bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatiotemporal variation in water quality and its association with cyanobacterial diversity in the Hirakud Reservoir, Sambalpur, Odisha, India
Authors: Sahu Ashish Kumar , Mir Showkat Ahmad , Nayak Binata , Baitharu Iswar 
Published: August 2024

ABSTRACT

The present study evaluates the impact of seasonal variation on the water quality and the cyanobacterial diversity in the Hirakud Reservoir. Different physicochemical water quality parameters were determined using standard methods as prescribed by American Public Health Association (APHA). Morphometric identification of cyanobacterial species and their diversity in reservoir water were assessed during three different seasons. The Trophic State Index (TSI) of the reservoir was calculated based on the depth of the water and the phosphate and chlorophyll-a contents. The physicochemical parameters of the water samples revealed a minimum of 3.8 mg/L of dissolved oxygen during the pre-monsoon season, and a maximum of 6.2 mg/L during the monsoon season. Nitrate content in water was found to be maximum (12.7 mg/L) in the post-monsoon season, whereas total phosphate concentration was recorded to be maximum (4.17 mg/L) during the pre-monsoon period. Higher cyanobacterial diversity was observed during pre-monsoon and was mostly dominated by Microcystis species. Cyanobacterial species such as Anabaena, Calothrix, Oscillatoria, Chroococcus, Phormidium, Cylindrospermum, Nostoc, Spirulina, and Phormidium were recorded in the reservoir. The TSI analysis indicated that the reservoir is in transition from the mesotrophic state to the eutrophic state. Principal Component Analysis indicated that increased anthropogenic activities upstream and around the reservoir contributed significantly to nutrient enrichment and subsequent deterioration of water quality.
Expression, Purification, and Evaluation of Antibody Responses and Antibody-Immunogen Complex Simulation of a Designed Multi-Epitope Vaccine against SARS-COV-2
Authors: Jamal Ghadir A. , Jahangirian Ehsan , Tarrahimofrad Hossein 
Published: August 2024

Background:
The spread of the COVID-19 disease is the result of an infection caused
by the SARS-CoV2 virus. Four crucial proteins, spike (S), membrane (M), nucleocapsid (N), and
envelope (E) in coronaviruses have been considered to a large extent.

Objective:
This research aimed to express the recombinant protein of a multiepitope immunogen
construct and evaluate the immunogenicity of the multiepitope vaccine that was previously designed
as a candidate immunogenic against SARS-Cov-2.

Materials and Methods:
Plasmid pET26b was transferred to the expression host E. coli BL21
(DE3) and the recombinant protein was expressed with IPTG induction. The recombinant protein
was purified by Ni-NTA column affinity chromatography, and western blotting was used to confirm
it. Finally, mice were immunized with recombinant protein in three doses. Then, the interaction
of the 3D structure of the vaccine with the human neutralizing antibodies3D structures (7BWJ
and 7K8N) antibody was evaluated by docking and molecular dynamics simulation.

Results:
The optimized gene had a codon compatibility index of 0.96. The expression of the recombinant
protein of the SARS-Cov-2 vaccine in an E. coli host led to the production of the recombinant
protein with a weight of about 70 kDa with a concentration of 0.7 mg/ml. Immunization
of mice with recombinant protein of SARS-Cov-2 vaccine-induced IgG serum antibody response.
Statistical analysis showed that the antibody titer in comparison with the control sample
has a significant difference, and the antibody titer was acceptable up to 1/256000 dilution. The simulation
of vaccine binding with human antibodies by molecular dynamics showed that Root
Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration,
and H-bond as well as van der Waals energies and electrostatic of Molecular mechanics Poisson–
Boltzmann surface area (MM/PBSA) analysis have stable interaction.

Conclusion:
This recombinant protein can probably be used as an immunogen candidate for the
development of vaccines against SARS-CoV2 in future research.
Melanin Synthesized by the Endophytic Aureobasidium Pullulans AKW: A Multifaceted Biomolecule with Antioxidant, Wound Healing, and Selective Anti-Cancer Activity
Authors: Elattar Khaled M. , Ghoniem Abeer A. , Al-Askar Abdulaziz A. , El-Gazzar Usama Bhgat , El-Hersh Mohammed S. , Elsherbiny Elsherbiny A. , Eldadamony Noha M. , Saber WesamEldin I.A. 
Published: August 2024

Introduction:
This study explores the potential of the endophytic fungus Aureobasidium
pullulans AKW for melanin production and its anticancer activity.

