Polyketide Quinones Are Alternate Intermediate Electron Carriers during Mycobacterial Respiration in Oxygen-Deficient Niches.

Mycobacterium tuberculosis (Mtb) adaptation to hypoxia is considered crucial to its prolonged latent persistence in humans. Mtb lesions are known to contain physiologically heterogeneous microenvironments that bring about differential responses from bacteria. Here we exploit metabolic variability within biofilm cells to identify alternate respiratory polyketide quinones (PkQs) from both Mycobacterium smegmatis (Msmeg) and Mtb. PkQs are specifically expressed in biofilms and other oxygen-deficient niches to maintain cellular bioenergetics. Under such conditions, these metabolites function as mobile electron carriers in the respiratory electron transport chain. In the absence of PkQs, mycobacteria escape from the hypoxic core of biofilms and prefer oxygen-rich conditions. Unlike the ubiquitous isoprenoid pathway for the biosynthesis of respiratory quinones, PkQs are produced by type III polyketide synthases using fatty acyl-CoA precursors. The biosynthetic pathway is conserved in several other bacterial genomes, and our study reveals a redox-balancing chemicocellular process in microbial physiology.

COVID-19 pandemic: Insights into structure, function, and hACE2 receptor recognition by SARS-CoV-2.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a newly emerging, highly transmissible, and pathogenic coronavirus in humans that has caused global public health emergencies and economic crises. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism(s) through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor-binding domain (RBD) of the spike (S) glycoprotein to recognize angiotensin-converting enzyme 2 (ACE2) receptors on the human cells; this initiates host-cell entry by promoting viral-host cell membrane fusion through large-scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the structure of RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 and its significance in drug discovery and explain the receptor recognition mechanisms of coronaviruses. Further, we provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins and their receptor-binding specificity and discuss the differences in their antigenicity based on biophysical and structural characteristics.

RRBP1 rewires cisplatin resistance in oral squamous cell carcinoma by regulating Hippo pathway.

BACKGROUND: Chemoresistance is one of the major factors for treatment failure in OSCC. Identifying key resistance triggering molecules will be useful strategy for developing novel treatment methods. METHODS: To identify the causative factors of chemoresistance, we performed RNA sequencing and global proteomic profiling of human OSCC lines presenting with sensitive, early and late cisplatin-resistance patterns. RESULTS: From the common set of dysregulated genes from both the analysis, RRBP1 was identified to be upregulated in both early and late cisplatin-resistant cells with respect to the sensitive counterpart. Analysis of OSCC patient sample indicates that RRBP1 expression is upregulated in chemotherapy-non-responder tumours as compared to chemotherapy-responder tumours. Genetic (knockout) or pharmacological (Radezolid, represses expression of RRBP1) inhibition of RRBP1 restores cisplatin-mediated cell death in chemo-resistant OSCC. Mechanistically, RRBP1 regulates Yes-associated protein1 (YAP1), a key protein in the Hippo pathway to induce chemoresistance. The PDC xenograft data suggests that knockout of RRBP1 induces cisplatin-mediated cell death and facilitates a significant reduction of tumour burden. CONCLUSION: Overall, our data suggests that (I) RRBP1 is a major driver of cisplatin-resistance in OSCC, (II) RRBP1 regulates YAP1 expression to mediate cisplatin-resistance, (III) Radezolid represses RRBP1 expression and (IV) targeting RRBP1 reverses cisplatin-induced chemoresistance in advanced OSCC.

The phytochemical bergenin as an adjunct immunotherapy for tuberculosis in mice.

