Prevalence and Factors Affecting the Optimal and Non-optimal Peak Inspiratory Flow Rate in Stable and Exacerbation Phases of Chronic Obstructive Pulmonary Disease and Bronchial Asthma in India.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) and bronchial asthma pose significant threats and challenges to global health care, emphasizing the need for precise inhaler therapies to overcome this burden. The optimal peak inspiratory flow rate (PIFR) is a crucial determinant for the right selection and effective use of an inhaler device. It also helps to improve the treatment effectiveness of obstructive airway diseases worldwide as it allows effective drug delivery to distal airways and lung parenchyma. It is used as a selection criterion by physicians around the world for selecting personalized inhaler devices. OBJECTIVE: To find out the optimal and non-optimal PIFR prevalence and its influencing factors in stable and exacerbation phases of COPD and bronchial asthma in Tamil Nadu, India. METHODOLOGY: It is a single-center, observational, cross-sectional study conducted from February 2022 to August 2023. The patients who meet the diagnostic criteria specified by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines for COPD and the Global Initiative for Asthma (GINA) guidelines for bronchial asthma are enrolled in our study. The PIFR was measured using a hand-held digital spirometry device, along with demographic data collection. Statistical analyses, including t-tests and chi-square tests, were performed using SPSS version 21 (IBM Corp., Armonk, NY). RESULTS: Gender, height, and disease severity significantly impacted the PIFR. Females, normal BMI individuals, and those with moderate disease severity exhibited higher optimal PIFR rates. Stable or exacerbation phases, disease, and smoking status do not influence either optimal or non-optimal PIFR. Notably, substantial differences in lung function parameters were observed between optimal (60-90 L/min) and non-optimal PIFR (insufficient: <30 L/min, suboptimal: 30-60 L/min, excessive: >90 L/min) groups, highlighting their impact on respiratory health. CONCLUSION: This study emphasizes the importance of personalized inhaler strategies, considering gender, height, and disease severity. Proper inhaler device selection, continuous monitoring of inhaler technique, and tailored inhaler education at every OPD visit are vital for optimizing effective COPD and bronchial asthma management and improving adherence to treatment.

An automatic diagnostic model for the detection and classification of cardiovascular diseases based on swarm intelligence technique.

Globally, cardiovascular diseases (CVDs) rank among the leading causes of mortality. One out of every three deaths is attributed to cardiovascular disease, according to new World Heart Federation research. Cardiovascular disease can be caused by a number of factors, including stress, alcohol, smoking, a poor diet, inactivity, and other medical disorders like high blood pressure or diabetes. In contrast, for the vast majority of heart disorders, early diagnosis of associated ailments results in permanent recovery. Using newly developed data analysis technology, examining a patient's medical record could aid in the early detection of cardiovascular disease. Recent work has employed machine learning algorithms to predict cardiovascular illness on clinical datasets. However, because of their enormous dimension and class imbalance, clinical datasets present serious issues. An inventive model is offered in this work for addressing these problems. An efficient decision support system, also known as an assistive system, is proposed in this paper for the diagnosis and classification of cardiovascular disorders. It makes use of an optimisation technique and a deep learning classifier. The efficacy of traditional techniques for predicting cardiovascular disease using medical data is anticipated to advance with the combination of the two methodologies. Deep learning systems can reduce mortality rates by predicting cardiovascular illness based on clinical data and the patient's severity level. For an adequate sample size of synthesized samples, the optimisation process chooses the right parameters to yield the best prediction from an enhanced classifier. The 99.58% accuracy was obtained by the proposed method. Also, PSNR, sensitivity, specificity, and other metrics were calculated in this work and compared with systems that are currently in use.

Understanding the structural basis of the binding specificity of c-di-AMP to M. smegmatis RecA using computational biology approach.