Method:
We report a significant achievement: A. pullulans AKW synthesized 4.89 g/l of melanin
in a simple fermentation medium devoid of tyrosine, a precursor typically required for melanin
biosynthesis. This suggests a potentially novel pathway for melanin production compared to previous
studies relying on complex media and tyrosine. Furthermore, the isolated and characterized
melanin exhibited promising selectivity as an anti-cancer agent. It triggered apoptosis in A431 cancer
cells, demonstrating some selectivity compared to normal cells. This selectivity was confirmed
by IC50 values and further supported by gene expression changes in A431 cells. Melanin treatment
downregulated the anti-apoptotic Bcl2 gene while upregulating pro-apoptotic Bax and p53 genes,
indicating its ability to induce programmed cell death in cancer cells.

Result:
Our results demonstrate that A. pullulans AKW-derived melanin exhibits cytotoxic effects
against A431, HEPG2, and MCF7 cell lines. Interestingly, the present fungal strain synthesized
melanin in a simple medium without requiring precursors.

Conclusion:
The selective activity of the current melanin towards cancer cells, its ability to induce
apoptosis, and its relatively low toxicity towards normal cells warrant further investigation
for its development as a novel therapeutic option.
Advancements in Computational Approaches for Antidiabetic Drug Discovery: A Review
Authors: Rossafi Bouchra , Abchir Oussama , El Kouali Mhammed , Chtita Samir 
Published: August 2024

Abstract:
Diabetes mellitus (DM) manifests as a complex and chronic metabolic disorder, posing
a significant threat to global public health and contributing substantially to mortality rates. It is
characterized by elevated blood glucose levels or hyperglycemia and requires effective preventive
and therapeutic strategies. One promising approach involves targeting the inhibition of α-
glucosidase and α-amylase, key enzymes responsible for carbohydrate hydrolysis. Inhibiting these
enzymes proves beneficial in reducing postprandial glucose levels and mitigating postprandial
hyperglycemia. However, existing antidiabetic medications are associated with undesirable side
effects, highlighting the need to develop new molecules with increased efficacy and reduced side
effects. Traditional methods for designing such molecules are often lengthy and costly. To address
this, computer-based molecular modeling tools offer a promising approach to evaluate the antidiabetic
activities of chemical compounds. This review aims to compile information on chemical
compounds assessed for their anti-diabetic activities through molecular modeling, with a particular
focus on the period from 2020 to 2023.
Impact of the COVID-19 Pandemic on People Newly Diagnosed with HIV and those Already in -care in Türkiye
Authors: Arzu Nazlı , Sabri Atalay , Nazlıhan Yalcın , Gamze Helvacı , Hividar Altan , Deniz Gokengin 
Published: August 2024

Background:
COVID-19 has inevitably influenced health systems. HIV testing rates
have been reduced, and access to antiretroviral treatment has been scaled down. We evaluated the
impact of COVID-19 on the management of people living with HIV (PLWH) in Türkiye.

Methods:
We conducted a cross-sectional study in three tertiary care hospitals. We compared the
baseline characteristics at the first visit and viral suppression rates at the 24th week of new HIV
diagnoses during the pandemic with those during the previous two years. To observe the effect
of the pandemic on people living with HIV who were already in care, we compared the metabolic
and clinical parameters like weight, blood pressure, blood lipid levels, fasting glucose levels, and
liver and renal function tests, of the same people before and during the pandemic.

Results:
The first group included 380 cases (127 diagnosed during the pandemic and 253 diagnosed
during the previous year). The demographic characteristics were similar. The newly diagnosed
PLWH during the pandemic had significantly higher baseline HIV RNA levels (p=0.005),
a lower number of clinical visits (p=0.0005), and a lower number of cases with undetectable viral
loads at 24 weeks of treatment (p=0.0005) than those diagnosed during the pre-pandemic period.

:
The second group included 261 individuals with a mean follow-up duration of 24.7 (SD± 3.5;
min- max 12-144) months. The comparison of laboratory parameters revealed that in the postpandemic
period, virologic suppression was maintained at 90.1%, body mass index (p=0,0001),
total cholesterol (p=0,0001), and LDL levels (p=0,0001) increased significantly, and creatinine
levels decreased significantly (p=0,0001).

