Predictions of Milk Fatty Acid Contents by Mid-Infrared Spectroscopy in Chinese Holstein Cows.

Genetic improvement of milk fatty acid content traits in dairy cattle is of great significance. However, chromatography-based methods to measure milk fatty acid content have several disadvantages. Thus, quick and accurate predictions of various milk fatty acid contents based on the mid-infrared spectrum (MIRS) from dairy herd improvement (DHI) data are essential and meaningful to expand the amount of phenotypic data available. In this study, 24 kinds of milk fatty acid concentrations were measured from the milk samples of 336 Holstein cows in Shandong Province, China, using the gas chromatography (GC) technique, which simultaneously produced MIRS values for the prediction of fatty acids. After quantification by the GC technique, milk fatty acid contents expressed as g/100 g of milk (milk-basis) and g/100 g of fat (fat-basis) were processed by five spectral pre-processing algorithms: first-order derivative (DER1), second-order derivative (DER2), multiple scattering correction (MSC), standard normal transform (SNV), and Savitzky-Golsy convolution smoothing (SG), and four regression models: random forest regression (RFR), partial least square regression (PLSR), least absolute shrinkage and selection operator regression (LassoR), and ridge regression (RidgeR). Two ranges of wavebands (4000~400 cm-1 and 3017~2823 cm-1/1805~1734 cm-1) were also used in the above analysis. The prediction accuracy was evaluated using a 10-fold cross validation procedure, with the ratio of the training set and the test set as 3:1, where the determination coefficient (R2) and residual predictive deviation (RPD) were used for evaluations. The results showed that 17 out of 31 milk fatty acids were accurately predicted using MIRS, with RPD values higher than 2 and R2 values higher than 0.75. In addition, 16 out of 31 fatty acids were accurately predicted by RFR, indicating that the ensemble learning model potentially resulted in a higher prediction accuracy. Meanwhile, DER1, DER2 and SG pre-processing algorithms led to high prediction accuracy for most fatty acids. In summary, these results imply that the application of MIRS to predict the fatty acid contents of milk is feasible.

Tunable In Situ Synthesis of Ultrathin Extracellular Matrix-Derived Membranes in Organ-on-a-Chip Devices.

Thin cell culture membranes in organ-on-a-chip (OOC) devices are used to model a wide range of thin tissues. While early and most current platforms use microporous or fibrous elastomeric or thermoplastic membranes, there is an emerging class of devices using extra-cellular matrix (ECM) protein-based membranes to improve their biological relevance. These ECM-based membranes present physiologically relevant properties, but they are difficult to integrate into OOC devices due to their relative fragility. Additionally, the specialized fabrication methods developed to date make comparison between methods difficult. This work presents the development and characterization of a method to produce ultrathin matrix-derived membranes (UMM) in OOC devices that requires only a preassembled thermoplastic device and a micropipette, decoupling the device and UMM fabrication processes. Control over the thickness and permeability of the UMM is demonstrated, along with integration of the UMM in a device enabling high-resolution on-chip microscopy. The reliability of the UMM fabrication method is leveraged to develop a medium-throughput well-plate format device with 32 independent UMM-integrated samples. Finally, proof-of-concept cell culture experiments are demonstrated. Due to its simplicity and controllability, the presented method has the potential to overcome technical barriers preventing wider adoption of physiologically relevant ECM-based membranes in OOC devices.

A review of potential neuropathological changes associated with ketamine.

INTRODUCTION: Ketamine is an established intervention for treatment-resistant depression (TRD). However, long-term adverse effects with repeated doses remain insufficiently characterized. Although several animal models have shown N-methyl-D-aspartate glutamate receptor antagonists to produce various neuropathological reactions, attention surrounding the risk of brain lesions has been minimal. AREAS COVERED: The current review focuses on potential neuropathological changes associated with ketamine. Search terms included variations of ketamine, Olney lesions, tau hyperphosphorylation, and parvalbumin interneurons. EXPERT OPINION: Daily high-dose ketamine use in substance use disorder (SUD) populations was associated with clear neurotoxic effects, while no studies specifically evaluated effects of ketamine protocols used for TRD. It is difficult to discern effects directly attributable to ketamine due to methodological factors, such as comorbidities and dramatic differences in dose in SUD populations versus infrequent sub-anesthetic doses typically prescribed for TRD. Taken together, animal models and human ketamine SUD populations suggest potential neuropathology with chronic high-dose ketamine exposure exceeding those recommended for adults with TRD. It is unknown whether repeat sub-anesthetic dosing of ketamine in adults with TRD is associated with Olney lesions or other neuropathologies. In the interim, practitioners should be vigilant for this possibility recognizing that the condition itself is associated with neurodegenerative processes.