Mycobacterium tuberculosis RecA (MtRecA), a protein involved in DNA repair, homologous recombination and SOS pathway, contributes to the development of multidrug resistance. ATP binding-site in RecA has been a drug target to disable RecA dependent DNA repair. For the first time, experiments have shown the existence and binding of c-di-AMP to a novel allosteric site in the C-terminal-Domain (CTD) of Mycobacterium smegmatis RecA (MsRecA), a close homolog of MtRecA. In addition, it was observed that the c-di-AMP was not binding to Escherichia coli RecA (EcRecA). This article analyses the possible interactions of the three RecA homologs with the various c-di-AMP conformations to gain insights into the structural basis of the natural preference of c-di-AMP to MsRecA and not to EcRecA, using the structural biology tools. The comparative analysis, based on amino acid composition, homology, motifs, residue types, docking, molecular dynamics simulations and binding free energy calculations, indeed, conclusively indicates strong binding of c-di-AMP to MsRecA. Having very similar results as MsRecA, it is highly plausible for c-di-AMP to strongly bind MtRecA as well. These insights from the in-silico studies adds a new therapeutic approach against TB through design and development of novel allosteric inhibitors for the first time against MtRecA.Communicated by Ramaswamy H. Sarma.

S-adenosyl-l-methionine interaction signatures in methyltransferases.

The switching on or off of methylation, a change from a normal methylation to hyper or hypo methylation is implicated in many diseases that include cancers, infectious, neurodegenerative diseases and others. Methyltransferases are one of the most sought targets that have diversified for the methylation of a variety of substrates. However, without S-adenosyl-l-methionine (SAM), the universal methyl donor, the majority of the methyltransferases remain functionally inactive. In this article, we did a comprehensive analysis of all available SAM-receptor crystal structures at atom, moiety and structure levels to gain deeper insights into the structure and function of SAM. SAM demonstrated flexibility in binding to a variety of receptors irrespective of the size of the binding pockets. Further analysis of the binding pockets resulted in all SAM conformations clustering into four natural shapes. The conserved interaction analysis provides an unambiguous orientation of SAM binding to receptors which has been elusive till now. SAM peptide moiety (SPM) and SAM nucleobase moiety (SNM) show up to 89% interactions with receptors whereas only 11% interactions with SAM ribose moiety (SRM). It is found that SPM and SNM terminal atoms anchor to the highly conserved receptor subsites creating a workbench for catalysis. It is seen that every interacting atom and its position is crucial in the methyl transfer phenomenon. A very unique observation is that the methyl group of SAM does not have even one interaction with the receptor. The deep insights gained help in the design and development of novel drugs against the methyltransferases.Communicated by Ramaswamy H. Sarma.

Multi-region minutiae depth value-based efficient forged finger print analysis.

The application of biometrics has expanded the wings to many domains of application. However, various biometric features are being used in different security systems; the fingerprints have their own merits as it is more distinct. A different algorithm has been discussed earlier to improve the security and analysis of fingerprints to find forged ones, but it has a deficiency in expected performance. A multi-region minutiae depth value (MRMDV) based finger analysis algorithm has been presented to solve this issue. The image that is considered as input has been can be converted into noisy free with the help of median and Gabor filters. Further, the quality of the image is improved by sharpening the image. Second, the preprocessed image has been divided into many tiny images representing various regions. From the regional images, the features of ridge ends, ridge bifurcation, ridge enclosure, ridge dot, and ridge island. The multi-region minutiae depth value (MRMDV) has been computed based on the features which are extracted. The test image which has a similarity to the test image is estimated around MRMDV value towards forgery detection. The MRMDV approach produced noticeable results on forged fingerprint detection accuracy up to 98% with the least time complexity of 12 seconds.

Conformational variation of site specific glycated albumin: A Molecular dynamics approach.

Human serum albumin (HSA) is a major cargo protein, which undergoes glycation in hyperglycaemic conditions and results in impaired function. In physiological conditions, HSA plays a crucial role in pharmacological activities such as drug transport or delivery through its binding capacity and also by its enzymatic activity, which enables the translation of pro-drugs into active drugs. In this study, the impact of the methylglyoxal-mediated glycation on dynamic behaviour of inter-domain motion, Cys34 reactivity, binding site residual interaction and secondary structure transition were investigated through molecular dynamics simulation. The alteration in inter-domain motion reflects the effect of glycation-mediated changes on the structural conformation of albumin. The binding site residue interactions and volume analysis revealed the impact of glycation on the geometry of the binding site. We also found the correlation of Cys34 reactivity with increase of turns in the region between Ia-h4 and Ia-h5. The rise in turn formation in that region keeps Tyr84 farther away from Cys34 which could lead to higher Cys34 reactivity. In parallel, significant alterations in alpha helical content of helices in the binding sites were observed. These structural and conformational changes in glycated albumin could be the causative agents for functional impairment which leads to diabetic complications.