Conclusion:
Our study showed that COVID-19 deteriorated the HIV management of PLHIV.
Strengthening the medical infrastructure of basic services for PLWH is critical for future crises.
Study on the Prediction of Liver Injury in Acute Pancreatitis Patients by Radiomic Model Based on Contrast-Enhanced Computed Tomography
Authors: Liu Lu , Yu Ningjun , Liu Tingting , Chen Shujun , Pu Yu , Zhang Xiaoming , Li Xinghui 
Published: August 2024

Objectives:
This study aimed to predict liver injury in AP patients by establishing a radiomics model based on CECT.

Methods:
A total of 1223 radiomic features were extracted from late arterial-phase pancreatic CECT images of 209 AP patients (146 in the training cohort
and 63 in the test cohort), and the optimal radiomic features retained after dimensionality reduction by LASSO were used to construct a radiomic
model through logistic regression analysis. In addition, clinical features were compiled to develop a clinical model, and a joint model was
established by combining the best radiomic features and clinical features to evaluate the practicality and application value of the radiomic models,
clinical model, and combined model.

Results:
Four potential features were selected from the pancreatic parenchyma to construct the radiomic model, and the AUC of the radiomic model was
significantly greater than that of the clinical model for both the training cohort (0.993 vs. 0.653, p = 0.000) and test cohort (0.910 vs. 0.574, p =
0.000). The joint model had a greater AUC than the radiomics model for both the training cohort (0.997 vs. 0.993, p = 0.357) and the test cohort
(0.925 vs. 0.910, p = 0.302).

Conclusion:
The radiomic model based on CECT has good performance in predicting liver injury in AP patients and can guide clinical decision-making and
improve the prognosis of patients with AP.
Inhibitory Effects of Aspirin and Ibuprofen Overdose on Cholinesterase
Activity: In Vivo and In Vitro Studies
Authors: Saberi-Hasanabadi Parisa , Dezfulynejad Hesam , Mohammadi Hamidreza 
Published: August 2024

Background:
In recent years, it has been reported that long-term use of Non-Steroidal
Anti-Inflammatory Drugs (NSAIDs) may have protective effects against neurodegenerative diseases
by inhibiting the activity of cholinesterase enzymes. The exact biological mechanism of
these protective effects is not yet known. This study aims to assess the in vivo and in vitro effects
of aspirin and ibuprofen injection on the activity of acetylcholinesterase and butyrylcholinesterase.

Materials and Methods:
In this experimental study, 70 adult male mice (20-25 g) were divided
randomly into 7 groups (n= 10) including a control group that received normal saline and other
groups that received different dosages of aspirin and ibuprofen (100, 200, and 300 mg/kg) in the
form of intraperitoneal injection. Mice were anesthetized by ether, and blood samples were taken
from the heart. Ellman´s methods were used to measure cholinesterase, erythrocytes, and serum,
respectively.

objective:
This study aims to assess the in vivo and in vitro effects of aspirin and ibuprofen injection on the activity of acetylcholinesterase and butyrylcholinesterase.

Results:
The activity of cholinesterase enzymes in serum and erythrocytes decreased significantly
(P<0.0001) in treated groups with aspirin and ibuprofen compared to the control samples after
3 and 24 hours. However, these inhibitory effects were variable depending on the dose of the injected
drugs, and they were statistically significant at higher injection doses in vitro and in vivo
analysis.

Conclusion:
The result of this study showed that non-steroidal anti-inflammatory drugs can inhibit
the activity of the cholinesterase enzymes in both in vivo and in vitro conditions compared
to the control group.
Screening and Identification of Natural Compounds as Potential Inhibitors of Glutamate Racemase, an Emerging Drug Target of Food Pathogen E. coli O157:H7: An In-silico Approach to Combat Increasing Drug Resistance
Authors: Kumar Rajnish , Gupta Samarth , Adhana Sujata , Khanna Anoushka , Sahoo Sibasis , Faiza Muniba , Baweja Renu , Pandey Archna , Mittal Avneesh , Chaudhry Uma 
Published: August 2024

Background:
Shiga Toxin-Producing Escherichia coli (E. coli O157:H7), capable of causing serious food-borne illnesses, is extensively studied and is known to be transmitted through animal reservoirs or person-to-person contact, leading to severe disease outbreaks. The emergence of antibiotic resistance in these strains, coupled with increased adverse effects of existing therapeutics, underscores the urgent need for alternative therapeutic strategies.

