SIYUAN LIU, YUAN ZHAO, YU YU, DOU YE, QIAN WANG, ZHAOYAN WANG, ZUO LUAN^*

BIOCELL, Vol.48, No.7, pp. 1115-1126, 2024, DOI:10.32604/biocell.2024.050493 - 03 July 2024

Abstract Introduction: Transplantation of mesenchymal stromal cells (MSCs) is a promising therapy for type 1 diabetes (T1D). However, whether the infused MSCs affect the endoplasmic reticulum stress or subsequent unfolded protein response in β cells remains unclear. Methods: To investigate this, we induced early-onset T1D in non-obese diabetic mice using streptozotocin. Subsequently, T1D mice were randomly assigned to receive either MSCs or phosphate-buffered saline. We observed the in vivo homing of MSCs and assessed their effectiveness by analyzing blood glucose levels, body weight, histopathology, pancreatic protein expression, and serum levels of cytokines, proinsulin, and C-peptide. Results: Infused MSCs… More > Graphic Abstract

Xiaolu Qin^1,3, Xinyu Li^1,3, Yi Yang², Mei Huang², Shengli Wu¹, Pianchou Gongpan¹, Lianzhang Wu², Juncai He², Changan Geng^1,3,*

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 875-883, 2024, DOI:10.32604/phyton.2024.048192 - 28 May 2024

Abstract The fruits of Amomum tsao-ko (Cao-Guo) were documented in Chinese Pharmacopoeia for the treatment of abdominal pain, vomiting, and plague. In our previous study, a series of diarylheptanes and flavonoids with α-glucosidase and protein tyrosine phosphatase 1B (PTP1B) inhibitory activity have been reported from the middle-polarity part of A. tsao-ko, whereas the antidiabetic potency of the low-polarity constituents is still unclear. In this study, three new hydroxytetradecenals, (2E, 4E, 8Z, 11Z)-6R-hydroxytetradeca-2,4,8,11-tetraenal (1), (2E, 4E, 8Z)-6R-hydroxytetradeca-2,4,8-trienal (2) and (2E, 4E)-6R-hydroxytetradeca-2,4-dienal (3) were obtained from the volatile oils of A. tsao-ko. The structures of compounds 1–3 were determined using spectroscopic data involving 1D and 2D nuclear magnetic More >

Fatma Nese Efil¹, Sania Qureshi^1,2,3, Nezihal Gokbulut^1,4, Kamyar Hosseini^1,3, Evren Hincal^1,4,*, Amanullah Soomro²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 485-512, 2024, DOI:10.32604/cmes.2024.047907 - 16 April 2024

Abstract The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in… More >

Yamixa Delgado^1,*, Caliani Gaytan¹, Naydi Perez², Eric Miranda³, Bryan Colón Morales¹, Mónica Santos¹

Congenital Heart Disease, Vol.19, No.1, pp. 19-31, 2024, DOI:10.32604/chd.2024.046339 - 20 March 2024

Abstract Background: Given the pervasive issues of obesity and diabetes both in Puerto Rico and the broader United States, there is a compelling need to investigate the intricate interplay among body mass index (BMI), pregestational, and gestational maternal diabetes, and their potential impact on the occurrence of congenital heart defects (CHD) during neonatal development. Methods: Using the comprehensive System of Vigilance and Surveillance of Congenital Defects in Puerto Rico, we conducted a focused analysis on neonates diagnosed with CHD between 2016 and 2020. Our assessment encompassed a range of variables, including maternal age, gestational age, BMI,… More >

HANY M. ABD EL-LATEEF^1,2,*, SAFA H. QAHL³, EMAN FAYAD⁴, SARAH A. ALTALHI⁴, IBRAHIM JAFRI⁴, EL SHAIMAA SHABANA⁵, MARWA K. DARWISH^6,7, REHAB MAHER⁸, SAAD SHAABAN^1,9, SHADY G. EL-SAWAH^10,*

