bluuebunny/crossref_metadata_2025 huggingface dataset:
Tanshinone IIA alleviates liver fibrosis through inducing inactivation and ferroptosis in hepatic stellate cells
Authors: Wang Dan , Tan Qingquan , Zheng Qing , Ma Yanling , Feng Li
Published: November 2024

Background
Tanshinone ⅡA is derived from Salvia miltiorrhiza and has multiple therapeutic targets and functions. Numerous studies have reported positive outcomes regarding its influence on liver diseases. However, the exact therapeutic effect as well as the underlying hepatoprotective mechanisms are still lacking.
Methods
Liver fibrosis model was established via ligation of the common bile duct. Mice received intraperitoneal administration of different concentrations Tanshinone ⅡA (4 mg·kg-1,8 mg·kg-1) for 2 weeks. Liver function was assessed through Hematoxylin and Eosin (HE), Masson, and Sirus red. Serum levels of ASL, ALT and MDA level were quantified using enzyme-linked immunosorbent assay (ELISA).The total Iron content of liver was quantified by Triple Quad-ICP-MS. TGFβ-induced hepatic stellate cells (HSCs) as a cell model of liver fibrosis, and were treated with Tanshinone ⅡA at different concentrations (10mM, 20mM, 30mM, 40mM). Combination of Tanshinone ⅡA with YAP agonists as well as YAP inhibitors was applied in activated HSCs and animal models.
Results
Tanshinone ⅡA treatment exhibited relieved liver fibrosis, mitigated histological liver damage, lowered serum levels of ALT and AST, reduced macrophage infiltration and ferroptosis. Tanshinone ⅡA suppressed the activation of HSCs, collagen production and induced ferroptosis of HSCs through blocking YAP signal pathway, and the combination of YAP agonist and Tanshinone ⅡA reversed the therapeutic effect of Tanshinone ⅡA on activated HSC and bile duct ligation-induced liver fibrosis.
Conclusion
Tanshinone ⅡA inhibited activation as well as collagen production, and promoted the ferroptosis of HSCs, alleviating the bile duct ligation-induced liver fibrosis by inhibiting YAP signal pathway.
Genetic diversity and population structure assessment among 376 maize inbred lines using single nucleotide polymorphism markers
Authors: Oyekunle Muhyideen , Abubakar Adamu Masari , Zakariya Saminu , Ado Shehu Garki , Usman Inuwa Shehu , Uwais Umar Umar , Gidel Melaku
Published: November 2024

Background: Knowledge and understanding of the patterns of population structure and diversity are crucial for the sustainable development of outstanding products in any breeding programme. A study was conducted to assess the genetic distances, infer population structure and identify the best putative hybrid combinations of newly developed 376 maize inbred lines using single nucleotide polymorphism (SNP) markers.
Results: Leaf samples of the 376 inbred lines were genotyped using mid-density 3305 DArTseq-based SNP markers. Following quality checks, 2219 SNP markers were retained for further analysis. Polymorphic SNP markers averaged 0.37 and were well distributed across the genome, covering 306 Mb total length. On average, 221 SNP markers were mapped per chromosome, with chromosome 5 having the highest number of markers (293). The minor allele frequency and observed heterozygosity ranged from 0.05 to 0.50 and 0.01 to 0.93, respectively. Analysis of molecular variance indicated genetic differentiation among and within groups and the pairwise genetic distance (GD) had a mean of 0.37, indicating the existence of substantial genetic variation in the germplasm panel. The model-based population structure, and discriminant analysis of principal components grouped the 376 inbred lines into five subpopulations. More than 30,000 intergroup hybrid combinations had the GD above the average of 0.37.
Conclusion: Wide genetic variability existed among the inbred lines, making all possible cross combinations of putative parents difficult. Therefore, planned crosses involving representative lines from opposing heterotic groups would be required. The results of this study would help breeders in developing breeding strategies for sustainable genetic improvement in maize.
RANK pathway inhibition sensitizes triple-negative breast cancer to CDK4/6 inhibitors and enhances immune response
Authors: Casimiro Sandra , Gomes Inês , Martelo Maria , Vilela Rúben , Torres Sofia , Corredeira Patrícia , Miranda Joana , Mansinho André , Torres Sofia , Abreu Catarina , Sousa Rita , Costa Luis
Published: November 2024

Despite chemotherapy's limitations and toxic effects, it remains the primary treatment for most triple-negative breast cancer (TNBC) patients. While cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy have revolutionized luminal breast cancer treatment, CDK4/6i alone are largely ineffective in TNBC, even with functional retinoblastoma protein (pRB). The receptor activator of nuclear factor-κB (RANK) pathway has been linked to poor prognosis in TNBC. Previous research connected RANK with resistance to CDK4/6i in luminal breast cancer, which could be reversed by RANK ligand inhibitors (RANKLi). In this study, RANK knockdown or RANKLi treatment sensitized pRB-proficient TNBC cells to CDK4/6i, reducing tumor growth and metastasis. Combining CDK4/6i with RANKLi enhanced cell cycle arrest and elicited an immune response in the tumor microenvironment across BC subtypes. These findings suggest that combining CDK4/6i and RANKLi is a promising therapeutic approach for pRB-proficient TNBC, with potential immunomodulatory benefits, warranting further investigation.
Non-linear Reconfigurable Threshold Logic Gates Based on Nanostructured Metallic films
Authors: Martini Gianluca , Paroli Bruno , Milani Paolo
Published: November 2024

