Jorjani Biomedicine Journal

Rethinking technology for an aging population: From active aging to digital aging

Maryam Chehrehgosha

Given the rapidly growing older adult population, it is necessary to provide appropriate care and ensure an adequate healthcare workforce. During the COVID-19 pandemic, older adults experienced deficiencies in care and were deprived of face-to-face services. In addition, the shortage of healthcare providers was particularly evident during this period. Conversely, the COVID-19 pandemic accelerated the use of smart technologies, AI, robotics, and wearable technologies, which help reduce the care burden on healthcare providers. However, the adoption of these technologies faces several limitations. These include the top-down approach to technology development, which disregards older adults’ priorities and preferences, as well as concerns about cybersecurity, privacy, trust, and costs. Although the use of these technologies offers many advantages for the older adult population, further research is needed to determine their actual effectiveness in accordance with older adults’ willingness to use them. More importantly, technology must complement human interaction rather than replace it.

Molecular docking reveals curcumin and catechin as potent inhibitors of histamine N-Methyltransferase (HNMT) and its T105I and L208P variants

Mehdi Sadeghi

Background: Histamine plays a crucial role in regulating diverse physiological and pathophysiological functions, including gastric acid secretion, vasodilation, and bronchoconstriction. As a neurotransmitter, it is also implicated in allergic reactions, contributing to symptoms such as itching, sneezing, and inflammation. Given the potential adverse effects of histamine activity, antihistamines are frequently prescribed to mitigate its effects. However, the associated side effects of these drugs have prompted researchers to investigate natural alternatives, such as curcumin from turmeric and catechins from green tea. This study investigates the potential effect of curcumin and catechin on the histamine N-methyltransferase (HNMT) receptor and its T105I and L208P mutant variants.
Methods: Molecular docking was employed to analyze ligand-receptor interactions. The protein structure was obtained from the Protein Data Bank (PDB), and ligands were retrieved from PubChem. Ligand structures were optimized using Avogadro software, and docking studies were subsequently performed using AutoDock Tools and the Vina algorithm.
Results: Molecular docking studies have demonstrated strong binding affinities of catechin and curcumin to the target protein, with binding energies of -8.5 and -8.4 kcal/mol, respectively, which is more than twice the binding affinity of histamine (-4.0 kcal/mol). Analysis of docking results with variant proteins revealed a slight reduction in ligand binding energies compared to the normal protein. These findings suggest that both catechin and curcumin hold promise as potential therapeutic agents for patients with the studied variants of the target protein. Furthermore, docking analysis revealed key stabilizing interactions, including π-π stacking and hydrogen bonding.
Conclusion: Phe243 is a key binding site residue in HNMT, showing consistent strong interactions with all tested ligands. Its structural flexibility enables effective binding to compounds like catechin and curcumin, making it a prime target for designing new HNMT inhibitors.

Attitudes toward fertility and childbearing among childless female teachers working in the Gorgan education system in 2023

Elham Adib Moghaddam

Background: Fertility is an important determinant of population dynamics and a key topic in demographic and public health research. This study aimed to assess attitudes toward fertility and childbearing among childless female teachers working in the education system of Gorgan, Iran, in 2023.
Methods: This was a cross-sectional study. A total of 465 eligible female teachers were recruited using systematic sampling. Data were collected using a demographic information form and the validated Persian version of Söderberg et al.'s Attitudes to Fertility and Childbearing Scale (AFCS). The data were analyzed in SPSS software version 19, using analysis of variance, independent t-tests, and Pearson’s correlation. The level of statistical significance was set at 0.05.
Results: The mean age of the participants was 36.42 ± 6.95 years, and the mean fertility attitude score was 55.65 ± 11.01. No significant association was found between the fertility attitude score and teachers’ education level, spouse’s occupation, employment status, homeownership status, or type of contraceptive method (P-value range: 0.31 to 0.92; all P-Value > 0.05). However, Pearson’s correlation analysis showed positive correlations between the fertility attitude score and both age (r = 0.10, P-Value = 0.03) and their work experience (r = 0.11, P-Value = 0.02). Additionally, the relationship between the fertility attitude score and both household income level and spouse’s education level was borderline significant (P-Value = 0.05).
Conclusion: The results of this study suggest a significant relationship between age and work experience and attitudes towards fertility among female teachers in Gorgan. A positive correlation between older age/more work experience and a more favorable attitude toward fertility may be attributed to factors such as personal maturity, job stability, and psychological economic security. Therefore, cultural policies and programs related to fertility for this group could focus on creating supportive conditions for job stabilization and reducing stressors during the early years of service, aiming to foster a more positive experience of combining employment and childbearing.

