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The reduction of nitroarenes to anilines is a key transformation with real-life context, central to the preparation of many important fine chemicals. The importance of this transformation has led to its inclusion in not only university organic chemistry courses but also preuniversity, especially in Europe. A variety of reagent combinations have been developed to achieve this reduction, each with its own merits; we report herein comparison of the most common methods and what and how this transformation is taught to students. Reviewing preuniversity syllabi and a variety of textbooks, we reveal a misalignment between what is taught and the conditions most commonly used in research. Palladium-catalyzed hydrogenation and iron/ammonium chloride are the most popular reaction choices in the literature, yet these methods are often not mentioned, with other, less general, methods being taught, e.g., tin/concentrated hydrochloric acid, zinc/acid, and lithium aluminum hydride. Where multiple methods are taught, the rationale for inclusion of these is often not presented, particularly considering functional group compatibility, ease of purification, safety, or sustainability. Considering the textbooks reviewed, the mechanisms involved in the reduction are generally not discussed. We argue that, despite the perceived complexity of the reaction, coverage of the sequential nature of the reduction is important in aiding students' understanding of this reaction, e.g., to account for the formation of various intermediates and/or byproducts. We present suggestions to enable educators to discuss the processes involved in this important transformation, drawing parallels with the presentation of other frequently taught reaction pathways.

The use of red cabbage ("Brassica oleracea var. capitata F. rubra") extract as a pH indicator is a versatile and popular demonstration that is employed by educators in many schools and universities. Previous variations of this demonstration have used red cabbage extracts to prepare paper that changes color when solutions of acid or base are applied as "inks". In this report, we highlight the ability of red cabbage extracts to function as invisible inks. Colorless solutions are prepared by bleaching anthocyanin extracts with aqueous sodium metabisulfite, and the resulting mixture can then be used to write hidden messages on paper. The invisible messages can be revealed by the addition of citric acid solution, or by using potassium aluminum sulfate (alum) as developers. The demonstration does not require specialist equipment or chemicals, and options to use additional plant sources to prepare the ink are described.

Applications of machine learning in chemistry are many and varied, from prediction of structure-property relationships, to modeling of potential energy surfaces for large scale atomistic simulations. We describe a generalized approach for the application of machine learning to the classification of spectra which can be used as the basis for a wide variety of undergraduate projects. While our examples use FTIR and mass spectra, the approach could equally well be used with UV-visible, Raman, NMR, or indeed any other type of spectra. We summarize a number of different unsupervised and supervised machine learning algorithms that can be used to classify spectra into groups, and illustrate their application using data from three different projects carried out by fourth year chemistry undergraduates. The three projects investigated the ability of the various machine learning approaches to correctly classify spectra of a variety of fruits, whiskies, and teas, respectively. In all cases the algorithms were able to differentiate between the various samples used in each study, and the trained machine learning models could then be used to classify unknown samples with a high degree of accuracy (>98% in many cases). Depending on the extent to which students are expected to write their own code to perform the data analysis, the general model adopted in this work can be adapted for a variety of purposes, from short (one to two day) practical exercises and workshops, to much longer independent student projects.

To develop expertise, novice chemistry students require deliberate practice with immediate and thoughtful feedback. Whereas opportunities for practice are often abundant, opportunities for feedback tend to be much scarcer. To address this challenge, we collaborated with students to develop a flexible and scalable online platform called "Alchemy." Students interact with the software through a series of prompts and multiple-choice questions, receiving targeted feedback at each step. Each student can navigate a scenario differently, influenced by their prior knowledge and misconceptions. In design, scenarios are instructor-created graphs that model their expert-level thought process­(es) and teaching experience. This graph format is a distinct and advantageous feature of Alchemy that supports linear, nonlinear, and cyclical progression through a concept or problem. Alchemy-based homework has been assigned in lecture and lab courses, at the sophomore and junior levels, with enrollments ranging from many tens to many hundreds of students. Approximately 80% of students rated Alchemy as very/extremely helpful to their learning, emphasizing the value of the step-by-step process and feedback. Alchemy is discussed in the contexts of other software platforms, its advantages and limitations, lessons learned in its initial deployments, and future directions for its development and usage.