The dominion of Boolean logic circuits (BLCs) in current electronic design and synthesis tools is increasingly being called into question by challenges posed by the extreme miniaturization and energy footprint typical of AI applications. Compared to BLCs, Threshold Logic Gates (TLGs), by programming the weights, allow for more than two input states, which can enhance complexity in simplifying circuit design. Memristors organized in crossbar arrays architectures have been proposed to implement the programmable weights of threshold logic elements. An alternative TLG design, called Receptron, has been recently proposed: it is based on nonlinear weights thus widening the spectrum of Boolean computable functions while simplifying training thanks to a random search protocol. Here we present a theoretical and an experimental characterization of the Receptron model to determine the connection between the structure of the weights and function computability, identifying sub-linearity as an enabling feature. These results allowed the fabrication of an improved version of a Receptron device, enhancing its sub-linearity and random search efficiency thanks to an ad hoc circuit. This nonlinear threshold logic gate device can be considered for the integration with other conventional logic components for higher levels of computational complexity. Corresponding authors: paolo.milani@mi.infn.it; bruno.paroli@unimi.it
Biological Activity and Phytochemical Analysis of Cucumis callous (Rottl.) Cong Underutilization Vegetable
Authors: Vaghasiya Shraddha , Ishnava Kalpesh
Published: November 2024

Cucumis callosus is a member of the cucumber family and widely many regions of world for its underutilization vegetable and medicinal purposes. The present study focuses on assess biological activity of different extracts and evaluate the presence of phytochemicals through qualitative tests. Fruit powder extracted in soxhlet extractor using different organic solvent (Chloroform, Ethanol, Methanol, Petroleum ether). All four extracts study the anti- inflammatory activity, in vitro alpha – amylase inhibitory activity, anthelmintic activity and antibacterial activity. The qualitative analysis of different organic solvent extracts evaluated. Four different organic solvent out of this methanol solvent extract give comparatively show better biological. activity in protein denaturation and alpha – Amylase. C. callosus extracts have demonstrated significant alpha-amylase inhibitory activity, which could be useful in the management of diabetes. Methanolic extracts have shown potential anthelmintic activity against various intestinal parasites, which could be useful in the treatment of parasitic infections. Fruit extracts have exhibited antibacterial activity against several bacterial strains, which could be beneficial in the treatment of bacterial infections. All organic solvent presents the alkaloid, phenol and Tannins. The presence of these phytochemicals in the plant extract may contribute to their curing of disease. The present bioactive compounds in C. callosus it may be potential therapeutic properties make it a promising candidate for the development of new natural medicines for various diseases and conditions. However, further studies are needed to fully understand the mechanisms of action and cytotoxicity of C. callosus extracts.
Molecular docking and dynamics as a tool to study benzimidazole resistance in helminths: A scoping review
Authors: Tenorio Jan Clyden
Published: November 2024

Background: Benzimidazole (BZ) resistance remains an emerging grave concern in helminths of public and veterinary health concerns. Resistance against BZ drugs is due to mutations that change the amino acid comprising the β-tubulin protein, which negatively affects its interactions with BZ drug molecules. Several in silico modeling studies have been published to decipher the precise mechanism of BZ resistance, but inconsistencies on the resistance consequence mutations confer and the effect of different BZ ligands have led to further confusion regarding the exact mechanism of resistance. Hence, this scoping review was done to unravel the mechanism of BZ resistance based on published research on molecular docking and dynamics.
Methods: A scoping review was conducted in ScienceDirect, MEDLINE via PubMed and Scopus using the search term “Benzimidazole Resistance AND Beta Tubulin AND Molecular Docking”. A total of 37 hits were recovered and from these 6 were included after selection, inclusion, and risk of bias assessment.
Results: The six research papers included in this review studied several helminth species: Haemonchus conturtos, Trichinella spiralis, Ancylostoma duodenale, Ancylostoma caninum, Ancylostoma ceylanicum, Necator americanus, Trichuris trichiura, Trichuris suis, Anisakis simplex, Ascaris suum, Ascaridia galli, Parascaris equorum, Toxocara canis, and Fasciola hepatica. The benzimidazole resistance-associated mutations studied included F167Y (TTC, TTT → TAC, TAT), E198A (GAG, GAA → GCG, GCA), and F200Y (TTC, TTT → TAC, TAT). The results show that the E198A can markedly reduce the binding affinity of BZ ligand-β-tubulin interactions. The F167Y and F200Y also showed a similar effect that could vary based on the helminth species. The F200Y mutation can alter the conformation of the β-tubulin active site, negatively affecting drug binding.
Conclusion: While the impact of these mutations can vary depending on the specific helminth species and the BZ drug involved, the overall findings highlight the importance of targeting these residues for the development of novel anthelmintic strategies to address emerging drug resistance.
The association between urban land demarcation and household food insecurity among formal and informal settlements in southernDurban city, KwaZulu Natal
Authors: Ngema-Msomi Primrose Z.
Published: November 2024

