Synthesis and characterization of lactide from Bacillus amyloliquefaciens brewed lactic acid utilizing cheap agricultural sources.

Lactic acid (LA) is a nifty molecule with an eclectic range of applications in innumerable industries and is produced through biological and chemical processes. Factually, LA is converted into lactide (LAC), which is the precursor for polylactic acid (PLA). PLA is considered one of the first-rate replacements for petroleum-based products and is believed to be environmentally sustainable. Nevertheless, it has always been challenging due to increased PLA productivity costs. Reduction in the LA and LAC production price directly echoes the production price of PLA. Therefore, low-cost LA and LAC production methods have to be found to produce PLA effectively. Hence, this study uses cheap agricultural sources derived microbial LA to make LAC through dimerization. Produced LAC was analyzed through FT-IR, NMR, TGA and XRD. FT-IR results revealed that the successful dimerization of LA to LAC, NMR analysis revealed that the aligning of methine and methyl groups in produced LAC, TGA analysis exposed that the microbial LAC has more thermal stability than the commercial LAC, XRD results showed that the produced LACs are crystalline with 32% and 42% crystallinity. To the best of our acquaintance, this manuscript is pioneering one to describe LA production through microbial fermentation and uses this monomer to produce LAC through dimerization.

Recent trends in lactic acid-producing microorganisms through microbial fermentation for the synthesis of polylactic acid.

Polylactic acid (PLA) is a range of unique bioplastics that are bio-based and biodegradable. PLA is currently driving market expansion for lactic acid (LA) due to its high demand as a building block in production. One of the most practical and environmentally benign techniques for synthesising PLA is through enzymatic polymerisation of microbial LA monomers. However, microbial LA fermentation does have some limitations. Firstly, it requires the use of a nutritionally rich medium. Secondly, LA production can be disrupted by bacteriophage infection or other microorganisms. Lastly, the yield can be low due to the formation of by-products through heterofermentative pathway. Considering the potential use of PLA as a replacement for conventional petrochemical-based polymers in industrial applications, researchers are focused on exploring the diversity of LA-producing microorganisms from various niches. Their goal is to study the functional properties of these microorganisms and their ability to produce industrially valuable metabolites. This review highlights the advantages and disadvantages of lactic acid-producing microorganisms used in microbial fermentation for PLA synthesis.

Optimization of sodium alginate-galactoxyloglucan blended hydrogel beads through ionotropic gelation method.

Hydrogels are 3D crosslinking networks of hydrophilic biopolymers which can able to absorb and retain large amount of water. In this present study, the Sodium alginate (SA)- Galactoxyloglucan (GXG) blended hydrogel beads were prepared and optimized through two level optimization steps. Alginate and xyloglucan are the cell wall polysaccharides biopolymers obtained from the plant sources, Sargassum sp. and Tamarindus indica L. respectively. The extracted biopolymers were confirmed and characterized by UV-Spectroscopy, FT-IR, NMR and TGA analysis. Based on the hydrophilicity, non-toxicity and biocompatibility, SA-GXG hydrogel were prepared and optimized through two-level optimization steps. The optimized hydrogel bead formulation was characterized through FT-IR, TGA and SEM analysis. From the obtained result, it is found that the polymeric formulation GXG (2 % w/v)-SA (1.5 % w/v), cross-linker (CaCl2) concentration at 0.1 M and the cross-linking time at 15 Min showed significant swelling index. The optimized hydrogel beads are porous and show good swelling capacity and thermal stability. The optimized protocol of hydrogel beads may be useful in designing hydrogel beads for specific applications in agricultural, Biomedical and remediation sectors.

Machine Learning-Based Continuous Intracranial Pressure Prediction for Traumatic Injury Patients.

Structured Abstract-Objective: Abnormal elevation of intracranial pressure (ICP) can cause dangerous or even fatal outcomes. The early detection of high intracranial pressure events can be crucial in saving lives in an intensive care unit (ICU). Despite many applications of machine learning (ML) techniques related to clinical diagnosis, ML applications for continuous ICP detection or short-term predictions have been rarely reported. This study proposes an efficient method of applying an artificial recurrent neural network on the early prediction of ICP evaluation continuously for TBI patients. Methods: After ICP data preprocessing, the learning model is generated for thirteen patients to continuously predict the ICP signal occurrence and classify events for the upcoming 10 minutes by inputting the previous 20-minutes of the ICP signal. Results: As the overall model performance, the average accuracy is 94.62%, the average sensitivity is 74.91%, the average specificity is 94.83%, and the average root mean square error is approximately 2.18 mmHg. Conclusion: This research addresses a significant clinical problem with the management of traumatic brain injury patients. The machine learning model data enables early prediction of ICP continuously in a real-time fashion, which is crucial for appropriate clinical interventions. The results show that our machine learning-based model has high adaptive performance, accuracy, and efficiency.

