Predicting Natural Rubber Crystallinity by a Novel Machine Learning Algorithm Based on Molecular Dynamics Simulation Data.

Natural rubber (NR) with excellent mechanical properties, mainly attributed to its strain-induced crystallization (SIC), has garnered significant scientific and technological interest. With the aid of molecular dynamics (MD) simulations, we can investigate the impacts of crucial structural elements on SIC on the molecular scale. Nonetheless, the computational complexity and time-consuming nature of this high-precision method constrain its widespread application. The integration of machine learning with MD represents a promising avenue for enhancing the speed of simulations while maintaining accuracy. Herein, we developed a crystallinity algorithm tailored to the SIC properties of natural rubber materials. With the data enhancement algorithm, the high evaluation value of the prediction model ensures the accuracy of the computational simulation results. In contrast to the direct utilization of small sample prediction algorithms, we propose a novel concept grounded in feature engineering. The proposed machine learning (ML) methodology consists of (1) An eXtreme Gradient Boosting (XGB) model to predict the crystallinity of NR; (2) a generative adversarial network (GAN) data augmentation algorithm to optimize the utilization of the limited training data, which is utilized to construct the XGB prediction model; (3) an elaboration of the effects induced by phospholipid and protein percentage (ω), hydrogen bond strength (εH), and non-hydrogen bond strength (εNH) of natural rubber materials with crystallinity prediction under dynamic conditions are analyzed by employing weight integration with feature importance analysis. Eventually, we succeeded in concluding that εH has the most significant effect on the strain-induced crystallinity, followed by ω and finally εNH.

Electrospinning Superassembled Mesoporous AIEgen-Organosilica Frameworks Featuring Diversified Forms and Superstability for Wearable and Washable Solid-State Fluorescence Smart Sensors.

Flexible optical sensors are widely studied and applied in many fields. However, developing highly stable and washable wearable sensors in optics is still facing significant challenges. Here, we demonstrate an AIEgen-organosilica framework (TPEPMO) hybrid nanostructure-based flexible optical sensor, which is prepared by a two-step co-condensation and electrospinning superassembly process. Organosilica precursors with aggregation-induced emission (AIE) features are covalently linked into periodic mesoporous organosilica (PMO) frameworks with high fluorescent efficiency due to the restriction of intramolecular motion. The three-dimensional space of ordered porous materials provides abundant reaction sites, allowing rapid and sensitive monitoring of analytes. TPEPMOs exhibit good properties as acidic pH fluorescent sensors with a pKa of 4.3. A flexible film is obtained by dispersing TPEPMO nanospheres in a poly(lactic-co-glycolic acid) (PLGA) and polyacrylonitrile (PAN) hybrid fibrous matrix (TPEPMO-CFs) using the electrospinning superassembly technique and is successfully served as an efficient fluorescent probe for the naked eye detection of ammonia gas and HCl vapor by emission changes. The fluorescence of TPEPMO-CFs can be reversed in the presence of volatile acidic/alkaline gas for more than five cycles, exhibiting excellent recyclability. In addition, TPEPMO-CF sensors show excellent washability and long-term photostability (fluorescence was maintained above 94% after washing 10 times). These stimuli-responsive AIEgen-organosilica frameworks featuring diversified forms and superstability for wearable and washable solid-state fluorescence exhibit great potential for smart gas sensors, wearable devices, and solid-state lighting applications.

Investigating the Effect of APAP Crystals on Tablet Behavior Manufactured by Direct Compression.

In this work, the effect of API's (Active Pharmaceutical Ingredient) shape and size on tablet characteristics is investigated for high API dose formulation manufactured by direct compression. Three different classes of APAP (acetaminophen) are selected, and tablets are produced in both single and batch processes. After performing and comparing comprehensive series of standard characterization tests including hardness, dissolution, disintegration, and friability on the tablets, the test results show the relation between the quality of APAP tablets and the shape and size of the crystals. We also investigate the effect of scaling up the manufacturing process (from single to batch) by evaluating dosage uniformity and possibility of segregation in blends. The results indicate a strong interaction between manufacturing parameters such as speed and scale of production to API crystal size and shape. This places crystal properties in the critical parameter set that requires tracking and monitoring in order to maintain consistent tablet properties in high-dose formulation continuous manufacturing operations.

Mixing Cell: a Device to Mimic Extent of Lubrication and Shear in Continuous Tubular Blenders.

