Achieving High-Precision, Low-Cost Microfluidic Chip Fabrication with Flexible PCB Technology

Soft lithography has long remained the state of the art to generate the necessary micropatterning for molded microfluidic (MF) chips. Previous attempts to use printed circuit boards (PCBs) as a cheap and accessible alternative to expensive lithographed molds for the production of PDMS MF chip prototypes have shown their limitations. A more in-depth exploration of using PCBs as a mold substrate and a novel methodology of using flexible PCBs to produce highly accurate MF chips is reported here for the first time. Cross sections highlight the improved accuracy of this method, and peel testing is performed to demonstrate suitable adhesion between the glass substrate and PDMS cast. Positive cell growth viability showcases this novel method as a high-accuracy, high-accessibility, low-cost prototyping method for microfluidic chips while still maintaining all favorable properties provided by the PDMS material.

The Consequences of Financial Leverage: Certified B Corporations' Advantages Compared to Common Commercial Firms

Firms usually need to attract debt to form and grow, but increasing financial leverage also entails increased risks and costs for stakeholders, such as customers and employees. Accordingly, past research suggests that for common commercial firms (CCFs), which prioritize profits, higher leverage leads to lower sales growth and higher employment costs. However, Certified B Corporations (CBCs) distinguish themselves by having a credible prosocial mission and, therefore, might be better insulated against the adverse effects of higher leverage. Using a European multi-country matched sample of 136 CBCs and 136 CCFs, we find that the negative relationship between leverage and sales growth and the positive relationship between leverage and employment costs are weaker for CBCs than CCFs. Taken together, due to their certified prosocial mission, CBCs enjoy an advantage in debt financing compared to CCFs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10551-023-05349-5.

Adverse Effects of fine particulate matter on human kidney functioning: a systematic review

BACKGROUND

Ambient fine particulate matter (PM < 2.5 μm, PM2.5) is gaining increasing attention as an environmental risk factor for health. The kidneys are considered a particularly vulnerable target to the toxic effects that PM2.5 exerts. Alteration of kidney function may lead to a disrupted homeostasis, affecting disparate tissues in the body. This review intends to summarize all relevant knowledge published between January 2000 and December 2021 on the effects of ambient PM2.5 and the adverse effects on kidney function in adults (≥ 18 years).

RESULTS AND DISCUSSION

Studies published in peer-reviewed journals, written in English, regarding the effects of PM2.5 on kidney function and the development and/or exacerbation of kidney disease(s) were included. Of the 587 nonduplicate studies evaluated, 40 were included, comprising of studies on healthy or diagnosed with pre-existing disease (sub)populations. Most of the studies were cohort studies (n = 27), followed by 10 cross-sectional, 1 ecological and 2 time-series studies. One longitudinal study was considered intermediate risk of bias, the other included studies were considered low risk of bias. A large portion of the studies (n = 36) showed that PM2.5 exposure worsened kidney outcome(s) investigated; however, some studies show contradictory results. Measurement of the estimated glomerular filtration rate, for instance, was found to be positively associated (n = 8) as well as negatively associated (n = 4) with PM2.5.

LIMITATIONS AND CONCLUSION

The main limitations of the included studies include residual confounding (e.g., smoking) and lack of individual exposure levels. The majority of included studies focused on specific subpopulations, which may limit generalizability. Evidence of the detrimental effects that ambient PM2.5 may exert on kidney function is emerging. However, further investigations are required to determine how and to what extent air pollution, specifically PM2.5, exerts adverse effects on the kidney and alters its function.

REGISTRATION

The systematic review protocol was submitted and published by the International Prospective Register of Systematic Reviews (PROSPERO; CRD42020175615 ).

Artificial intelligence with deep learning in nuclear medicine and radiology

The use of deep learning in medical imaging has increased rapidly over the past few years, finding applications throughout the entire radiology pipeline, from improved scanner performance to automatic disease detection and diagnosis. These advancements have resulted in a wide variety of deep learning approaches being developed, solving unique challenges for various imaging modalities. This paper provides a review on these developments from a technical point of view, categorizing the different methodologies and summarizing their implementation. We provide an introduction to the design of neural networks and their training procedure, after which we take an extended look at their uses in medical imaging. We cover the different sections of the radiology pipeline, highlighting some influential works and discussing the merits and limitations of deep learning approaches compared to other traditional methods. As such, this review is intended to provide a broad yet concise overview for the interested reader, facilitating adoption and interdisciplinary research of deep learning in the field of medical imaging.