Tracking the Molecular Fingerprint of Head and Neck Cancer for Recurrence Detection in Liquid Biopsies

The 5-year relative survival for patients with head and neck cancer, the seventh most common form of cancer worldwide, was reported as 67% in developed countries in the second decade of the new millennium. Although surgery, radiotherapy, chemotherapy, or combined treatment often elicits an initial satisfactory response, relapses are frequently observed within two years. Current surveillance methods, including clinical exams and imaging evaluations, have not unambiguously demonstrated a survival benefit, most probably due to a lack of sensitivity in detecting very early recurrence. Recently, liquid biopsy monitoring of the molecular fingerprint of head and neck squamous cell carcinoma has been proposed and investigated as a strategy for longitudinal patient care. These innovative methods offer rapid, safe, and highly informative genetic analysis that can identify small tumors not yet visible by advanced imaging techniques, thus potentially shortening the time to treatment and improving survival outcomes. In this review, we provide insights into the available evidence that the molecular tumor fingerprint can be used in the surveillance of head and neck squamous cell carcinoma. Challenges to overcome, prior to clinical implementation, are also discussed.     

Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.     

Physical filtration efficiency analysis of a polyaniline hybrid composite filter with graphite oxide for particulate matter 2.5

Particulate matter (PM) 2.5 pollution is a prevalent environmental and public health issue that has raised serious global concerns. Because standard heating, ventilation, and air conditioning filters are incapable of filtering out PM 2.5 particles efficiently, different methods of PM 2.5 filtration, such as physical filtration and electrostatic filtration, are under investigation to develop a filter with a high filtration efficiency and a low pressure drop. According to various studies, pressure drop has a significant influence on the filtration efficiency. An equation for the theoretical trend was generated based on the composite data gathered from similar filtration studies and was used to evaluate the relationship between pressure drop and filtration efficiency. Here, the theoretical equation indicated that the filtration efficiency increased as the pressure drop on a filter increased until 0.01 psi where the efficiency remained near constant at approximately 99.9%. In this study, we introduce a graphite oxide (GO) and polyaniline (PANi) composite hybrid filter in order to create a low-pressure (1.2 psi) drop filter. By adding GO flakes to the PANi matrix, we not only produced a highly permeable filter while allowing continuous gas flow, but also achieved a remarkable and highly effective PM 2.5 filter with a filtration efficiency of 99.7 ± 0.08%.     

Properties of Oleogels Formed With High‐Stearic Soybean Oils and Sunflower Wax

In an effort to develop alternatives for harmful trans fats produced by partial hydrogenation of vegetable oils, oleogels of high‐stearic soybean (A6 and MM106) oils were prepared with sunflower wax (SW) as the oleogelator. Oleogels of high‐stearic oils did not have greater firmness when compared to regular soybean oil (SBO) at room temperature. However, the firmness of high‐stearic oil oleogels at 4 °C sharply increased due to the high content of stearic acid. High‐stearic acid SBO had more polar compounds than the regular SBO. Polar compounds in oil inversely affected the firmness of oleogels. Differential scanning calorimetry showed that wax crystals facilitated nucleation of solid fats of high‐stearic oils during cooling. Polar compounds did not affect the melting and crystallization behavior of wax. Solid fat content (SFC) showed that polar compounds in oil and wax interfered with crystallization of solid fats. Linear viscoelastic properties of 7% SW oleogels of three oils reflected well the SFC values while they did not correlate well with the firmness of oleogels. Phase‐contrast microscopy showed that the wax crystal morphology was slightly influenced by solid fats in the high‐steric SBO, A6.     

Integration of anammox into the aerobic granular sludge process for main stream wastewater treatment at ambient temperatures

Anaerobic ammonium oxidation, nitrification and removal of COD was studied at ambient temperature (18 °C ± 3) in an anoxic/aerobic granular sludge reactor during 390 days. The reactor was operated in a sequencing fed batch mode and was fed with acetate and ammonium containing medium with a COD/N ratio of 0.5 [g COD/gN]. During influent addition, the medium was mixed with recycled effluent which contained nitrate in order to allow acetate oxidation and nitrate reduction by anammox bacteria. In the remainder of the operational cycle the reactor was aerated and controlled at a dissolved oxygen concentration of 1.5 mg O₂/l in order to establish simultaneous nitritation and Anammox. Fluorescent in-situ hybridization (FISH) revealed that the dominant Anammox bacterial population shifted toward Candidatus “Brocadia fulgida” which is known to be capable of organotrophic nitrate reduction. The reactor achieved stable volumetric removal rates of 900 [g N₂-N/m³/day] and 600 [g COD/m³/day]. During the total experimental period Anammox bacteria remained dominant and the sludge production was 5 fold lower than what was expected by heterotrophic growth suggesting that consumed acetate was not used by heterotrophs. These observations show that Anammox bacteria can effectively compete for COD at ambient temperatures and can remove effectively nitrate with a limited amount of acetate. This study indicates a potential successful route toward application of Anammox in granular sludge reactors on municipal wastewater with a limited amount of COD.     

APOB CRISPR-Cas9 Engineering in Hypobetalipoproteinemia: A Promising Tool for Functional Studies of Novel Variants

Hypobetalipoproteinemia is characterized by LDL-cholesterol and apolipoprotein B (apoB) plasma levels below the fifth percentile for age and sex. Familial hypobetalipoproteinemia (FHBL) is mostly caused by premature termination codons in the APOB gene, a condition associated with fatty liver and steatohepatitis. Nevertheless, many families with a FHBL phenotype carry APOB missense variants of uncertain significance (VUS). We here aimed to develop a proof-of-principle experiment to assess the pathogenicity of VUS using the genome editing of human liver cells. We identified a novel heterozygous APOB-VUS (p.Leu351Arg), in a FHBL family. We generated APOB knock-out (KO) and APOB-p.Leu351Arg knock-in Huh7 cells using CRISPR-Cas9 technology and studied the APOB expression, synthesis and secretion by digital droplet PCR and ELISA quantification. The APOB expression was decreased by 70% in the heterozygous APOB-KO cells and almost abolished in the homozygous-KO cells, with a consistent decrease in apoB production and secretion. The APOB-p.Leu351Arg homozygous cells presented with a 40% decreased APOB expression and undetectable apoB levels in cellular extracts and supernatant. Thus, the p.Leu351Arg affected the apoB secretion, which led us to classify this new variant as likely pathogenic and to set up a hepatic follow-up in this family. Therefore, the functional assessment of APOB-missense variants, using gene-editing technologies, will lead to improvements in the molecular diagnosis of FHBL and the personalized follow-up of these patients.     

Light emission from Si/SiO2 superlattices fabricated by RPECVD

Si/SiO₂ superlattices that exhibit intense luminescence properties were fabricated by remote plasma enhanced chemical vapor deposition. (RPECVD) and subsequent rapid thermal annealing for silicon crystallization. The effects of charge carrier confinement like blue shifting of the PL spectra and intensity increase with decreasing Silicon quantum well thickness are observed in low temperature photoluminescence experiments. The Si/SiO₂ interface quality is calculated from capacitance voltage (CV) measurements on metal oxide semiconductor teststructures showing excellent layer and Si/SiO₂ interface properties. The Si crystallization process is investigated and analyzed by Raman and transmission electron microscopy. Decreasing the Si quantum well thickness to 2 nm leads to light emission at room temperature.