Prognostic Factors and Outcomes of Early-Stage Hodgkin's Lymphoma: Multi-Institutional Data From South India.

Early-stage Hodgkin's lymphoma (ESHL) is highly curable, usually with a combination of chemotherapy and radiation. Real-world data may show differences in survival and prognostic factors when compared to clinical trials. There is limited published literature on ESHL from India. The data on the baseline characters, treatment, and outcomes of patients with ESHL (stage IA, IB, and IIA) were obtained from five institutions' medical records and entered in a common database. Event-free survival (EFS) and overall survival (OS) were estimated using the Kaplan Meier method, and cox-regression analysis was used to identify prognostic factors. There were 258 patients [median age was 37 (18-75) years; [males:160 (62%); stage I: 41%; B symptoms: 17 (6%); bulky disease:19 (15%)] treated between 2000 and 2020 who were evaluable. The common chemotherapies used were ABVD [N = 180 (70%)], COPP-ABVD hybrid [N = 52 (21%)], and COPP [N = 14 (5%)]. Median number of cycles were 4 (2-8) and 93 (47%) received radiation at end of treatment. After a median follow-up of 60 months, the 5 years EFS was 87% and OS was 92%. On multivariate analysis, the following factors adversely affected the EFS: Male gender [hazard ratio (HR) = 2.23, P = 0.02] and Hemoglobin < 10.5g/dL [hazard ration (HR) = 2.20, P = 0.02], and the following adversely affected the OS: Hemoglobin < 10.5g/dL [hazard ratio (HR) = 4.05, P = 0.001], Male gender [hazard ratio (HR) = 3.59, P = 0.004], Stage 2 [hazard ratio (HR) = 2.65, P = 0.002] and ECOG PS (2-3) [hazard ratio (HR) = 3.35, P = 0.01]. Using the hemoglobin, stage and gender a 3-item prognostic score could identify patients with very good outcomes (score 0; 5 years OS:100%) and poor outcomes (score 3; 5 years OS; 49%). This is one of the first multi-center real-world data exclusively focusing on ESHL from India. Though the survival of the entire population was good, there are subsets of patients who have poor outcomes, which may be identified using simple parameters. These parameters need validation in a larger dataset. Supplementary Information: The online version contains supplementary material available at 10.1007/s12288-023-01692-9.

Secondary metabolite profiling using HR-LCMS, antioxidant and anticancer activity of Bacillus cereus PSMS6 methanolic extract: In silico and in vitro study.

Novel anticancer drugs of natural origin have increased tremendously due to the resistance of multiple chemotherapeutic drugs in breast cancer therapy and their high toxicity with undesirable side effects. The study investigates the bioactivity of secondary metabolites derived from Bacillus cereus PSMS6 isolated from marine soil sediment in the Velar estuary, Parangepattai, Cuddalore district, Tamil Nadu, and India. Strains were isolated and antagonistic activity was screened using the agar well diffusion method. B. cereus PSMS6 exhibited potency, and its crude extract was tested for antioxidant, anticancer, and cytotoxic MTT assay potential. The methanolic extract of B. cereus PSMS6 was analyzed by mass spectrometry HRLC-MS and FT-IR to determine the bioactive compounds. A drug interaction study with the anti-breast cancer protein HER2 was performed by molecular docking analysis. Antioxidant activities were determined using total antioxidant scavenging assay, ABTS and DPPH free radical scavenging assays. The total antioxidant scavenging assay of the crude extract of B. cereus methanol had an IC50 value of 28.33±1.01, in ABTS IC50 value of the extract was 29.00±0.28 and in DPPH the IC50 of the extract was 34.91±0.09. The negative ion compound Palmitoylglycerone phosphate had a LibDock score of 149.487 and the positive ion compound N5-(4-Methoxybenzyl) glutamine had 120.116. These compounds show promising anticancer activity. The current study reported that the bioactive secondary metabolite of B. cereus PSMS6 retains anti-cancer, and antioxidant properties. This is the first report to show the production of the Palmitoylglycerone phosphate metabolite from B. cereus PSMS6.

A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration.

Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott's index of agreement (WI), and Legates-McCabe's index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships.

Peptide-Directed Synthesis of Aggregation-Induced Emission Enhancement-Active Gold Nanoclusters for Single- and Two-Photon Imaging of Lysosome and Expressed αvß3 Integrin Receptors.

