Prebiotic potential of Azolla pinnata (R.Br.) and dietary inclusion effect of pulverised azolla on the growth performance of milkfish fingerlings

The growth of the aquaculture sector leads to a demand for sustainable feed ingredients. Prebiotics are potential sustainable feed ingredients that can promote the improved performance of aquaculture species without the use of antimicrobials. This study investigated the potential of Azolla pinnata as a candidate prebiotic source. Prebiotic characteristics and dietary effect of commercial diet (CD) with varying pulverised azolla (PA) inclusion was evaluated. Results showed that PA (9.40% moisture) constitutes around 16.1% ash, 22.3% crude fibre, 20.9% crude protein, 1.7% crude fat and 29.6% nitrogen-free extract. Crude xylan and cellulose content of PA were 13.7% and 12.6% dry matter (DM) respectively. Growth of Lactobacillus rhamnosus in PA-supplemented MRS broth remarkably improved after 4 to 6 hours of incubation. Feeding trials results revealed that PA inclusion had no adverse effect on average survival of milkfish fingerlings, albeit significant improvement (p < 0.01) was noted in group fed with 2% PA-replaced CD in terms of the total weight gain (119.9%), specific growth rate (2.62% day–1) and feed efficiency (79.9%). The present study demonstrated the prebiotic activity of PA, as well as its potential use as dietary feed component for improved growth and feed efficiency of cultured milkfish

BIOCONVERSION OF CITROFORTUNELLA MICROCARPA FRUIT WASTE INTO LACTIC ACID BY LACTOBACILLUS PLANTARUM

The processing of Citrofortunella mircocarpa fruit juice generates large volume of solid waste, causing disposal problem. Several studies have demonstrated that wastes from agricultural and food processing industries such as fruit and vegetable peels contain high amount of polysaccharides that can be transformed into useful chemicals, including lactic acid, through fermentation. Lactic acid is widely used in various industries, such as in the manufacture of biodegradable plastic, and the demand for this chemical justifies the search of renewable feedstock for its biotechnological production. This study aimed to produce lactic acid from C. microcarpa fruit waste biomass through fermentation with Lactobacillus plantarum. The hydrolysate from C. microcarpa fruit waste was prepared, inoculated with different amounts of L. plantarum cell suspension, and incubated for three days. Lactic acid production was monitored daily. The lactic acid produced from the fermentation was precipitated as calcium lactate crystals. The identity of the crystals was evaluated using Fourier transform infrared spectroscopy (FTIR) spectroscopy and paper chromatography. The highest lactic acid production was observed in fermentation mixtures containing the highest number of L. plantarum cells. Within three days of fermentation, the amount of lactic acid production increased with increasing period of incubation. Partial characterization of the crystals recovered from the fermentation mixtures by FTIR spectroscopy showed that the peaks in the spectrum were consistent with the chemical structure of lactate. Paper chromatography results likewise confirmed that the crystals are lactate. C. microcarpa fruit waste can afford lactic acid when fermented with L. plantarum. The results of the study may serve as basis for the development of technology for the utilization of C. microcarpa fruit waste biomass as renewable resource for industrial production of lactic acid

Valorizing fish processing waste: Production of protein hydrolysates from milkfish (Chanos chanos) by-products using acid hydrolysis

Milkfish (Chanos chanos) by-products were used as raw material for the production of protein hydrolysates. Acid hydrolysis was performed at 121 °C for 90 min at 15 psi using various concentrations of hydrochloric acid (4, 6, and 8M). The protein hydrolysates were characterized for the degree of hydrolysis (DH), and antioxidant and other functional food properties. The yield obtained ranged from 5.14±0.42% to 6.08±1.53%. High DH was observed at a high acid concentration with 43.88±9.50% DH for 8M HCl. Regarding the functional food properties, solubility of over 80% over a wide range of pH (2-12) was observed, and emulsifying and foaming properties were found to depend on the pH (2-10). As for the antioxidant activity, 8M exhibited the highest antioxidant activity among the three treatments. The results showed that milkfish by-products have potential to serve as raw material for protein hydrolysates that can be used as ingredients for food formulations

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Distilled Spirit Extraction of Phenolic Antioxidants from Fruit and Vegetable Residues

