a viable approach towards ternaries as illustrated with the pyrene structure. Finally, the crystal engineer should well be able to anticipate halogen bonds that are stronger than hydrogen bonds.

A Biomechanical Model of Tumor-Induced Intracranial Pressure and Edema in Brain Tissue.

Brain tumor growth and tumor-induced edema result in increased intracranial pressure (ICP), which, in turn, is responsible for conditions as benign as headaches and vomiting or as severe as seizures, neurological damage, or even death. Therefore, it has been hypothesized that tracking ICP dynamics may offer improved prognostic potential in terms of early detection of brain cancer and better delimitation of the tumor boundary. However, translating such theory into clinical practice remains a challenge, in part because of an incomplete understanding of how ICP correlates with tumor grade. Here, we propose a multiphase mixture model that describes the biomechanical response of healthy brain tissue-in terms of changes in ICP and edema-to a growing tumor. The model captures ICP dynamics within the diseased brain and accounts for the ability/inability of healthy tissue to compensate for this pressure. We propose parameter regimes that distinguish brain tumors by grade, thereby providing critical insight into how ICP dynamics vary by severity of disease. In particular, we offer an explanation for clinically observed phenomena, such as a lack of symptoms in low-grade glioma patients versus a rapid onset of symptoms in those with malignant tumors. Our model also takes into account the effects tumor-derived proteases may have on ICP levels and the extent of tumor invasion. This work represents an important first step toward understanding the mechanisms that underlie the onset of edema and ICP in cancer-afflicted brains. Continued modeling effort in this direction has the potential to make an impact in the field of brain cancer diagnostics.

Mathematical Modeling of Cellular Cross-Talk Between Endothelial and Tumor Cells Highlights Counterintuitive Effects of VEGF-Targeted Therapies.

Tumor growth and progression are critically dependent on the establishment of a vascular support system. This is often accomplished via the expression of pro-angiogenic growth factors, including members of the vascular endothelial growth factor (VEGF) family of ligands. VEGF ligands are overexpressed in a wide variety of solid tumors and therefore have inspired optimism that inhibition of the different axes of the VEGF pathway-alone or in combination-would represent powerful anti-angiogenic therapies for most cancer types. When considering treatments that target VEGF and its receptors, it is difficult to tease out the differential anti-angiogenic and anti-tumor effects of all combinations experimentally because tumor cells and vascular endothelial cells are engaged in a dynamic cross-talk that impacts key aspects of tumorigenesis, independent of angiogenesis. Here we develop a mathematical model that connects intracellular signaling responsible for both endothelial and tumor cell proliferation and death to population-level cancer growth and angiogenesis. We use this model to investigate the effect of bidirectional communication between endothelial cells and tumor cells on treatments targeting VEGF and its receptors both in vitro and in vivo. Our results underscore the fact that in vitro therapeutic outcomes do not always translate to the in vivo situation. For example, our model predicts that certain therapeutic combinations result in antagonism in vivo that is not observed in vitro. Mathematical modeling in this direction can shed light on the mechanisms behind experimental observations that manipulating VEGF and its receptors is successful in some cases but disappointing in others.

Trans-acting oligodeoxythymidine phosphorothioate triester reagents for transient transfection optimized and facilitated by a high-throughput microbioreactor system.

A rapid and cost-effective transient transfection method for mammalian cells is essential for screening biopharmaceuticals in early stages of development. A library of 25 amphipathic trans-acting oligodeoxythymidine phosphorothioate triester (dTtaPS) transfection reagents, carrying positively charged and lipophilic groups, has been constructed for this purpose. High-throughput screening of the library, using an imaging cytometer and an automated microbioreactor system, has led to the identification of dTtaPS10+ as a potent transfection reagent. This reagent efficiently delivers a plasmid encoding enhanced green fluorescent protein in adherent HeLa cells while exhibiting low cytotoxicity. The microbioreactor system has been particularly useful for assessing the ability of dTtaPS10+ to deliver a plasmid encoding immunoglobulin IgG1 in a fed-batch serum-free suspension CHO cell culture; dTtaPS10+ -mediated transfection resulted in the production of IgG1 in yields comparable to or better than those obtained with commercial lipid-based transfection reagents under similar conditions. The ability of dTtaPS10+ to deliver plasmids is essentially unaffected by the presence of a silicone-based antifoaming reagent, which is commonly used in bioreactor cell cultures. The transfection efficiency of lyophilized dTtaPS10+ -plasmid complexes has been significantly restored upon aqueous reconstitution when compared to that achieved while using commercial transfection reagent complexes under similar conditions. The results of all experiments underscore the potential of dTtaPS10+ for transient transfection of plasmids into adherent cells and fed-batch serum-free suspension CHO cells and rapid screening of reagents in a microbioreactor system.

