The rapid increase in both the quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches, such as machine learning (ML), have become indispensable tools for revealing hidden patterns or deducing correlations for which conventional analytical methods face limitations or challenges. However, ML concepts and practices have not been widely utilized by researchers in ESE. This feature explores the potential of ML to revolutionize data analysis and modeling in the ESE field, and covers the essential knowledge needed for such applications. First, we use five examples to illustrate how ML addresses complex ESE problems. We then summarize four major types of applications of ML in ESE: making predictions; extracting feature importance; detecting anomalies; and discovering new materials or chemicals. Next, we introduce the essential knowledge required and current shortcomings in ML applications in ESE, with a focus on three important but often overlooked components when applying ML: correct model development, proper model interpretation, and sound applicability analysis. Finally, we discuss challenges and future opportunities in the application of ML tools in ESE to highlight the potential of ML in this field.

A microfluidic device was developed to separate heterogeneous particle or cell mixtures in a continuous flow using acoustophoresis. In this device, two identical surface acoustic waves (SAWs) generated by interdigital transducers (IDTs) propagated toward a microchannel, which accordingly built up a standing surface acoustic wave (SSAW) field across the channel. A numerical model, coupling a piezoelectric effect in the solid substrate and acoustic pressure in the fluid, was developed to provide a better understanding of SSAW-based particle manipulation. It was found that the pressure nodes across the channel were individual planes perpendicular to the solid substrate. In the separation experiments, two side sheath flows hydrodynamically focused the injected particle or cell mixtures into a very narrow stream along the centerline. Particles flowing through the SSAW field experienced an acoustic radiation force that highly depends on the particle properties. As a result, dissimilar particles or cells were laterally attracted toward the pressure nodes at different magnitudes, and were eventually switched to different outlets. Two types of fluorescent microspheres with different sizes were successfully separated using the developed device. In addition, Escherichia coli bacteria premixed in peripheral blood mononuclear cells (PBMCs) were also efficiently isolated using the SSAW-base separation technique. Flow cytometric analysis on the collected samples found that the purity of separated E. coli bacteria was 95.65%.

We investigated the relationship between nuclear hits by alpha particles and the subsequent occurrence of sister chromatid exchanges (SCEs) in normal human diploid lung fibroblasts (HFL1). Cells were exposed to 238Pu alpha particles at doses ranging from 0.4-12.9 cGy and subsequently analyzed for SCEs. A significant increase in SCE frequency was observed even at the lowest dose examined. The extent of induction of SCEs in the HFL1 cells showed dose dependency in the very low dose range, i.e. 0.4-2.0 cGy. Thereafter, induction of SCEs was independent of dose. Based on measurements of the nuclear areas of the HFL1 cells in conjunction with target theory calculations, the lowest dose resulted in an approximately 8.6-fold increase in the percentage of cells showing excessive SCEs over the theoretically expected percentage of cells whose nuclei were calculated to be traversed by one or more alpha particles. The extent of the discrepancies between theoretically expected and experimentally observed frequencies of SCEs became progressively reduced with increasing radiation dose. We additionally determined that SCEs induced by the alpha particles have no significant dependency on the time of cell collection after exposure to a selected dose of alpha particles, thereby confirming that the differences between the theoretically predicted and observed SCE frequencies were not due to an artifact of the time of cell sampling for the SCE measurements. These results obtained with normal human cells are similar to those of other investigators who observed excessive SCEs in immortalized rodent cells beyond that which could be attributed exclusively to nuclear traversals by alpha particles. Such consistent findings point to the existence of an alternative, extranuclear target through which alpha particles cause DNA damage, as detected by SCE analysis. The existence of an extranuclear compartment as a target for alpha particles may have important implications for the susceptibility of lung cells to the DNA-damaging effects of alpha-particle exposure due to the inhalation of radon progeny.

Combating bioterrorism is a challenge to all of us. To be proactive, the U.S. Government has formalized the discipline of "microbial forensics" to deter and attribute perpetrators of such acts. This Policy Forum describes the foundations of the microbial forensics program: the creation of a national bioforensics laboratory, a partnership laboratory network, and a peer-consensus scientific working group and the promulgation of quality assurance guidelines.

Large, fluorescently stained restriction fragments of lambda phage DNA are sized by passing individual fragments through a focused continuous wave laser beam in an ultrasensitive flow cytometer at a rate of 60 fragments per second. The size of the fluorescence burst emitted by each stained DNA fragment, as it passes through the laser beam, is measured in one millisecond. One hundred sixty four seconds of fluorescence burst data allow linear sizing of DNA with an accuracy of better than two percent over a range of 10 to 50 kbp. This corresponds to analyzing less than 1 pg of DNA. Sizing of DNA fragments by this approach is much faster, requires much less DNA, and can potentially analyze large fragments with better resolution and accuracy than with gel-based electrophoresis.