The study assessed the association between urban land demarcation and household food insecurity in three neighborhoods: the Malukazi (MIS), Uganda Informal Settlements (UIS) and Isipingo Hills (IH) formal settlements. Ninety households were interviewed, stratified into 30. The findings were that 80% of the Malukazi informal settlements and 66% of the Uganda Transit Camp respondents indicated that the development of vegetable gardens would sustain household food security. However, both areas were dissatisfied with their housing designs and landsizes, especially the Reconstruction Development Plan (RDP) vicinity and shack dwellings, further indicating that land scarcity hinders the development of vegetable gardens. Furthermore, household food insecurity was the result of a high employment rate and low income, some of which were solely dependent on social grants. Constantly opting for scrap sales to boost their income and own less than 3x3 m2 of space. In contrast, IHs were satisfied with their employment opportunities, had incomes above R4000 and had acceptable housing and land. The results revealed a wide gap in living standards among the three neighborhoods. The household food consumption score indicated that the MIS was classified as food insecurity or poor (0 to 21) (66%). Individuals with UIS (poor [0 to 21] [53%] consumed 3 of the 8 food groups according to the household dietary diversity score. Isipingo Hills had borderline scores ranging from 21.5 to 35 (56%), and 33% had acceptable scores (35). Negative findings indicated weak institutional support and inappropriate government policies, resulting in severe food insecurity and housing dissatisfaction. The government should address land inequality issues and increase the involvement of poor urban households in government food security programmes to stabilize urban food security.
Effect of Emissivity on Wall Temperature of Air Frames
Authors: KARTHIK MURI VENKATESWARA
Published: November 2024

This study explores the influence of emissivity on the surface temperature of airframes under transient thermal conditions, employing ANSYS APDL for simulation. The research is driven by the critical need for effective thermal management in airframes, which are essential structural components in aerospace and automotive industries. The analysis was conducted on a hollow steel airframe with an external diameter of 250 mm, an internal diameter of 248 mm, and a length of 300 mm. The model was discretized using solid-8 node 70 element, with a mesh size of 1 mm. A constant heat flux of 10,000 W/m² was applied to the airframe’s wall over a period of 300 seconds, with a time step of 1 second, to simulate the heat transfer conditions. The study systematically varied the emissivity from 0.05 to 1, in increments of 0.05, to assess its impact on the airframe's surface temperature. Results indicate a clear inverse relationship between emissivity and surface temperature. As emissivity increases, the airframe's ability to emit thermal radiation improves, leading to a significant reduction in surface temperature. This effect is particularly pronounced at higher emissivity values, where a substantial decrease in surface temperature was observed. The findings underscore the pivotal role of emissivity in thermal management. Airframes with higher emissivity demonstrate enhanced heat dissipation capabilities, which is critical for maintaining structural integrity under high thermal loads. The study provides valuable insights for the design and optimization of airframes, particularly in applications where precise thermal regulation is essential. By selecting materials with appropriate emissivity characteristics, engineers can achieve superior thermal performance, thereby improving the safety, durability, and efficiency of airframes in demanding operational environments.
Understanding the Rise of Right-Wing Crimes, and Intergroup Threat Theory: Global Perspective & Case Studies
Authors: Bhangoo Aila Sajid , Cho Suhhae , Hashmi Rehana Saeed
Published: November 2024

The rise in right-wing extremist offenses has become a significant global concern, particularly in the United States. These offenses are usually fuelled by radical ideologies such as nationalism and white supremacy, and have quadrupled over the past decade. Our analysis reveals that far-right extremist offenses in the U.S. have surpassed violence previously linked with jihadist-groups, with right-wing factions responsible for over 60% of extremist-related casualties since 2014. Moreover, the increase in these offenses is strongly corelated with a rise in immigration influx and demographic changes. This study employs a systematic literature review guided by the PRISMA framework and synthesizes relevant works to explore the relationship between rising immigration rates and the increase in right-wing extremist offenses. While the study mainly draws on intergroup threat theory, other sociological and psychological frameworks are also presented to shed light on how economic downturns and demographic transitions can provoke hostile right-wing sentiments toward immigrants and minorities, often culminating in violent crimes. Our findings and analysis emphasize the need for comprehensive policy interventions which not only address the rise in extremist discourse but also curb those societal factors that contribute to their growth. Additionally, we examine the role of social media in disseminating extremist ideologies and suggest that immigration policy reforms can help mitigate xenophobic attitudes. Moreover, we also recommend that efforts to combat right-wing extremism should focus on promoting social inclusion, economic justice, and close monitoring of extremist organizations, both online and offline.
Determinants of sustainability performance in information technology companies: Cooperation through strategic alliances and business strategies
Authors: Emilia Sari Ria , Arief Muhtosim , Hamsal Mohammad , Kartono Rahim Rano
Published: November 2024

The rapid progress in information technology has presented both opportunities and challenges for companies, particularly within the IT industry in Indonesia. This study examines the impact of hybrid business strategies and corporate strategic alliances on the sustainability performance of IT companies. Adopting quantitative methods, data were collected from 389 management professionals in IT companies through a structured questionnaire. The analysis employed structural equation modeling (SEM) to assess the relationships between hybrid business strategies, strategic alliances, and sustainability performance. The results indicate that hybrid business strategies positively influence corporate strategic alliances (t-value = 2.243, p-value = 0.025) and positively influence corporate sustainability performance (t-value = 5.294, p-value = 0.000). Additionally, corporate strategic alliances significantly enhance sustainability performance (t-value = 5.603, p-value = 0.000), mediating the relationship between hybrid strategies and sustainability outcomes (t-value = 1.995, p-value = 0.047). The findings emphasize the critical role of strategic alliances in achieving long-term sustainability goals in the IT industry. The study concludes that integrating hybrid business strategies with effective strategic alliances is essential for IT companies to maintain competitiveness and achieve sustainable growth.
Characterization of Fertile and Infertile Dog Seminal Plasma Proteins and Their Correlation with Semen Quality: Preliminary Study
Authors: ESIN BURCU , GIZEM MERVE , KABAY SEZENER , KAYA CUMALI , ERGÜDEN VOLKAN , ÇEVIK MESUT
Published: November 2024

