Tag: nevin manimala

Int Microbiol. 2021 Aug 7. doi: 10.1007/s10123-021-00199-5. Online ahead of print.

ABSTRACT

Naringin, considered as the main bitter component of grapefruit, requires the use of enzymes to reduce the level of this substance during juice processing. For this reason, it has been the focus of many studies. In this study, to increase the production of naringinase by Aspergillus niger cultivated in solid-state fermentation (SSF), a three-component simplex-centric mixing design along with a response surface methodology (RSM) was applied to generate statistical models and analyze the dataset. First, grapefruit peel, rice bran, and wheat bran were used for substrate selection for naringinase production and, finally, selected the best of the three inducers or their mixtures to remove the bitterness of grapefruit juice. Cultivation with 2.3 g of grapefruit peel, 2.5 g of rice bran, and 5.2 g of wheat bran and medium supplementation with a mixture of naringin, rutin, and hesperidin in the concentration of 2, 5, 4.5, and 3.0 g/L, respectively, resulted in a maximum activity of 28 U/mL. The results indicate that the sequencing procedure, which allowed the definition of an optimal mixture of components, is a new way for microorganisms to have a high naringinase yield, in particular by SSF, since our data showed a 96% increase in the production of naringinase. This dataset can help other researchers apply a mixing design to increase enzyme production.

PMID:34363150 | DOI:10.1007/s10123-021-00199-5

Prostate Cancer Prostatic Dis. 2021 Aug 6. doi: 10.1038/s41391-021-00433-1. Online ahead of print.

ABSTRACT

PURPOSE: Prostate cancer is a heterogeneous disease with variable clinical outcomes. Despite numerous recent approvals of novel therapies, castration-resistant prostate cancer remains lethal. A “real-world” clinical-genomic database is urgently needed to enhance our characterization of advanced prostate cancer and further enable precision oncology.

METHODS: The Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) is a consortium whose aims are to establish a repository of de-identified clinical and genomic patient data that are linked to patient outcomes. The consortium structure includes a (1) bio-informatics committee to standardize genomic data and provide quality control, (2) biostatistics committee to independently perform statistical analyses, (3) executive committee to review and select proposals of relevant questions for the consortium to address, (4) diversity/inclusion committee to address important clinical questions pertaining to racial disparities, and (5) patient advocacy committee to understand patient perspectives to improve patients’ quality of care.

RESULTS: The PROMISE consortium was formed by 16 academic institutions in early 2020 and a secure RedCap database was created. The first patient record was entered into the database in April 2020 and over 1000 records have been entered as of early 2021. Data entry is proceeding as planned with the goal to have over 2500 patient records by the end of 2021.

CONCLUSIONS: The PROMISE consortium provides a powerful clinical-genomic platform to interrogate and address data gaps that have arisen with increased genomic testing in the clinical management of prostate cancer. The dataset incorporates data from patient populations that are often underrepresented in clinical trials, generates new hypotheses to direct further research, and addresses important clinical questions that are otherwise difficult to investigate in prospective studies.

PMID:34363009 | DOI:10.1038/s41391-021-00433-1

J Trop Pediatr. 2021 Jul 2;67(3):fmab060. doi: 10.1093/tropej/fmab060.

ABSTRACT

BACKGROUND: With Nigeria being one of the countries with the highest neonatal mortality rate globally, identifying the risk factors associated with neonatal mortality is essential as we strive to proffer sustainable solutions.

AIM: This retrospective hospital-based survey aimed to bridge this gap by evaluating the trends and risk factors associated with neonatal mortality in a teaching hospital in Southwestern Nigeria.

METHODS: Records of newborns admitted at the special care baby unit from January 2018 to December 2019 (n = 1098) were accessed, and available data were extracted. Descriptive analysis and inferential statistics were performed at 0.05 level of significance.

RESULTS: The mortality rate was determined to be 16.9% (inborn babies- 12.9% and out-born babies- 22.3%), with 83.3% of the newborns dying within the first week. Some of the factors associated with neonatal mortality were proximity of newborns’ mothers home to the hospital [p = 0.041; Odds Ratio (OR) = 0.670; 95% Confidence Interval (CI) = 0.455-0.985], maturity of the baby at delivery (p < 0.001; OR = 0.514; CI = 0.358-0.738), place of delivery-inborn or out-born (p < 0.001; OR = 0.515; CI = 0.375-0.709), place of delivery-in a hospital or a non-hospital setting (p = 0.048; OR = 0.633; CI = 0.401-0.999), and baby’s weight (p < 0.001; CI = -0.684 to -0.411).