Inadequacy of Augmentation Index for Monitoring Arterial Stiffness: Comparison with Arterial Compliance and Other Hemodynamic Variables.

PURPOSE: Augmentation Index (AIx) is used clinically for monitoring both wave reflections and arterial stiffness, which when increased is a risk factor of cardiovascular mortality and morbidity. We hypothesize that AIx is not solely related to vascular stiffness as described by arterial compliance and other hemodynamic parameters since AIx underestimates wave reflections. METHODS: Aortic pressure and flow datasets (n = 42) from mongrel dogs were obtained from our experiments and Mendeley Data under various conditions. Arterial compliances based on the Windkessel model (Ct), the stroke volume (SV) to pulse pressure (PP) ratio (Cv = SV/PP), and at inflection pressure point (CPi) were computed. Other relevant hemodynamic factors are also computed. RESULTS: AIx was poorly associated with arterial stiffness calculated from Ct (r = 0.299, p = 0.058) or CPi (r = 0.203, p = 0.203), even when adjusted for heart rates. Ct and Cv were monotonically associated. Alterations in inflection pressure (Pi) did not follow the changes in pulse pressure (PP) (r = 0.475, p = 0.002), and Pi was quantitatively similar to systolic pressure (r = 0.940, p < 0.001). CONCLUSION: AIx is neither linearly correlated with arterial stiffness, nor with arterial compliance and several cardiac and arterial parameters have to be considered when AIx is calculated.

Noninvasive Glucose Monitor Using Dielectric Spectroscopy.

OBJECTIVE: The Alertgy noninvasive continuous glucose monitor (ANICGM) is a novel wristband device that reports glucose levels without entailing skin puncture. This study evaluated the performance of the ANICGM compared to a Food and Drug Administration-approved glucose meter in patients with type 2 diabetes. METHODS: The ANICGM device measures changes in the electromagnetic field generated by its sensor to produce a dielectric spectrum. The data contained within this spectrum are used in tandem with machine learning algorithms to estimate blood glucose levels. Values from the ANICGM were collected, sent to the Alertgy lab, formatted, and compared with fingerstick blood glucose levels, which were measured using the Accuchek Inform II glucometer. Fifteen patients completed three 120-minute sessions. The mean absolute relative difference (MARD) was calculated. RESULTS: MARD values were compared between study days 2 and 3. The MARD for day 2 was 18.5% (95% CI, 12.8-42.2%), and the MARD for day 3 was 15.3% (95% CI, 12.3-18.4%). The difference in the MARD between days 2 and 3 was not statistically significant (P = .210). CONCLUSION: The resulting MARDs suggest that further investigation into the use of dielectric spectroscopy for glucose monitoring should be explored.

Stress Analysis Based on Simultaneous Heart Rate Variability and EEG Monitoring.

OBJECTIVE: Stress is a significant risk factor for various diseases such as hypertension, heart attack, stroke, and even sudden death. Stress can also lead to psychological and behavioral disorders. Heart rate variability (HRV) can reflect changes in stress levels while other physiological factors, like blood pressure, are within acceptable ranges. Electroencephalogram (EEG) is a vital technique for studying brain activities and provides useful data regarding changes in mental status. This study incorporates EEG and a detailed HRV analysis to have a better understanding and analysis of stress. Investigating the correlation between EEG and HRV under stress conditions is valuable since they provide complementary information regarding stress. METHODS: Simultaneous electrocardiogram (ECG) and EEG recordings were obtained from fifteen subjects. HRV /EEG features were analyzed and compared in rest, stress, and meditation conditions. A one-way ANOVA and correlation coefficient were used for statistical analysis to explore the correlation between HRV features and features extracted from EEG. RESULTS: The HRV features LF (low frequency), HF (high frequency), LF/HF, and rMSSD (root mean square of the successive differences) correlated with EEG features, including alpha power band in the left hemisphere and alpha band power asymmetry. CONCLUSION: This study demonstrated five significant relationships between EEG and HRV features associated with stress. The ability to use stress-related EEG features in combination with correlated HRV features could help improve detecting stress and monitoring the progress of stress treatments/therapies. The outcomes of this study could enhance the efficiency of stress management technologies such as meditation studies and bio-feedback training.