This study explores the synthesis and characterization of aggregation-induced emission enhancement (AIEE)-active gold nanoclusters (AuNCs), focusing on their near-infrared luminescence properties and potential applications in biological imaging. These AIEE-active AuNCs were synthesized via the NaBH4-mediated reduction of HAuCl4 in the presence of peptides. We systematically investigated the influence of the peptide sequence on the optical features of the AuNCs, highlighting the role of glutamic acid in enhancing their quantum yield (QY). Among the synthesized peptide-stabilized AuNCs, EECEE-stabilized AuNCs exhibited the maximum QY and a pronounced AIEE effect at pH 5.0, making them suitable for the luminescence imaging of intracellular lysosomes. The AIEE characteristic of the EECEE-stabilized AuNCs was demonstrated through examinations using transmission electron microscopy, dynamic light scattering, zeta potential analysis, and single-particle imaging. The formation of the EECEE-stabilized AuNCs was confirmed by size-exclusion chromatography and mass spectrometry. Spectroscopic and electrochemical examinations uncover the formation process of EECEE-stabilized AuNCs, comprising EECEE-mediated reduction, NaBH4-induced nucleation, complex aggregation, and subsequent cluster growth. Furthermore, we demonstrated the utility of these AuNCs as luminescent probes for intracellular lysosomal imaging, leveraging their pH-responsive AIEE behavior. Additionally, cyclic arginylglycylaspartic acid (RGD)-modified AIEE dots, derived from cyclic RGD-linked peptide-induced aggregation of EECEE-stabilized AuNCs, were developed for single- and two-photon luminescence imaging of αvß3 integrin receptor-positive cancer cells.

Harnessing Resilience in the Healthy Ageing Discourse: Insights from Attappadi Indigenous Older Adults, Kerala, India.

In this "Decade of Healthy Ageing," the integration of resilience into the healthy aging discourse becomes paramount, particularly in the context of indigenous communities grappling with the enduring effects of historical oppression, persistent poverty, and health disparities in their aging journey. Employing a phenomenological lens, this study seeks to derive the resilient characteristics exhibited by the Attappadi indigenous older adults of Kerala, aiming to explore the role of resilience in their pursuit of healthy aging. In-depth phenomenological interviews (n = 34), observation, and document analysis have revealed four key themes: A life course marked by adversities, Embracing the unyielding strength within, Personal resilience catalysts, and Extrinsic resilience catalysts. The participants exhibited a reasonably well-functioning collective, given their persistent adversities in their life course. Narratives illuminated a notable connection between the presence of resilience characteristics and the overall functioning of older adults. From a social work standpoint on resilience, this article underscores the vital interplay between individual agency and environmental factors in addressing adversity. The article advocates culturally sensitive, asset-based strategies to strengthen indigenous older adults' intrinsic and extrinsic resilience to ensure that they are not left behind in the global pursuit of healthy aging.

Arg40 is critical for stability and activity of Adenylosuccinate lyase; a purine salvage enzyme from Leishmania donovani.

Purine salvage enzymes have been of significant interest in anti-Leishmanial drug development due to the parasite's critical dependence on this pathway for the supply of nucleotides in the absence of a de novo purine synthesis pathway. Adenylosuccinate lyase (ADSL) one of the key enzymes in this pathway is a homo-tetramer, where the active site is formed by residues from three distinct subunits. Analysis of the subunit interfaces of LdADSL, revealed a conserved Arg40 forming critical inter-subunit interactions and also involved in substrate binding. We hypothesized that mutating this residue can affect both the structural stability and activity of the enzyme. In our study, we used biochemical, biophysical, and computational simulation approaches to understand the structural and functional role of Arg40 in LdADSL. We have replaced Arg40 with an Ala and Glu using site directed mutagenesis. The mutant enzymes were similar to wild-type enzyme in secondary structure and subunit association. Thermal shift assays indicated that the mutations affected the protein stability. Both mutants showed decreased specific activities in both forward and reverse directions with significantly weakened affinities towards succinyl-adenosine monophosphate (SAMP). The mutations resulted in changes in C3 loop conformation and D3 domain rotation. Consequently, the orientation of the active site amino acid residues changed resulting in compromised activity and stability. Studies so far have majorly focused on the ADSL active site for designing drugs against it. Our work indicates that an alternative inhibitory mechanism for the enzyme can be designed by targeting the inter-subunit interface.

