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The use of two-dimensional liquid chromatography (2D-LC) to assess peak purity is becoming common in the pharmaceutical industry. In this application space, it is critically valuable to demonstrate that all compounds eluted from a column during an LC assay are accounted for, and that no impurities are 'hiding' under the peaks of known compounds. Although the addition of the second dimension ([.sup.2]D) separation makes 2D-LC an exquisitely powerful tool, it also warrants additional care when interpreting the results to avoid misidentification of apparently new peaks as coeluted impurities, when in fact they are analytical artifacts. In this installment of 'LC Troubleshooting,' we describe one such possible artifact that can arise because of the degradation of compounds during the transfer of fractions of the first dimension ([.sup.1]D) column effluent to the [.sup.2]D separation. We suggest simple experiments to determine whether new peaks observed in 2D chromatograms result from degradation, ultimately increasing our confidence in the interpretation of 2D-LC results., IN RECENT YEARS, two-dimensional liquid chromatography (2D-LC) has gained popularity in pharmaceutical analysis. Although more work is still needed before this technique can be used routinely in Good Manufacturing Practice [...]

Addressing the complex equipment and network challenges in new energy power plant industrial control systems, this study introduces a Markov time-varying machine learning algorithm, leveraging classification-constrained Boltzmann machines for real-time network security risk prediction. By employing a hybrid training mode for innovative feature extraction and classification, the algorithm forecasts future security risk states through an up-to-date state transition probability matrix. Integrating with the Markov time-varying model enhances the efficiency over traditional Boltzmann machines, facilitating nuanced network state analyses. The proposed model demonstrates high effectiveness against various network attacks, with average precision, recall, and F1 scores of 0.96, 0.93, and 0.94, respectively, and maintains over 80% accuracy under noise levels up to 40 dB. This research provides a solid foundation for proactive security defense mechanisms in industrial control systems.

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.

Understanding the relationship between the acceptor dopant size and proton conductivity in barium zirconate, BaZrO3, is important for maximizing efficiency in this promising fuel cell material. While proton conduction pathways with larger Y Zr ′ and smaller Al Zr ′ defects have been explored, proton pathways with Sc Zr ′ , a defect of comparable size to the replaced ion, have not been investigated using centrality measures, periodic pathway searches, and kinetic Monte Carlo (KMC). Centrality measures in BaSc0.125Zr0.875O3 highlight a trapping region by Sc Zr ′ and scattered high centrality regions on undoped planes. Connected long-range high centrality regions are found mainly in undoped planes for BaAl0.125Zr0.875O3 and in the dopant planes for BaY0.125Zr0.875O3. The best long-range proton conduction periodic pathways in Al Zr ′ and Sc Zr ′ systems travel between dopant planes, while those for yttrium-doped BaZrO3 remained on dopant planes. KMC trajectories at 1000 K show long-range proton conduction barriers of 0.86 eV, 0.52 eV, and 0.25 eV for Al Zr ′ , Sc Zr ′ , and Y Zr ′ systems, respectively. Long-range periodic conduction highway limiting barrier averages correlate well with the connectivity of the most central regions in each system but ignore diffusion around the dopant and through other high centrality regions. BaSc0.125Zr0.875O3 shows an intermediate overall conduction barrier limited by trapping, which earlier experiments and simulations suggest that it can be mitigated with increased oxygen vacancy concentration. [ABSTRACT FROM AUTHOR]

A simple and easy-to-build high-throughput analysis system was constructed. The system consisted of three major components: (1) a multichannel device with 16 parallel capillaries, (2) a desorption electrospray ionization (DESI) source, and (3) a linear ion trap mass spectrometer. When analyses were performed, the multichannel device was moved horizontally on a translation stage controlled by a step motor. Our design expands the functions of DESI, in which the liquid sample in capillary was driven out by the nebulizing gas, ionized, and then transferred to a mass spectrometer. To assess the high-throughput performance of the system, 5 mg/L 1,3-diethyl-l,3-diphenylurea (DDU) solution and 10 mg/L angiotensin I solution were alternatively loaded into the reservoirs and capillaries in the multichannel device. Results indicated that analyses of the all the samples in 16 capillaries were completed within 1.6 min, which means a throughput of 600 samples/h. Reactive DESI experiment was also successfully performed with this system to show the feasibility of online derivatization. The relative standard deviations for a single capillary and five identical capillaries were 7.6 (n = 16) and 12.3%, respectively. Linear relative abundance response was achieved for DDU (r=0.9971).