Environmental DNA reveals aquatic biodiversity of an urban backwater area, southeast coast of India.

Strong conservation management needs comprehensive data on biodiversity. Rapid methods that document aquatic biodiversity or assess the health condition of an ecosystem remain scarce. Herein, we have performed a metagenomics study on environmental DNA (eDNA) collected from an urban backwater area - Muttukadu, located in the southeast coast of India. Shotgun metagenomics approach using Illumina®NextSeq500 sequencing yielded 88.4 million raw reads. The processed data was assigned as 80% prokaryotes, 0.4% eukaryotes, ~2% viruses, and ~17% remain unknown. This approach has the potential to identify small micro-eukaryote, unseen species from both estuarine and marine environments. We have identified 156 eukaryote organisms represented from 21 phyla and 112 families, including those that are of conservational significance and ecological importance. Furthermore, our data also demonstrated the presence of pathogenic microorganisms due to sewage mixing with the backwaters. Given its sensitivity, we suggest this approach for an initial assessment of biodiversity structure in an ecosystem for the biomonitoring program.

Preliminary Comparison of Zero-Gravity Chair With Tilt Table in Relation to Heart Rate Variability Measurements.

Heart rate variability (HRV) measurements are performed using a tilt-table (TT) to diagnose dysfunctionality in the autonomic nervous system (ANS) and the cardiovascular system. To maintain homeostasis, the ANS adapts to body position changes through alterations in sympathetic and parasympathetic responses that can be quantified by extracting time-domain and frequency-domain parameters from the heart rate signal. When body position is changed from supine to erect, a healthy subject's response also shows changes in ANS activity. However, TT can be unsafe or uncomfortable for elderly or overweight subjects. Furthermore, it may induce anxiety which alters the HRV measurements. This study proposes an alternative strategy to replace the TT with a zero-gravity chair (ZGC). The statistical analysis between HRV parameters from the TT and the ZGC shows that ZGC can be a feasible alternative to TT. Therefore, ZGC can be used as a more convenient, secure, stable and safer option to the traditional HRV analysis with TT.

Augmentation index in the assessment of wave reflections and systolic loading.

BACKGROUND: Augmentation index (AIx) is used to quantify the augmented systolic aortic pressure that impedes ventricular ejection. Its use as an index of wave reflections is questionable. We hypothesize that AIx is quantitatively different from the reflection coefficient under varied physiological conditions. METHODS: 42 datasets of aortic pressure and flow waveforms were obtained during induced hypertension (methoxamine infusion) and vasodilation (nitroprusside infusion) in our mongrel dog experiments (n = 5) and from Mendeley data during various interventions (vasoconstrictors, vasodilators, pacing, stimulation, hemorrhage and hemodilution). Wave reflections and principal components of reflection coefficients were computed for comparison to AIx and heart rate normalized AIx. RESULTS: Principal reflection coefficient, Γ1, increased in hypertension and decreased in vasodilation, hemorrhage and hemodilution. AIx followed the trend in many cases but was consistently lower than Γ1 in almost all the subjects. The Bland-Altman analysis also showed that both AIx and normalized AIx underestimated Γ1. The relationship between augmentation index and reflection coefficient was explained by a linear regression model (r2 = 0.23, p < 0.01) in which AIx followed directional changes in Γ1 and the normalization of AIx resulted in a linear model that explained less variation in the relationship between AIx and Γ1. CONCLUSION: AIx is a reasonable clinical trend indicator, albeit not an accurate surrogate measure of the amount of wave reflections.

Energetically wasteful wave reflections due to impedance mismatching in hypertension and their reversal with vasodilator: Time and frequency domain evaluations.

BACKGROUND: Increased pulse wave reflections in hypertension arise due to impedance mismatching and the effective energy transmission to the vasculature is compromised. Their quantification in the time and the frequency domains are compared and the beneficial effect of vasodilator is evaluated in the study. METHODS: A simple, fast time domain method for the resolution of aortic pressure and flow pulses into their forward and reflected components is presented, together with frequency domain reflection coefficient and impedance calculations. Both steady and pulsatile energy components are quantified during induced hypertension (HBP) and subsequent vasodilator (VSD, nitroprusside) treatment in experimental mongrel dogs. Corresponding power generation and usage are also analyzed. RESULTS: Characteristic impedance and peripheral resistance were not statistically different between the methods (p > 0.05). Time domain reflection coefficient identified significant differences among control, HBP and VSD groups (p < 0.05) while the frequency domain method did not adequately differentiate the control and the HBP groups. Impedance calculations were similar between the two methods. Frequency domain calculations of total, mean and pulsatile power were, on average, 32.6 mW higher, 12.8 mW lower and 45.4 mW higher than their respective time domain calculations (p < 0.05). Hypertension increased energy consumption, on average, by 88.8 mJ (p < 0.05) and subsequent VSD decreased the energy consumption, on average, by 99.4 mJ (p < 0.05). CONCLUSION: Impedance mismatching in hypertension which leads to increased wave reflections and significantly increased pulsatile work, could be effectively alleviated through vasodilator therapy. This can be quantified through the time-domain method, which is fast and equally accurate as the time-consuming frequency domain approach. The time domain method to quantify crucial parameters such as stroke work cannot be readily determined using the frequency domain methods.

