Medical, pharmaceutical, and nutritional applications of 3D-printing technology in diabetes

AIMS

Despite numerous studies covering the various features of three-dimensional printing (3D printing) technology, and its applications in food science and disease treatment, no study has yet been conducted to investigate applying 3D printing in diabetes. Therefore, the present study centers on the utilization and impact of 3D printing technology in relation to the nutritional, pharmaceutical, and medicinal facets of diabetes management. It highlights the latest advancements, and challenges in this field.

METHODS

In this review, the articles focusing on the application and effect of 3D printing technology on medical, pharmaceutical, and nutritional aspects of diabetes management were collected from different databases.

RESULT

High precision of 3D printing in the placement of cells led to accurate anatomic control, and the possibility of bio-printing pancreas and β-cells. Transdermal drug delivery via 3D-printed microneedle (MN) patches was beneficial for the management of diabetes disease. 3D printing supported personalized medicine for Diabetes Mellitus (DM). For instance, it made it possible for pharmaceutical companies to manufacture unique doses of medications for every diabetic patient. Moreover, 3D printing allowed the food industry to produce high-fiber and sugar-free products for the individuals with DM.

CONCLUSIONS

In summary, applying 3D printing technology for diabetes management is in its early stages, and needs to be matured and developed to be safely used for humans. However, its rapid progress in recent years showed a bright future for the treatment of diabetes.

Psychometric validation of the nursing care behavior questionnaire during emerging disease epidemics: A theory of planned behavior approach

Background and objective

The Covid-19 pandemic could compromise the quality of care by impacting nurses' intention to provide care. Hence, investigating nurses' behavioral intentions when caring for patients during epidemics is essential. This research aims to assess the psychometrics of the "Nursing Care Behavior in Epidemics of Emerging Diseases" questionnaire, based on the constructs of the Theory of Planned Behavior.

Methods

This cross-sectional study involved 311 nurses working in Covid-19 wards of selected hospitals in Ilam City, all of whom were enrolled through a census in 2021. The questionnaire underwent initial translation from English to Persian, followed by evaluations of its face, content, and construct validities. The nursing caring behavior questionnaire, comprising 46 items, was designed to assess behavioral beliefs, normative beliefs, control beliefs, behavioral attitudes, subjective norms, perceived behavioral control, and nurses' intentions to care for Covid-19 patients. Data were analyzed for face, content, and construct validity using the Theory of Planned Behavior and Pearson correlation. Reliability was determined by calculating the Cronbach's alpha coefficient.

Results

The intention to care dimension demonstrated an inverse correlation with the behavioral attitude dimension (p < 0.001). The most robust correlations were observed between the following paired dimensions: behavioral attitude and perceived power (p < 0.001), subjective norms and intention to care (p < 0.001), perceived behavioral control and subjective norms (p < 0.001), care intention and behavioral beliefs (p < 0.001), behavioral beliefs and behavioral outcome evaluation (p < 0.001), and normative beliefs with motivation to comply (p = 0.001). The Cronbach's alpha coefficient of the instrument exceeded 0.75.

Conclusion

According to the Theory of Planned Behavior, the nursing care behavior questionnaire proved to be a valid and reliable tool for evaluating nurses' care behaviors amidst emerging disease epidemics.

In vitro study of the binding between chlorpyrfos and sex hormones using headspace solid-phase microextraction combined with high-performance liquid chromatography: A new aspect of pesticides and breast cancer risk

Endocrine-disrupting chemicals are compounds that alter the normal functioning of the endocrine system. Organophosphorus insecticides, as chlorpyrifos (CPS), receive an increasing consideration as potential endocrine disrupters. Physiological estrogens, including estrone (E1), 17β-estradiol (E2), and diethylstilbestrol (DES) fluctuate with life stage, suggesting specific roles for them in biological and disease processes. There has been great interest in whether certain organophosphorus pesticides can affect the risk of breast cancer. An understanding of the interaction processes is the key to describe the fate of CPS in biological media. The objectives of this study were to evaluate total, bound, and freely dissolved amount of CPS in the presence of three estrogenic sex hormones (ESHs). In vitro experiments were conducted utilizing a headspace solid phase microextraction (HS-SPME) combined with high-performance liquid chromatography (HPLC) method. The obtained Scatchard plot based on the proposed SPME-HPLC method was employed to determine CPS-ESHs binding constant and the number of binding sites as well as binding percentage of each hormone to CPS. The number of binding sites per studied hormone molecule was 1.10, 1, and 0.81 for E1, E2, and DES, respectively. The obtained results confirmed that CPS bound to one class of binding sites on sex hormones.

Measurement of depth-dose of linear accelerator and simulation by use of Geant4 computer code

Radiation therapy is an established method of cancer treatment. New technologies in cancer radiotherapy need a more accurate computation of the dose delivered in the radiotherapy treatment plan. This study presents some results of a Geant4-based application for simulation of the absorbed dose distribution given by a medical linear accelerator (LINAC). The LINAC geometry is accurately described in the Monte Carlo code with use of the accelerator manufacturer's specifications. The capability of the software for evaluating the dose distribution has been verified by comparisons with measurements in a water phantom; the comparisons were performed for percentage depth dose (PDD) and profiles for various field sizes and depths, for a 6-MV electron beam. Experimental and calculated dose values were in good agreement both in PDD and in transverse sections of the water phantom.

PVC membrane sensor for diclofenac: applications in pharmaceutical analysis and drug binding studies

A PVC membrane sensor for diclofenac based on its ion pair complex with silver is prepared. The influences of membrane composition (PVC, plasticizer, and ion pair complex), pH of test solution and presence of other anions on the performance of the electrode were investigated. The optimized membrane demonstrates Nernstian response (-58.9 +/- 0.2 mV/decade) for diclofenac anions over a wide linear range from 5.2 x 10(-5) to 1.1 x 10(-2) M at 25 +/- 1 degree C. The potentiometric response is independent from pH at the range of 6.0-9.5. The advantages of the proposed sensor are: easy preparation, good selectivity and fast response time. It was successfully used for determination of diclofenac in pharmaceuticals and also in potentiometric study of interaction of diclofenac with bovine serum albumin. The results of diclofenac assay with the proposed sensor were in good agreement with the official HPLC method.