This paper summarizes my experience with teaching a first-year, General Chemistry course to a visually impaired student. This includes accommodations and modifications for both the lecture material and the laboratory. Included are also examples of formats and syntax for txt-based quizzes, tests, and laboratory reports, as well as other general accommodations for both the student and the service dog.

A practical focusing on the synthesis, isolation, and hydrolysis of ammonia borane (AB), H[subscript 3]N·BH[subscript 3], was developed for first-year undergraduate students. By requiring students to propose their own experimental setup to measure the amount of gas produced upon hydrolysis, experimental design skills were introduced and developed during the practical. As a result of the COVID-19 pandemic, remote and face-to-face versions of the practical were created to enable inclusivity in which experimental design skills were a key feature. Students identified and reported an appreciable increase in their experimental design skills. The multifaceted nature of the practical allows for flexibility in its implementation, dependent on students' prior knowledge, local logistical considerations, and the learning objectives of an institution.

The overhead mechanical stirrer is a versatile and valuable tool for the laboratory. Even a low-end mechanical stirrer is rather expensive and can pose serious safety concerns for use by high school or undergraduate students. The construction and application of a low-cost overhead mechanical stirrer is described in this work. The mechanical stirrer is constructed using a commercially available USB powered mini-pottery wheel and other low-cost materials. The total cost of construction is less than $50 per stirrer. This overhead mechanical stirrer is designed for use with low to medium viscosity liquids. This stirrer has been successfully used in the synthesis of a ferrofluid in the Advanced Inorganic Chemistry laboratory at Radford University. The fabrication of the glass stirring shaft is used as an opportunity for students to learn scientific glassblowing skills.

The importance of culture and social interactions in disciplinary learning and language development within specific social practices and contexts is now an agreed-upon notion in the science education literature. In a pivotal article in 1990, Lemke introduced the idea of manual-technical operations as one of four modes making up the "hybrid language of science". Our aim in this paper is to further unpack the concept of manual-technical operations as a mode, thereby contributing to the more complex understanding of when and how this mode enhances meaning-making and communication of ideas. Drawing from researchers in diverse disciplines, we present a visual of the complex and integrated manual-technical operations mode. It is our hope that the theoretical model proposed in this manuscript will allow researchers to develop analytic frameworks to capture and assess change in the manual-technical operations mode of the hybrid language of science.

Since the sudden emergence of COVID-19 global pandemic, all educational institutions have looked to move resources and delivery online. Some institutions had already embraced delivering instruction in this way; however, broader adaptation to this teaching style is new to many educators. While the teaching of theoretical concepts is more easily transferred to a blended learning environment, the teaching of practical chemistry poses significant challenges, yet it is crucial to the chemist's identity. Here we describe the establishment of a new, international, network to consider how practical chemistry can be taught outside of the traditional laboratory environment and invite readers of this special edition of the journal to join. Meeting fortnightly and maintaining links through a shared networked drive between meetings, the network has been accessed by over 100 delegates in the U.K., mainland Europe, North America, and Australasia. The traditional siloes of chemistry have not defined the discussions, which have instead focused on logistical aspects such as social distancing and the pastoral role of the laboratory environment. Initial evaluation shows the network is valued by its members and is making progress toward its aims.

Teaching practical chemistry skills remotely is not a task that would have been high on the agenda only a few months ago. However, in light of the COVID-19 pandemic, students around the world are having to work from home, and the chemistry education community has been forced to adapt to the new circumstances. In response, we discuss the use of simulations in place of practical laboratory work, with emphasis on the development of students' experimental design skills. The simulation of Michaelis-Menten enzyme kinetics is given as an example exercise, which other instructors could implement with immediate effect.