Assessment of Confidence in Communication Skills and Its Practice With Patients Among Medical Professionals in Trichy, India.

Introduction One of the most fundamental aspects of medicine is the doctor-patient relationship. Many factors influenced this link, including socio-cultural patterns, economic levels, political systems, and health systems. In India, there is an increase in violence toward physicians. Almost every now and then, the newspaper comes with headlines about a doctor being abused by patients or their families. Concerns regarding the absence of good doctor-patient communication among Indian doctors prompted an assessment of the current situation. The major purpose of this study is to assess the confidence of tertiary care hospital interns and post-graduates in their communication skills. Materials and methods In May and June 2021, a cross-sectional survey was conducted among all interns and post-graduates from various departments at a tertiary care hospital and research center in Trichy, Tamil Nadu, India. The questions were designed to measure the confidence of physicians' communication with patients. The Likert scale was used to rate the "confidence in using" and "actual use" of communication skills with patients, which constitute two sections in our questionnaire. Google forms were used to collect data. The information was then exported to a Microsoft Excel spreadsheet. SPSS software version 22.0 was used to analyze the data. Results For confidence in their communication skills, the participants obtained a mean score of 2.98 (S.D. = 0.44). Participants obtained an average score of 2.28 (S.D. = 0.89) for practicing confident communication with patients. It was found that persons who had higher confidence levels had a negative correlation (ρ = -0.318) with that during their communication with patients and this was statistically significant (p-value = < 0.001) Conclusion Despite having confident communication skills, medical practitioners in India hardly ever practice them with their patients. This gap must be explored by conducting qualitative studies to address effective communication skills among health professionals.

Estimated sensitivity profiles of lung cancer specific uncommon BRAF mutants towards experimental and clinically approved kinase inhibitors.

Current experimental and clinical data are inadequate to conclusively predict the oncogenicity of uncommon BRAF mutants and their sensitivity towards kinase inhibitors. Therefore, the present study aims at estimating sensitivity profiles of uncommon lung cancer specific BRAF mutations towards clinically approved as well as experimental therapeutics based on computationally derived direct binding energies. Based on the data derived from cBioportal, BRAF mutants displayed significant mutual exclusivity with KRAS and EGFR mutants indicating them as potential drivers in lung cancer. Predicted sensitivity of BRAF-V600E conformed to published experimental and clinical data thus validating the usefulness of computational approach. The BRAF-V600K displayed higher sensitivity to most inhibitors as compared to that of the BRAF-V600E. All the uncommon mutants displayed higher sensitivity than both the wild type and BRAF-V600E towards PLX 8394 and LSN3074753. While V600K, G469R and N581S displayed favorable sensitivity profiles to most inhibitors, V600L/M, G466A/E/V and G469A/V displayed resistance profiles to a variable degree. Notably, molecular dynamic (MD) simulation revealed that increased number of interactions caused enhanced sensitivity of G469R and N581S towards sorafenib. RAF kinase inhibitors were further classified into two groups as per their selectivity (Group I: BRAF-V600E-selective and Group II: CRAF-selective) based on which potential mutation-wise combinations of RAF kinase inhibitors were proposed to overcome resistance. Based on computational inhibitor sensitivity profiles, appropriate treatment strategies may be devised to prevent or overcome secondary drug resistance in lung cancer patients with uncommon mutations.

An in silico approach to study the role of epitope order in the multi-epitope-based peptide (MEBP) vaccine design.

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches, especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidates. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison and ranking for the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency (RMVP), MEBP vaccine potency (MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. Further, the MEBP variants with IDs, SPVC_446 and SPVC_537, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be preferred candidates for immediate experimental testing and validation. The method enables quicker selection and high throughput experimental validation of vaccine candidates. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time.

Toxic epidermal necrolysis in adult patients: Experience from the West Australian Collaboration.