Continuous manufacturing (CM) has clear potential for manufacturing solid oral dosages. It provides several advantages that may aid the manufacturing and quality of drug products. However, one of the main challenges of this technology is the relatively large amount of knowledge required and the amounts of material needed to develop the process during the early stages of development. Early process development evaluations of continuous manufacturing equipment often require larger amounts of material compared with batch, which hinder CM prospect for drugs during the early stages of process development. In this work, a small-scale evaluation of the mixing process occurring in a continuous mixing system was performed. The evaluation involved the use of a small-scale "mixing cell" which was able to replicate the lubrication process of a continuous mixer. It is worth mentioning that we designed the mixing cell by reconfiguration of an existing continuous tubular blender. The extent of lubrication evaluation was performed for three example formulations and was done by mimicking the amount of shear provided to a formulation by means of matching the number of paddle-passes that a formulation experiences within a continuous blending process in the batch mixing cell. The evaluation showed that the small-scale mixing cell was able to replicate the extent of lubrication-evaluated by measuring the tensile strength of compacts being made with both the continuous and mixing cell experiments-occurring in the continuous mixer using a fraction of the amount of materials needed to perform the same evaluation in the continuous blending process.

Capillary Drop Penetration Method to Characterize the Liquid Wetting of Powders.

We present a method to characterize the wettability of powders, based on the penetration dynamics of a sessile drop deposited on a slightly compressed powder bed. First, we show that a direct comparison of the wetting properties of different liquids is possible without having to solve the three-dimensional liquid penetration problem, by considering the appropriate dimensionless variables. We show that the contact area between the sessile drop and the powder bed remains constant during most of the penetration process and demonstrate that as a result, the evolution of the dimensionless penetration volume is given by a universal function of the dimensionless time, with no dimensionless parameters. Then, using a reference liquid that completely wets the powder, it is possible to obtain an effective contact angle for a test liquid of interest, independent of other properties of the powder bed, such as permeability and a characteristic pore size. We apply the proposed method to estimate the contact angle of water with different powder blends, by using silicone oil as the reference liquid. Finally, to highlight the potential of the proposed method to characterize pharmaceutical powders, we consider a blend of lactose, acetaminophen, and a small amount of lubricant (magnesium stearate). The proposed method adequately captures a significant decrease in hydrophilicity that results from exposing the blend to excessive mixing, a well-known effect in the pharmaceutical industry.

A microRNA 221- and 222-mediated feedback loop maintains constitutive activation of NFκB and STAT3 in colorectal cancer cells.

BACKGROUND & AIMS: Constitutive activation of the transcription factors nuclear factor κB (NF-κB) and STAT3 is involved in the development and progression of human colorectal cancer (CRC). Little is known about how these factors become activated in cancer cells. We investigated whether microRNA miR-221 and miR-222 regulate NF-κB and signal transducer and activator of transcription 3 (STAT3) activation in human CRC cell lines. METHODS: CRC cell lines (HCT116 and RKO) were transfected with miR-221 or miR-222 mimics or inhibitors. The activity levels of NF-κB and STAT3 were measured in dual luciferase reporter assays. We used immunoblot and real-time polymerase chain reaction analyses to measure protein and messenger RNA (mRNA) levels. Cells were analyzed by proliferation, viability, and flow cytometry analyses. Mice were given injections of azoxymethane, followed by dextran sodium sulfate, along with control lentivirus or those expressing mRNAs that bind miR-221 and miR-222 (miR-221/miR-222 sponge). The levels of miR-221 and miR-222 as well as RelA, STAT3, and PDLIM2 mRNAs were measured in 57 paired CRC and adjacent nontumor tissues from patients. RESULTS: In CRC cell lines, mimics of miR-221 and miR-222 activated NF-κB and STAT3, further increasing expression of miR-221 and miR-222. miR-221 and miR-222 bound directly to the coding region of RelA mRNA, increasing its stability. miR-221 and miR-222 also reduced the ubiquitination and degradation of the RelA and STAT3 proteins by binding to the 3' untranslated region of PDLIM2 mRNA (PDLIM2 is a nuclear ubiquitin E3 ligase for RelA and STAT3). Incubation of CRC cells with miR-221 and miR-222 inhibitors reduced their proliferation and colony formation compared with control cells. In mice with colitis, injection of lentiviruses expressing miR-221/miR-222 sponges led to formation of fewer tumors than injection of control lentiviruses. Human CRC tissues had higher levels of miR-221 and miR-222 than nontumor colon tissues; increases correlated with increased levels of RelA and STAT3 mRNAs. Levels of PDLIM2 mRNA were lower in CRC than nontumor tissues. CONCLUSIONS: In human CRC cells, miR-221 and miR-222 act in a positive feedback loop to increase expression levels of RelA and STAT3. Antagonism of miR-221 and miR-222 reduces growth of colon tumors in mice with colitis.

Gel-confined fabrication of fully bio-based filtration membrane for green capture and rapid detection of airborne microbes.