The COVID-19 pandemic has resulted in a need for social distancing measures in public spaces and will have an important impact on university level teaching going forward. Remote methods to complete laboratory related activities are a potential means of students achieving practical credit while still isolating or social distancing. We outline the implementation of two novel remote exercises, based on coding in Mathematica, and the methods used to provide ongoing help to students. These exercises are used as a case study to identify potential problems with remote exercises based on student feedback. Suggestions for how these problems might be overcome in further iterations of these remote exercises are explored.

Data-handling, processing, and analysis skills are an integral part of a chemist's skill set and, more generally, are highly sought by employers. We report a self-directed workshop to develop and advance these key skills using the popular spreadsheet program Microsoft Excel. Making use of its accessible user interface, various contextualized problems relevant to chemistry are introduced, linking theory to practical applications and providing insight and understanding of processes that operate behind-the-scenes in many specialized data processing packages. The workshop has been delivered as a remote exercise for both our first and second year undergraduate cohorts (216 students completed). Students reported a positive impact from the workshop, including the development of a wide range of important skills, the utility for future practical work, and the effectiveness of communication remotely to address their issues.

Classroom observation data using tools such as the Classroom Observation Protocol for Undergraduate STEM (COPUS) are frequently collected in instructional settings for large-scale research studies and program assessment. While COPUS data may be provided to instructors, it is often provided with little or no guidance on how the data can be used to inform teaching practice. This communication is designed to serve as a guide for chemistry instructors to understand the COPUS data from their course, facilitate engagement with the results, and provide strategies for making meaningful changes in response to the data.

Earth's field nuclear magnetic resonance (EFNMR) spectroscopy offers students a unique opportunity to consolidate their understanding of NMR spectroscopic theory through hands-on practice with a simple spectrometer. A comprehensive, 6 h experiment is presented for the introduction of low-field NMR techniques, covering spectroscopy, relaxivity, and imaging experiments in the Earth's magnetic field. This multifaceted practical session explores the concepts of free induction decay, pulse sequences, field homogeneity, relaxation times, J-coupling, and magnetic resonance imaging (MRI), which are reinforced through a series of experiments carried out within an undergraduate teaching laboratory. Students are required to alter parameters as they see fit in order to obtain data, ensuring their understanding of the theory behind NMR spectroscopy. The challenges overcome for the implementation of EFNMR spectroscopy in a modern undergraduate laboratory are also discussed, and detailed instructions are included for spectrometer setup.

Scientific literacy is far more than knowing a list of terms and definitions. Scientific literacy is the ability to do processes related to a specific scientific field and knowing, at minimum, basic problem solving. This paper discusses what students need to know in the different science and mathematics fields and describes the teacher's role in this process. (MVL)

The ability of science undergraduate students to capably communicate course content and their understanding of scientific phenomena through writing has long been considered a problem. Effective methods for improving student writing skills are often fragmented and undertaken on a course-by-course basis rather than as a coordinated approach. This paper describes the implementation of a departmental effort to enhance and evaluate chemistry student writing in several upper-year laboratory courses. The program involves introducing extensive writing focused aspects to course assignments and reports and has impacted over 600 students during a six-year period. Student feedback has been exceptionally positive from undergraduates as well as graduate students who previously participated in the initiative.

Increase in tuition fees means there will be renewed pressure on universities to provide "value for money" courses that provide extensive training in both subject-specific and generic skills. For graduates of chemistry this includes embedding the generic, practical, and laboratory-based skills associated with industrial research as an integral part of undergraduate training. Acknowledging the perception from industrial employers that the laboratory skills of high-achieving graduates in chemistry do not match their academic ability, we present SChemEs (structured chemistry examinations), a novel method of authentic assessment that focuses on developing and rewarding competency in the laboratory. Emphasizing the importance of these skills for future employment and thus embedding them in an undergraduate's skills portfolio will enhance graduate employability. This article outlines the methodological development of SChemEs (which was inspired by the objective structured clinical examinations used in clinical programs), provides an overview of how a SChemEs assessment runs, gives examples and grading criteria used in the exercise, and presents data from a pilot study on attainment and student viewpoint regarding SChemEs.