The widespread availability and use of modern synthetic therapeutic agents have led to a massive decline in ethnomedical therapies. However, these synthetic agents often possess toxicity leading to various adverse effects. For instance, anti-tubercular treatment (ATT) is toxic, lengthy, and severely impairs host immunity, resulting in posttreatment vulnerability to reinfection and reactivation of tuberculosis (TB). Incomplete ATT enhances the risk for the generation of multidrug- or extensively drug-resistant (MDR or XDR, respectively) variants of Mycobacterium tuberculosis (M. tb), the TB-causing microbe. Therefore, a new therapeutic approach that minimizes these risks is urgently needed to combat this deadly disease and prevent future TB epidemics. Previously, we have shown that the phytochemical bergenin induces T helper 1 (Th1)- and Th17 cell-based protective immune responses and potently inhibits mycobacterial growth in a murine model of M. tb infection, suggesting bergenin as a potential adjunct agent to TB therapy. Here, we combined ATT therapy with bergenin and found that this combination reduces immune impairment and the length of treatment in mice. We observed that co-treatment with the anti-TB drug isoniazid and bergenin produces additive effects and significantly reduces bacterial loads compared with isoniazid treatment alone. The bergenin co-treatment also reduced isoniazid-induced immune impairment; promoted long-lasting, antigen-specific central memory T cell responses; and acted as a self-propelled vaccine. Of note, bergenin treatment significantly reduced the bacterial burden of a multidrug-resistant TB strain. These observations suggest that bergenin is a potent immunomodulatory agent that could be further explored as a potential adjunct to TB therapy.

Metabolomic fingerprinting and systemic inflammatory profiling of asthma COPD overlap (ACO).

BACKGROUND: Asthma-COPD overlap (ACO) refers to a group of poorly studied and characterised patients reporting with disease presentations of both asthma and COPD, thereby making both diagnosis and treatment challenging for the clinicians. They exhibit a higher burden in terms of both mortality and morbidity in comparison to patients with only asthma or COPD. The pathophysiology of the disease and its existence as a unique disease entity remains unclear. The present study aims to determine whether ACO has a distinct metabolic and immunological mediator profile in comparison to asthma and COPD. METHODS: Global metabolomic profiling using two different groups of patients [discovery (D) and validation (V)] were conducted. Serum samples obtained from moderate and severe asthma [n = 34(D); n = 32(V)], moderate and severe COPD [n = 30(D); 32(V)], ACO patients [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using gas chromatography mass spectrometry (GC-MS). Multiplexed analysis of 25 immunological markers (IFN-γ (interferon gamma), TNF-α (tumor necrosis factor alpha), IL-12p70 (interleukin 12p70), IL-2, IL-4, IL-5, IL-13, IL-10, IL-1α, IL-1ß, TGF-ß (transforming growth factor), IL-6, IL-17E, IL-21, IL-23, eotaxin, GM-CSF (granulocyte macrophage-colony stimulating factor), IFN-α (interferon alpha), IL-18, NGAL (neutrophil gelatinase-associated lipocalin), periostin, TSLP (thymic stromal lymphopoietin), MCP-1 (monocyte chemoattractant protein- 1), YKL-40 (chitinase 3 like 1) and IL-8) was also performed in the discovery cohort. RESULTS: Eleven metabolites [serine, threonine, ethanolamine, glucose, cholesterol, 2-palmitoylglycerol, stearic acid, lactic acid, linoleic acid, D-mannose and succinic acid] were found to be significantly altered in ACO as compared with asthma and COPD. The levels and expression trends were successfully validated in a fresh cohort of subjects. Thirteen immunological mediators including TNFα, IL-1ß, IL-17E, GM-CSF, IL-18, NGAL, IL-5, IL-10, MCP-1, YKL-40, IFN-γ, IL-6 and TGF-ß showed distinct expression patterns in ACO. These markers and metabolites exhibited significant correlation with each other and also with lung function parameters. CONCLUSIONS: The energy metabolites, cholesterol and fatty acids correlated significantly with the immunological mediators, suggesting existence of a possible link between the inflammatory status of these patients and impaired metabolism. The present findings could be possibly extended to better define the ACO diagnostic criteria, management and tailoring therapies exclusively for the disease.

Essential amino acid profiling of the four lac hosts belonging to genus Flemingia: its implications on lac productivity.

