A generalizable methodology for predicting retention time of small molecule pharmaceutical compounds across reversed-phase HPLC columns.

Quantitative structure retention relation (QSRR) is an active field of research, primarily focused on predicting chromatography retention time (Rt) based on molecular structures of an input analyte on a single or limited number of reversed-phase HPLC (RP-HPLC) columns. However, in the pharmaceutical chemistry manufacturing and controls (CMC) settings, single-column QSRR models are often insufficient. It is important to translate retention time across different HPLC methods, specifically different stationary phases (SP) and mobile phases (MP), to guide the HPLC method development, and to bridge organic impurity profiles across different development phases and laboratories.

RANK IVVY motif plays crucial roles in osteoclastogenesis.

RANKL and its receptor RANK play a vital role in osteoclastogenesis. RANK primarily recruits TRAFs to promote osteoclastogenesis but also contains an TRAF-independent motif (IVVY), which mediates osteoclast lineage commitment in vitro. Here, we have developed knockin mice in which inactivating mutations are introduced in the IVVY motif (IVVY to IVAF).

Lithiation: Advancing Material Synthesis and Structural Engineering for Emerging Applications.

Lithiation, a process of inserting lithium ions into a host material, is revolutionizing nanomaterials synthesis and structural engineering as well as enhancing their performance across emerging applications, particularly valuable for large-scale synthesis of high-quality low-dimensional nanomaterials. Through a systematic investigation of the synthetic strategies and structural changes induced by lithiation, this review aims to offer a comprehensive understanding of the development, potential, and challenges associated with this promising approach. First, the basic principles of lithiation/delithiation processes will be introduced.

scHiCyclePred: a deep learning framework for predicting cell cycle phases from single-cell Hi-C data using multi-scale interaction information.

The emergence of single-cell Hi-C (scHi-C) technology has provided unprecedented opportunities for investigating the intricate relationship between cell cycle phases and the three-dimensional (3D) structure of chromatin. However, accurately predicting cell cycle phases based on scHi-C data remains a formidable challenge. Here, we present scHiCyclePred, a prediction model that integrates multiple feature sets to leverage scHi-C data for predicting cell cycle phases.

Evaluating the Improvement of Blend Potency Measurements in the Feed Frame of a Rotary Tablet Press Using Combined NIR and Raman Spectroscopy.

This study investigated the added value of combining both near-infrared (NIR) and Raman spectroscopy into a single NIRaman Combi Fiber Probe for in-line blend potency determination in the feed frame of a rotary tablet press. A five-component platform formulation was used, containing acetylsalicylic acid as the Active Pharmaceutical Ingredient (API). Calibration models for the determination of 1 and 5% label claim tablets were developed using NIR and Raman spectra of powder blends ranging from 0.

Exploring dissolved NO characteristics and unearthing indirect NO emission factors in the shallow groundwater of paddy and upland fields.

Indirect emissions of nitrous oxide (NO) stemming from nitrogen (N) leaching in agricultural fields constitute a significant contributor to atmospheric NO. Groundwater nitrate (NO-N) pollution is severe in the Ningxia Yellow River Irrigation Area (NYRIA), coupled with high NO-N leaching, exacerbates the risk of indirect NO emissions from groundwater. Over two years of field observations, this study investigated the characteristics and interannual variations of dissolved NO (dNO) concentrations and indirect NO emission factors (EF) in shallow groundwater.

CTPredictor: A comprehensive and robust framework for predicting cell types by integrating multi-scale features from single-cell Hi-C data.

Single-cell Hi-C (scHi-C) has emerged as a powerful technology for deciphering cell-to-cell variability in three-dimensional (3D) chromatin organization, providing insights into genome-wide chromatin interactions and their correlation with cellular functions. Nevertheless, the accurate identification of cell types across different datasets remains a formidable challenge, hindering comprehensive investigations into genome structure. In response, we introduce CTPredictor, an innovative computational method that integrates multi-scale features to accurately predict cell types in various datasets.

Ditch level-dependent N removal capacity of denitrification and anammox in the drainage system of the Ningxia Yellow River irrigation district.

Drainage networks, consisting of different levels of ditches, play a positive role in removing reactive nitrogen (N) via self-purification before drainage water returns to natural water bodies. However, relatively little is known about the N removal capacity of irrigation agricultural systems with different drainage ditch levels. In this study, we employed soil core incubation and soil slurry N paired tracer techniques to investigate the N removal rate (i.

