Engineered extracellular vesicles carrying let-7a-5p for alleviating inflammation in acute lung injury.

BACKGROUND: Acute lung injury (ALI) is a life-threatening respiratory condition characterized by severe inflammation and lung tissue damage, frequently causing rapid respiratory failure and long-term complications. The microRNA let-7a-5p is involved in the progression of lung injury, inflammation, and fibrosis by regulating immune cell activation and cytokine production. This study aims to use an innovative cellular electroporation platform to generate extracellular vesicles (EVs) carring let-7a-5p (EV-let-7a-5p) derived from transfected Wharton's jelly-mesenchymal stem cells (WJ-MSCs) as a potential gene therapy for ALI. METHODS: A cellular nanoporation (CNP) method was used to induce the production and release of EV-let-7a-5p from WJ-MSCs transfected with the relevant plasmid DNA. EV-let-7a-5p in the conditioned medium were isolated using a tangential flow filtration (TFF) system. EV characterization followed the minimal consensus guidelines outlined by the International Society for Extracellular Vesicles. We conducted a thorough set of therapeutic assessments, including the antifibrotic effects using a transforming growth factor beta (TGF-ß)-induced cell model, the modulation effects on macrophage polarization, and the influence of EV-let-7a-5p in a rat model of hyperoxia-induced ALI. RESULTS: The CNP platform significantly increased EV secretion from transfected WJ-MSCs, and the encapsulated let-7a-5p in engineered EVs was markedly higher than that in untreated WJ-MSCs. These EV-let-7a-5p did not influence cell proliferation and effectively mitigated the TGF-ß-induced fibrotic phenotype by downregulating SMAD2/3 phosphorylation in LL29 cells. Furthermore, EV-let-7a-5p regulated M2-like macrophage activation in an inflammatory microenvironment and significantly induced interleukin (IL)-10 secretion, demonstrating their modulatory effect on inflammation. Administering EVs from untreated WJ-MSCs slightly improved lung function and increased let-7a-5p expression in plasma in the hyperoxia-induced ALI rat model. In comparison, EV-let-7a-5p significantly reduced macrophage infiltration and collagen deposition while increasing IL-10 expression, causing a substantial improvement in lung function. CONCLUSION: This study reveals that the use of the CNP platform to stimulate and transfect WJ-MSCs could generate an abundance of let-7a-5p-enriched EVs, which underscores the therapeutic potential in countering inflammatory responses, fibrotic activation, and hyperoxia-induced lung injury. These results provide potential avenues for developing innovative therapeutic approaches for more effective interventions in ALI.

The relationship between cardiorespiratory fitness and inhibitory control following acute stress: An ERP study.

Although the relationships among acute stress, cardiorespiratory fitness (CRF), and cognitive function have been examined, whether CRF is related to behavioral and neuroelectric indices of inhibitory control following acute stress remains unknown. The purpose of the current study was to investigate the combined influence of acute stress and CRF on inhibitory control. Participants, aged 20-30 years, were stratified into the Higher-Fit (n = 31) and the Lower-Fit (n = 32) groups, and completed a Stroop task following the modified Maastricht Acute Stress Test (MAST) in the stress condition and the sham-MAST in the non-stress condition, during which electroencephalography was recorded. Behavioral (i.e., response time and accuracy) and neuroelectric (N2 and P3b components of the event-related potential) outcomes of inhibitory control were obtained. While the Higher-Fit group demonstrated shorter response times and higher accuracy than the Lower-Fit group following both the MAST and the sham-MAST, they also exhibited selective benefits of acute stress on inhibitory control performance (i.e., decreased response times and diminished interference scores). CRF-dependent alterations in neuroelectric indices were also observed, with the Higher-Fit group displaying smaller N2 and greater P3b amplitudes than the Lower-Fit group following the sham-MAST, and increased N2 and attenuated P3b amplitudes following the MAST. Collectively, these findings not only confirm the positive relationship between CRF and inhibitory control but also provide novel insights into the potential influence of CRF on inhibitory control and associated neuroelectric activity following acute stress.

HeapMS: An Automatic Peak-Picking Pipeline for Targeted Proteomic Data Powered by 2D Heatmap Transformation and Convolutional Neural Networks.