Significant deterioration in semen quality is associated with increased male infertility. Alterations in the sperm proteome resulting from infertility are not well understood. The aim of this study was to examine the connection between the proteome and the quality of spermatozoa in fertile and infertile dogs. The research was conducted on 11 male dogs, including 3 German shepherds, 3 Turkish Kangal, 2 Cane Corso, and 3 Golden Retrievers, aged 4 and 6 years (4.81 ± 0.75). Four of the 11 dogs constituted the infertile study group because of conception failure observed in at least 3 (3-5) matings with different fertile females within 1 year, and seven dogs from different owners constituted the fertile control group. Semen was manually manipulated and collected from all dogs in the presence of a female dog in heat. Ejaculates were used for spermatological examination and protein analysis. Computer-assisted semen analysis (CASA) was used to evaluate semen samples. In spermatological parameters, motility, kinematic parameters, morphology and plasma membrane integrity were evaluated. Gel electrophoresis (SDS-PAGE) was used to analyze proteins in sperm. The semen quality of infertile dogs was significantly lower. Motility, progressive motility, viability and plasma membrane integrity were statistically significantly lower in the infertile group than in the fertile group (P < 0.05). In morphological parameters, acrosome, head, middle part, tail and total defects were found to be statistically significantly higher in sterile dogs than in fertile dogs (P < 0.05). In the study, a total of 8 protein bands with molecular weights (MW) ranging from 11.0 to 245.0 kDa were identified in the protein analysis of semen. Variations in the sperm proteome composition were shown to be dependent on fertility. These proteins were associated with important metabolite pathways. Additionally, correlations of these bands with various spermatological parameters were revealed. The result of the study suggests that seminal plasma proteins play a role in semen quality and may be potential fertility biomarkers.
DETERMINAÇÃO DE ÁCIDO SALICÍLICO EM LEITE UTILIZANDO SPOT TEST EM PAPEL E PROCESSAMENTO DE IMAGENS DIGITAIS
Authors: Magalhães Conrado Josiele Aparecida , da Silveira Petruci João Flávio
Published: November 2024

DETERMINATION OF SALICYLIC ACID IN MILK USING PAPER-BASED SPOT TESTS AND DIGITAL IMAGE TREATMENT. Milk is a worldwide consumed product, and therefore, quality control is essential. The addition of salicylic acid (SA) represents a common type of adulteration, used to reduce the growth of microorganisms and extend shelf life. However, excessive ingestion of SA can cause gastrointestinal issues and even lead to death. This study describes the development of a simple analytical method for the determination of salicylic acid in milk based on the colorimetric reaction between the analyte and FeIII ions. The quantification was performed by digital image treatment. Different linear ranges were obtained for each type of milk analyzed: 100 to 1500 mg L-1 for raw milk, 300 to 2000 mg L-1 for skimmed milk, 500 to 2000 mg L-1 for powdered milk, 100 to 2000 mg L-1 for whole milk, and 100 to 1500 mg L-1 for lactose-free milk. The accuracy of the method was obtained by comparison with a reference method, and the recovery percentage provided values between 71 and 120%. An RSD (relative standard deviation) of 0.7% was obtained. The parameters evaluation resulted in a simple and miniaturized analytical method without a sample preparation step for the determination of SA in milk, serving as a tool for identifying adulteration practices.
NARRATIVA HISTÓRICA NO MUSEU DIGITAL DE CAMPINA GRANDE
Authors: Morais de Lima Thuca Kércia
Published: November 2024

O Museu Digital de Campina Grande, ligado ao Departamento de Regional do Serviço Social da Indústria (SESI/PB), é constituído por recursos midiáticos com curadoria histórica. O presente texto discute como a narrativa histórica é apresentada tendo como recorte a inserção do museu dentro de uma cultura digital possibilitada pela popularização das Tecnologias da Informação e Comunicação. O museu sendo (re)produtor de dada identidade campinense, suscita a crítica a respeito das memórias impostas como hegemônicas e que constituem o substrato do imaginário da cidade que gira em torno da ideia de grandeza. A observação do espaço se deu de forma empírica e sua problematização entrelaçou-se a pressupostos teóricos-metodológicos da História Cultural na interface entre memórias, museus, cidades e identidades.
MUSEU MAGÜTA
Authors: Trindade Thaís Lima , Batista de Oliveira Joaquina Maria
Published: November 2024