The Indian lac insect (Kerria lacca), a hemipteran, phloem sap sucking sedentary insect is an important bioresource which thrives on tender twigs of more than 400 plant species belonging to various genera and families. The most common commercial host plants for lac cultivation are big trees hence cultivation was concentrated mainly to dense forests across the country till last decade. Recently, a new bushy host plant belonging to the genus Flemingia has been introduced so that lac can be cultivated on farmlands like other cash crops. The insect is sedentary and feeds on the phloem sap of the host plants, the only source of its nutrition. Interestingly, the biological attributes of the insect as well as the qualitative and quantitative production of lac is influenced by the host plant on which the insect feeds upon. The present study was thus aimed at deciphering the effect of phloem sap constituents obtained from four plant host taxa belonging to the same genus Flemingia viz. F. semialata, F. macrophylla, F. bracteata and F. chapar (essential amino acids only-EAAs) on lac productivity. Moreover, a newer method for phloem sap collection i.e. Dot-blot in addition to the facilitated exudation using EDTA was also investigated. Dot-blot method for phloem sap collection also came out to be a promising method for field studies; although slightly higher concentration of EAAs were obtained from EDTA method, thus the later was used for further analysis. Phloem sap of four plant host taxa belonging to the same genus Flemingia were qualitatively and quantitatively analysed for seven EAAs (Arginine, Glycine, Leucine, Methionine, Phenylalanine Tyrosine and Valine). Amino acid concentration regime and further analysis done using statistical tools (ANOVA and PCA) points out the EAA concentration in the phloem sap is in congruency with the lac production data obtained through previous studies as F. semialata > F. macrophylla > F. chapar > F. bracteata. The present study thus scientifically points out that F. semialata can be a promising plant for lac cultivation on the basis of higher EAA content as compared to the rest three.

Estimation of nuclear DNA content and its variation among Indian Tea accessions by flow cytometry.

Nuclear DNA content and genome size variation among 36 Indian tea accessions were analyzed by flow cytometry. Initial standardization of protocols for isolation of nuclei, DNA staining and selection of an internal standard for tea accessions which have significantly high amount of phenolic secondary metabolites in their cytosol was carried out. Results obtained revealed that 2C DNA content of Indian tea is 7.46 pg which corresponds to 1C genome size of 3673 Mb. Inter accession variation in 2C DNA content was also observed among 35 diploid taxa ranging from 7.23 to 7.73 pg which was significant at 1% probability level. The 2C DNA content of triploid (UPASI 3) was observed to be 11.47 pg which is concurrent with the expected value. Results obtained showed that Assam and Cambod type tea accession have higher 2C DNA content of 7.73 pg whereas Assam Cambod hybrids and Assam China hybrids have reduction in DNA content with 2C amounts, 7.23 and 7.32 pg DNA respectively. The present study suggests that the species involved in origin of Indian tea must have differed in their genome sizes owing to significant inter accession variation in nuclear DNA content.

Improving PET/MR brain quantitation with template-enhanced ZTE.

PURPOSE: The impact of MR-based attenuation correction on PET quantitation accuracy is an ongoing cause of concern for advanced brain research with PET/MR. The purpose of this study was to evaluate a new, template-enhanced zero-echo-time attenuation correction method for PET/MR scanners. METHODS: 30 subjects underwent a clinically-indicated 18F-FDG-PET/CT, followed by PET/MR on a GE SIGNA PET/MR. For each patient, a 42-s zero echo time (ZTE) sequence was used to generate two attenuation maps: one with the standard ZTE segmentation-based method; and another with a modification of the method, wherein pre-registered anatomical templates and CT data were used to enhance the segmentation. CT data, was used as gold standard. Reconstructed PET images were qualified visually and quantified in 68 volumes-of-interest using a standardized brain atlas. RESULTS: Attenuation maps were successfully generated in all cases, without manual intervention or parameter tuning. One patient was excluded from the quantitative analysis due to the presence of multiple brain metastases. The PET bias with template-enhanced ZTE attenuation correction was measured to be -0.9% ±â€¯0.9%, compared with -1.4% ±â€¯1.1% with regular ZTE attenuation correction. In terms of absolute bias, the new method yielded 1.1% ±â€¯0.7%, compared with 1.6% ±â€¯0.9% with regular ZTE. Statistically significant bias reduction was obtained in the frontal region (from -2.0% to -1.0%), temporal (from -1.2% to -0.2%), parietal (from -1.9% to -1.1%), occipital (from -2.0% to -1.1%) and insula (from -1.4% to -1.1%). CONCLUSION: These results indicate that the co-registration of pre-recorded anatomical templates to ZTE data is feasible in clinical practice and can be effectively used to improve the performance of segmentation-based attenuation correction.

Zero TE-based pseudo-CT image conversion in the head and its application in PET/MR attenuation correction and MR-guided radiation therapy planning.