The process of peak picking and quality assessment for multiple reaction monitoring (MRM) data demands significant human effort, especially for signals with low abundance and high interference. Although multiple peak-picking software packages are available, they often fail to detect peaks with low quality and do not report cases with low confidence. Furthermore, visual examination of all chromatograms is still necessary to identify uncertain or erroneous cases. This study introduces HeapMS, a web service that uses artificial intelligence to assist with peak picking and the quality assessment of MRM chromatograms. HeapMS applies a rule-based filter to remove chromatograms with low interference and high-confidence peak boundaries detected by Skyline. Additionally, it transforms two histograms (representing light and heavy peptides) into a single encoded heatmap and performs a two-step evaluation (quality detection and peak picking) using image convolutional neural networks. HeapMS offers three categories of peak picking: uncertain peak picking that requires manual inspection, deletion peak picking that requires removal or manual re-examination, and automatic peak picking. HeapMS acquires the chromatogram and peak-picking boundaries directly from Skyline output. The output results are imported back into Skyline for further manual inspection, facilitating integration with Skyline. HeapMS offers the benefit of detecting chromatograms that should be deleted or require human inspection. Based on defined categories, it can significantly reduce human workload and provide consistent results. Furthermore, by using heatmaps instead of histograms, HeapMS can adapt to future updates in image recognition models. The HeapMS is available at: https://github.com/ccllabe/HeapMS.

Predictive role of neutrophil-percentage-to-albumin, neutrophil-to-lymphocyte and eosinophil-to-lymphocyte ratios for mortality in patients with COPD: Evidence from NHANES 2011-2018.

BACKGROUND AND OBJECTIVE: This study evaluated the predictive roles of hematologic inflammatory biomarkers including neutrophil-percentage-to-albumin ratio (NPAR), neutrophil-to-lymphocyte ratio (NLR) and eosinophil-to-lymphocyte ratio (ELR) for mortality in community-dwelling individuals with chronic obstructive pulmonary disease (COPD). METHODS: This longitudinal study extracted data of adults 40-79 years who had physician-diagnosed COPD from the United States (US) National Health and Nutrition Examination Survey (NHANES) 1999-2018. Cox regressions determined the associations between NPAR, NLR, ELR and their components, with all-cause mortality, cardiovascular disease (CVD) mortality and mortality from chronic lower respiratory disease (CLRD). Receiver operating characteristic (ROC) curve analysis estimated the predictive performances of these biomarkers for 5-year all-cause mortality. RESULTS: Data of 1158 subjects were analysed. After adjustment, higher NPAR was significantly associated with increased all-cause and CVD mortality, and mortality from CLRD (adjusted hazard ratio [aHR] = 1.14, 1.15 and 1.16). Higher NLR was associated with an increased all-cause and CVD mortality (aHR = 1.16 and 1.29). Higher neutrophil was associated with increased all-cause mortality and mortality from CLRD (aHR = 1.13 and 1.34). Albumin was associated with decreased all-cause and CVD mortality (aHR = 0.91 and 0.86). ELR, eosinophil or lymphocyte was not significantly associated with either mortality outcomes. Adjusted AUC of NPAR and NLR in predicting 5-year all-cause mortality were 0.808 (95% CI: 0.722-0.845) and 0.799 (95% CI: 0.763-0.835), respectively. CONCLUSION: In community-dwelling US adults with COPD, increased NPAR and NLR are associated with mortality risks. NPAR outperforms the other hematologic inflammatory biomarkers in predicting 5-year all-cause mortality.

An approach to constructing prosodic grammar for Mandarin read speech.

A data-driven approach to constructing a prosodic grammar of Mandarin read speech is proposed. Prosodic labeling is performed, first, on a large speech corpus with syntactic-tree parsing to add four-level break indices. Two types of prosodic grammatical rules are explored. One type is composed of simplified rules to compute break-type distributions at critical junctures for 5 phrase-level and 11 basic syntactic patterns. The other type entails detailed rules to compute break-type distributions conditioned on syntactic function for four determinative-measure (DM)-related syntactic patterns. Effectiveness of the approach was confirmed by meaningful interpretations of the resulting main prosodic patterns and outliers of targeted syntactic patterns by inferred rules. The main findings are given below. Strong paused breaks are found at VE-clause object (VE, active verb with a sentential object) junctures and junctures after idioms. For DM-related patterns, the entropies of break-type distributions decrease significantly as syntactic functions are involved; break-type distributions on both edges are seriously affected by their syntactic functions; when acting as subject (S) and object (O), their prosodic phenomena support the tendency of Mandarin to be S(VO) (V, verb); strong paused breaks at postboundaries of DM-2-DM-4 are caused by their more complex syntactic structures and greater lengths; and the insertions of modifier + DE (special tag for the word DE) into DM-N (N, noun) junctures cause more paused-break insertions at junctures after DMs.