Drainage ditches are significant sources of indirect NO emissions regulated by available carbon to nitrogen substrates in salt-affected farmlands.

Agriculture is a main source of nitrous oxide (NO) emissions. In agricultural systems, direct NO emissions from nitrogen (N) addition to soils have been widely investigated, whereas indirect emissions from aquatic ecosystems such as ditches are poorly known, with insufficient data available to refine the IPCC emission factor. In this contribution, in situ NO emissions from two ditch water‒air interfaces based on a diffusion model were investigated (almost once per month) from June 2021 to December 2022 in an intensive arable catchment with high N inputs and salt-affected conditions in the Qingtongxia Irrigation District, northwestern China.

Phase-appropriate Application of Process Analytical Technology for Early Pharmaceutical Development of Oral Solid Dosage Forms-the Case Study of Uniformity Screening of Dosage Units and Blends.

Process analytical technology (PAT) in late-stage drug product development is typically used for real-time process monitoring, in-process control, and real-time release testing. In early research and development (R&D), PAT usage is limited as the manufacturing scale is relatively small with frequent changes and only a few batches are produced on an annual basis. However, process understanding is critical at early R&D in order to identify process and formulation boundaries, so PAT applications could be particularly useful in early-stage R&D.

Salinity and high pH reduce denitrification rates by inhibiting denitrifying gene abundance in a saline-alkali soil.

Denitrification, as the main nitrogen (N) removal process in farmland drainage ditches in coastal areas, is significantly affected by saline-alkali conditions. To elucidate the effects of saline-alkali conditions on denitrification, incubation experiments with five salt and salt-alkali gradients and three nitrogen addition levels were conducted in a saline-alkali soil followed by determination of denitrification rates and the associated functional genes (i.e.

Development of a Near-Infrared Spectroscopy (NIRS)-Based Characterization Approach for Inherent Powder Blend Heterogeneity in Direct Compression Formulations.

With the advent of continuous direct compression (CDC) process, it becomes increasingly desirable to characterize inherent powder blend heterogeneity at a small batch scale for a robust and CDC-amenable formulation. To accomplish this goal, a near infrared spectroscopy (NIRS)-based characterization approach was developed and implemented on multiple direct compression (DC) blends in this study, with the intended purpose of complementing existing formulation development tools and enabling to build an early CMC data package for late-phased process analytical technology (PAT) method development. Three fumaric acid DC blends, designed to harbor varied degrees of inherent blend heterogeneity, were employed.

Spectroscopy-Based Local Modeling Method for High-Throughput Quantification of Nucleic Acid Loading in Lipid Nanoparticles.

Lipid nanoparticles (LNPs) are the most widely investigated delivery systems for nucleic acid-based therapeutics and vaccines. Loading efficiency of nucleic acids may vary with formulation conditions, and it is considered one of the critical quality attributes of LNP products. Current analytical methods for quantification of cargo loading in LNPs often require external standard preparations and preseparation of unloaded nucleic acids from LNPs; therefore, they are subject to tedious and lengthy procedures, LNP stability, and unpredictable recovery rates of the separated analytes.

Do biochar and polyacrylamide have synergistic effect on net denitrification and ammonia volatilization in saline soils?

Salt-affected soils have poor structure and physicochemical properties, which affect soil nitrogen cycling process closely related to the environment, such as denitrification and ammonia volatilization. Biochar and polyacrylamide (PAM) have been widely used as soil amendments to improve soil physicochemical properties. However, how they affect denitrification and ammonia volatilization in saline soils is unclear.

Multivariate Spectroscopic Method Lifecycle Management as Part of the Quality Management System.

Multivariate model based spectroscopic methods require model maintenance through their lifecycle. A survey conducted by the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) in 2019 showed that regulatory reporting categories for the model related changes can be a hurdle for the routine use of these types of methods. This article introduces industry best practices on multivariate method and model lifecycle management within the Pharmaceutical Quality System.

Fractal and Polarization Properties of Light Scattering Using Microcrystalline Pharmaceutical Aggregates.

Fractal and polarization analysis of diffusively scattered light is applied to determine the complex relationship between fractal dimension of structural morphology and concentration of chemically active ingredients in two pharmaceutical mixture systems including a series of binary mixtures of acetaminophen in lactose and three multicomponent blends with a proprietary active ingredient. A robust approach is proposed to identify and filter out multiple- and single-scattering components of scattering indicatrix. The fractal dimension extracted from scattering field reveals complex structural details of the sample, showing strong dependence on low-dose drug concentration in the blend.