Air filtration has become a desirable route for collecting airborne microbes. However, the potential biotoxicity and sterilization of current air filtration membranes often lead to undesired inactivation of captured microbes, which greatly limits microbial non-traumatic transfer and recovery. Herein, we report a gel-confined phase separation strategy to rationally fabricate a fully bio-based filtration membrane (SGFM) using soluble soybean polysaccharide and gelatin. The versatile SGFM features fascinating honeycomb micro-nano architecture and hierarchical interconnected porous structures for microbial capture, and achieves a lower pressure drop, higher interception efficiency (99.3%), and superior microbial survivability than commercial gelatin filtration membranes. Particularly, the water-dissolvable SGFM can greatly simplify the elution and extraction process after bioaerosol sampling, thereby bringing about maximum sample transfer and vigorous recovery of collected microbes. Meanwhile, green capture coupled with ATP bioluminescence endows the SGFM with rapid and quantitative detection capability for airborne microbes. This work may pave the way for designing green protocols for the detection of bioaerosols.

Versatile filter membrane for effective sampling and real-time quantitative detection of airborne pathogens.

Construction of air filter membranes bearing prominent collecting and transferring capability is highly desirable for detecting airborne pathogens but remains challenging. Here, a hyaluronic acid air filter membrane (HAFM) with tunable heterogeneous micro-nano porous structures is straightforwardly constructed through the ethanol-induced phase separation strategy. Airborne pathogens can be trapped and collected by HAFM with high performance due to the ideal trade-off between removal efficiency and pressure drop. By exempting the sample elution and extraction processes, the HAFM after filtration sampling can not only directly disperse on the agar plate for colony culture but also turn to an aqueous solution for centrifugal enrichment, which significantly reduces the damage and losses of the captured microorganisms. The following combination with ATP bioluminescence endows the HAFM with a real-time quantitative detection function for the captured airborne pathogens. Benefiting from high-efficiency sampling and non-traumatic transfer of airborne pathogens, the real-world bioaerosol concentration can be facilely evaluated by the HAFM-based ATP assay. This work thus not only provides a feasible strategy to fabricate air filter membranes for efficient microbial collection and enrichment but also sheds light on designing advanced protocols for real-time detection of bioaerosols in the field.

Exploration of Potential Diagnostic Value of Protein Content in Serum Small Extracellular Vesicles for Early-Stage Epithelial Ovarian Carcinoma.

Epithelial ovarian carcinoma (EOC) is one of the most common gynecologic malignancies with a high mortality rate. Serum biomarkers and imaging approaches are insufficient in identifying EOC patients at an early stage. This study is to set up a combination of proteins from serum small extracellular vesicles (sEVs) for the diagnosis of early-stage EOC and to determine its performance. A biomarker for early-stage ovarian cancer (BESOC) cohort was used as a Chinese multi-center population-based biomarker study and registered as a Chinese Clinical Trial ChiCTR2000040136. The sEV protein levels of CA125, HE4, and C5a were measured in 299 subjects. Logistic regression was exploited to calculate the odds ratio and to create the sEV protein model for the predicted probability and subsequently receiver-operating characteristic (ROC) analysis. The combined sEV marker panel of CA125, HE4, and C5a as a sEV model obtained an area under curve (AUC) of 0.912, which was greater than the serum model (0.809), by ROC analysis to identify EOC patients from the whole cohort. With the cutoff of 0.370, the sensitivity and specificity of the sEV model were 0.80 and 0.89, which were much better performance than the serum markers (sensitivity: 0.55~0.66; specificity: 0.59~0.68) and the risk of ovarian malignancy algorithm (ROMA) index approved by the U.S. Food and Drug Administration (sensitivity: 0.65; specificity: 0.61), to identify EOC patients from patients with benign ovarian diseases or other controls. The sEV levels of CA125 significantly differed among early-stage and late-stage EOC (p < 0.001). Moreover, the AUC of ROC to identify early-stage EOC patients was 0.888. Further investigation revealed that the sEV levels of these 3 proteins significantly decreased after cytoreductive surgery (CA125, p = 0.008; HE4, p = 0.025; C5a, p = 0.044). In summary, our study showed that CA125, HE4, and C5a levels in serum sEVs can identify EOC patients at the early stage, elucidating the possibility of using a sEV model for the diagnosis of early-stage EOC.

A drop penetration method to measure powder blend wettability.

Water wettability of pharmaceutical blends affects important quality attributes of final products. We investigate the wetting properties of a pharmaceutical blend lubricated with Magnesium Stearate (MgSt) as a function of the mechanical shear strain applied to the blend. We measure the penetration dynamics of sessile drops deposited on slightly compressed powder beds. We consider a blend composed of 9% Acetaminophen 90% Lactose and 1% MgSt by weight. Comparing the penetration time of water and a reference liquid Polydimethylsiloxane (silicon oil) we obtain an effective cosine of the contact angle with water, based on a recently developed drop penetration method. We repeat the experiments for blends exposed to increasing levels of shear strain and demonstrate a significant decrease in water wettability (decrease in the cosine of the contact angle). The results are consistent with the development of a hydrophobic film coating the powder particles as a result of the increased shear strain. Finally, we show that, as expected dissolution times increase with the level of shear strain. Therefore, the proposed drop penetration method could be used to directly assess the state of lubrication of a pharmaceutical blend and act as a quality control on powder blend attributes before the blend is tableted.