Easy and Rapid Approach to Obtaining the Binding Affinity of Biomolecular Interactions Based on the Deep Learning Boost.

Recently, the deep learning (DL) dimension of artificial intelligence has received much attention from biochemical researchers and thus has gradually become the key approach adopted in the area of biosensing applications. Studies have shown that the use of DL techniques for sensing can not only shorten the time of data analysis but also significantly increase the accuracy of data analysis and prediction, resulting in the performance improvement of biosensing systems in comparison to conventional methods. However, obtaining reliable equilibrium and rate constants of biomolecular interactions during the detection process remains difficult and time-consuming to date. In this study, we propose a transformed model based on the deep transfer learning and sequence-to-sequence autoencoder that can successfully transfer the SPR sensorgram to the protein-binding constants, that is, the association rate constant (ka) and dissociation rate constant (kd), which provide crucial information to understand the mechanisms of drug action and the functional structures of biomolecules. Experimentally, we first trained and tested the pre-trained model using the Langmuir model which generated ideal SPR sensorgrams and then we fine-tuned the pre-trained model through the augmented SPR sensorgrams which were synthesized by using the synthesized minority oversampling technique (SMOTE) through the moderate-scale experiment. Next, the fine-tuned model was inputted with a short experimental SPR sensorgram that only needs 110 s, and the sensorgram was directly transformed into a reconstructed ideal sensorgram. Finally, the binding kinetic constants, that is, ka and kd, as outputs, were obtained through fitting the reconstructed ideal sensorgram. The results showed that the prediction errors of ka and kd obtained by our model were less than 12 and 24%, respectively. Based on the convenience, accuracy, and reliability of the proposed DL approach, we believe our strategy significantly boosts the feasibility to monitor the binding affinity of antibodies online during production.

LC-MS Quantification of Site-Specific Phosphorylation Degree by Stable-Isotope Dimethyl Labeling Coupled with Phosphatase Dephosphorylation.

Protein phosphorylation is a crucial post-translational modification that plays an important role in the regulation of cellular signaling processes. Site-specific quantitation of phosphorylation levels can help decipher the physiological functions of phosphorylation modifications under diverse physiological statuses. However, quantitative analysis of protein phosphorylation degrees is still a challenging task due to its dynamic nature and the lack of an internal standard simultaneously available for the samples differently prepared for various phosphorylation extents. In this study, stable-isotope dimethyl labeling coupled with phosphatase dephosphorylation (DM + deP) was tried to determine the site-specific degrees of phosphorylation in proteins. Firstly, quantitation accuracy of the (DM + deP) approach was confirmed using synthetic peptides of various simulated phosphorylation degrees. Afterwards, it was applied to evaluate the phosphorylation stoichiometry of milk caseins. The phosphorylation degree of Ser130 on α-S1-casein was also validated by absolute quantification with the corresponding synthetic phosphorylated and nonphosphorylated peptides under a selected reaction monitoring (SRM) mode. Moreover, this (DM + deP) method was used to detect the phosphorylation degree change of Ser82 on the Hsp27 protein of HepG2 cells caused by tert-butyl hydroperoxide (t-BHP) treatment. The results showed that the absolute phosphorylation degree obtained from the (DM + deP) approach was comparable with the relative quantitation resulting from stable-isotope dimethyl labeling coupled with TiO2 enrichment. This study suggested that the (DM + deP) approach is promising for absolute quantification of site-specific degrees of phosphorylation in proteins, and it may provide more convincing information than the relative quantification method.

Pathogenic Protist Transmembranome database (PPTdb): a web-based platform for searching and analysis of protist transmembrane proteins.