PURPOSE: To describe a method for converting Zero TE (ZTE) MR images into X-ray attenuation information in the form of pseudo-CT images and demonstrate its performance for (1) attenuation correction (AC) in PET/MR and (2) dose planning in MR-guided radiation therapy planning (RTP). METHODS: Proton density-weighted ZTE images were acquired as input for MR-based pseudo-CT conversion, providing (1) efficient capture of short-lived bone signals, (2) flat soft-tissue contrast, and (3) fast and robust 3D MR imaging. After bias correction and normalization, the images were segmented into bone, soft-tissue, and air by means of thresholding and morphological refinements. Fixed Hounsfield replacement values were assigned for air (-1000 HU) and soft-tissue (+42 HU), whereas continuous linear mapping was used for bone. RESULTS: The obtained ZTE-derived pseudo-CT images accurately resembled the true CT images (i.e., Dice coefficient for bone overlap of 0.73 ± 0.08 and mean absolute error of 123 ± 25 HU evaluated over the whole head, including errors from residual registration mismatches in the neck and mouth regions). The linear bone mapping accounted for bone density variations. Averaged across five patients, ZTE-based AC demonstrated a PET error of -0.04 ± 1.68% relative to CT-based AC. Similarly, for RTP assessed in eight patients, the absolute dose difference over the target volume was found to be 0.23 ± 0.42%. CONCLUSION: The described method enables MR to pseudo-CT image conversion for the head in an accurate, robust, and fast manner without relying on anatomical prior knowledge. Potential applications include PET/MR-AC, and MR-guided RTP.

Zero TE MR bone imaging in the head.

PURPOSE: To investigate proton density (PD)-weighted zero TE (ZT) imaging for morphological depiction and segmentation of cranial bone structures. METHODS: A rotating ultra-fast imaging sequence (RUFIS) type ZT pulse sequence was developed and optimized for 1) efficient capture of short T2 bone signals and 2) flat PD response for soft-tissues. An inverse logarithmic image scaling (i.e., -log(image)) was used to highlight bone and differentiate it from surrounding soft-tissue and air. Furthermore, a histogram-based bias-correction method was developed for subsequent threshold-based air, soft-tissue, and bone segmentation. RESULTS: PD-weighted ZT imaging in combination with an inverse logarithmic scaling was found to provide excellent depiction of cranial bone structures. In combination with bias correction, also excellent segmentation results were achieved. A two-dimensional histogram analysis demonstrates a strong, approximately linear correlation between inverse log-scaled ZT and low-dose CT for Hounsfield units (HU) between -300 HU and 1,500 HU (corresponding to soft-tissue and bone). CONCLUSIONS: PD-weighted ZT imaging provides robust and efficient depiction of bone structures in the head, with an excellent contrast between air, soft-tissue, and bone. Besides structural bone imaging, the presented method is expected to be of relevance for attenuation correction in positron emission tomography (PET)/MR and MR-based radiation therapy planning.

Dosimetric analysis of Co-60 source based high dose rate (HDR) brachytherapy: A case series of ten patients with carcinoma of the uterine cervix.

AIM: To analyse the dosimetric parameters of Co-60 based high dose rate (HDR) brachytherapy plans for patients of carcinoma uterine cervix. BACKGROUND: Co-60 high dose rate (HDR) brachytherapy unit has been introduced in past few years and is gaining importance owing to its long half life, economical benefits and comparable clinical outcome compared to Ir-192 HDR brachytherapy. MATERIALS AND METHODS: A study was conducted on ten patients with locally advanced carcinoma of the uterine cervix (Ca Cx). Computed tomography (CT) images were taken after three channel applicator insertions. The planning for 7 Gray per fraction (7 Gy/#) was done for Co-60 HDR brachytherapy unit following the American Brachytherapy Society (ABS) guidelines. All the patients were treated with 3# with one week interval between fractions. RESULTS: The mean dose to high risk clinical target volumes (HRCTV) for D90 (dose to 90% volume) was found to be 102.05% (Standard Deviation (SD): 3.07). The mean D2cc (dose to 2 cubic centimeter volume) of the bladder, rectum and sigmoid were found to be 15.9 Gy (SD: 0.58), 11.5 Gy (SD: 0.91) and 4.1 Gy (SD: 1.52), respectively. CONCLUSION: The target coverage and doses to organs at risk (OARs) were achieved as per the ABS guidelines. Hence, it can be concluded that the Co-60 HDR brachytherapy unit is a good choice especially for the centers with a small number of brachytherapy procedures as no frequent source replacement is required like in an Ir-192 HDR unit.