CONCLUSION: Findings from the study indicate that newborns delivered at home, traditional birth attendant centres or hospitals without essential healthcare facilities have a higher mortality risk. This suggests that measures to improve the accessibility of pregnant women to essential healthcare services are a prerequisite to reducing the neonatal mortality rate in Nigeria.

PMID:34363078 | DOI:10.1093/tropej/fmab060

J Mol Model. 2021 Aug 7;27(9):239. doi: 10.1007/s00894-021-04852-8.

ABSTRACT

Protein kinases (in this case, HER-2 and EGFR) are involved in cancer-related diseases. Some reports have shown unique CoMFA models using the sum of activities expressed as pIC₅₀ (-log IC₅₀), as the classical CoMFA technique would not be the best strategy to construct models for multitarget therapy considering that the molecular alignment will not be the same for different targets. An alternative for this problem is the use of Topomer-CoMFA, a variation of CoMFA, which does not require the alignment step in the generation of 3D models. In this study, we propose the combined use of the sum of activities and Topomer-CoMFA for the construction of a unique dual 3D model considering the inhibitory activities against EGFR and HER-2. For this, 88 compounds from the literature were divided into two groups: training (71) and test (17) sets. The biological activity of each compound, expressed as IC₅₀ for EGFR and HER-2, was transformed into pIC₅₀, summed, and used as the dependent variable in the Topomer-CoMFA analyses. The obtained model was considered statistically robust in the prediction of the dual activity of new compounds. Finally, based on the obtained model, we proposed structural modifications to some of the compounds used to improve the biological data. From the 3D model, we suggested new derivative compounds with improved biological activity for both targets. Therefore, the combination of the techniques proposed in this study proves to be a good strategy to construct better statistical models that can predict biological activities in multitarget systems.

PMID:34363097 | DOI:10.1007/s00894-021-04852-8

Sci Rep. 2021 Aug 6;11(1):16014. doi: 10.1038/s41598-021-95282-2.

ABSTRACT

The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15-20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation -being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness.

PMID:34362950 | DOI:10.1038/s41598-021-95282-2

Sci Rep. 2021 Aug 6;11(1):16030. doi: 10.1038/s41598-021-95587-2.

ABSTRACT

In this study, a mathematical model is developed to scrutinize the transient magnetic flow of Cross nanoliquid past a stretching sheet with thermal radiation effects. Binary chemical reactions and heat source/sink effects along with convective boundary condition are also taken into the consideration. Appropriate similarity transformations are utilized to transform partial differential equations (PDE’s) into ordinary ones and then numerically tackled by shooting method. The impacts of different emerging parameters on the thermal, concentration, velocity, and micro-rotation profiles are incorporated and discussed in detail by means of graphs. Results reveal that, the escalation in magnetic parameter and Rayleigh number slowdowns the velocity and momentum of the fluid. The increase in Biot number, radiation and heat sink/source parameters upsurges the thermal boundary but, converse trend is seen for escalating Prandtl number. The density number of motile microorganisms acts as a growing function of bioconvection Lewis number and declining function of bioconvection Peclet number.

PMID:34362971 | DOI:10.1038/s41598-021-95587-2

Nat Commun. 2021 Aug 6;12(1):4754. doi: 10.1038/s41467-021-25099-0.

ABSTRACT

Chaperonins are homo- or hetero-oligomeric complexes that use ATP binding and hydrolysis to facilitate protein folding. ATP hydrolysis exhibits both positive and negative cooperativity. The mechanism by which chaperonins coordinate ATP utilization in their multiple subunits remains unclear. Here we use cryoEM to study ATP binding in the homo-oligomeric archaeal chaperonin from Methanococcus maripaludis (MmCpn), consisting of two stacked rings composed of eight identical subunits each. Using a series of image classification steps, we obtained different structural snapshots of individual chaperonins undergoing the nucleotide binding process. We identified nucleotide-bound and free states of individual subunits in each chaperonin, allowing us to determine the ATP occupancy state of each MmCpn particle. We observe distinctive tertiary and quaternary structures reflecting variations in nucleotide occupancy and subunit conformations in each chaperonin complex. Detailed analysis of the nucleotide distribution in each MmCpn complex indicates that individual ATP binding events occur in a statistically random manner for MmCpn, both within and across the rings. Our findings illustrate the power of cryoEM to characterize a biochemical property of multi-subunit ligand binding cooperativity at the individual particle level.