BACKGROUND: Pathogenic protist membrane transporter proteins play important roles not only in exchanging molecules into and out of cells but also in acquiring nutrients and biosynthetic compounds from their hosts. Currently, there is no centralized protist membrane transporter database published, which makes system-wide comparisons and studies of host-pathogen membranomes difficult to achieve. RESULTS: We analyzed over one million protein sequences from 139 protists with full or partial genome sequences. Putative transmembrane proteins were annotated by primary sequence alignments, conserved secondary structural elements, and functional domains. We have constructed the PPTdb (Pathogenic Protist Transmembranome database), a comprehensive membrane transporter protein portal for pathogenic protists and their human hosts. The PPTdb is a web-based database with a user-friendly searching and data querying interface, including hierarchical transporter classification (TC) numbers, protein sequences, functional annotations, conserved functional domains, batch sequence retrieving and downloads. The PPTdb also serves as an analytical platform to provide useful comparison/mining tools, including transmembrane ability evaluation, annotation of unknown proteins, informative visualization charts, and iterative functional mining of host-pathogen transporter proteins. CONCLUSIONS: The PPTdb collected putative protist transporter proteins and offers a user-friendly data retrieving interface. Moreover, a pairwise functional comparison ability can provide useful information for identifying functional uniqueness of each protist. Finally, the host and non-host protein similarity search can fulfill the needs of comprehensive studies of protists and their hosts. The PPTdb is freely accessible at http://pptdb.cgu.edu.tw .

Hierarchical prosody modeling for Mandarin spontaneous speech.

In this paper, a hierarchical prosody model (HPM)-based method for Mandarin spontaneous speech is proposed. First, an HPM is designed for describing relations among acoustic features of utterances, linguistic features of texts, and prosodic tags representing the underlying hierarchical prosodic structures of utterances. Subsequently, a sequential optimization algorithm is employed to train the HPM based on a large conversational speech corpus, the Mandarin Conversational Dialogue Corpus (MCDC), which features orthographic transcriptions and prosodic event annotations. In this unsupervised training method, all utterances of the MCDC are labeled with two types of prosodic tags, namely, break and prosodic states, automatically and simultaneously. After training, the HPM parameters are examined to identify critical prosodic properties of Mandarin spontaneous speech, which are then compared with their counterparts in the read-speech HPM. The prosodic tags on the studied utterances enable mapping of various prosodic events onto the hierarchical prosodic structures of the utterances. Prosodic analyses of some disfluent events are conducted using the prosodic tags affixed to the MCDC. Finally, an application of the HPM to assist in Mandarin spontaneous-speech recognition is discussed. Significant relative error rate reductions of 9.0%, 9.2%, 15.6%, and 7.3% are obtained for base-syllable, character, tone, and word recognition, respectively.

A Sensitive Ratiometric Long-Wavelength Fluorescent Probe for Selective Determination of Cysteine/Homocysteine.

The development of sensitive fluorescence probes to detect biothiols such as cysteine and homocysteine has attracted great attention in recent times. Herein, we described the design and synthesis of coumarin based long-wavelength fluorescence probe, Bromo-2-benzothiazolyl-3-cyano-7-hydroxy coumarin (BBCH, 2) for selective detections of cysteine and homocysteine. The probe is rationally designed in such a way that both sulfhydryl and adjacent amino groups of thiols are involved in sensing process. Only cysteine/homocysteine able to react with BBCH to release fluorescence reporter (BCH, 1); while, glutathione and other amino acids unable to react with BBCH due to the absence of adjacent amino groups. In presence of cysteine, the color of BBCH is turns from colorless to red and thus BBCH is a naked eye fluorescence indicator for cysteine. Besides, BBCH can discriminate cysteine and homocysteine based on color changes and different reaction rates. The described sensing platform showed good sensing performances to detect cysteine and homocysteine with detection limits of 0.87 and 0.19 µM, respectively. Practical applicability was verified in biological and pharmaceutical samples.

Cardiorespiratory fitness, independent of APOE genotype, is associated with better neurocognitive function in older adults: An ERP study.