Switching anti-EGFR antibody re-sensitizes head and neck cancer patient following acquired resistance to cetuximab.

Cetuximab induces responses in about 13% of head and neck squamous cell carcinomas (HNSCC). We describe the molecular mechanism of acquired resistance to cetuximab, which could be overcome by switching to a different anti-EGFR antibody. Biopsies were collected at three different time points: before the start of cetuximab (PRE-cetux), at acquired resistance to cetuximab (AR-cetux), and at acquired resistance to duligotuzumab (AR-duligo). Biopsies were analyzed using tumor and normal whole-exome sequencing, RNASeq, and targeted panel sequencing with ultra-deep coverage to generate differential mutation and expression profiles. WES and targeted sequencing analysis identified an EGFR p.G465R extracellular domain mutation in AR-cetux biopsy. Furthermore, RNASeq confirmed the expression of this mutation in the tumor tissue. This mutation prevented the binding of cetuximab to EGFR and was not present in PRE-cetux and AR-duligo biopsies, suggesting a potential mechanism of acquired resistance to cetuximab. Molecular dynamic simulations confirmed that duligotuzumab effectively binds EGFR with a p.G465R mutation. Interestingly, the p.G465R mutation improved the stability of the duligotuzumab-EGFR complex as compared to the wild-type EGFR. This is the first report of an EGFR ECD mutation associated with acquired resistance to cetuximab, posing a need for further validation. We suggest appropriate serial mutational profiling to identify ECD mutations should be considered for select patients with initial cetuximab benefit.

Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis.

BACKGROUND: Positron emission tomography-magnetic resonance (PET-MR) attenuation correction is challenging because the MR signal does not represent tissue density and conventional MR sequences cannot image bone. A novel zero echo time (ZTE) MR sequence has been previously developed which generates signal from cortical bone with images acquired in 65 s. This has been combined with a deep learning model to generate a synthetic computed tomography (sCT) for MR-only radiotherapy. This study aimed to evaluate this algorithm for PET-MR attenuation correction in the pelvis. METHODS: Ten patients being treated with ano-rectal radiotherapy received a [Formula: see text]F-FDG-PET-MR in the radiotherapy position. Attenuation maps were generated from ZTE-based sCT (sCTAC) and the standard vendor-supplied MRAC. The radiotherapy planning CT scan was rigidly registered and cropped to generate a gold standard attenuation map (CTAC). PET images were reconstructed using each attenuation map and compared for standard uptake value (SUV) measurement, automatic thresholded gross tumour volume (GTV) delineation and GTV metabolic parameter measurement. The last was assessed for clinical equivalence to CTAC using two one-sided paired t tests with a significance level corrected for multiple testing of [Formula: see text]. Equivalence margins of [Formula: see text] were used. RESULTS: Mean whole-image SUV differences were -0.02% (sCTAC) compared to -3.0% (MRAC), with larger differences in the bone regions (-0.5% to -16.3%). There was no difference in thresholded GTVs, with Dice similarity coefficients [Formula: see text]. However, there were larger differences in GTV metabolic parameters. Mean differences to CTAC in [Formula: see text] were [Formula: see text] (± standard error, sCTAC) and [Formula: see text] (MRAC), and [Formula: see text] (sCTAC) and [Formula: see text] (MRAC) in [Formula: see text]. The sCTAC was statistically equivalent to CTAC within a [Formula: see text] equivalence margin for [Formula: see text] and [Formula: see text] ([Formula: see text] and [Formula: see text]), whereas the MRAC was not ([Formula: see text] and [Formula: see text]). CONCLUSION: Attenuation correction using this radiotherapy ZTE-based sCT algorithm was substantially more accurate than current MRAC methods with only a 40 s increase in MR acquisition time. This did not impact tumour delineation but did significantly improve the accuracy of whole-image and tumour SUV measurements, which were clinically equivalent to CTAC. This suggests PET images reconstructed with sCTAC would enable accurate quantitative PET images to be acquired on a PET-MR scanner.