A atual construção de processos museais próprios dos povos indígenas ganha espaço frente aos discursos colonialistas impregnados durante muito tempo nos museus etnográficos. Apresenta-se uma revisão de literatura, combinada a análise de outras fontes sobre museus etnográficos, povos indígenas e patrimônio cultural indígena brasileiro. Atualmente os museus indígenas buscam a aproximação e a participação dos indígenas, além do surgimento dos museus legitimamente indígenas, como o Museu Magüta da etnia Ticuna, que refletem uma tomada de consciência e a reafirmação da identidade dessas populações e do campo museal
A Methodical Review of Intranasal Delivery of Nanocarriers for the Treatment of Glioblastoma: An Emerging Therapeutic Option
Authors: Popli Pankaj , Monika  , Pragi  , Kumar Varun , Sharma Deepanshu , Shrikant  , Kumari Shabnam , Garg Deepak
Published: November 2024

Glioblastoma multiforme (GBM) is responsible for about half of all primary malignant
tumors in the central nervous system (CNS). Nanotechnology and nanocarrier-based drug delivery
may prove to be an asset in the ongoing fight against the difficulties associated with treating
GBM. Obstacles to effective drug delivery in GBM treatment include prolonged blood circulation,
sufficient BBB transit, effective internalization, and controlled drug release within GBM cells. By
virtue of the non-specific and non-targeted character of anti-tumor medicines, the efficiency of
medication delivery to gliomas is still impoverished. Glioma diagnosis and therapy have undergone
a paradigm change solely because of nanotechnology. The highly invasive nature of this malignant
glioma makes surgical resection a challenging procedure, and the current approved standard
of care—follow-up radiation therapy with concurrent temozolomide (TMZ)—will only prolong
the lifespan of patients by a few months. Drug delivery nanosystems (DDNSs) have garnered
attention in the treatment of cancer, particularly gastrointestinal cancer, according to recent
studies. This is because DDNPs have proven to be effective substitutes for conventional formulations
currently on the market, in addition to optimizing the delivery of drugs to neoplastic cells,
ameliorating the profile of toxicity and unfavorable effects, and reducing the overall harmful effects
of formulations that include antineoplastic agents. Specifically, nanocarriers have proven to
have an exceptional ability to get over the difficulties to achieve drug accumulation in the brain
without going through the system delivering by IN route. Pre-clinical research on polymeric nanocarriers
for treating GBM is ongoing, with few drug delivery systems entering clinical trials. This
study examines nanoparticle forms, and brain tumor statistics, and summaries the diagnosis and
treatment of GBM utilizing nanotechnology.
Nanotechnology Based Herbal Drug Delivery System: Current Insights and Future Prospects
Authors: Chowdhury Sailee , Nath Debabrata , Das Smriti Rekha Chanda , Kar Koyel , Chakraborty Priyanka , Kapoor Devesh U. , Prajapati Bhupendra G.
Published: November 2024

Herbal medicines, integral to human history, remain vital in developing countries owing
to the high costs of synthetic drugs, with 80% of the population relying on traditional practices.
There has been an escalating focus within the scientific community on the exploration of
phytoconstituents. This growing interest is due to the diverse benefits offered by herbal or plant-
based ingredients. Despite the dominance of allopathic treatments, medicinal plants are still widely
used but face challenges like poor absorption and low bioavailability. Many plant-derived pharmacologically
active compounds, such as tannins, flavonoids, and terpenoids, show poor solubility
in water. This low solubility, amalgamated with their inability to efficiently cross lipid-cell
membranes due to their large molecular size, considerably hinders their absorption. These factors
lead to declined efficacy and lower bioavailability of these compounds. Nanotechnology enhances
the effectiveness of medicinal plants through strategies such as polymeric nanoparticles (NPs),
solid lipid nanoparticles (SLNPs) and liposomes, improving solubility, protection and controlled
release. These advances revolutionize drug delivery, surging the bioavailability and therapeutic
value of herbal formulations. Nanomedicine employs NPs and nanorobots for enhanced bioavailability,
solubility and targeted delivery, despite challenges like understanding working principles,
potential toxicity and production scalability. Innovations in biopolymer-based systems, including
chitosan and alginate NPs and advanced delivery systems like dendrimers and inorganic NPs,
show significant potential. NPs have been effectively utilized to improve the pharmacokinetic and
pharmacodynamic properties of various drugs. By integrating biotechnological systems and phytosomes,
the bioavailability and bioactivity of herbal drug formulations can be significantly enhanced.
The future of nanomedicine is promising, with ongoing research enhancing therapy precision
and effectiveness and reducing adverse effects, making continued exploration in this field
highly worthwhile.
Prospects for Cancer Diagnosis, Treatment, and Surveillance: [18F]FDG PET/CT and Innovative Molecular Imaging to Direct Immunotherapy in Cancer
Authors: Rais Juhi , Ora Manish , Dixit Manish
Published: November 2024

Positron Emission Tomography (PET), a noninvasive technique, is most
suitable for quantitative evaluation of in vivo tumor biology. Based on its metabolic
activity, the accumulation of F-18 fluorodeoxyglucose ([18F]FDG), a positron emitter
radionuclide, is most explored indicative of tumor features. Quantitative evaluation of
FDG uptake is frequently used for treatment monitoring following chemotherapy or
chemoradiotherapy. Several investigations showed that FDG PET, which measures
metabolic change, was a more sensitive marker than CT or MRI, which measures
morphological change. [18F]FDG is now frequently used to assess tumor metabolism as
well as to track the effectiveness of immunotherapy, which is a useful treatment for
several malignancies. With the use of in vivo whole-body CD8+ T cell and PD-L1
expression imaging, for instance, radiopharmaceuticals that are novel in nature offer
the rare chance to characterize the immunological tumor microenvironment (TME) and
more accurately forecast which patients may react to therapy. Longitudinal molecular
imaging may also aid in clarifying potent changes, especially in instances of resistance
that occurred during immunotherapy, and aid in guiding a more individualized
therapeutic strategy. To categorize, forecast, and track treatment response and
molecular dynamics in areas of therapeutic need, this review focuses on new and
existing uses of [18F]FDG for imaging.
2-Deoxy-D-Glucose as an Emerging Chemotherapeutic Agent in Cancer Management
Authors: Singh Ashutosh , Kumar Ravinsh , Srivastava Amrita
Published: November 2024