Abstract PTPN2 (protein tyrosine phosphatase non-receptor type 2, or TC-PTP) and PTPN1 are attractive immuno-oncology targets, with the deletion of Ptpn1 and Ptpn2 improving response to immunotherapy in disease models. Targeted protein degradation has emerged as a promising approach to drug challenging targets including phosphatases. We developed potent PTPN2/N1 dual heterobifunctional degraders (Cmpd-1 and Cmpd-2) which facilitate efficient complex assembly with E3 ubiquitin ligase CRL4CRBN, and mediate potent PTPN2/N1 degradation in cells and mice. To provide mechanistic insights into the cooperative complex formation introduced by degraders, we employed a combination of structural approaches. Our crystal structure reveals how PTPN2 is recognized by the tri-substituted thiophene moiety of the degrader. We further determined a high-resolution structure of DDB1-CRBN/Cmpd-1/PTPN2 using single-particle cryo-electron microscopy (cryo-EM). This structure reveals that the degrader induces proximity between CRBN and PTPN2, albeit the large conformational heterogeneity of this ternary complex. The molecular dynamic (MD)-simulations constructed based on the cryo-EM structure exhibited a large rigid body movement of PTPN2 and illustrated the dynamic interactions between PTPN2 and CRBN. Together, our study demonstrates the development of PTPN2/N1 heterobifunctional degraders with potential applications in cancer immunotherapy. Furthermore, the developed structural workflow could help to understand the dynamic nature of degrader-induced cooperative ternary complexes.

Learning goal (LG) identification can greatly inform curriculum, teaching, and evaluation practices. The complex laboratory course setting, however, presents unique obstacles in developing appropriate LGs. For example, in addition to the large quantity and variety of content supported in the general chemistry laboratory program, the interests of faculty members from various chemistry subdisciplines and the service goals of such a course should be addressed. To optimize the instructional impact of limited laboratory contact time, achieve learning gains in basic and transferable (i.e., valuable in other sciences) laboratory learning content, and establish departmental consensus, a model was created for LG and assessment development that was inspired by interdisciplinary science laboratory LGs implemented at Rice University. These newly developed processes and materials were used to enhance the introductory chemistry laboratory curriculum at the University of British Columbia, involving a large (>1700 student) laboratory program. This model has potential to guide alignment and build consensus within, and possibly across, science laboratory instructional programs.

A systematic way to understand the intricacies of quantum mechanical computations done by a software package known as "Gaussian" is undertaken via an undergraduate research project. These computations involve the evaluation of key parameters in a fitting procedure to express a Slater-type orbital (STO) function in terms of the linear combination of Gaussian-type orbital (GTO) functions. A procedure for the optimization process based on the Newton-Raphson method is developed and is applied to STO-2G and STO-3G basis sets. Satisfactory results obtained by this procedure are used to illustrate the importance of ab initio computations for inclusion in the chemistry or physics undergraduate curriculum. Programming languages such as Python and Maple were employed to obtain the results.

Summary: Diagnosis of respiratory tract infections (RTIs), especially in primary care, is typically made on clinical features and in the absence of quick and reliable diagnostic tests. Even in secondary care, where diagnostic microbiology facilities are available, these tests take 24–48 h to provide an indication of the etiology. This multicentre study used a portable gas chromatography-ion mobility spectrometer (GC-IMS) for the diagnosis of bacterial RTIs. Breath samples taken from 570 participants with 149 clinically validated bacterial and 421 non-bacterial RTIs were analyzed to distinguish bacterial from non-bacterial RTIs. Through the integration of a sparse logistic regression model, we identified a moderate diagnostic accuracy of 0.73 (95% CI 0 · 69, 0 · 77) alongside a sensitivity of 0 · 85 (95% CI 0 · 79, 0 · 91) and a specificity of 0 · 55 (95% CI 0 · 50, 0 · 60). The GC-IMS diagnostic device provides a promising outlook in distinguishing bacterial from non-bacterial RTIs and was also favorably viewed by participants.