This study assessed the association between cardiorespiratory fitness and carriage of the apolipoprotein-E ε4 (APOE ε4) alleles and cognitive function using behavioral and neuroelectric measures obtained from cognitively normal older adults. A total of 159 adults aged 50-70 years were categorized into four groups based on cardiorespiratory fitness (i.e., higher vs. lower fitness) and the APOE genotype status (i.e., APOE ε4 carrier vs. non-carrier). Neurocognitive functions were indexed using response time and accuracy measures from the Stroop task and averaged mean P3 amplitudes of event-related potentials obtained during task performance. A significant main effect of cardiorespiratory fitness (p = .01) and the Stroop congruency (p < .001), but not the APOE genotype status, with shorter response times for the higher fitness group than for the lower fitness group and for the congruent condition relative to the incongruent condition, were observed. Similar findings were also revealed, with larger averaged mean P3 amplitudes for the higher fitness group than those in the lower fitness group, and in the congruent condition than in the incongruent condition. These findings suggest that higher cardiorespiratory fitness is linked to better neurocognitive function, and the positive association is evident regardless of the APOE ε4 status and the cognitive domain assessed in cognitively normal older adults.

Improved N(α)-acetylated peptide enrichment following dimethyl labeling and SCX.

Protein N-terminal acetylation is one of the most common modifications occurring co- and post-translationally on either eukaryote or prokaryote proteins. However, compared to other protein modifications, the physiological role of protein N-terminal acetylation is relatively unclear. To explore the biological functions of protein N-terminal acetylation, a robust and large-scale method for qualitative and quantitative analysis of this modification is required. Enrichment of N(α)-acetylated peptides or depletion of the free N-terminal and internal tryptic peptides prior to analysis by mass spectrometry are necessary based on current technologies. This study demonstrated a simple strong cation exchange (SCX) fractionation method to selectively enrich N(α)-acetylated tryptic peptides via dimethyl labeling without the need for tedious protective labeling and depleting procedures. This method was introduced for the comprehensive analysis of N-terminal acetylated proteins from HepG2 cells. Several hundred N-terminal acetylation sites were readily identified in a single SCX flow-through fraction. Moreover, the N(α)-acetylated peptides of some protein isoforms were simultaneously observed in the SCX flow-through fraction, which indicated that this approach can be utilized to discriminate protein isoforms with very similar full sequences but different N-terminal sequences, such as ß-actin/γ-actin, ERK1/ERK2, α-centractin/ß-centractin, and ADP/ATP translocase 2 and 3. Compared to other methods, this method is relatively simple and can be directly implemented in a two-dimensional separation (SCX-RP)-mass spectrometry scheme for quantitative N-terminal proteomics using stable-isotope dimethyl labeling.

Quercetin-3-O-ß-d-glucuronide in the Nuciferine Leaf Polyphenol Extract Promotes Neurogenesis Involving the Upregulation of the Tropomyosin Receptor Kinase (Trk) Receptor and AKT/Phosphoinositide 3-Kinase Signaling Pathway.

Neurogenesis is crucial during the human lifespan for the maintenance of synaptic plasticity and normal function. The impairment of hippocampal neurogenesis in adults may lead to neurodegenerative disease, such as Alzheimer's disease. Miquelianin (quercetin-3-O-ß-d-glucuronide, Q3GA) is a constituent of the nuciferine leaf polyphenol extract (NLPE), and it has protective effects against neurodegeneration. In this study, we examined the effect of the NLPE on neurogenesis and the mechanisms underlying Q3GA on neurogenesis. We fed 24-week-old male C57BL/6 mice with 0.1 or 0.25% NLPE for 2 weeks. NLPE treatment increased small spindle-shaped stem cell numbers in the subgranular zone and the number of doublecortin (DCX)- and neuron-specific nuclear protein (NeuN)-expressing neurons. HT22, a hippocampal cell line, treated with Q3GA revealed significant neurite growth and upregulated TrkR and PI3K/Akt levels. The evidence from a model of retinoic acid-induced SH-SY5Y cell differentiation showed that Q3GA or NLPE increases neurite growth significantly. Taken together, the NLPE containing Q3GA to promote neurogenesis involving the upregulation of TrkR and the PI3K/Akt signaling pathway might be potentiated as an alternative strategy for the treatment of neurodegeneration.

Delay Analysis in Closed-Loop EEG Phase-Triggered Transcranial Magnetic Stimulation.