Cancer cells have a unique property of uncontrolled growth and thus they
require a constant supply of energy. Warburg observed that tumor cells prefer
glycolysis even under oxygenic conditions and the process is known as aerobic
glycolysis. Hence, cancerous cells show an enhanced glucose-to-lactate conversion
rate. As cancerous growth is accompanied by enhanced glucose uptake, this feature is
best suited for the management of unwanted cell proliferation by blocking the glucose
metabolism of cancer cells. 2-deoxy-D-glucose (2DG), a glucose antimetabolite is
considered a competitive inhibitor of glucose transport and glucose phosphorylation. It
inhibits the glycolytic pathway primarily due to the inhibition of phosphohexose
isomerase by 2-deoxy-D-glucose-6-phosphate (2DG- 6P). Its chemical resemblance to
2-deoxymannose causes interruption in the initial steps of N-linked glycosylation
leading to the misfolding of proteins resulting in endoplasmic reticulum stress. In
addition to the two properties of 2DG namely, the prevention of glycolysis and
selective storage in the tumor cells, there are several other attributes of 2DG apart from
the ones mentioned above that make it an attractive target for use as an antitumor
agent. Some properties include the capability of inducing autophagy in tumor cells,
inhibiting genomic replication as well as mRNA expression of viral genes responsible
for Omit the induction of oncogenesis, blocking pathological angiogenesis while being
cautious towards established endothelial tubes and prominent anti-metastatic effect. In
the present chapter, various aspects of the use of 2DG in cancer management have been
discussed.
2-Deoxy-D-Glucose: A Glycolysis Inhibitor in the Treatment of Cancer
Authors: Aruna Poorani Arunagiri Sivanesan , Mohamed Ismail Mohamed Ibrahim , Santhoshkumar Pandeeswaran , Suresh Palaniswamy
Published: November 2024

Cancer involves abnormal and rapid cell growth, which requires an
increased energy supply for proliferating cells. As the demand for glucose rises in
cancer cells, the expression and activity of glucose transporters (GLUTs) also increase
to facilitate higher cellular glucose uptake. Cancer cells tend to shift their glucose
metabolic pathway from mitochondrial oxidative phosphorylation towards aerobic
glycolysis. 2-Deoxy-D-glucose competes with glucose and involves aerobic glycolysis.
It leads to the inhibition of HK and PGI, diminishes ATP production, and induces
apoptosis. Further, the increase in the AMP/ATP ratio promotes the AMPK signaling,
downregulating VEGF, and leading to angiogenesis inhibition and autophagy. As the
structural mimic of mannose, 2-DG interferes with the N-linked glycosylation, leading
to ER stress, and triggering the mitochondrial apoptotic pathway. 2-DG has been
employed as an antiproliferative, antiangiogenic, and antimetastatic drug by being
involved in the energy metabolic pathway. Combination therapy shows improved
results and reduces chemotherapeutic drug resistance. In this chapter, we will discuss
the Warburg effect, the role of 2-DG in the inhibition of aerobic glycolysis, and how 2-
DG inhibits the various other cancer hallmarks in energy metabolic pathway. Also,
reports on cancer treatment as well as cancer cell-imaging and risks associated with
chronic exposure are discussed.
Nanorobots and Nanomedicine in Drug Delivery and Diagnosis
Authors: Mishra Anupam , Mishra Koushlesh K. , Mishra Sushma , Mishra Rajeev , Mane Sheetal
Published: November 2024

Nanobotics is a developing field of nanotechnology that features a nanoscale
measurement and can be anticipated to work at the nuclear, atomic, and cellular levels.
Nanobotics offers a new frontier in biomedicine, with the potential to transform
diagnostics and therapeutics through its unique ability to manipulate biological systems
at a nanoscale level. Nanobots have a carbon-based skeleton and a toolkit that includes
components such as a hole containing the medicine, a payload, a capacitor, and a
microcamera with a tail having the action of swimming. Nanobots are equipped with
special sensors that diagnose target particles and molecules inside the body. These
sensors can be used to diagnose and treat different imperative infections like cancer,
diabetes, atherosclerosis, kidney stones, etc. Nanobots can be used to deliver targeted
drugs to target areas of the body that are difficult to reach through traditional drug
delivery methods such as blood circulation. Nanobots are either powered by exogenous
energy (e.g., magnetic field, light, acoustic field, electric field, etc.) or endogenous
energy (chemical reactions energy). They have been shown to be capable of
encapsulating, transporting, and delivering therapeutic content directly to the site of
disease, improving the therapeutic effectiveness and reducing systemic adverse
reactions of toxic drugs. This chapter covers the following topics: Nano-based
nanobots for diagnostics and disease management, types of nanobots, advantages and
limitations, robotic approaches in drug delivery, biomedical applications of nanobots,
and their future prospects.
Role of Artificial Intelligence in Drug Product Design and Optimization of Process Parameters
Authors: Pandey Pankaj Kumar , Likhariya Manoj , Bhadoria Juhi , Vinchurkar Kuldeep , Jain Priya
Published: November 2024