We present the details for adapting a diode array UV-vis spectrophotometer to incorporate the use of polypropylene microcentrifuge tubes--fuge tubes--as cuvettes. Optical data are presented validating that the polyethylene fuge tubes are equivalent to the standard square cross section polystyrene or glass cuvettes generally used in spectrophotometers. The fuge tubes also can serve as reaction vessels, which permits the ready study of chemical systems involving heterogeneous phases by eliminating the need for tedious separations. (Contains 3 figures.)

In an attempt to establish the role of the laboratory in chemistry instruction, an historical perspective is developed, in the hope of extracting the consensus of commentators on the subject concerning the important features of the laboratory experience. We present arguments to support the idea that laboratory instruction involves student experiences that mimic what chemists do. We discuss possible techniques to formalize (i.e., in a standard classroom setting) the research experience. (Contains 3 notes.)

ChemPrep was developed to be a stand-alone preparatory short-course to help students succeed in general chemistry. It is Web-based and delivered using the OWL system. Students reported that the ChemPrep materials (short information pages, parameterized questions with detailed feedback, tutorials, and answers to questions through the OWL message system) permitted them to work independently without the need for textbook or lecture. On average, students who completed ChemPrep had higher grades in the subsequent GenChem, Nursing, and Honors chemistry courses, with a greater percentage achieving a grade of C- or higher. Participation in ChemPrep was voluntary, and more women than men responded. Students in the Honors course enrolled in ChemPrep in higher percentages than students in GenChem and Nursing. SAT and departmental math placement exam scores were used as proxy measures of prior achievement and ability. Based on these, Honors chemistry ChemPrep users were on par with their peers but performed better in the course than non-users. In GenChem and Nursing chemistry courses, ChemPrep helped students of high prior achievement and ability perform better than their achievement scores would predict. Weaker or less motivated students did not respond to the voluntary offerings of ChemPrep in the same numbers as stronger or more motivated students, and we are seeking alternate ways to reach this population. (Contains 2 figures, 8 tables, and 8 notes.)

An experiment is described, which is designed for a junior-level chemical engineering "fundamentals of measurements and data analysis" course, where students are introduced to the concept of statistical process control (SPC) through a simple inline mixing experiment. The students learn how to create and analyze control charts in an effort to evaluate the benefits of a mixer.

Describes a project using a multidisciplinary approach for the simultaneous integration of a theme into several disciplines in which participating students apply techniques they learned during the semester and report their findings with a poster presentation. (YDS)

Single-vesicle molecular profiling of cancer-associated extracellular vesicles (EVs) is increasingly being recognized as a powerful tool for cancer detection and monitoring. Mask and target dual imaging is a facile method to quantify the fraction of the molecularly targeted population of EVs in biofluids at the single-vesicle level. However, accurate and efficient dual imaging vesicle analysis has been challenging due to the interference of false signals on the mask images and the need to analyze a large number of images in clinical samples. In this work, we report a fully automatic dual imaging analysis method based on machine learning and use it with dual imaging single-vesicle technology (DISVT) to detect breast cancer at different stages. The convolutional neural network Resnet34 was used along with transfer learning to produce a suitable machine learning model that could accurately identify areas of interest in experimental data. A combination of experimental and synthetic data were used to train the model. Using DISVT and our machine learning-assisted image analysis platform, we determined the fractions of EpCAM-positive EVs and CD24-positive EVs over captured plasma EVs with CD81 marker in the blood plasma of pilot HER2-positive breast cancer patients and compared to those from healthy donors. The amount of both EpCAM-positive and CD24-positive EVs was found negligible for both healthy donors and Stage I patients. The amount of EpCAM-positive EVs (also CD81-positive) increased from 18% to 29% as the cancer progressed from Stage II to III. No significant increase was found with further progression to Stage IV. A similar trend was found for the CD24-positive EVs. Statistical analysis showed that both EpCAM and CD24 markers can detect HER2-positive breast cancer at Stages II, III, or IV. They can also differentiate individual cancer stages except those between Stage III and Stage IV. Due to the simplicity, high sensitivity, and high efficiency, the DISVT with the AI-assisted dual imaging analysis can be widely used for both basic research and clinical applications to quantitatively characterize molecularly targeted EV subtypes in biofluids.