The recent development of closed-loop EEG phase-triggered transcranial magnetic stimulation (TMS) has advanced potential applications of adaptive neuromodulation based on the current brain state. Closed-loop TMS involves instantaneous acquisition of the EEG rhythm, timing prediction of the target phase, and triggering of TMS. However, the accuracy of EEG phase prediction algorithms is largely influenced by the system's transport delay, and their relationship is rarely considered in related work. This paper proposes a delay analysis that considers the delay of the closed-loop EEG phase-triggered TMS system as a primary factor in the validation of phase prediction algorithms. An in-silico validation using real EEG data was performed to compare the performance of commonly used algorithms. The experimental results indicate a significant influence of the total delay on the algorithm performance, and the performance ranking among algorithms varies at different levels of delay. We conclude that the delay analysis framework should be widely adopted in the design and validation of phase prediction algorithms for closed-loop EEG phase-triggered TMS systems.

Exploring Possible Diagnostic Precancerous Biomarkers for Oral Submucous Fibrosis: A Narrative Review.

Oral submucous fibrosis (OSF) stands as a progressive oral ailment, designated as a potentially malignant disorder. OSF has gained widespread recognition as a significant precursor to malignant transformation. In the pursuit of dependable, straightforward, and non-invasive diagnostic measures for the early detection of oral malignant progression, research has delved into potential diagnostic biomarkers of OSF. This comprehensive review delves into current investigations that explore the correlation between various biomarkers and OSF. The molecular biomarkers of OSF are categorized based on cytology and sampling methods. Moreover, this review encompasses pertinent studies detailing how these biomarkers are acquired and processed. Within this scope, we scrutinize four potential biomarkers that hold the promise of facilitating the development of diagnostic tools for detecting early-stage OSF.

Dual targeted extracellular vesicles regulate oncogenic genes in advanced pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) tumours carry multiple gene mutations and respond poorly to treatments. There is currently an unmet need for drug carriers that can deliver multiple gene cargoes to target high solid tumour burden like PDAC. Here, we report a dual targeted extracellular vesicle (dtEV) carrying high loads of therapeutic RNA that effectively suppresses large PDAC tumours in mice. The EV surface contains a CD64 protein that has a tissue targeting peptide and a humanized monoclonal antibody. Cells sequentially transfected with plasmid DNAs encoding for the RNA and protein of interest by Transwell®-based asymmetric cell electroporation release abundant targeted EVs with high RNA loading. Together with a low dose chemotherapy drug, Gemcitabine, dtEVs suppress large orthotopic PANC-1 and patient derived xenograft tumours and metastasis in mice and extended animal survival. Our work presents a clinically accessible and scalable way to produce abundant EVs for delivering multiple gene cargoes to large solid tumours.

Inorganic arsenic in drinking water accelerates N-butyl-N-(4-hydroxybutyl)nitrosamine-induced bladder tissue damage in mice.

Epidemiological studies have revealed that exposure to an arsenic-contaminated environment correlates with the incidence of bladder cancer. Bladder cancer is highly recurrent after intravesical therapy, and most of the deaths from this disease are due to invasive metastasis. In our present study, the role of inorganic arsenic in bladder carcinogenesis is characterized in a mouse model. This work provides the first evidence that inorganic arsenic in drinking water promotes N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN)-induced bladder tissue damage, including the urothelium and submucosal layer. This damage to the bladder epithelium induced by BBN includes thickening of the submucosal layer, the loss of the glycosaminoglycan layer and an increase in both the deoxyguanosine oxidation and cytosine methylation levels in the DNA. Further, when 10ppm inorganic arsenic is combined with BBN, the number of bladder submucosal capillaries is increased. In addition, inorganic arsenic also increases the deoxyguanosine oxidation level, alters the cytosine methylation state, decreases the activities of glutathione reductase and glucose-6-phosphate dehydrogenase, decreases the protein expression of NAD(P)H quinone oxidoreductase-1 (NQO-1) and increases the protein expression of specific protein 1 (Sp1) in bladder tissues. In summary, our data reveal that inorganic arsenic in drinking water promotes the BBN-induced pre-neoplastic damage of bladder tissue in mice, and that the 8-hydroxy-2'-deoxyguanosine, 5-methylcytosine, NQO-1 protein and Sp1 protein levels may be pre-neoplastic markers of bladder tumors.

Filling-Balance-Oriented Parameters for Multi-Cavity Molds in Polyvinyl Chloride Injection Molding.