Deep learning-based pseudo-CT synthesis from zero echo time MR sequences of the pelvis.

OBJECTIVES: To generate pseudo-CT (pCT) images of the pelvis from zero echo time (ZTE) MR sequences and compare them to conventional CT. METHODS: Ninety-one patients were prospectively scanned with CT and MRI including ZTE sequences of the pelvis. Eleven ZTE image volumes were excluded due to implants and severe B1 field inhomogeneity. Out of the 80 data sets, 60 were used to train and update a deep learning (DL) model for pCT image synthesis from ZTE sequences while the remaining 20 cases were selected as an evaluation cohort. CT and pCT images were assessed qualitatively and quantitatively by two readers. RESULTS: Mean pCT ratings of qualitative parameters were good to perfect (2-3 on a 4-point scale). Overall intermodality agreement between CT and pCT was good (ICC = 0.88 (95% CI: 0.85-0.90); p < 0.001) with excellent interreader agreements for pCT (ICC = 0.91 (95% CI: 0.88-0.93); p < 0.001). Most geometrical measurements did not show any significant difference between CT and pCT measurements (p > 0.05) with the exception of transverse pelvic diameter measurements and lateral center-edge angle measurements (p = 0.001 and p = 0.002, respectively). Image quality and tissue differentiation in CT and pCT were similar without significant differences between CT and pCT CNRs (all p > 0.05). CONCLUSIONS: Using a DL-based algorithm, it is possible to synthesize pCT images of the pelvis from ZTE sequences. The pCT images showed high bone depiction quality and accurate geometrical measurements compared to conventional CT. CRITICAL RELEVANCE STATEMENT: pCT images generated from MR sequences allow for high accuracy in evaluating bone without the need for radiation exposure. Radiological applications are broad and include assessment of inflammatory and degenerative bone disease or preoperative planning studies. KEY POINTS: pCT, based on DL-reconstructed ZTE MR images, may be comparable with true CT images. Overall, the intermodality agreement between CT and pCT was good with excellent interreader agreements for pCT. Geometrical measurements and tissue differentiation were similar in CT and pCT images.

"Phloem sap analysis of Schleichera oleosa (Lour) Oken, Butea monosperma (Lam) Taub. and Ziziphus mauritiana (Lam) and hemolymph of Kerria lacca (Kerr) using HPLC and tandem mass spectrometry".

Females of lac insects especially of Kerria lacca (Kerr) secret a resin known as lac for their own protection, which has tremendous applications. Lac insect completes its lifecycle on several host taxa where it exclusively feeds on phloem sap but Schleichera oleosa (Lour.) Oken, Butea monosperma (Lam.) and Ziziphus mauritiana (Lam.) are its major hosts. Analysis of phloem sap constituents as well as hemolymph of lac insect is important because it ultimately gets converted into lac by insect intervention. Main phloem sap constituent's viz. sugars and free amino acids and hemolymph of lac insect were analyzed using HPLC and tandem mass spectrometry, respectively. The results were transformed to relative percentage of the total sugars and free amino acids analyzed in each sample for comparison among lac insect hemolymph and the phloem sap of the three different host taxa. Sucrose (58.9 ± 3.6-85.6 ± 0.9) and trehalose (62.3 ± 0.4) were the predominant sugars in phloem sap of three taxa and hemolymph of lac insect, respectively. Glutamic acid (33.1 ± 1.4-39.8 ± 1.4) was found to be main amino acid among the phloem sap of three taxa while tyrosine (61 ± 2.6) was the major amino acid in hemolymph of lac insect. The relative percentage of non-essential amino acids (60.8 %-69.9 %) was found to be more in all the three host taxa while essential amino acids (30.1 %-35.4 %) were present at a lower relative percentage. In contrast to this, the relative percentage of essential amino acids (81.9 %) was observed to be higher as compared to non-essential amino acids (17.7 %) in lac insect hemolymph. These results led to the detection of lac insect's endosymbionts. Moreover, this study revealed a clue regarding the importance of development of a synthetic diet for this insect so that a precise pathway of lac biosynthesis could be investigated for thorough understanding.