Stepwise activation of a metabotropic glutamate receptor.

Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain that is linked via a cysteine-rich domain to their 7-transmembrane domain1. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the extracellular ligand-binding domain to the G protein-coupling 7-transmembrane domain2. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging, we reveal distinct receptor conformations upon allosteric modulator and G protein binding.

Development and evaluation of a pH-responsive Mimosa pudica seed mucilage/ß- cyclodextrin-co-poly(methacrylate) hydrogel for controlled drug delivery: In vitro and in vivo assessment.

In this comprehensive investigation, a novel pH-responsive hydrogel system comprising mimosa seed mucilage (MSM), ß-cyclodextrin (ß-CD), and methacrylic acid (MAA) was developed via free radical polymerization technique to promote controlled drug delivery. The hydrogel synthesis involved strategic variations in polymer, monomer, and crosslinker content in fine-tuning its drug-release properties. The resultant hydrogel exhibited remarkable pH sensitivity, selectively liberating the model drug (Capecitabine = CAP) under basic conditions while significantly reducing release in an acidic environment. Morphological, thermal, and structural analyses proved that CAP has a porous texture, high stability, and an amorphous nature. In vitro drug release experiments showcased a sustained and controlled release profile. Optimum release (85.33 %) results were recorded over 24 h at pH 7.4 in the case of MMB9. Pharmacokinetic evaluation in healthy male rabbits confirmed bioavailability enhancement and sustained release capabilities. Furthermore, rigorous toxicity evaluations and histopathological analyses ensured the safety and biocompatibility of the hydrogel. This pH-triggered drug delivery system can be a promising carrier system for drugs involving frequent administrations.

Recent Advances in Drug Delivery Systems Targeting Insulin Signalling for the Treatment of Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the accumulation of neurofibrillary tangles and amyloid-ß plaques. Recent research has unveiled the pivotal role of insulin signaling dysfunction in the pathogenesis of AD. Insulin, once thought to be unrelated to brain function, has emerged as a crucial factor in neuronal survival, synaptic plasticity, and cognitive processes. Insulin and the downstream insulin signaling molecules are found mainly in the hippocampus and cortex. Some molecules responsible for dysfunction in insulin signaling are GSK-3ß, Akt, PI3K, and IRS. Irregularities in insulin signaling or insulin resistance may arise from changes in the phosphorylation levels of key molecules, which can be influenced by both stimulation and inactivity. This, in turn, is believed to be a crucial factor contributing to the development of AD, which is characterized by oxidative stress, neuroinflammation, and other pathological hallmarks. Furthermore, this route is known to be indirectly influenced by Nrf2, NF-κB, and the caspases. This mini-review delves into the intricate relationship between insulin signaling and AD, exploring how disruptions in this pathway contribute to disease progression. Moreover, we examine recent advances in drug delivery systems designed to target insulin signaling for AD treatment. From oral insulin delivery to innovative nanoparticle approaches and intranasal administration, these strategies hold promise in mitigating the impact of insulin resistance on AD. This review consolidates current knowledge to shed light on the potential of these interventions as targeted therapeutic options for AD.

Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran).

The estimation of groundwater levels is crucial and an important step in ensuring sustainable management of water resources. In this paper, selected piezometers of the Hamedan-Bahar plain located in west of Iran. The main objective of this study is to compare effect of various pre-processing methods on input data for different artificial intelligence (AI) models to predict groundwater levels (GWLs). The observed GWL, evaporation, precipitation, and temperature were used as input variables in the AI algorithms. Firstly, 126 method of data pre-processing was done by python programming which are classified into three classes: 1- statistical methods, 2- wavelet transform methods and 3- decomposition methods; later, various pre-processed data used by four types of widely used AI models with different kernels, which includes: Support Vector Machine (SVR), Artificial Neural Network (ANN), Long-Short Term memory (LSTM), and Pelican Optimization Algorithm (POA) - Artificial Neural Network (POA-ANN) are classified into three classes: 1- machine learning (SVR and ANN), 2- deep learning (LSTM) and 3- hybrid-ML (POA-ANN) models, to predict groundwater levels (GWLs). Akaike Information Criterion (AIC) were used to evaluate and validate the predictive accuracy of algorithms. According to the results, based on summation (train and test phases) of AIC value of 1778 models, average of AIC values for ML, DL, hybrid-ML classes, was decreased to -25.3%, -29.6% and -57.8%, respectively. Therefore, the results showed that all data pre-processing methods do not lead to improvement of prediction accuracy, and they should be selected very carefully by trial and error. In conclusion, wavelet-ANN model with daubechies 13 and 25 neurons (db13_ANN_25) is the best model to predict GWL that has -204.9 value for AIC which has grown by 5.23% (-194.7) compared to the state without any pre-processing method (ANN_Relu_25).