Objective:
This study aims to evaluate Glutamate Racemase (MurI protein) of the food-path-ogenic E. coli O157:H7 (EC MurI) as a novel drug target. Furthermore, the study seeks to identify new compounds with potential inhibitory effects against this protein.

Methods:
Using computational tools, the study identified inhibitor binding sites on EC MurI and identified relevant inhibitors capable of binding to these sites. Molecular docking tech-niques were employed to assess potential hits, and selected compounds were further analyzed for their structural activity and binding affinity to the protein.

Results:
The results of the study revealed that Frigocyclinone and Deslanoside, exhibited the best binding affinity with EC-MurI. Subsequent molecular dynamic (MD) simulations of the selected complexes indicated that both compounds were stable. This suggests that Frigocy-clinone and Deslanoside have the potential to serve as potent inhibitors of EC-MurI.

Conclusion:
In summary, this study highlights the urgent need for alternative therapies against food-pathogenic E. coli, focusing on E. coli O157:H7. Evaluation of Glutamate Race-mase as a drug target identified Frigocyclinone and Deslanoside as promising inhibitors. MD simulations indicated their stability, suggesting their potential as lead molecules for further research and treatment development.
A Study of Micellar Catalyses on Oxidation of Glycine by QDC in the Presence of Sodium Dodecyl Sulphate (SDS) in Aqueous Perchloric Acid Medium
Authors: Meena Priyanka , Meena Kamini , Dhanraj  , Yadav Manju Bala 
Published: August 2024

Aims:
To study the micellar effect of SDS on the oxidation of glycine by
Quinolinium Dichromate (QDC) in perchloric acid medium.

Background:
Among the amino acids, glycine plays a major role in multiple metabolic
reactions, such as glutathione synthesis and one-carbon metabolism. The oxidation of
glycine has received importance because it is the major neurotransmitter inhibitor in the
spinal cord and brainstem. In the oxidation process of amino acids, highly toxic chromium
(VI) compounds are converted into non-toxic chromium (III) by quinolinium dichromate
(QDC) oxidant in an appropriate pH value medium.

Objective:
1. To study the catalytic role of anionic surfactant (SDS) on the oxidation of
glycine by QDC through micellization, evaluation of critical micelles concentration
(CMC) in the presence and absence of glycine and other surface properties along with
thermodynamic quantities. 2. Determination of rate constant and order of reaction with
respect to QDC, glycine, acid and surfactant which will help to study the kinetics of the
reaction 3. Analysis of oxidation product by FT-IR and calculation of activation parameters.
4. Synthesis of oxidant (QDC) and its characterization by UV-Visible spectrophotometer
and NMR spectroscopy.

Methods:
The reaction was monitored spectrophotometrically at λmax = 440 nm using
Systronics Spectrophotometer-166 and 2203. The reaction mixture containing glycine,
perchloric acid, SDS and water was taken in a separate flask in a thermostat and the oxidation
reaction was started by adding the required amount of oxidant.

Results:
First-order kinetics was observed with respect to oxidant, glycine and hydrogen
ions. The rate of reaction increased remarkably with an increase in the concentration of
surfactant (SDS). The kinetic results show that the ionic strength variation does not have
any significant effect on the rate whereas the increase in the dielectric constant of the
medium shows a remarkable effect on the rate constant. From stoichiometry study, it was
found that 2 moles of oxidant (QDC) consumed 3 moles of glycine to produce aldehyde
(Formaldehyde).

Conclusion:
The observed negative value of (ΔS) entropy of activation and positive
(ΔH) enthalpy of activation suggests a more ordered activated complex formation and
highly solvated transition state. The kinetics of the reaction in a perchloric acid medium
is found to be accelerated in the presence of surfactant (SDS). The kinetics of the reaction
follow pseudo first-order decay of Cr(VI) species (QDC), a unity dependence of rate
on glycine and perchloric acid. The oxidation product formaldehyde was identified by
FTIR. NMR spectrum analysis of synthesized QDC shows a resemblance with pure
QDC.
Graphene-based Nanomaterials As Catalysts for the Synthesis of Medicinally Privileged Heterocycles: Importance and Outlook
Authors: Roy Babli , Basu Basudeb 
Published: August 2024

:
Catalysis is an integral part of sustainable and green chemical processes. During the last two decades, the wonder 2D carbon material with
honeycomb structure, graphene, and other functionalized graphenes have emerged as extremely versatile and robust nanomaterials in
heterogeneous catalysis. The incredible catalytic efficacy of such carbon nanomaterials relies on their unique physicochemical properties, including
large surface area, diverse catalytic active sites, multiple chemical functionalities, tunable electron density, synergistic effect, etc., making them
noteworthy as metal-free catalysts and catalytic supports.