The integration of artificial intelligence (AI) in pharmaceutical research has
revolutionized drug product design and the optimization of process parameters,
marking a paradigm shift in the traditional drug development paradigm. This abstract
explores the multifaceted role of AI in these critical aspects of pharmaceutical
manufacturing. The chapter elaborates the significance of AI in revolutionizing
processes like drug discovery, formulation optimization, personalized medicine
development, predictive analytics, drug design, improved patient outcomes, and many
more. In drug product design, AI-driven methodologies have demonstrated
unparalleled capabilities in expediting the identification of novel drug candidates and
predicting their pharmacokinetic properties. Machine learning algorithms analyze vast
datasets, including molecular structures, biological interactions, and clinical trial
outcomes, to unravel complex relationships and generate insights that guide rational
drug design. This accelerates the discovery process and enhances the efficiency of lead
optimization, ultimately reducing the time and costs associated with drug development.
Furthermore, AI plays a pivotal role in optimizing process parameters during drug
manufacturing. The pharmaceutical industry faces challenges in ensuring the
reproducibility, scalability, and cost-effectiveness of production processes. AI
algorithms, particularly in combination with process analytical technologies (PAT),
enable real-time monitoring and control, ensuring the quality and consistency of drug
products. Through iterative learning and adaptive control, AI-driven systems can
dynamically optimize manufacturing parameters, minimizing variations and ensuring
the robustness of the production process. In conclusion, the incorporation of AI in drug
product design and process optimization is transformative, fostering innovation and
efficiency in the pharmaceutical industry. As the field continues to evolve,
collaborative efforts between computational scientists, chemists, and engineers are essential to harness the full potential of AI, ultimately advancing drug development and
improving patient outcomes.
Regulatory Insights into Artificial Intelligence in Drug Delivery and Medical Devices
Authors: Sharma Nayany , Bisht Rekha , Sontakke Rupali , Vinchurkar Kuldeep
Published: November 2024

The pharmaceutical industry is grappling with challenges that impede the
sustainability of drug development programs, primarily due to escalating research and
development costs coupled with diminishing efficiency. This chapter explores the
potential of leveraging artificial intelligence (AI), particularly machine learning (ML)
and its subset, deep learning (DL), to bring about a transformative impact on the drug
development process. ML, characterized by its capacity to learn from data with or
without explicit programming, holds promise for addressing the complexities inherent
in pharmaceutical research. DL, employing artificial neural networks (ANNs) as a
multi-objective simultaneous optimization technique, has demonstrated efficacy in
optimizing drug delivery systems. AI has the potential to transform drug discovery,
clinical trials, drug delivery, and medical devices, emphasizing alignment with
regulatory guidelines. However, challenges such as data quality and model complexity
limit its transformative impact on medicine delivery and device development.This chapter is structured into three parts, each addressing a distinct aspect of AI in the
pharmaceutical landscape. The first part provides a foundational introduction to AI in
the pharmaceutical industry, elucidating its role in overcoming inherent challenges.
The second part delves into the diverse applications of AI-based tools and systems,
encompassing drug discovery, various drug delivery systems, and the development of
medical devices. Finally, the third part of the chapter sheds light on the regulatory
challenges associated with AI-based drug delivery and medical device development,
offering insights into the evolving regulatory landscape.
Brain Health in Metabolic Disease and Exercise
Authors: Tomiga Yuki
Published: November 2024

Modern lifestyles, such as a Western diet, excessive food consumption, and
physical inactivity, are closely associated with brain health and noncommunicable
diseases, including type 2 diabetes. Epidemiological evidence suggests that an
unhealthy lifestyle leads to impaired brain health, manifesting in conditions such as
depression and anxiety. Conversely, mental illness can contribute to the development
of type 2 diabetes. Thus, it has been suggested that there is a bidirectional relationship
between brain health and metabolic diseases, but the detailed mechanisms remain
unclear.Exercise is considered the primary choice for the treatment of obesity or type 2
diabetes. This is attributed to the fact that increased physical activity contributes to a
reduction in body weight and the accumulation of excess adipose tissue. Furthermore,
it has long been recognized that exercise enhances brain health. Recent studies have
revealed that, in addition to these indirect effects, exercise exerts its beneficial effects
by releasing bioactive substances. This chapter presents how metabolic diseases affect
brain health and how exercise mitigates these detrimental effects, focusing particularly
on the molecular mechanisms in the brain.
Interpretação de normas constitucionais na interface entre semântica e pragmática: Estudo de caso de uma decisão do Supremo Tribunal Federal
Authors: Pádua João Pedro
Published: November 2024