Toxic epidermal necrolysis (TEN) is a rare and life-threatening mucocutaneous disease triggered by a reaction to a drug. Despite reported mortality of 30%, management differs between healthcare settings. Our hospital was established in February 2015 becoming the new state burns centre in Western Australia (WA). Following this, we collaborated on comprehensive multidisciplinary guidelines for the management of TEN. These guidelines are updated annually to reflect the weight of emerging evidence in managing TEN. Our aim was to review the management and outcomes of TEN patients presenting to our hospital between February 2015 and May 2021 (inclusive). We collected data for 10 patients on year, age, ethnicity, gender, medical history, culprit drug and exposure, SCORTEN, length of stay, maximum percentage of skin detachment, mucosal surface involvement, ophthalmic amniotic membrane transplant, burns unit input/admission, intensive care unit admission, weight, systemic treatment(s), complications and outcome. We excluded 7 out of 17 flagged patients who did not strictly meet the definition of TEN as greater than 30% epidermal detachment, with epidermal detachment defined as bullae, erosions, and/or positive Nikolsky. We found that the mortality rate in WA from TEN is improving compared with two previous WA studies, with a mortality rate in our study of 20% (2 deaths). Though limited by small sample size and retrospective design, our study suggests a shift towards at least one systemic therapy per patient (most commonly cyclosporine), the growing use of etanercept and the ophthalmic use of amniotic membrane transplants. It demonstrates the importance of burns unit input and the utility of comprehensive multidisciplinary guidelines. While the management and outcomes of TEN patients in WA are continuing to improve, we support calls for large registry data to facilitate evidence growth and collaboration for this rare life-threatening condition.

16S rRNA Methyltransferases as Novel Drug Targets Against Tuberculosis.

Tuberculosis (TB) is an airborne infectious disease caused by Mycobacterium tuberculosis (M.tb) whose natural history traces back to 70,000 years. TB remains a major global health burden. Methylation is a type of post-replication, post-transcriptional and post-translational epi-genetic modification involved in transcription, translation, replication, tissue specific expression, embryonic development, genomic imprinting, genome stability and chromatin structure, protein protein interactions and signal transduction indicating its indispensable role in survival of a pathogen like M.tb. The pathogens use this epigenetic mechanism to develop resistance against certain drug molecules and survive the lethality. Drug resistance has become a major challenge to tackle and also a major concern raised by WHO. Methyltransferases are enzymes that catalyze the methylation of various substrates. None of the current TB targets belong to methyltransferases which provides therapeutic opportunities to develop novel drugs through studying methyltransferases as potential novel targets against TB. Targeting 16S rRNA methyltransferases serves two purposes simultaneously: a) translation inhibition and b) simultaneous elimination of the ability to methylate its substrates hence stopping the emergence of drug resistance strains. There are ~ 40 different rRNA methyltransferases and 13 different 16S rRNA specific methyltransferases which are unexplored and provide a huge opportunity for treatment of TB.

Epitope order Matters in multi-epitope-based peptide (MEBP) vaccine design: An in silico study

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidate. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison, ranking, and the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency(RMVP), MEBP vaccine potency(MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. When the MEBP variants were ranked in descending order of their MVP scores, the published MEBPVC had the least MVP score. Further, the MEBP variants with IDs, SPVC_387 and SPVC_206, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be prioritized for experimental testing and validation. Through this method, more vaccine candidates will be available for experimental validation and testing. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time. The computationally validated top-ranked MEBPVCs must be experimentally tested, validated, and verified. The differences and deviations between experimental results and computational predictions provide an opportunity for improving and developing more efficient algorithms and reliable scoring schemes and software.

The effects of a novel inhibitor of tumor necrosis factor (TNF) alpha on prepulse inhibition and microglial activation in two distinct rodent models of schizophrenia.

Increased neuroinflammation has been shown in individuals diagnosed with schizophrenia (SCHZ). This study evaluated a novel immune modulator (PD2024) that targets the pro-inflammatory cytokine tumor necrosis factor-alpha (TNFα) to alleviate sensorimotor gating deficits and microglial activation employing two different rodent models of SCHZ. In Experiment 1, rats were neonatally treated with saline or the dopamine D2-like agonist quinpirole (NQ; 1 mg/kg) from postnatal day (P) 1-21 which produces increases of dopamine D2 receptor sensitivity throughout the animal's lifetime. In Experiment 2, rats were neonatally treated with saline or the immune system stimulant polyinosinic:polycytidylic acid (Poly I:C) from P5-7. Neonatal Poly I:C treatment mimics immune system activation associated with SCHZ. In both experiments, rats were raised to P30 and administered a control diet or a novel TNFα inhibitor PD2024 (10 mg/kg) in the diet from P30 until P67. At P45-46 and from P60-67, animals were behaviorally tested on auditory sensorimotor gating as measured through prepulse inhibition (PPI). NQ or Poly I:C treatment resulted in PPI deficits, and PD2024 treatment alleviated PPI deficits in both models. Results also revealed that increased hippocampal and prefrontal cortex microglial activation produced by neonatal Poly I:C was significantly reduced to control levels by PD2024. In addition, a separate group of animals neonatally treated with saline or Poly I:C from P5-7 demonstrated increased TNFα protein levels in the hippocampus but not prefrontal cortex, verifying increased TNFα in the brain produced by Poly I:C. Results from this study suggests that that brain TNFα is a viable pharmacological target to treat the neuroinflammation known to be associated with SCHZ.