PVC injection molding has constrained temperature and shear rate owing to its temperature sensitivity and high viscosity, as well as its low conductivity. Many challenges are associated with the PVC injection molding process used for producing PVC fittings with a multi-cavity mold. Once filling imbalance occurs, the gates and/or runner of the mold should be changed by machine tools, which is time- and cost-intensive. Using Moldex3D and the Taguchi method, this study reveals an approach to eliminate imbalanced filling of multi-cavity molds for PVC injection molding. The injection rate optimization of the filling stage is successfully verified to reduce the imbalance. Furthermore, the temperatures of the molded PVC fittings are only slightly increased by the change in injection rate. The temperatures of fittings in the filling and packing are lower than the degradation temperature of PVC. This approach may help technicians to obtain pilot-run samples for the optimization of molding parameters and ensure degradation-free PVC molding.

Inorganic Flame-Retardant Coatings Based on Magnesium Potassium Phosphate Hydrate.

A magnesium potassium phosphate hydrate-based flame-retardant coating (MKPC) is formulated by dead-burnt magnesium oxide (magnesia) and potassium dihydrogen phosphate (KH2PO4), behaving as a matrix. Constituents of the MKPC include wollastonite, vermiculite, aluminum fluoride, aluminum trihydroxide, and calcium carbonate. Some of the ingredients inter-react to produce mullite whiskers at high temperatures, despite an acid-base hydration induced reaction between magnesia and KH2PO4. The MKPC's thermal, corrosion-resistant, mechanical, and flame-resistant properties were analyzed using scanning electron microscopy, electrochemical corrosion testing, compression testing, thermogravimetric analysis, and freeze/thaw tests. The results show that with the molar ratio = 4 of magnesia to KH2PO4, MKPC demonstrates lower thermal conductivity (0.19 W/m K), along with better corrosion resistance, stronger compressive strength (10.5 MPa), and higher bonding strength (6.62 kgf/cm2) to the steel substrate. Furthermore, acceptable additives to the formulation could enhance its flame-retardancy and increase its mechanical strength as well. Mullite whisker formed from the interaction of wollastonite, aluminum trihydroxide, and aluminum fluoride acts as an outer ceramic shield that enhances mechanical strength and compactness. In addition, Mg-containing minerals with calcium carbonate treated at high temperatures, transform into magnesium calcium carbonate after releasing CO2. At the optimum composition of MKPC (magnesia/KH2PO4 molar ratio = 4; wollastonite:vermiculite = 20:10 wt.%; aluminum trihydroxide = 10 wt.%; and calcium carbonate = 5 wt.%), coated on a steel substrate, the flame-resistance limit results exhibit below 200 °C on the back surface of the steel substrate after one hour of flaming (ca. 1000 °C) on the other surface, and the flame-resistance rating results demonstrate only 420 °C on the back surface of the steel substrate after three hours of flaming (>1000 °C) on the other surface. Both requirements for the flame-resistance limit and three-hour flame-resistance rating are met with the optimum compositions, indicating that MKPC plays an effective role in establishing flame-retardancy.

Factors and Outcomes Associated with Failed Noninvasive Positive Pressure Ventilation in Patients with Acute Respiratory Failure.

Background: The decision guild for non-invasive positive pressure ventilation (NPPV) application in acute respiratory failure (ARF) patients still needs to work out. Methods: Adult patients with acute hypoxemic or hypercapnic respiratory failure were recruited and treated with NPPV or primary invasive mechanical ventilation (IMV). Patients' characteristic and clinical outcomes were recorded. Logistic regression models were used to estimate the adjusted odds ratio (aOR) and 95% confidence intervals for baseline characteristics and clinical outcomes. Subgroup analyses by reason behind successful NPPV were conducted to ascertain if any difference could influence the outcome. Results: A total of 4525 ARF patients were recruited in our facility between year 2015 and 2017. After exclusion, 844 IMV patients, 66 patients with failed NPPV, and 74 patients with successful NPPV were enrolled. Statistical analysis showed APACHE II score (aOR = 0.93), time between admission and start NPPV (aOR = 0.92), and P/F ratio (aOR = 1.04) were associated with successful NPPV. When comparing with IMV patients, failed NPPV patients displayed a significantly lower APACHE II score, higher Glasgow Coma Scale, longer length of stay in hospital, longer duration of invasive ventilation, RCW/Home ventilator, and some comorbidities. Conclusion: APACHE II score, time between admission and start NPPV, and PaO2 can be predictors for successful NPPV. The decision of NPPV application is critical as ARF patients with failed NPPV have various worse outcomes than patients receiving primary IMV.