Myocardial oxygen balance during acute normovolemic hemodilution: A novel compartmental modeling approach.

BACKGROUND: Hemodilution was introduced initially as a blood conservation technique to reduce allogeneic blood transfusion in patients undergoing surgical procedures. Although the technique has been approved by the National Institute of Health consensus panel, limits of hemodilution under anesthetic conditions have not been established as they have in animal models. METHODS: A novel multi-compartmental modeling approach has been proposed that includes the effect of anesthesia to quantify the effect of hemodilution on myocardial oxygen balance during myocardial ischemia. RESULTS: The results showed that isovolemic hemodilution would cause detrimental effects around a hematocrit of 15%. Even though the fall in oxygen content caused by the decrease in hemoglobin concentration was compensated by an increase in coronary blood flow induced by hypoxic vasodilation and decreased viscosity, the endocardial tissue received less oxygen compared to the epicardial regions, and this sub-endocardial ischemia eventually led to cardiac failure. Statistical analysis also showed that the type of acellular replacement fluid failed to affect the heart rate, the stroke index or the cardiac index during hemodilution, and supplemental oxygen improved the endocardial oxygen supply. CONCLUSION: The model validates the clinical conclusions that sub-endocardial ischemia causes cardiac failure under extreme hemodilution conditions and the model can also be easily integrated into other human simulators.

A novel compliance-pressure loop approach to quantify arterial compliance in systole and in diastole.

Arterial compliance has been recognized as a critical parameter in governing pulsatile flow dynamics. It has traditionally been assumed constant throughout the cardiac cycle and its computation has been based either on the classic Windkessel model (C) in diastole or the stroke volume over pulse pressure (Cv) method in systole. Other methods using area (Cam) or two-area (Ctam) and exponential (C(P)exp1) methods were used for the cardiac cycle. We proposed a novel compliance-pressure loop (CPP loop) approach for the quantification of arterial compliance and compared it to existing linear and nonlinear methods. Experimental data were gathered in 5 dogs and blood pressure levels were varied (systolic pressure of 100 mmHg-185 mmHg) with induced hypertension and vasodilation. Results showed the limited regime of validity of C (Control:0.4681 ±â€¯0.1270 ml/mmHg, MTX:0.3015 ±â€¯0.1264 ml/mmHg and NTP:1.8323 ±â€¯0.7207 ml/mmHg) and Cv (Control:0.3583 ±â€¯0.0158 ml/mmHg, MTX:0.2602 ±â€¯0.1275 ml/mmHg and NTP:0.4131 ±â€¯0.0589 ml/mmHg), Cam (Control:0.4175 ±â€¯0.0505, MTX:0.3086 ±â€¯0.1568 and NTP:1.4181 ±â€¯0.4812) and Ctam (Control: 0.2064 ±â€¯0.0228 ml/mmHg, MTX:0.1967 ±â€¯0.0884 ml/mmHg, NTP:0.0881 ±â€¯0.0375 ml/mmHg) and that C(P)exp1 underestimates the arterial compliance compared to our method (Control:0.2233 ±â€¯0.0168 ml/mmHg vs 0.4481 ±â€¯0.0515 ml/mmHg, MTX:0.1976 ±â€¯0.0964 ml/mmHg vs 0.3273 ±â€¯0.1443 ml/mmHg and NTP: 0.2177 ±â€¯0.0273 ml/mmHg vs 1.9990 ±â€¯1.8221 ml/mmHg at mean arterial pressure). The CPP method based on the exponential method is superior, as it provides continuous compliance variations and CPP loop area can be readily visualized from hypotension to hypertension conditions. We conclude that the concept of using compliance-pressure loop is advantageous as it can afford continuous and accurate tracking of the dynamic arterial behavior despite greatly varying blood pressure levels.