Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.     

Reciprocal Peer Support for Post-partum Patients with Diabetes: A Needs Assessment for the Diabetes Buddy Program

While peer support has been investigated in multiple clinical contexts, its application to the postpartum setting is unknown. The aim was to assess acceptability of a postpartum peer support program for women with diabetes. Observational survey-based needs assessment of forty low-income women with diabetes, receiving care at a major medical institution. Mean age and gravidity were 30.7 years and 3.15 ± 1.67 respectively. 45 % expressed interest in a “buddy.” There was no significant difference between groups desiring and not desiring this program. A majority of respondents desired telephone, text messaging, and in-person contacts (79.2, 72.1, 83.8 %), with 72.5 % of patients desiring diabetes-related activities during clinic waiting time. Many women desire a postpartum diabetes reciprocal peer program for support outside of clinician visits. Patients are receptive to educational services during their wait and outside of clinic time, a potentially valuable opportunity to share important health information.     

Three-dimensional measurement of radiographic bone–implant contact lengths of zygomatic implants in zygomatic bone: a retrospective study of 66 implants in 28 patients

Zygomatic implant treatment is widely applied for severe maxillary atrophy to help rehabilitate the maxillary dentition. This retrospective study was performed to evaluate the actual radiographic bone–implant contact (rBIC) lengths of zygomatic implants. The records of 28 patients who underwent zygomatic implant surgery and subsequent follow-up examinations between August 2013 and September 2018 in the Department of Oral and Maxillofacial Surgery, Taipei Tzu Chi Hospital were reviewed. The surgeries were performed by a single surgeon using the same treatment protocol. All patients had a computed tomography scan at 1 year after the surgery. Using three-dimensional imaging software, an investigator measured the rBIC lengths of 66 implants and documented their clinical status. The implant survival rate was 100%. The mean rBIC length was significantly longer in male patients than in female patients (20.80 ± 5.88 mm versus 17.79 ± 6.34 mm; P = 0.028). The mean rBIC length of double zygomatic implants was significantly longer when compared to that of single implants (21.11 ± 6.23 mm versus 17.75 ± 5.85 mm; P = 0.027). This article is novel in reporting the exact rBIC lengths of zygomatic implants in a clinical setting. The results showed that zygomatic implants are a viable treatment modality for full-mouth rehabilitation.     

Risk factors associated with postoperative prosthetic graft patency in Leriche syndrome

Background

In Leriche syndrome, postoperative graft thrombosis remains one of the most significant clinical challenges.

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.