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality in the first trimester. Using an untargeted metabolomic approach, we sought to identify putative plasma biomarkers using tandem liquid chromatography–mass spectrometry for the detection of tubal EP. This case-control study included the prospective recruitment of 50 tubal EP cases and 50 early intrauterine pregnancy controls. To avoid over-fitting, logistic regression models were developed in a randomly selected discovery group (30 cases vs. 30 controls) and validated in the test group (20 cases vs. 20 controls). In total, 585 mass spectral features were detected, of which 221 molecular features were significantly altered in EP plasma (p < 0.05). Molecular networking and metabolite identification was employed using the Global Natural Products Social Molecular Networking (GNPS) database, which identified 97 metabolites at a high confidence level. Top significant metabolites include subclasses of sphingolipids, carnitines, glycerophosphocholines, and tryptophan metabolism. The top regression model, consisting of D-erythro-sphingosine and oleoyl-carnitine, was validated in a test group and achieved an area under receiving operating curve (AUC) (95% CI) = 0.962 (0.910–1) with a sensitivity of 100% and specificity of 95.9%. Metabolite alterations indicate alterations related to inflammation and abnormal placentation in EP. The validation of these metabolite biomarkers in the future could potentially result in improved early diagnosis.

This laboratory experiment, using proton NMR spectroscopy to determine the dissociation constant for heterocyclic bases, has been modified from a previously described experiment. A solution of a substituted pyridine is prepared using deuterium oxide (D[subscript 2]O) as the solvent. The pH of the solution is adjusted and proton NMR spectra are collected for a variety of pH values. The chemical shifts of the peaks in the NMR spectrum change depending on the degree of protonation of the pyridine ring. Analysis of the spectral data is used to calculate the dissociation constant of the substituted pyridine. This experiment is suitable for a variety of advanced chemistry laboratories including analytical chemistry and instrumental analysis. (Contains 1 table and 2 figures.)

Nitrogen cycling in pasture soils differing in drainage characteristics and fertilization legacy needs more research to determine efficient nutrient management strategies. This study compared differences in nitrate (NO3−), ammonium (NH4+), inorganic N (IN = NO3− + NH4+), potentially mineralizable nitrogen (PMN), loss-on-ignition carbon (C), and soil pH in 10, 0.7 ha pastures in Eatonton, Georgia, historically fertilized with the same amount of N as either broiler litter (BL; >15 years, 6 pastures) or mineral fertilizer (Min; 4 pastures). We sampled to 90 cm (0–5, 5–10, 10–20, 20–40, 40–60, and 60–90 cm) on a 20 m grid. An analysis of variance indicated that below 5 cm BL pastures had significantly greater amounts of NO3−, IN, PMN, and soil pH compared to Min pastures. Comparisons of drainage classes (well drained~WD, moderately well drained~MWD, and somewhat-poorly drained~SPD) for each BL and Min were analyzed using linear regression for C:IN, C:PMN, pH: NO3−, and pH: NH4+ with all depths combined. In MWD soils, BL had 0.1 and 0.2 mg N kg−1 greater PMN and IN, respectively, for each unit increase in C. In WD soils NO3− decreased in BL by 7.4 and in Min by 12.1 mg N kg−1, while in MWD soils, this level decreased in BL by 7.8 and in Min by 4.5 mg N kg−1 for each pH unit. Five years after N fertilization stopped, BL soils have retained more inorganic N but are losing more NO3− at a greater rate in the MWD soils when all depths are considered. These losses are a combination of plant uptake, emissions, runoff and leaching. While more research is needed, these results strongly suggest the need to design N fertilization practices with drainage class and fertilization legacy in mind to improve N-use efficiency.