Designing a next generation multi-epitope based peptide vaccine candidate against SARS-CoV-2 using computational approaches.

COVID-19 caused by SARS-CoV-2 was declared a global pandemic by WHO (World Health Organization) in March, 2020. Within 6 months, nearly 750,000 deaths are claimed by COVID-19 across the globe. This called for immediate social, scientific, technological, public and community interventions. Considering the severity of infection and the associated mortalities, global efforts are underway to develop preventive measures against SARS-CoV-2. Among the SARS-CoV-2 target proteins, Spike (S) glycoprotein (a.k.a S Protein) is the most studied target known to trigger strong host immune response. A detailed analysis of S protein-based epitopes enabled us to design a novel B-cell-derived T-cell Multi-epitope-based peptide (MEBP) vaccine candidate. This involved a systematic and comprehensive computational protocol consisting of prediction of dual-purpose epitopes and designing an MEBP vaccine construct. This was followed by 3D structure validation, MEBP complex interaction studies, in silico cloning and vaccine dose-based immune response simulation to evaluate the immunogenic potency of the vaccine construct. The dual-purpose epitope prediction protocol was designed such that the same epitope elicits both humoral and cellular immune response unlike the earlier designs. Further, the epitopes predicted were screened against stringent criteria to ensure selection of a potent candidate with maximum antigen coverage and best immune response. The vaccine dose-based immune response simulation studies revealed a rapid antigen clearance through antibody generation and elevated levels of cell-mediated immunity during repeated exposure of the vaccine. The favourable results of the analysis strongly indicate that the vaccine construct is indeed a potent vaccine candidate and ready to proceed to the next steps of experimental validation and efficacy studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-020-02574-x.

Investigation of multiphase multicomponent aerosol flow dictating pMDI-spacer interactions.

The use of Pressurized metered dose inhalers (pMDIs) for the treatment of asthma and other chronic obstructive pulmonary diseases is frequently associated with breath-actuation synchronization problems and poor pulmonary delivery, particularly amongst the pediatric and geriatric population groups. Spacers, or Valved Holding Chambers (VHCs), are frequently used to address these problems. However, the performance of spacers with different pMDIs is also highly variable and needs to be investigated. The purpose of the current study is to develop a computational fluid dynamics (CFD) model which can characterize multiphase multicomponent aerosol flow issuing from a commercial suspension-based pMDI into a spacer. The CFD model was initially calibrated against published experimental measurements in order to appropriately model the spray characteristics. This model was subsequently used to examine several combinations of inhaler, spacer and USP Throat geometries under different discharge rates of coflow air. The CFD model predictions compared favorably with experimental measurements. In particular, the predictions show, in accordance with experimental determinations, a decrease of drug retained by the spacers with increasing coflow air. The recirculation observed near the obstructions in axial path of the spray within either spacer is considered to be central for increasing spray retention and drug deposition behavior. Fluid flow patterns within the spacers were correlated with drug deposition behavior through a dimensionless variable, the Recirculation index (RCI). Bigger particles were found to be selectively retained within the spacer.

Evaluation of Abbreviated Impactor Measurements (AIM) and Efficient Data Analysis (EDA) for Dry Powder Inhalers (DPIs) Against the Full-Resolution Next Generation Impactor (NGI).