Investigation of MuRF1 and Atrogin-1 gene expression changes in the soleus muscle of obese diabetic rats following 8 weeks of high-intensity interval training combined with quercetin supplementation

Ali Rajabi

Background: MuRF1 and Atrogin-1 are two key genes involved in the muscle atrophy pathway and are upregulated in diabetes, particularly under conditions of insulin resistance and inflammation, leading to increased degradation of muscle proteins and reduced muscle mass. Therefore, this study aimed to investigate changes in MuRF1 and Atrogin-1 gene expression in the soleus muscle of obese diabetic rats following 8 weeks of high-intensity interval training (HIIT) combined with quercetin supplementation.
Methods: In this experimental study, 25 adult male rats (Age= 12 weeks old and weight= 180-200 gr) were purchased and randomly assigned to five groups: healthy control (HC, n= 5), diabetes control (DC, n= 5), quercetin control (QC, n= 5), HIIT (HIIT, n= 5), and HIIT with quercetin (QHIIT, n= 5). Eight weeks of HIIT training was performed. Type 2 diabetes (T2DM) was induced in the rats using STZ and 8 weeks of a high-fat diet. Quercetin was injected for 8 weeks in the supplementation groups. One-way analysis of variance with Tukey's post-hoc test was used to analyze the data. Significance was set at P-Value < 0.05.
Results: The results showed that after T2DM induction, blood glucose and MuRF1 and Atrogin-1 gene expression levels in the soleus muscle of rats significantly increased (P-Value<0.001). After eight weeks of training and supplementation interventions, blood glucose significantly decreased in all intervention groups (P-Value =0.001), and only in the HIIT with quercetin supplementation group was there a significant decrease in both MuRF1 and Atrogin-1 gene expression (P-Value =0.001).
Conclusion: HIIT and quercetin supplementation alone reduced blood glucose levels in diabetic rats. Although HIIT and quercetin supplementation alone did not affect MuRF1 and Atrogin-1 gene expression, the combination of both interventions resulted in significant changes. This suggests that the combined use of HIIT exercise and quercetin supplementation has a notable effect on selected factors related to atrophy in diabetic rats.

Hybrid machine-learning algorithms for predicting the number of road accident patients in Golestan Province using time-series data

Manoochehr Babanezhad

Background: This study employs hybrid machine learning algorithms to analyze the number of patients resulting from road accidents in hospitals in Golestan Province over a five-year period from March 2020 to March 2025. It also aims to predict the number of traffic accident patients from March 2025 to March 2027.
Methods: In this retrospective study, a five-year dataset covering March 2020 to March 2025 was used. Hybrid machine-learning algorithms, including SARIMA-LSTM and CNN-LSTM, were applied for analysis and prediction in comparison with the traditional Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The performance of these algorithms was evaluated using root mean square error (RMSE), mean absolute error (MAE), and root mean square logarithmic error (RMSLE).
Results: The observed number of patients referred following road accidents in Golestan Province increased from 13,679 in 2020 to 20,323 in 2025. A statistically significant difference was observed in patient numbers between men and women (P-Value < 0.001), with five-year increases of 45% for men and 60% for women. For predictions covering March 2025-March 2027, the CNN-LSTM model achieved the lowest error metrics (MAE (%) = 4.5, RMSE = 6.50, RMSLE = 0.21), followed by SARIMA-LSTM (MAE (%) = 8.60, RMSE = 12.45, RMSLE 0.65= 0.15), whereas the conventional SARIMA model exhibited the highest errors (MAE (%) = 12.69, RMSE = 15.37, RMSLE = 0.78).
Conclusion: These findings may assist policymakers and health managers in improving health services through optimal resource allocation and enhanced planning. Furthermore, the use of machine-learning models in hospitals is recommended to support the management and prediction of traffic-accident-related patient volumes.

