Biomedical microelectromechanical systems (BioMEMS): Revolution in drug delivery and analytical techniques

Advancement in microelectromechanical system has facilitated the microfabrication of polymeric substrates and the development of the novel class of controlled drug delivery devices. These vehicles have specifically tailored three dimensional physical and chemical features which together, provide the capacity to target cell, stimulate unidirectional controlled release of therapeutics and augment permeation across the barriers. Apart from drug delivery devices microfabrication technology’s offer exciting prospects to generate biomimetic gastrointestinal tract models. BioMEMS are capable of analysing biochemical liquid sample like solution of metabolites, macromolecules, proteins, nucleic acid, cells and viruses. This review summarized multidisciplinary application of biomedical microelectromechanical systems in drug delivery and its potential in analytical procedures.     

Uterine stromal sarcoma cell line. A cytogenetic and electron microscopic study.

Uterine sarcomas constitute approximately 3% of all malignant uterine corpus tumors. Of these, the tumors that originate solely in the stromal elements of the uterine wall are relatively infrequent and have not been well characterized cytogenetically. We report data from a low-grade endometrial stromal sarcoma both at the time of resection and after months in long-term tissue culture. Cytogenetic analysis showed a clonal population of cells with an abnormal karyotype of 46,XX,del(5)(q31.1),der(7)t(6;7)(p21;p22) which remained unchanged in long-term culture. Electron microscopy suggests that these cells are similar to other neoplastic cells in having immature-appearing nuclei surrounded by a relatively mature cytoplasm (with well-developed organelles). Determination of the specificity of these observations must await study of additional stromal sarcomas.     

Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0–27 days), infants (0–11 months), and children age 12–59 months. We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known. We estimate U5ACSM within 0.1–0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios. The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.     

Effects of Simvastatin on NF-kB-DNA Binding Activity and Monocyte Chemoattractant Protein-1 Expression in a Rabbit Model of Atherosclerosis

To observe the effects of simvastatin on nuclear factor kappaB （NF-kB）-DNA binding activity and on the expression of monocyte chemoattractant protein-1 （MCP-1） in atherosclerotic plaque in rabbits and to explore the anti-atherosclerotic properties beyond its lipid-lowering effects. Thirty-six New Zealand male rabbits were randomly divided into low-cholesterol group （LC）, high- cholesterol group （HC）, high-cholesterol＋ simvastatin group （HC＋S） and then were fed for 12 weeks. At the end of the experiment, standard enzymatic assays, electrophoretic mobility shift as- say （EMSA）, immunohistochemical staining, and morphometry were performed to observe serum lipids, NF-kB-DNA binding activity, MCP-1 protein expression, intirna thickness and plaque area of aorta respectively in all three groups. Our results showed that the serum lipids, NF-kB-DNA binding activity, expression of MCP-1 protein, intima thickness, and plaque area of aorta in the LC and HC＋S groups were significantly lower than those in the HC group （P〈0.05）. There was no significant difference in the serum lipids between the LC and HC＋S groups （P〉0.05）, but the NF-kB-DNA binding activity, the expression of MCP-1 protein and the intirna thickness and plaque area of aorta in the HC＋S group were significantly decreased as compared to the LC group （P〈0. 05）. This study demonstrated that simvastatin could decrease atherosclerosis by inhibiting the NF-kB-DNA binding activity and by reducing the expression of MCP-1 protein.     

How to Optimally Apply Impedance in the Evaluation of Esophageal Dysmotility

The utilization of impedance technology has enhanced our understanding and assessment of esophageal dysmotility. Esophageal high-resolution manometry (HRM) catheters incorporated with multiple impedance electrodes help assess esophageal bolus transit, and the combination is termed high-resolution impedance manometry (HRIM). Novel metrics have been developed with HRIM—including esophageal impedance integral ratio, bolus flow time, nadir impedance pressure, and impedance bolus height—that augments the assessment of esophageal bolus transit. Automated impedance-manometry (AIM) analysis has enhanced understanding of the relationship between bolus transit and pressure phenomena. Impedance-based metrics have improved understanding of the dynamics of esophageal bolus transit into four distinct phases, may correlate with symptomatic burden, and can assess the adequacy of therapy for achalasia. An extension of the use of impedance involves impedance planimetry and the functional lumen imaging probe (FLIP), which assesses esophageal biophysical properties and distensibility, and could detect patterns of esophageal contractility not seen on HRM. Impedance technology, therefore, has a significant impact on esophageal function testing in the present day.     

Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease

Background

Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort study, we determined feasibility of automated AI extraction of baseline impedance (AIBI) and evaluated clinical value of novel AI metrics.

Methods

pH-impedance data from a convenience sample of symptomatic patients studied off (n = 117, 53.1 ± 1.2 years, 66% F) and on (n = 93, 53.8 ± 1.3 years, 74% F) anti-secretory therapy and from asymptomatic volunteers (n = 115, 29.3 ± 0.8 years, 47% F) were uploaded into dedicated prototypical AI software designed to automatically extract AIBI. Acid exposure time (AET) and manually extracted mean nocturnal baseline impedance (MNBI) were compared to corresponding total, upright, and recumbent AIBI and upright:recumbent AIBI ratio. AI metrics were compared to AET and MNBI in predicting  ≥ 50% symptom improvement in GERD patients.

Results

Recumbent, but not upright AIBI, correlated with MNBI. Upright:recumbent AIBI ratio was higher when AET  > 6% (median 1.18, IQR 1.0–1.5), compared to  < 4% (0.95, IQR 0.84–1.1), 4–6% (0.89, IQR 0.72–0.98), and controls (0.93, IQR 0.80–1.09, p ≤ 0.04). While MNBI, total AIBI, and the AIBI ratio off PPI were significantly different between those with and without symptom improvement (p < 0.05 for each comparison), only AIBI ratio segregated management responders from other cohorts. On ROC analysis, off therapy AIBI ratio outperformed AET in predicting GERD symptom improvement when AET was  > 6% (AUC 0.766 vs. 0.606) and 4–6% (AUC 0.563 vs. 0.516) and outperformed MNBI overall (AUC 0.661 vs. 0.313).

Conclusions

BI calculation can be automated using AI. Novel AI metrics show potential in predicting GERD treatment outcome.