BIOCELL, Vol.47, No.8, pp. 1885-1895, 2023, DOI:10.32604/biocell.2023.030680 - 28 August 2023

Abstract Background: The increasing occurrence of diabetes mellitus (DM) noted worldwide has considerably elicited concern in the recent past. DM is associated with elevated vascular complications, morbidity, mortality, and poor quality of life. In this context, mesenchymal stem cells (MSCs) have shown significant therapeutic potentialities in managing and curing type 1 DM owing to their self-renewable, immunosuppressive, and differentiation capacities. We investigated the potential action of N, N′-diphenyl-1,4-phenylenediamine (DPPD), a well-known synthetic antioxidant to enhance the therapeutic ability of the adipose-derived stem cells (AD-MSCs) in alleviating kidney and liver complications in diabetic rats. Methods: Over the… More > Graphic Abstract

B. Ramesh, Kuruva Lakshmanna^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2513-2528, 2023, DOI:10.32604/cmes.2023.028944 - 03 August 2023

Abstract Major chronic diseases such as Cardiovascular Disease (CVD), diabetes, and cancer impose a significant burden on people and healthcare systems around the globe. Recently, Deep Learning (DL) has shown great potential for the development of intelligent mobile Health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere. The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this… More > Graphic Abstract

JING JIN^1,2,#, XIE LI^1,#, TING QIU^1,#, LEI SONG¹, YUANYUE CUI¹, GUANGYA ZHANG^3,4, SHU LI², WENCHENG ZHAO^5,*

BIOCELL, Vol.47, No.7, pp. 1645-1650, 2023, DOI:10.32604/biocell.2023.029493 - 21 June 2023

Abstract Background: This work aimed to reveal the expression profiles of tRNA-derived small RNAs (tsRNAs) in diabetes. Methods: Thirty-five diabetes patients and thirty-three controls were enrolled. The serum samples of 4 diabetes patients and 4 controls were subjected to tRF and tiRNA polymerase chain reaction (PCR) Array analysis. Then quantitative PCR (qPCR) validation was performed on all the samples. Bioinformatics analyses were conducted to explore their functions. Results: We found 115 tsRNAs that significantly differed between the two groups. 3′tiR-080-ProTGG(mt) was selected for further qPCR validation in all participants, and it was significantly decreased in diabetes patients More >

JAMES L. ROSENBERG¹, WILLIAM WOOLLEY¹, IHSAN ELNUNU¹, JULIA KAMML², DAVID S. KAMMER², CLAIRE ACEVEDO^1,3,*

BIOCELL, Vol.47, No.7, pp. 1651-1659, 2023, DOI:10.32604/biocell.2023.028014 - 21 June 2023

Abstract Age and diabetes have long been known to induce an oxidative reaction between glucose and collagen, leading to the accumulation of advanced glycation end-products (AGEs) cross-links in collagenous tissues. More recently, AGEs content has been related to loss of bone quality, independent of bone mass, and increased fracture risk with aging and diabetes. Loss of bone quality is mostly attributed to changes in material properties, structural organization, or cellular remodeling. Though all these factors play a role in bone fragility disease, some common recurring patterns can be found between diabetic and age-related bone fragility. The More >

Niharika Gupta¹, Baijnath Kaushik¹, Mohammad Khalid Imam Rahmani^2,*, Saima Anwar Lashari^2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 347-366, 2023, DOI:10.32604/cmc.2023.038864 - 08 June 2023

Abstract Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision… More >

Alawi Alqushaibi^1,2,*, Mohd Hilmi Hasan^1,2, Said Jadid Abdulkadir^1,2, Amgad Muneer^1,2, Mohammed Gamal^1,2, Qasem Al-Tashi³, Shakirah Mohd Taib^1,2, Hitham Alhussian^1,2

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3223-3238, 2023, DOI:10.32604/cmc.2023.035655 - 31 March 2023

Abstract Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction… More >