Unveiling the Molecular Mechanism of Diosmetin and its Impact on Multifaceted Cellular Signaling Pathways.

BACKGROUND: Diosmetin is an O-methylated flavone and the aglycone part of the flavonoid glycosides diosmin that occurs naturally in citrus fruits. Pharmacologically, diosmetin is reported to exhibit anticancer, antimicrobial, antioxidant, oestrogenic, and anti-inflammatory activities. OBJECTIVE: This comprehensive review was aimed to critically explore diverse pharmacological activities exhibited by diosmetin. Along with that, this review can also identify potential research areas with an elucidation of the multifactorial underlying signaling mechanism of action of diosmetin in different diseases. METHODS: A comprehensive collection of evidence and insights was obtained from scientific journals and books from physical libraries and electronic platforms like Google Scholar and PubMed. The time frame selected was from year 1992 to July 2023. RESULTS: The review delves into diosmetin's impact on cellular signaling pathways and its potential in various diseases. Due to its ability to modulate signaling pathways and reduce oxidative stress, it can be suggested as a potential versatile therapeutic agent for mitigating oxidative stressassociated pathogenesis. CONCLUSION: The amalgamation of the review underscores diosmetin's promising role as a multifaceted therapeutic agent, highlighting its potential for drug development and clinical applications.

Systematically assessing the quality of dental electronic health record data for an investigation into oral health care disparities.

OBJECTIVES: This work describes the process by which the quality of electronic health care data for a public health study was determined. The objectives were to adapt, develop, and implement data quality assessments (DQAs) based on the National Institutes of Health Pragmatic Trials Collaboratory (NIHPTC) data quality framework within the three domains of completeness, accuracy, and consistency, for an investigation into oral health care disparities of a preventive care program. METHODS: Electronic health record data for eligible children in a dental accountable care organization of 30 offices, in Oregon, were extracted iteratively from January 1, 2014, through March 31, 2022. Baseline eligibility criteria included: children ages 0-18 with a baseline examination, Oregon home address, and either Medicaid or commercial dental benefits at least once between 2014 and 2108. Using the NIHPTC framework as a guide, DQAs were conducted throughout data element identification, extraction, staging, profiling, review, and documentation. RESULTS: The data set included 91,487 subjects, 11 data tables comprising 75 data variables (columns), with a total of 6,861,525 data elements. Data completeness was 97.2%, the accuracy of EHR data elements in extracts was 100%, and consistency between offices was strong; 29 of 30 offices within 2 standard deviations of the mean (s = 94%). CONCLUSIONS: The NIHPTC framework proved to be a useful approach, to identify, document, and characterize the dataset. The concepts of completeness, accuracy, and consistency were adapted by the multidisciplinary research team and the overall quality of the data are demonstrated to be of high quality.

Synthesized pyrrole ester ameliorates adjuvant­induced arthritis in Wistar rats by alleviating inflammation and downregulating the pro­inflammatory cytokines.