The full-resolution next generation impactor (NGI) and three abbreviated impactor systems were used to obtain the apparent aerodynamic particle size distribution (APSD) and other quality measures for marketed dry powder inhalers (DPIs) using the compendial method and efficient data analysis (EDA). APSD for the active pharmaceutical ingredient (API) in Spiriva® Handihaler®, Foradil® Aerolizer®, and Relenza® Diskhaler® was obtained using a full-resolution NGI at 39, 60, and 90 L/min, respectively. Two reduced NGI (rNGI) configurations, the filter-only configuration (rNGI-f) and the modified-cup configuration (rNGI-mc), and the fast-screening impactor (FSI) with appropriate inserts to provide a 5-µm cut size were evaluated. The fine particle dose (FPD) obtained using the FSI for Spiriva was statistically similar to that obtained using the full NGI. However, the FPD for both Foradil and Relenza obtained using the FSI was significantly different from that obtained using the full NGI. Despite this, no significant differences were observed for the fine particle fraction (FPF) obtained using the FSI relative to that obtained from the full NGI for any of the DPIs. The use of abbreviated impactor systems appears promising with good agreement observed with the full-resolution NGI, except for small differences observed for the rNGI-mc configuration. These small differences may be product- and/or flow rate-specific, and further evaluation will be required to resolve these differences.

Holocene deceleration of the Greenland Ice Sheet.

Recent peripheral thinning of the Greenland Ice Sheet is partly offset by interior thickening and is overprinted on its poorly constrained Holocene evolution. On the basis of the ice sheet's radiostratigraphy, ice flow in its interior is slower now than the average speed over the past nine millennia. Generally higher Holocene accumulation rates relative to modern estimates can only partially explain this millennial-scale deceleration. The ice sheet's dynamic response to the decreasing proportion of softer ice from the last glacial period and the deglacial collapse of the ice bridge across Nares Strait also contributed to this pattern. Thus, recent interior thickening of the Greenland Ice Sheet is partly an ongoing dynamic response to the last deglaciation that is large enough to affect interpretation of its mass balance from altimetry.

A synthesis of the basal thermal state of the Greenland Ice Sheet.

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

Autophagy Modulation by Lanthionine Ketimine Ethyl Ester Improves Long-Term Outcome after Central Fluid Percussion Injury in the Mouse.

Diffuse axonal injury is recognized as a progressive and long-term consequence of traumatic brain injury. Axonal injury can have sustained negative consequences on neuronal functions such as anterograde and retrograde transport and cellular processes such as autophagy that depend on cytoarchitecture and axon integrity. These changes can lead to somatic atrophy and an inability to repair and promote plasticity. Obstruction of the autophagic process has been noted after brain injury, and rapamycin, a drug used to stimulate autophagy, has demonstrated positive effects in brain injury models. The optimization of drugs to promote beneficial autophagy without negative side effects could be used to attenuate traumatic brain injury and promote improved outcome. Lanthionine ketimine ethyl ester, a bioavailable derivative of a natural sulfur amino acid metabolite, has demonstrated effects on autophagy both in vitro and in vivo. Thirty minutes after a moderate central fluid percussion injury and throughout the survival period, lanthionine ketimine ethyl ester was administered, and mice were subsequently evaluated for learning and memory impairments and biochemical and histological changes over a 5-week period. Lanthionine ketimine ethyl ester, which we have shown previously to modulate autophagy markers and alleviate pathology and slow cognitive decline in the 3 × TgAD mouse model, spared cognition and pathology after central fluid percussion injury through a mechanism involving autophagy modulation.

Oral TNFα Modulation Alters Neutrophil Infiltration, Improves Cognition and Diminishes Tau and Amyloid Pathology in the 3xTgAD Mouse Model.

Cytokines such as TNFα can polarize microglia/macrophages into different neuroinflammatory types. Skewing of the phenotype towards a cytotoxic state is thought to impair phagocytosis and has been described in Alzheimer's Disease (AD). Neuroinflammation can be perpetuated by a cycle of increasing cytokine production and maintenance of a polarized activation state that contributes to AD progression. In this study, 3xTgAD mice, age 6 months, were treated orally with 3 doses of the TNFα modulating compound isoindolin-1,3 dithione (IDT) for 10 months. We demonstrate that IDT is a TNFα modulating compound both in vitro and in vivo. Following long-term IDT administration, mice were assessed for learning & memory and tissue and serum were collected for analysis. Results demonstrate that IDT is safe for long-term treatment and significantly improves learning and memory in the 3xTgAD mouse model. IDT significantly reduced paired helical filament tau and fibrillar amyloid accumulation. Flow cytometry of brain cell populations revealed that IDT increased the infiltrating neutrophil population while reducing TNFα expression in this population. IDT is a safe and effective TNFα and innate immune system modulator. Thus small molecule, orally bioavailable modulators are promising therapeutics for Alzheimer's disease.