There is a growing interest in natural antioxidants due to their potential in improving the quality of food and cosmetic products and their health-promoting properties. Distilled spirits contain high amount of ethanol and may be an alternative to the food-grade solvents, while agricultural by-products contain phenolic substances that may have antioxidant properties. This study was therefore conducted to find out if gin, vodka, and tequila flavored spirit, alcoholic beverages with about 40% ethanol, can extract the phenolic compounds from agricultural by-products, and to determine if the extracts possess the antioxidant activity. Peels of ripe banana (Musa acuminata), ripe mango (Mangifera indica), calamansi (Citrofortunella microcarpa), squash (Cucurbita maxima), ripe pineapple (Ananas comosus), purple yam (Dioscorea alata), and sweet potato (Ipomea batatas) were collected, dried, and ground. The phenolic substances in the plant materials were extracted with alcoholic beverages or 40% ethanol. The total phenolic content (TPC) of the extracts was determined by means of UV-Vis spectroscopy using Folin-Ciocalteau reagent and gallic acid as reference compound. The antioxidant activity of the extracts was evaluated through the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay. Butylated hydroxyanisole (BHA) served as positive control in the DPPH assay. Non-linear regression was applied to the DPPH assay data to estimate the values of median effective concentration (EC50). All three alcoholic beverages were able to extract the phenolic materials from the plant samples. However, the ability of vodka and gin to extract the phenolic substances was either statistically comparable or better than 40% ethanol. The results of the DPPH scavenging assay showed that the M. indica peel had the strongest activity, while C. microcarpa had the weakest scavenging activity. At 1000-ppm level, the antioxidant activity of the M. indica peel was comparable with that of BHA, regardless of the solvent used for extraction. Therefore, the M. indica peel can be a source of natural antioxidants and potential substitute to synthetic antioxidants. Both gin and vodka can be used as a substitute for food-compatible solvents

An application of generalized matrix learning vector quantization in neuroimaging

Background and objective: Neurodegenerative diseases like Parkinson’s disease often take several years before they can be diagnosed reliably based on clinical grounds. Imaging techniques such as MRI are used to detect anatomical (structural) pathological changes. However, these kinds of changes are usually seen only late in the development. The measurement of functional brain activity by means of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) can provide useful information, but its interpretation is more difficult. The scaled sub-profile model principal component analysis (SSM/PCA) was shown to provide more useful information than other statistical techniques. Our objective is to improve the performance further by combining SSM/PCA and prototype-based generalized matrix learning vector quantization (GMLVQ). Methods: We apply a combination of SSM/PCA and GMLVQ as a classifier. In order to demonstrate the combination’s validity, we analyze FDG-PET data of Parkinson’s disease (PD) patients collected at three different neuroimaging centers in Europe. We determine the diagnostic performance by performing a ten times repeated ten fold cross validation. Additionally, discriminant visualizations of the data are included. The prototypes and relevance of GMLVQ are transformed back to the original voxel space by exploiting the linearity of SSM/PCA. The resulting prototypes and relevance profiles have then been assessed by three neurologists. Results: One important finding is that discriminative visualization can help to identify disease-related properties as well as differences which are due to center-specific factors. Secondly, the neurologist assessed the interpretability of the method and confirmed that prototypes are similar to known activity profiles of PD patients. Conclusion: We have shown that the presented combination of SSM/PCA and GMLVQ can provide useful means to assess and better understand characteristic differences in FDG-PET data from PD patients and HCs. Based on the assessments by medical experts and the results of our computational analysis we conclude that the first steps towards a diagnostic support system have been taken successfully

An application of generalized matrix learning vector quantization in neuroimaging

Background and objective: Neurodegenerative diseases like Parkinson’s disease often take several years before they can be diagnosed reliably based on clinical grounds. Imaging techniques such as MRI are used to detect anatomical (structural) pathological changes. However, these kinds of changes are usually seen only late in the development. The measurement of functional brain activity by means of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) can provide useful information, but its interpretation is more difficult. The scaled sub-profile model principal component analysis (SSM/PCA) was shown to provide more useful information than other statistical techniques. Our objective is to improve the performance further by combining SSM/PCA and prototype-based generalized matrix learning vector quantization (GMLVQ). Methods: We apply a combination of SSM/PCA and GMLVQ as a classifier. In order to demonstrate the combination’s validity, we analyze FDG-PET data of Parkinson’s disease (PD) patients collected at three different neuroimaging centers in Europe. We determine the diagnostic performance by performing a ten times repeated ten fold cross validation. Additionally, discriminant visualizations of the data are included. The prototypes and relevance of GMLVQ are transformed back to the original voxel space by exploiting the linearity of SSM/PCA. The resulting prototypes and relevance profiles have then been assessed by three neurologists. Results: One important finding is that discriminative visualization can help to identify disease-related properties as well as differences which are due to center-specific factors. Secondly, the neurologist assessed the interpretability of the method and confirmed that prototypes are similar to known activity profiles of PD patients. Conclusion: We have shown that the presented combination of SSM/PCA and GMLVQ can provide useful means to assess and better understand characteristic differences in FDG-PET data from PD patients and HCs. Based on the assessments by medical experts and the results of our computational analysis we conclude that the first steps towards a diagnostic support system have been taken successfully