Piperine is an amide alkaloid responsible for producing the pungent smell that comes from black pepper. Piperine has been explained to exhibit significant properties such as anti-rheumatic, anti-inflammatory, and antihypertensive effects. The aim of the study was to synthesize pyrrole ester from piperine and evaluate its anti-arthritis effects in adjuvant-induced arthritis female Wistar rats. In this study, pyrrole ester (AU-5) was designed, synthesized and evaluated for ant-arthritic activity in adjuvant-induced arthritis Wistar rats. The synthesized pyrrole ester (AU-5) was administered in three selected doses (20, 10 and 5 mg/kg) to the arthritic-induced model. The administered ester significantly inhibited the increase in arthritis index, paw and ankle joint swelling compared to the arthritic control group. Similarly, the treated rats exhibited a remarkable increase in body weight increase, improved haematological, biochemical, histopathological and radiological parameters. Moreover, the excess production of rheumatoid factor (RF), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) was noticeably attenuated in all AU-5-treated rats. However, the spleen index, tumour necrosis factor (TNF-α) and interleukin-6 (IL-6) were distinctly lowered compared to arthritic control rats. Moreover, AU-5 showed promising liver protection by lowering the level of liver function markers Serum glutamic pyruvic transaminase (SGPT), Serum glutamic-oxaloacetic transaminase (SGOT) and alkaline phosphatase (ALP) in serum. Henceforth, it might be concluded that AU-5 has an anti-arthritic effect which can be credited to the down regulation of inflammatory markers and the pro-inflammatory cytokines.

A retrospective analysis of the role of age and sex in outcomes of non-surgical periodontal therapy at a single academic dental center.

The present study examined the role of age and sex in the outcomes of non-surgical periodontal therapy (NSPT). De-identified demographic and periodontal characteristics of patients who presented for baseline periodontal evaluation, NSPT, and periodontal re-evaluation were abstracted from electronic health records. Independent associations of age and sex with severe periodontitis defined as ≥ 5 mm clinical attachment loss (CAL) and ≥ 6 mm probing depth (PD) were determined using multinomial logistic regression. The null hypothesis was rejected at α < 0.05. A total of 2866 eligible subjects were included in the analysis. Significantly lower odds of CAL ≤ 4 mm than CAL ≥ 5 mm (reference) were observed in adults aged 35-64 (odds ratio, OR, 0.19; 95% confidence interval, CI 0.13, 0.29) and ≥ 65 years (OR 0.13; 95% CI 0.07, 0.25) compared to those aged 18-34 years. Odds of PD < 4 mm versus PD ≥ 6 mm (reference) were lower in adults aged 35-64 years than those aged 18-34 years (OR 0.71; 95% CI 0.55, 0.90) and higher in females compared to males (OR 1.67; 95% CI 1.14, 2.44). These results suggest more compromised post-NSPT outcomes in older adults and males compared to the respective populations and highlight the need for personalized therapeutic strategies in these populations.

Carbon nanotubes in plant dynamics: Unravelling multifaceted roles and phytotoxic implications.

Carbon nanotubes (CNTs) have emerged as a promising frontier in plant science owing to their unique physicochemical properties and versatile applications. CNTs enhance stress tolerance by improving water dynamics and nutrient uptake and activating defence mechanisms against abiotic and biotic stresses. They can be taken up by roots and translocated within the plant, impacting water retention, nutrient assimilation, and photosynthesis. CNTs have shown promise in modulating plant-microbe interactions, influencing symbiotic relationships and mitigating the detrimental effects of phytopathogens. CNTs have demonstrated the ability to modulate gene expression in plants, offering a powerful tool for targeted genetic modifications. The integration of CNTs as sensing elements in plants has opened new avenues for real-time monitoring of environmental conditions and early detection of stress-induced changes. In the realm of agrochemicals, CNTs have been explored for their potential as carriers for targeted delivery of nutrients, pesticides, and other bioactive compounds. CNTs have the potential to demonstrate phytotoxic effects, detrimentally influencing both the growth and developmental processes of plants. Phytotoxicity is characterized by induction of oxidative stress, impairment of cellular integrity, disruption of photosynthetic processes, perturbation of nutrient homeostasis, and alterations in gene expression. This review aims to provide a comprehensive overview of the current state of knowledge regarding the multifaceted roles of CNTs in plant physiology, emphasizing their potential applications and addressing the existing challenges in translating this knowledge into sustainable agricultural practices.

Design, Synthesis, and Biological Evaluation of Novel Coumarin Analogs Targeted against SARS-CoV-2.