Sample Mass Estimate for the Use of Near-Infrared and Raman Spectroscopy to Monitor Content Uniformity in a Tablet Press Feed Frame of a Drug Product Continuous Manufacturing Process.

Recently, feed frame-based process analytical technology measurements used to assure product quality during continuous manufacturing processes have received significant attention. These measurements are able to accurately determine uniformity of the powder blend before compression, and in these applications, it is necessary to understand the interrogated sample volume per measurement. This understanding ensures that the blend measurement can be indicative of the uniformity of the final dosage form.

Niclosamide and its derivative DK-520 inhibit RANKL-induced osteoclastogenesis.

Niclosamide is a potent inhibitor of osteoclastogenesis and bone remodeling. DK-520 is an acyl derivative of Niclosamide and significantly increased both the plasma concentration and the duration of exposure of Niclosamide when dosed orally. However, at present the effect of DK-520 on osteoclastogenesis has not been reported.

Review of real-time release testing of pharmaceutical tablets: State-of-the art, challenges and future perspective.

In the last decade significant advances have been made in process analytical technologies and digital manufacturing of pharmaceutical oral solid dosage forms leading to enhanced product knowledge and process understanding. These developments provide an excellent platform for realising real-time release testing (RTRT) to eliminate all, or certain, off-line end product tests assuring that the drug product is of intended quality. This review article presents the state of the art, an RTRT development workflow as well as challenges and opportunities of RTRT in batch and continuous manufacturing of pharmaceutical tablets.

Specific RANK Cytoplasmic Motifs Drive Osteoclastogenesis.

Upon receptor activator of NF-κB ligand (RANKL) binding, RANK promotes osteoclast formation through the recruitment of tumor necrosis factor (TNF) receptor-associated factors (TRAFs). In vitro assays identified two RANK intracellular motifs that bind TRAFs: PVQEET (Motif 2) and PVQEQG (Motif 3), which potently mediate osteoclast formation in vitro. To validate the in vitro findings, we have generated knock-in (KI) mice harboring inactivating mutations in RANK Motifs 2 and 3.

Characterization of Near-Infrared and Raman Spectroscopy for In-Line Monitoring of a Low-Drug Load Formulation in a Continuous Manufacturing Process.

Reflectance spectroscopy is an excellent candidate for process analytical technology (PAT) applications in continuous manufacturing of pharmaceutical tablets. Spectroscopic methods provide a real-time, nondestructive measurement of the active pharmaceutical ingredient (API) concentration in order to ensure product quality and uniformity. Of particular challenge is the powder blends with low drug loads (<5% w/w) where the measurement of the signal-to-noise and, in turn, precision limit the ability of the method.

First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing.

This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages.

Prediction of Dissolution Profiles From Process Parameters, Formulation, and Spectroscopic Measurements.

This study utilized multiple modeling approaches to predict immediate release tablet dissolution profiles of 2 model drugs: theophylline and carbamazepine. Two sets of designs of experiments were applied based on individual drug characteristics to build in adequate dissolution variability. The tablets were scanned using a near-infrared (NIR) spectrometer and then subjected to in vitro dissolution test at critical time points.

Characterizing drug product continuous manufacturing residence time distributions of major/minor excipient step changes using near infrared spectroscopy and process parameters.

The material residence time distribution in a continuous manufacturing process can be utilized to develop, design and justify the process control strategy. This paper successfully demonstrates using both major and minor formulation component step changes to determine the system response using either Near Infrared Spectroscopy or process parameters. These options provide development flexibility to determine the system's material residence time earlier in the development process and more cost effectively.

Development of Near Infrared Spectroscopy-based Process Monitoring Methodology for Pharmaceutical Continuous Manufacturing Using an Offline Calibration Approach.

A near-infrared (NIR) calibration was developed using an efficient offline approach to enable a quantitative partial least-squares (PLS) chemometric model to measure and monitor the concentration of active pharmaceutical ingredients (API) in powder blends in the feed frame (FF) of a tablet press. The approach leveraged an offline "feed frame table," which was designed to mimic the full process from a NIR measurement perspective, thereby facilitating a more robust model by allowing more sources of variability to be included in the calibration by minimizing the consumption of API and other raw materials. The design of experiment (DOE) for the calibration was established by an initial risk assessment and included anticipated variability from factors related to formulation, process, environment, and instrumentation.