PMID:34362932 | DOI:10.1038/s41467-021-25099-0

Sci Rep. 2021 Aug 6;11(1):16050. doi: 10.1038/s41598-021-93921-2.

ABSTRACT

A remarkable approach for grasping the relevant statistical features of real networks with the help of random graphs is offered by hyperbolic models, centred around the idea of placing nodes in a low-dimensional hyperbolic space, and connecting node pairs with a probability depending on the hyperbolic distance. It is widely appreciated that these models can generate random graphs that are small-world, highly clustered and scale-free at the same time; thus, reproducing the most fundamental common features of real networks. In the present work, we focus on a less well-known property of the popularity-similarity optimisation model and the [Formula: see text] model from this model family, namely that the networks generated by these approaches also contain communities for a wide range of the parameters, which was certainly not an intention at the design of the models. We extracted the communities from the studied networks using well-established community finding methods such as Louvain, Infomap and label propagation. The observed high modularity values indicate that the community structure can become very pronounced under certain conditions. In addition, the modules found by the different algorithms show good consistency, implying that these are indeed relevant and apparent structural units. Since the appearance of communities is rather common in networks representing real systems as well, this feature of hyperbolic models makes them even more suitable for describing real networks than thought before.

PMID:34362942 | DOI:10.1038/s41598-021-93921-2

J Neurol Neurosurg Psychiatry. 2021 Aug 6:jnnp-2021-326386. doi: 10.1136/jnnp-2021-326386. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate longitudinal brain atrophy in patients with neuromyelitis optica spectrum disorder (NMOSD).

METHODS: We investigated the longitudinal brain atrophy rate in patients with aquaporin-4 antibody-positive NMOSD (AQP4+NMOSD) and those with multiple sclerosis (MS) in a retrospective cohort study. Brain volume was calculated with statistical parametric mapping-12.

RESULTS: We enrolled 36 patients with AQP4+NMOSD and 60 with MS. Patients with NMOSD were older and had a higher Kurtzke’s expanded disability status scale score at baseline MRI compared with those with MS. Disease duration, annual relapse rate and intervals from the last attack and from disease-modifying drugs initiation were not significantly different between the two groups. Lower normalised lesion volume and higher normalised white matter volume were found in patients with NMOSD compared with those with MS at baseline MRI. However, the annualised atrophy rate of normalised brain volume was similar between the NMOSD (median 0.47; IQR 0.75; p=0.49) and MS (median 0.46; IQR 0.84) groups. After adjustment of age and the presence of clinical relapse, no differences of the annualised atrophy rate of normalised brain volume also were found for NMOSD and MS. Patients with AQP4+NMOSD with long cord lesion showed higher annualised atrophy rate of normalised grey matter volume compared with those without long cord lesion.

CONCLUSIONS: Silent progression of brain atrophy was present in patients with AQP4+NMOSD, as shown in patients with MS, even in the clinically inactive age-matched cases. Subclinical dying back degeneration may explain the brain atrophy in patients with AQP4 +NMOSD.

PMID:34362853 | DOI:10.1136/jnnp-2021-326386

Nat Commun. 2021 Aug 6;12(1):4763. doi: 10.1038/s41467-021-25089-2.

ABSTRACT

The comparison of gene regulatory networks between diseased versus healthy individuals or between two different treatments is an important scientific problem. Here, we propose sc-compReg as a method for the comparative analysis of gene expression regulatory networks between two conditions using single cell gene expression (scRNA-seq) and single cell chromatin accessibility data (scATAC-seq). Our software, sc-compReg, can be used as a stand-alone package that provides joint clustering and embedding of the cells from both scRNA-seq and scATAC-seq, and the construction of differential regulatory networks across two conditions. We apply the method to compare the gene regulatory networks of an individual with chronic lymphocytic leukemia (CLL) versus a healthy control. The analysis reveals a tumor-specific B cell subpopulation in the CLL patient and identifies TOX2 as a potential regulator of this subpopulation.

PMID:34362918 | DOI:10.1038/s41467-021-25089-2