SARS-CoV, an RNA virus, is contagious and displays a remarkable degree of adaptability, resulting in intricate disease presentations marked by frequent genetic mutations that can ultimately give rise to drug resistance. Targeting its viral replication cycle could be a potential therapeutic option to counter its viral growth in the human body leading to the severe infectious stage. The Mpro of SARS-CoV-2 is a promising target for therapeutic development as it is crucial for viral transcription and replication. The derivatives of ß-diketone and coumarin have already been reported for their antiviral potential and, thus, are considered as a potential scaffold in the current study for the computational design of potential analogs for targeting the viral replication of SARS-CoV-2. In our study, we used novel diketone-hinged coumarin derivatives against the SARS-CoV-2 MPro to develop a broad-spectrum antiviral agent targeting SARS-CoV-2. Through an analysis of pharmacokinetics and docking studies, we identified a list of the top 10 compounds that demonstrated effectiveness in inhibiting the SARS-CoV-2 MPro virus. On the basis of the pharmacokinetics and docking analyses, the top 5 novel coumarin analogs were synthesized and characterized. The thermodynamic stability of compounds KS82 and KS94 was confirmed by their molecular dynamics, and the stability of the simulated system indicated their inhibitory nature. Molecules KS82 and KS94 were further evaluated for their anti-viral potential using Vero E6 cells followed by RT-PCR assay against SARS-CoV-2. The test compound KS82 was the most active with the potential to inhibit SARS-CoV-2 replication in Vero E6 cells. These data indicate that KS82 prevents the attack of the virus and emerges as the primary candidate with promising antiviral properties.

Exogenous GABA supplementation to facilitate Cr (III) tolerance and lipid biosynthesis in Chlorella sorokiniana.

Microalgae possess the prospective to be efficiently involved in bioremediation and biodiesel generation. However, conditions of stress often restrict their growth and diminish different metabolic processes. The current study evaluates the potential of GABA to improve the growth of the microalga Chlorella sorokiniana under Cr (III) stress through the exogenous administration of GABA. The research also investigates the concurrent impact of GABA and Cr (III) stress on various metabolic and biochemical pathways of the microalgae. In addition to the control, cultures treated with Cr (III), GABA, and both Cr (III) and GABA treated were assessed for accurately analysing the influence of GABA. The outcomes illustrated that GABA significantly promoted growth of the microalgae, resulting in higher biomass productivity (19.14 mg/L/day), lipid productivity (3.445 mg/L/day) and lipid content (18%) when compared with the cultures under Cr (III) treatment only. GABA also enhanced Chl a content (5.992 µg/ml) and percentage of protein (23.75%). FAMEs analysis by GC-MS and total lipid profile revealed that GABA treatment can boost the production of SFA and lower the level of PUFA, a distribution ideal for improving biodiesel quality. ICP-MS analysis revealed that GABA supplementation could extend Cr (III) mitigation level up to 97.7%, suggesting a potential strategy for bioremediation. This novel study demonstrates the merits of incorporating GABA in C. sorokiniana cultures under Cr (III) stress, in terms of its potential in bioremediation and biodiesel production without disrupting the pathways of photosynthesis and protein production.

Chylolymphatic mesenteric cyst: A rare differential diagnosis of cystic mass in abdomen: A case report.

INTRODUCTION: Mesenteric cysts are the rare benign intraperitoneal tumor, which are common in the mesentery of the terminal ileum. Though mesenteric cysts are frequently seen, chylolymphatic mesenteric cysts in children are rare entities. CASE PRESENTATION: Our case is a case of a 3-year-old female child presenting to our center with a complain of abdominal pain. Ultrasonography (USG) of the abdomen revealed a cystic lesion in the right upper abdomen, and computed tomography (CT) scan showed a large homogenous fluid density lesion in the right upper abdomen, giving a provisional diagnosis of mesenteric cyst. She was managed surgically: the cyst was excised, the involved segment of bowel was resected and the remaining was anastomosed. On histopathology, the final diagnosis of a chylolymphatic mesenteric cyst was made. DISCUSSION: Clinical presentations may vary from asymptomatic abdominal lump to features of acute abdomen. Imaging modalities like ultrasonography and computed tomography scans are the mainstay of investigations. Surgical management with excision of cyst, and resection of the involved bowel segment is the treatment of choice, as done in our patient. The final diagnosis is made after the histopathologic examination of the excised specimen. CONCLUSION: Chylolymphatic mesenteric cysts are rare, and have varied clinical presentations. Although rare, chylolymphatic mesenteric cysts should be considered a differential diagnosis in patients presenting with cystic masses in the abdomen.