Exploring the Paradigm of Phyto-Nanofabricated Metal Oxide Nanoparticles: Recent Advancements, Applications, and Challenges.

The development of nanotechnology, in particular metal oxide nanoparticles, has captured immense scientific attention in the global arena due to their unique properties leading to their unique diverse applications. But the use of toxic precursors and high operational cost make existing methodologies inefficient for synthesising metal oxide nanoparticles (MONPs). Biogenic synthesis of MONPs has been hailed as a more sustainable approach for the synthesis of NPs due to its alignment with the principles of green chemistry. Microorganisms (bacteria, yeast, algae), animal sources (silk, fur, etc.), and plants are effective, low-cost, and eco-friendly means of synthesizing MONPs since they possess a high bio-reduction abilities to produce NPs of various shapes and sizes. The current review encompasses recent advancements in the field of plant-mediated MONP synthesis and characterisation. The detailed evaluation of various synthesis processes and parameters, key influencing factors affecting the synthesis efficiency and product morphology, practical applications with insight into the associated limitations and challenges presents a valuable database that will be helpful in developing alternative prospects and potential engineering applications.

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach. We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results. We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance. We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.

Comprehensive dose evaluation of a Deep Learning based synthetic Computed Tomography algorithm for pelvic Magnetic Resonance-only radiotherapy.

BACKGROUND AND PURPOSE: Magnetic Resonance (MR)-only radiotherapy enables the use of MR without the uncertainty of MR-Computed Tomography (CT) registration. This requires a synthetic CT (sCT) for dose calculations, which can be facilitated by a novel Zero Echo Time (ZTE) sequence where bones are visible and images are acquired in 65 seconds. This study evaluated the dose calculation accuracy for pelvic sites of a ZTE-based Deep Learning sCT algorithm developed by GE Healthcare. MATERIALS AND METHODS: ZTE and CT images were acquired in 56 pelvic radiotherapy patients in the radiotherapy position. A 2D U-net convolutional neural network was trained using pairs of deformably registered CT and ZTE images from 36 patients. In the remaining 20 patients the dosimetric accuracy of the sCT was assessed using cylindrical dummy Planning Target Volumes (PTVs) positioned at four different central axial locations, as well as the clinical treatment plans (for prostate (n = 10), rectum (n = 4) and anus (n = 6) cancers). The sCT was rigidly and deformably registered, the plan recalculated and the doses compared using mean differences and gamma analysis. RESULTS: Mean dose differences to the PTV D98% were ≤ 0.5% for all dummy PTVs and clinical plans (rigid registration). Mean gamma pass rates at 1%/1 mm were 98.0 ± 0.4% (rigid) and 100.0 ± 0.0% (deformable), 96.5 ± 0.8% and 99.8 ± 0.1%, and 95.4 ± 0.6% and 99.4 ± 0.4% for the clinical prostate, rectum and anus plans respectively. CONCLUSIONS: A ZTE-based sCT algorithm with high dose accuracy throughout the pelvis has been developed. This suggests the algorithm is sufficiently accurate for MR-only radiotherapy for all pelvic sites.

Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks.

The integrated positron emission tomography/magnetic resonance imaging (PET/MRI) scanner simultaneously acquires metabolic information via PET and morphological information using MRI. However, attenuation correction, which is necessary for quantitative PET evaluation, is difficult as it requires the generation of attenuation-correction maps from MRI, which has no direct relationship with the gamma-ray attenuation information. MRI-based bone tissue segmentation is potentially available for attenuation correction in relatively rigid and fixed organs such as the head and pelvis regions. However, this is challenging for the chest region because of respiratory and cardiac motions in the chest, its anatomically complicated structure, and the thin bone cortex. We propose a new method using unsupervised generative attentional networks with adaptive layer-instance normalisation for image-to-image translation (U-GAT-IT), which specialised in unpaired image transformation based on attention maps for image transformation. We added the modality-independent neighbourhood descriptor (MIND) to the loss of U-GAT-IT to guarantee anatomical consistency in the image transformation between different domains. Our proposed method obtained a synthesised computed tomography of the chest. Experimental results showed that our method outperforms current approaches. The study findings suggest the possibility of synthesising clinically acceptable computed tomography images from chest MRI with minimal changes in anatomical structures without human annotation.