A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.

Mathematical modeling has a long history in the field of cancer therapeutics, and there is increasing recognition that it can help uncover the mechanisms that underlie tumor response to treatment. However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability. Even in the case of structural (theoretical) identifiability, imperfect data and the resulting practical unidentifiability of model parameters can make it difficult to infer the desired information, and in some cases, to yield biologically correct inferences and predictions. Here, we examine parameter identifiability and estimability using a case study of two compartmental, ordinary differential equation models of cancer treatment with drugs that are cell cycle-specific (taxol) as well as non-specific (oxaliplatin). We proceed through model building, structural identifiability analysis, parameter estimation, practical identifiability analysis and its biological implications, as well as alternative data collection protocols and experimental designs that render the model identifiable. We use the differential algebra/input-output relationship approach for structural identifiability, and primarily the profile likelihood approach for practical identifiability. Despite the models being structurally identifiable, we show that without consideration of practical identifiability, incorrect cell cycle distributions can be inferred, that would result in suboptimal therapeutic choices. We illustrate the usefulness of estimating practically identifiable combinations (in addition to the more typically considered structurally identifiable combinations) in generating biologically meaningful insights. We also use simulated data to evaluate how the practical identifiability of the model would change under alternative experimental designs. These results highlight the importance of understanding the underlying mechanisms rather than purely using parsimony or information criteria/goodness-of-fit to decide model selection questions. The overall roadmap for identifiability testing laid out here can be used to help provide mechanistic insight into complex biological phenomena, reduce experimental costs, and optimize model-driven experimentation.

Mathematical modeling of prostate cancer progression in response to androgen ablation therapy.

Prostate cancer progression depends in part on the complex interactions between testosterone, its active metabolite DHT, and androgen receptors. In a metastatic setting, the first line of treatment is the elimination of testosterone. However, such interventions are not curative because cancer cells evolve via multiple mechanisms to a castrate-resistant state, allowing progression to a lethal outcome. It is hypothesized that administration of antiandrogen therapy in an intermittent, as opposed to continuous, manner may bestow improved disease control with fewer treatment-related toxicities. The present study develops a biochemically motivated mathematical model of antiandrogen therapy that can be tested prospectively as a predictive tool. The model includes "personalized" parameters, which address the heterogeneity in the predicted course of the disease under various androgen-deprivation schedules. Model simulations are able to capture a variety of clinically observed outcomes for "average" patient data under different intermittent schedules. The model predicts that in the absence of a competitive advantage of androgen-dependent cancer cells over castration-resistant cancer cells, intermittent scheduling can lead to more rapid treatment failure as compared to continuous treatment. However, increasing a competitive advantage for hormone-sensitive cells swings the balance in favor of intermittent scheduling, delaying the acquisition of genetic or epigenetic alterations empowering androgen resistance. Given the near universal prevalence of antiandrogen treatment failure in the absence of competing mortality, such modeling has the potential of developing into a useful tool for incorporation into clinical research trials and ultimately as a prognostic tool for individual patients.

Clinical Signs of Base of Skull Fracture in the South Indian Population.

Objective The clinical signs of base of skull fracture (BSF) are often ambiguous and difficult to identify, but are often used to make decisions on early medical interventions. This study aimed to assess the prevalence of the clinical signs of BSF, their dependency to diagnose this injury and to assess the correlation between the presence of these clinical signs and the severity of head injury and patient outcome. Materials and Methods A cross-sectional study was conducted in a tertiary care hospital in South India over a period of 3 years (2020-2023). Patients older than 18 years, with radiological or surgical evidence of BSF were monitored for developing the clinical signs including Battle's signs, raccoon's sign, otorrhea, and rhinorrhea. The presence of these clinical signs was correlated with demographical characteristics, patient presentation, complications, and their outcome. Results A total of 292 patients were included in the study. The mean age of the cohort was 36.27 ± 18.68 years. A total of 55 (18.8%) showed at least one of the four signs of BSF. Raccoon's sign was seen in 9.5% cases, Battle's sign in 5.5%, otorrhea in 5.5%, and rhinorrhea in 2.4% cases. Patients with frontal ( p = 0.021) or ethmoid (0.049) fractures and ENT bleeding ( p = 0.022) were significantly more likely to present with at least one sign of BSF. The patients who presented with clinical signs were more likely to have a complication during the course of the hospital stay ( p = 0.024) than those without clinical signs, including cranial nerve palsy ( p < 0.001) and cerebrospinal fluid leak ( p < 0.001). The outcome of the patient did not change based on the presence of clinical signs ( p = 0.926). Conclusion These study results indicate a limited diagnostic value of BSF clinical signs in the South Indian population. Thus, other modalities should be considered for the diagnosis when suspected. These results also discourage the use of the nasal route in all patients with suspected head injury and emphasize that during the nasal aspiration procedure, the use of a rigid device is fundamental to avoid false passage of the aspiration tube from the nasal to the intracranial region.

