In “comprehensive” two-dimensional liquid chromatography, the column effluent from the first separation system (the first dimension) is sequentially sampled by the second dimension separation system. The total analysis time is largely determined by the speed of the second dimension separation system; the most retained component must elute before the least retained component of the next second dimension separation. Optimization of multidimensional separation systems requires that one understand the relationship between system resolution and the number of second dimension samples across a first dimension peak. In this paper, we study the theoretical and experimental aspects of this sampling process. To obtain high two-dimensional resolution, each peak in the first dimension should be sampled at least three times into the second dimension when the sampling is in-phase. If the sampling is maximally out of phase, there should be at least four samples per peak for high-fidelity separation. The sensitivity of the resolution with respect to the sampling phase is discussed in detail and shown to be insignificant when four or greater samples are taken across the first dimension peak width. These results suggest optimal criteria for method development with multidimensional chromatography.

In the summer of 1983 a group of scientists working in the fields of meteorology, biology, and remote sensing met to discuss methods for modeling and observing land‐surface—atmosphere interactions on regional and global scales. They concluded, first, that the existing climate models contained poor representations of the processes controlling the exchanges of energy, water, heat, and carbon between the land surface and the atmosphere and, second, that satellite remote sensing had been underutilized as a means of specifying global fields of the governing biophysical parameters. Accordingly, a multiscale, multidisciplinary experiment, FIFE, was initiated to address these two issues. The objectives of FIFE were specified as follows: (1) Upscale integration of models: The experiment was designed to test the soil‐plant‐atmosphere models developed by biometeorologists for small‐scale applications (millimeters to meters) and to develop methods to apply them at the larger scales (kilometers) appropriate to atmospheric models and satellite remote sensing. (2) Application of satellite remote sensing: Even if the first goal were achieved to yield a “perfect” model of vegetation‐atmosphere exchanges, it would have very limited applications without a global observing system for initialization and validation. As a result, the experiment was tasked with exploring methods for using satellite data to quantify important biophysical states and rates for model input. The experiment was centered on a 15 × 15 km grassland site near Manhattan, Kansas. This area became the focus for an extended monitoring program of satellite, meteorological, biophysical, and hydrological data acquisition from early 1987 through October 1989 and a series of 12‐ to 20‐day intensive field campaigns (IFCs), four in 1987 and one in 1989. During the IFCs the fluxes of heat, moisture, carbon dioxide, and radiation were measured with surface and airborne equipment in coordination with measurements of surface and atmospheric parameters and satellite overpasses. The resulting data are held in a single integrated data base and continue to be analyzed by the participating scientists and others. The first two sections of this paper recount the history and scientific background leading up to FIFE; the third and fourth sections review the experiment design, the scientific teams and equipment involved, and the actual execution of the experiment; the fifth section provides an overview of the contents of this special issue; the sixth section summarizes the management and resources of the project; and the last section lists the acknowledgments.

Bispecific antibodies (BsAbs) are regarded as promising therapeutic agents due to their ability to simultaneously bind two different antigens. Several bispecific modalities have been developed, but their utility is limited due to problems with stability and manufacturing complexity. Here we report a versatile technology, based on a scaffold antibody and pharmacophore peptide heterodimers, that enables rapid generation and chemical optimization of bispecific antibodies, which are termed bispecific CovX-Bodies. Two different peptides are joined together using a branched azetidinone linker and fused to the scaffold antibody under mild conditions in a site-specific manner. Whereas the pharmacophores are responsible for functional activities, the antibody scaffold imparts long half-life and Ig-like distribution. The pharmacophores can be chemically optimized or replaced with other pharmacophores to generate optimized or unique bispecific antibodies. As a prototype, we developed a bispecific antibody that binds both vascular endothelial growth factor (VEGF) and angiopoietin-2 (Ang2) simultaneously, inhibits their function, shows efficacy in tumor xenograft studies, and greatly augments the antitumor effects of standard chemotherapy. This unique antiangiogenic bispecific antibody is in phase-1 clinical trials.

Two-dimensional liquid chromatography (2DLC) is anincreasingly popular technique which has the potential to provide a far more detailed separation and characterization of alcohol ethoxylates (AE) than has been shown by previously utilized separation techniques. The AE are unique in that these molecules have distributions in both alkyl and ethylene oxide chain lengths. In this paper, we compare the single-column techniques of open-tubular SFC, normal-and reversed-phase HPLC, and the multiple column technique of 2DLC in terms of the efficacy of separation and characterization of the alkyl and ethoxylate distributions in a select group of AE. The combination of normal-and reversed-phase HPLC in a 2DLC system accomplishes the simultaneous alkyl and ethylene oxide distribution analysis. The advantage of using 2DLC over one-dimensional chromatographic techniques is clearly demonstrated in the increased selectivity resulting in the ability to produce the ethylene oxide distributions of each alkyl component in an AE. In addition, 2DLC chromatograms are easier to interpret due to ordering of the chromatograms.

Abstract Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, the scientific community still lacks a secure and privacy-preserving infrastructure to support auditable data sharing and facilitate automated and legally compliant federated analysis on an international scale. Existing health informatics systems do not incorporate the latest progress in modern security and federated machine learning algorithms, which are poised to offer solutions. An international group of passionate researchers came together with a joint mission to solve the problem with our finest models and tools. The SCOR consortium has developed a ready-to-deploy secure infrastructure using world-class privacy and security technologies to reconcile the privacy/utility conflicts. We hope our effort will make a change and accelerate research in future pandemics with broad and diverse samples on an international scale.