:
The article presents an overview of the catalytic applications of various graphene-based nanomaterials (GBNs), either metal-free or embedded with
metal/metal oxide NPs, in synthesizing medicinally privileged heterocyclic compounds. It also summarizes the general methodologies for
preparing graphene and various GBNs, their chemical structures, characterization techniques, and discussions on the potential active sites that are
responsible for wider catalytic activity. Overall discussions unequivocally establish a promising paradigm for uncovering more innovative
graphene-based materials and their subsequent applications in diverse fields, including heterogeneous catalysis.
Phytochemical Marker-based Analysis, Antioxidant Potential, and Shelf-Life Study of Geographically Different Samples of Tinospora cordifolia (Stem)
Authors: Gandhi Yashika , Mishra Sujeet K , Kumar Vijay , Rawat Hemant , Kumar Ravi , Singh Gagandeep , Singh Ravindra , Singh Arjun , Narasimhaji Ch Venkata , Srikanth Narayanam , Acharya Rabinarayan 
Published: August 2024

Background:
Tinospora cordifolia (TC), commonly referred to as Guduchi, holds a prominent position in the Indian traditional system of medicine and has been
cited in Ayurvedic literature for its efficacy in the treatment of a range of ailments, including jaundice, urinary issues, diabetes, prolonged diarrhea,
skin conditions, stomachaches, and dysentery.

Methods:
The present study analyzed the content of phytochemical markers present in the stems of TC collected from five distinct geographical locations
(TC-01 to TC-05) and assessed the corresponding variations in their in-vitro antioxidant potential.

Results:
Lupeol content in various samples of TC varied from 217.9 to 510.9 μg/mg, while palmatine ranged from 0.002% to 0.025%. Total phenolic
content (TPC) ranged from 0.77 to 6.35 mg GAE/g wt., and total flavonoid content (TFC) from 12.15 to 20.03 mg QCE/g wt., with IC50 values
between 21.02 and 81.81 mg/mL. Elemental analysis of TC-01 to TC-05 showed significant essential elements and permissible levels of heavy
metals. A shelf-life study of TC samples indicated stability beyond three years.

Conclusion:
The considerable diversity in phytochemical content and antioxidant values underscores the substantial influence of geographical variation on the
therapeutic potential of TC.
Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study
Authors: Shen Jocelyn , DiPaola Daniella , Ali Safinah , Sap Maarten , Park Hae Won , Breazeal Cynthia 
Published: August 2024

Background
Empathy is a driving force in our connection to others, our mental well-being, and resilience to challenges. With the rise of generative artificial intelligence (AI) systems, mental health chatbots, and AI social support companions, it is important to understand how empathy unfolds toward stories from human versus AI narrators and how transparency plays a role in user emotions.

Objective
We aim to understand how empathy shifts across human-written versus AI-written stories, and how these findings inform ethical implications and human-centered design of using mental health chatbots as objects of empathy.

Methods
We conducted crowd-sourced studies with 985 participants who each wrote a personal story and then rated empathy toward 2 retrieved stories, where one was written by a language model, and another was written by a human. Our studies varied disclosing whether a story was written by a human or an AI system to see how transparent author information affects empathy toward the narrator. We conducted mixed methods analyses: through statistical tests, we compared user’s self-reported state empathy toward the stories across different conditions. In addition, we qualitatively coded open-ended feedback about reactions to the stories to understand how and why transparency affects empathy toward human versus AI storytellers.

Results
We found that participants significantly empathized with human-written over AI-written stories in almost all conditions, regardless of whether they are aware (t196=7.07, P<.001, Cohen d=0.60) or not aware (t298=3.46, P<.001, Cohen d=0.24) that an AI system wrote the story. We also found that participants reported greater willingness to empathize with AI-written stories when there was transparency about the story author (t494=–5.49, P<.001, Cohen d=0.36).

Conclusions
Our work sheds light on how empathy toward AI or human narrators is tied to the way the text is presented, thus informing ethical considerations of empathetic artificial social support or mental health chatbots.