Proteomic biomarkers in plasma that differentiate rapid and slow decline in lung function in adult cigarette smokers with chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of morbidity and mortality in the United States and cigarette smoking is a primary determinant of the disease. COPD is characterized by chronic airflow limitation as measured by the forced expiratory volume in one second (FEV₁). In this study, the plasma proteomes of 38 middle-aged or older adult smokers with mild to moderate COPD, with FEV₁ decline characterized as either rapid (RPD, n?=?20) or slow or absent (SLW, n?=?18), were interrogated using a comprehensive high-throughput proteomic approach, the accurate mass and time (AMT) tag technology. This technology is based upon a putative mass and time tag database (PMT), high-resolution LC separations and high mass accuracy measurements using FT-ICR MS with a 9.4-T magnetic field. The peptide and protein data were analyzed using three statistical approaches to address ambiguities related to the high proportion of missing data inherent to proteomic analysis. The RPD and SLW groups were differentiated by 55 peptides which mapped to 33 unique proteins. Twelve of the proteins have known roles in the complement or coagulation cascade and, despite an inability to adjust for some factors known to affect lung function decline, suggest potential mechanistic biomarkers associated with the rate of lung function decline in COPD. Whether these proteins are the cause or result of accelerated decline will require further research.     

Bispidine as a β-strand nucleator: from a β-arch to self-assembled cages and vesicles

The development of synthetic scaffolds that nucleate well-folded secondary structures is highly challenging. Herein, we designed and synthesized a series of core-modified peptides (F1, F2, F3, and F4) that fold into β-strand structures. These bispidine-scaffolded peptides were studied by CD, IR, NMR, single crystal XRD, and Molecular Dynamics (MD) simulations to investigate their conformational preferences. Solid-state and solution studies revealed that bispidine is a versatile scaffold that could be placed either at the terminal or at the middle of the peptide strand for nucleating the β-strand structure. Scaffolds that nucleate an isolated β-strand conformation are rare. Bispidine placed at the C-terminus of the peptide chain could nucleate a β-strand conformation, while bispidine placed at the middle resulted in a β-arch conformation. This nucleation activity stems from the ability to restrict the psi torsion angle (ψ) through intramolecular C5 hydrogen bonding between the equatorial hydrogen(s) of bispidine and the carbonyl oxygen(s) of the amino acid close to the scaffold. Furthermore, the bispidine peptidomimetic with a super secondary structure, namely β-arch, assembled into single-hole submicron cages and spherical vesicles as evident from microscopic studies. The design logic defined here will be a significant strategy for the development of β-strand mimetics and super secondary structures.

Bispidine is a versatile scaffold that could be placed either at the terminal or at the middle of the peptide strand for nucleating β-strand structures. These β-strand mimetics self-assemble to single hole submicron cages and vesicles.     

Realization of an advanced nozzle concept for compact chemical oxygen iodine laser

Conventional supersonic chemical oxygen–iodine lasers (SCOIL) are not only low-pressure systems, with cavity pressure of 2–3 Torr and Mach number of approximately 1.5, but also are high-throughput systems with a typical laser power per unit evacuation capacity of nearly 1 J/l, thus demanding high capacity vacuum systems which mainly determine the compactness of the system. These conventional nozzle-based systems usually require a minimum of a two-stage ejector system for realization of atmospheric pressure recovery in a SCOIL. Typically for a 500 W class SCOIL, a first stage requires a motive gas flow (air) of 120 gm/s to entrain a laser gas flow of 3 g/s and is capable of achieving the pressure recovery in the range of 60–80 Torr. On the other hand, the second stage ejector requires 4.5 kg/s of motive gas (air) to achieve atmospheric pressure recovery. An advanced nozzle, also known as ejector nozzle, suitable for a 500 W-class SCOIL employing an active medium flow of nearly 12 g/s, has been developed and used instead of a conventional slit nozzle. The nozzle has been tested in both cold as well as hot run conditions of SCOIL, achieving a typical cavity pressure of nearly 10 Torr, stagnation pressure of approximately 85 Torr and a cavity Mach number of 2.5. The present study details the gas dynamic aspects of this ejector nozzle and highlights its potential as a SCOIL pressure recovery device. This nozzle in conjunction with a diffuser is capable of achieving pressure recovery equivalent to a more cumbersome first stage of the pressure recovery system used in the case of a conventional slit nozzle-based system. Thus, use of this nozzle in place of a conventional slit nozzle can achieve atmospheric discharge using a single stage ejector system, thereby making the pressure recovery system quite compact.     