Effects of intraperitoneal tramadol and flunixin on pain and stress indices following ovariohysterectomy in rabbits

Seyedeh Ommolbanin Ghasemian

Background: Effective postoperative pain management is essential for improving recovery and promoting animal welfare in veterinary surgery. Rabbits are highly sensitive to surgical stress, and limited information is available regarding the comparative efficacy of intraperitoneally administered analgesics following ovariohysterectomy.
Methods: Fifteen healthy adult female New Zealand White rabbits weighing 1900-2500 g were randomly allocated into three groups (n = 5/group): control, tramadol (5 mg/kg, intraperitoneal), and flunixin meglumine (1 mg/kg, intraperitoneal). Animals were housed individually under controlled environmental conditions after a one-week acclimatization period. Following ovariohysterectomy, heart rate, respiratory rate, and rectal temperature were recorded at 0, 2, and 6 h postoperatively. Postoperative pain was assessed using the Rabbit Grimace Scale at 0, 1, 3, 6, 12, and 24 h. Serum cortisol and melatonin concentrations were measured using rabbit-specific ELISA kits, and serum glucose was analyzed using an automated biochemical analyzer. Data were analyzed using SPSS version 26. The level of statistical significance was set at 0.05.
Results: Postoperative stress was most pronounced during the second hour after surgery and was characterized by increased heart rate, respiratory rate, cortisol, and glucose concentrations, along with decreased melatonin levels. Both tramadol and flunixin significantly reduced physiological pain indices, such as heart and respiratory rates, compared with the control group (P-Value<0.001), while behavioral pain indices also decreased following treatment. Tramadol was more effective in attenuating early physiological stress responses, whereas flunixin provided more sustained control of behavioral pain during later postoperative time points. However, differences in some biochemical variables among treatment groups were not statistically significant.
Conclusion: Intraperitoneal administration of tramadol and flunixin reduced postoperative pain- and stress-related responses following ovariohysterectomy in rabbits. Tramadol showed greater efficacy during the early postoperative phase, whereas flunixin provided longer-lasting behavioral analgesia. These findings suggest that both agents may be useful for postoperative pain management in rabbits, although further studies with larger sample sizes are required.

Advanced technologies for herbal medicine development: Modern approaches to authentication, extraction, phytochemical analysis, and standardization

Sakshi Anil Avhad

Background: Herbal medicines have formed an integral component of healthcare systems since ancient times and continue to play an important role in contemporary therapeutics. Given the growing global demand for herbal products, assurance of their quality, safety, and efficacy has become increasingly important. Advanced technologies for herbal medicine provide scientific approaches to improving plant identification, extraction, standardization, and quality control.
Methods: Relevant literature on herbal medicine technology was reviewed, with emphasis on plant authentication methods, chromatographic techniques, and advanced extraction procedures used in the analysis and standardization of herbal medicines. Modern analytical methods, including thin-layer chromatography (TLC), high-performance thin-layer chromatography (HPTLC), high-performance liquid chromatography (HPLC), column chromatography, and paper chromatography, play important roles in the separation, identification, and quantification of phytoconstituents.
Results: Advanced extraction methods, including supercritical fluid extraction, pressurized liquid extraction, and ultrasound-assisted extraction, enhance extraction efficiency while preserving the potency and stability of bioactive compounds.
Conclusion: Advanced technologies have increased the reliability of herbal medicines by improving their identification, testing, and preparation. Integrating traditional knowledge with scientific standards and rigorous regulation can support the safer and more reliable use of herbal remedies in contemporary healthcare.

A protocol study of serotonin determination using a validated electrochemical sensing method in human blood serum

Kamyar Khoshnevisan

Serotonin (5-hydroxytryptamine, 5-HT) is a pivotal neurotransmitter involved in a myriad of physiological processes, including the regulation of mood, appetite, and sleep cycles. Accurate quantification of 5-HT levels in human serum is fundamental to elucidating its pathophysiology in various clinical conditions and disorders. Over the recent years, electrochemical sensing techniques have emerged as highly reliable and sensitive modalities for 5-HT detection. This article details a protocol study designed to determine 5-HT concentrations in human serum using a validated electrochemical sensing platform. The protocol encompasses a comprehensive overview of electrochemical sensing techniques, methodology validation, sample collection and processing, experimental procedures for 5-HT determination, and subsequent data analysis. The outcomes of this study hold significant potential for advancing the current understanding of 5-HT-associated disorders and may facilitate the development of novel, targeted therapeutic interventions.