The interpretation of normative texts is the basic, and perhaps the most im-portant, activity of the jurist. Therefore, doctrinal works on the so-called the-ory of interpretation are abundant in the legal literature, especially a subfieldthereof, which studies the particularities attributed to constitutional inter-pretation. In search of analytically more powerful concepts, legal doctrinesoften resort to language studies, in the fields of linguistics and philosophy oflanguage. However, the uses that are made of these concepts are problematicon two levels: (i) they turn such concepts, originally descriptive, that is, abouthow the language user really makes sense of discourses, into normative con-cepts, that is, how these meanings should be produced in the interpretationof legal norms. Furthermore, (ii) uses of concepts from language studies aredone carelessly, with little connection to how they are understood and usedin their fields of origin. In this article, I try to present a literature review ofhow semantics and pragmatics can be used coherently and descriptively toempirically analyze the real processes of sense making in the interpretationof legal (especially constitutional) rules. After creating a model based on thisreview, I test this model in a case study on Direct Constitutional Complaint4,277, a case judged in 2011 by the Brazillian Federal Supreme Court, whichrecognized the constitutionality of the same-sex civil union. Discussion andconclusion sections, with proposals on the relevance of this study for the the-ory of legal interpretation, for the separation of powers, and for the study ofthe language of legal rules construction close the article.
Effectiveness of Composite Ayurveda Regimen in a Black Box Design for the Management of Rheumatoid Arthritis: Protocol of a Single Arm, Community-Based Study
Authors: Makhija Deepa , Mata Sunita , Sharma Abha , Kachare Kalpana , Manathottathil Aparna , Jain Seema , Jameela Sophia , Rao Bhogavalli Chandrasekhara , Rana Rakesh , Tripathi Arunabh , Rana Kiran , Joshi Vandana , Singh Anukampa , Srikanth Narayanam , Acharya Rabinarayan
Published: November 2024

Background

Rheumatoid arthritis (RA) is an autoimmune disease that affects joints and can have extra-articular manifestations. RA usually tends to be progressive and leads to substantial health care burdens, both in terms of disability and economic costs. Despite the various treatment modalities available, there is still an urgent need for safe and effective medicine based on the pattern of disease presentation. The increasing interest in complementary and alternative medicine has created a demand for extensive research in this area.

Objective

This clinical study is designed to evaluate the effectiveness and tolerability of a composite Ayurveda regimen in RA.

Methods

The study is a single-arm (pre-post design), community-based interventional study with a black box design being conducted at 6 study centers. A total of 240 participants aged between 18 and 65 years, diagnosed with RA as per the 2010 American College of Rheumatology and the European League Against Rheumatism criteria are recruited as per the selection criteria. All the participants received Ayush-SG and Rasnasaptak Kashaya for 84 days along with customized treatment as per the disease presentation and associated complaints. The outcome measures include the change in disease activity score (DAS)-28 with erythrocyte sedimentation rate, disease-specific biochemical and inflammatory markers, Disability Index score, change in the participant’s assessment of pain and frequency of use of conventional analgesics or nonsteroidal anti-inflammatory drugs from baseline. The tolerability of interventions is assessed through the occurrence of adverse events. Categorical variables will be analyzed with McNemar chi-square test, and continuous variables will be assessed using the paired t test or Wilcoxon test for pre-post assessment. The level of significance will be 5%.

Results

The recruitment of participants was initiated in December 2023. The participant recruitment was completed in March 2024 and out of 240 participants enrolled, 222 (92.5%) completed the study up to the last follow-up. Data verification, compilation, and analysis are under process. After data analysis, the study’s findings will be published in a peer-reviewed journal.

Conclusions

This interventional study that incorporates the black box approach may provide a strong framework for managing RA. This design is a more reliable method for evaluating the effectiveness and tolerability of the composite Ayurveda regimen in RA.

Trial Registration

Clinical Trial Registry-India CTRI/2023/06/054203; https://tinyurl.com/4prvwr6z

International Registered Report Identifier (IRRID)

DERR1-10.2196/57918
Training and Assessing Teamwork in Interprofessional Virtual Reality-based Simulation using the TeamSTEPPS framework – Protocol for a Randomized Pre-post Intervention Study (Preprint)
Authors: Lehmann Marie , Mikulasch Jan , Poimann Horst , Backhaus Joy , König Sarah , Mühling Tobias
Published: November 2024

BACKGROUND

Interprofessional teamwork is essential for patient outcomes in emergency medicine, yet effective training in this area is scarce. Virtual reality (VR) offers a promising, resource-efficient solution for simulating emergency scenarios, but tools for assessing teamwork in VR environments are lacking.

OBJECTIVE

This study aims to adapt and validate the TeamSTEPPS framework to assess teamwork in VR-based training, with the goal of improving both team collaboration and medical performance.

METHODS

This prospective pre-post study involves nursing and medical students working in randomized interprofessional teams. On three time points (day 1, day 8, day 15), participants engage in a VR scenario simulating one out of three different emergency medical conditions. As intervention, a training video on successful teamwork is shown on day 8 immediately before the second VR-scenario. Teamwork is assessed objectively with the Team Performance Observation Tool (TPOT) which will be adapted and validated for application in VR settings and subjectively with the Teamwork Perceptions Questionnaire (T-TPQ). Medical performance will be recorded automatically by the VR software based on the medical measures conducted by the team.

RESULTS

As of May 2024, 15 interprofessional teams have been enrolled. Data analysis will begin in late 2025.

CONCLUSIONS

This study addresses the challenge of adapting teamwork assessment tools to VR environments and may provide insights into the potential of VR-based training for improving interprofessional collaboration in medical education. Future research could include a control group to measure the effects of team training more rigorously or use more enhanced technologies (e.g. natural language processing) to capture a broader range of teamwork behavior.