Cervical lymphadenitis from Mycobacterium avium complex.

We present an instructive case of cervical lymphadenitis in a young man without a history of HIV infection. The patient developed spontaneous left-sided neck swelling that progressed over 4 months. CT imaging demonstrated a necrotic left-sided neck mass within the cervical lymph node chain. He was initially prescribed azithromycin and rifampin for presumed cat scratch disease with improvement but incomplete resolution of symptoms. Blood cultures ordered 2 months later grew Mycobacterium avium complex (MAC) and the patient had an excellent clinical response to MAC therapy. Here, we review the case, including presentation and management, and describe the implications for the immune status of the host and long-term considerations for treatment.

Paradoxical development of Kimura's disease in a patient treated with mepolizumab for bronchial asthma.

A male patient in his early 30s was diagnosed with bronchial asthma 3 years previously. He responded well to inhaled corticosteroids and long-acting beta-agonists. Approximately 18 months from the onset, the patient reported worsening symptoms. These symptoms included severe functional limitations, requiring frequent exposure to high-dose prednisolone. Mepolizumab was added to the treatment, leading to optimal control of bronchial asthma. Despite receiving seven doses of mepolizumab at monthly intervals, the patient developed cervical and postauricular lymphadenopathy and subcutaneous swelling of soft tissue. A cervical lymph node biopsy confirmed the diagnosis of Kimura disease. Following treatment with oral glucocorticoids and methotrexate, the patient experienced a complete resolution of symptoms. He has been in remission and off oral prednisolone for the last 13 months. In this case, we highlight the development of Kimura disease in a patient undergoing mepolizumab treatment.

SMoRe GloS: An efficient and flexible framework for inferring global sensitivity of agent-based model parameters.

Agent-based models (ABMs) have become essential tools for simulating complex biological, ecological, and social systems where emergent behaviors arise from the interactions among individual agents. Quantifying uncertainty through global sensitivity analysis is crucial for assessing the robustness and reliability of ABM predictions. However, most global sensitivity methods demand substantial computational resources, making them impractical for highly complex models. Here, we introduce SMoRe GloS (Surrogate Modeling for Recapitulating Global Sensitivity), a novel, computationally efficient method for performing global sensitivity analysis of ABMs. By leveraging explicitly formulated surrogate models, SMoRe GloS allows for comprehensive parameter space exploration and uncertainty quantification without sacrificing accuracy. We demonstrate our method's flexibility by applying it to two biological ABMs: a simple 2D cell proliferation assay and a complex 3D vascular tumor growth model. Our results show that SMoRe GloS is compatible with simpler methods like the Morris one-at-a-time method, and more computationally intensive variance-based methods like eFAST. SMoRe GloS accurately recovered global sensitivity indices in each case while achieving substantial speedups, completing analyses in minutes. In contrast, direct implementation of eFAST amounted to several days of CPU time for the complex ABM. Remarkably, our method also estimates sensitivities for ABM parameters representing processes not explicitly included in the surrogate model, further enhancing its utility. By making global sensitivity analysis feasible for computationally expensive models, SMoRe GloS opens up new opportunities for uncertainty quantification in complex systems, allowing for more in depth exploration of model behavior, thereby increasing confidence in model predictions.

Monogenic lupus with neuroregression in an infant due to rare compound heterozygous variants in C1QA gene: Case based review.

BACKGROUND: Monogenic lupus is a rare variant of systemic lupus erythematosus (SLE) that develops in patients with a single gene disorder. Early complement component deficiencies were the first forms of monogenic lupus to be described and C1Q gene mutations are one of the most common forms. C1QA complement deficiency has been reported to occur usually due to biallelic variants in C1QA gene and compound heterozygous variants in C1QA gene have rarely been reported. Majority of the monogenic lupus patients with C1Q deficiency present with mucocutaneous, renal, and musculoskeletal manifestations. Our patient is an unusual case of monogenic lupus with severe neurological manifestations along with cutaneous, haematological, and hepatic manifestations secondary to rare compound heterozygous variants in C1QA gene and anti-ribosomal P autoantibody positivity. She was treated with glucocorticoids, rituximab and fresh frozen plasma with partial neurological recovery. Thus, we present a unique case of monogenic lupus due to a rare compound heterozygous variant in C1QA gene with a brief review of literature.