Texture rules for concentrated filled nematics

Defect textures in concentrated fiber-filled polygonal networks in nematic liquid crystals are analyzed using differential geometry and computational modeling based on Landau--de Gennes theory. Micron fibers exhibit singular cores of strength -1/2 for odd polygons and escaped cores of strength -(N-2)/2 for even polygons (N: number of sides), in agreement with experiments while simulations predict singular cores of strength -1/2 in submicron fibers. The computed textures satisfy physical and topological stability rules, and the total charge inside each polygon obeys the Poincaré-Brouwer theorem.     

Absence of preclassical solutions in Bianchi I loop quantum cosmology

Loop quantum cosmology, the symmetry reduction of quantum geometry for the study of various cosmological situations, leads to a difference equation for its quantum evolution equation. To ensure that solutions of this equation act in the expected classical manner far from singularities, additional restrictions are imposed on the solution. In this Letter, we consider the Bianchi I model, both the vacuum case and the addition of a cosmological constant, and show using generating function techniques that only the zero solution satisfies these constraints. This implies either that there are technical difficulties with the current method of quantizing the evolution equation, or else loop quantum gravity imposes strong restrictions on the physically allowed solutions.     

Spectral deep learning for prediction and prospective validation of functional groups

State-of-the-art identification of the functional groups present in an unknown chemical entity requires the expertise of a skilled spectroscopist to analyse and interpret Fourier transform infra-red (FTIR), mass spectroscopy (MS) and/or nuclear magnetic resonance (NMR) data. This process can be time-consuming and error-prone, especially for complex chemical entities that are poorly characterised in the literature, or inefficient to use with synthetic robots producing molecules at an accelerated rate. Herein, we introduce a fast, multi-label deep neural network for accurately identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra. We do not use any database, pre-established rules, procedures, or peak-matching methods. Our trained neural network reveals patterns typically used by human chemists to identify standard groups. Finally, we experimentally validated our neural network, trained on single compounds, to predict functional groups in compound mixtures. Our methodology showcases practical utility for future use in autonomous analytical detection.

A new multi-label deep neural network architecture is used to combine Infrared and mass spectra, trained on single compounds to predict functional groups, and experimentally validated on complex mixtures.     

Ultrasensitive Organic Humidity Sensor with High Specificity for Healthcare Applications

Humidity sensors have gained immense importance as non‐invasive, wearable healthcare devices for personal care as well as disease diagnostics. However, non‐specificity, poor stability at extreme conditions, and low sensitivity of the humidity sensor inhibit its usage as a health monitoring device. In the present study, N?F containing organic molecule, Selectfluor^TM (F‐TEDA) based humidity sensors with ～1–2 mm long needle‐shaped crystals is fabricated on interdigitated electrodes resulting in excellent performance. The unidirectional growth of crystals led to the formation of a conduction pathway for water molecules across the crystal, which otherwise are non‐conducting. The as‐fabricated humidity sensor at an operational voltage of 0.8 V displays a sensitivity of six orders in magnitude, best reported so far. The sensor does not exhibit any response upon exposure to various volatile organic compounds and reactive gases, indicating remarkable specificity. The sensor is tolerant to high moisture of 95 % for prolonged hours followed by monitoring over several days and degrades to 50 % of its original sensitivity only after continuous exposure for several days. Electrochemical impedance spectroscopy (EIS) shows reversal from resistive to capacitive behavior with increasing humidity levels. The fabricated humidity sensor acts as a healthcare device for breath rate monitoring and touch‐free examination of skin moisture.