Mammalian polyamines, including putrescine, spermidine, and spermine, are positively charged amines that are essential for all living cells including neoplastic cells. An increasing understanding of polyamine metabolism, its molecular functions, and its role in cancer has led to the interest in targeting polyamine metabolism as an anticancer strategy, as the metabolism of polyamines is frequently dysregulated in neoplastic disease. In addition, due to compensatory mechanisms, combination therapies are clinically more promising, as agents can work synergistically to achieve an effect beyond that of each strategy as a single agent. In this article, the nature of polyamines, their association with carcinogenesis, and the potential use of targeting polyamine metabolism in treating and preventing cancer as well as combination therapies are described. The goal is to review the latest strategies for targeting polyamine metabolism, highlighting new avenues for exploiting aberrant polyamine homeostasis for anticancer therapy and the mechanisms behind them.

Despite the well-known relevance of polyamines to many forms of life, little is known about how polyamines regulate osteogenesis and skeletal homeostasis. Here, we report a series of in vitro studies conducted with human-bone-marrow-derived pluripotent stromal cells (MSCs). First, we show that during osteogenic differentiation, mRNA levels of most polyamine-associated enzymes are relatively constant, except for the catabolic enzyme spermidine/spermine N1-acetyltransferase 1 (SAT1), which is strongly increased at both mRNA and protein levels. As a result, the intracellular spermidine to spermine ratio is significantly reduced during the early stages of osteoblastogenesis. Supplementation of cells with exogenous spermidine or spermine decreases matrix mineralization in a dose-dependent manner. Employing N-cyclohexyl-1,3-propanediamine (CDAP) to chemically inhibit spermine synthase (SMS), the enzyme catalyzing conversion of spermidine into spermine, also suppresses mineralization. Intriguingly, this reduced mineralization is rescued with DFMO, an inhibitor of the upstream polyamine enzyme ornithine decarboxylase (ODC1). Similarly, high concentrations of CDAP cause cytoplasmic vacuolization and alter mitochondrial function, which are also reversible with the addition of DFMO. Altogether, these studies suggest that excess polyamines, especially spermidine, negatively affect hydroxyapatite synthesis of primary MSCs, whereas inhibition of polyamine synthesis with DFMO rescues most, but not all of these defects. These findings are relevant for patients with Snyder–Robinson syndrome (SRS), as the presenting skeletal defects—associated with SMS deficiency—could potentially be ameliorated by treatment with DFMO.

An accurate petrophysical model of the subsurface is essential for resource development and CO2 sequestration. We present a new workflow that provides a high-resolution estimate of petrophysical reservoir properties using seismic data with rock physics modeling and machine-learning techniques (i.e., deep learning neural networks). First, we compare the sequential prediction of the following petrophysical attributes: mineralogy, porosity, and fluid saturation, with the simultaneous prediction of all of the properties using the Volve field in the Norwegian North Sea as an example. The workflow shows that the sequential prediction produces a more efficient and accurate classification of petrophysical properties (the RMS error between the predicted and the original seismic trace is 50% smaller for the sequential compared to the simultaneous procedure). Next, the seismic amplitude response of the reservoirs was studied using rock physics modeling and amplitude versus offset (AVO) analysis to distinguish the different lithologies and fluid types. To ascertain the optimal hydrocarbon production areas, we performed Bayesian seismic inversion and applied machine learning to estimate the petrophysical properties. We examined how porosity, Vclay, and fluid variations affect the elastic properties. In Poisson’s ratio versus the P-wave impedance domain, a 10% porosity increase decreases the acoustic impedance (AI) by 30%, while a 20% Vclay decrease increases the AI by 12%. The Utsira Formation in the Volve field (5 km north of the Sleipner Øst field) was evaluated as a potential CO2 geological storage unit using Gassmann fluid substitution and seismic modeling. We look to assess the elastic property variation caused by CO2 saturation changes for monitoring purposes and simulate the effect. In the first 10% CO2 substitution, the P-wave velocity decrease is 12%, a subtle effect is observed for higher CO2 saturation values, and S-wave velocity (Vs) increases with CO2 saturation. Our analysis aspires to assist future reservoir studies and CO2 sequestration in similar fields.

Pattern recognition receptors (PRRs) recognize danger signals such as PAMPs/MAMPs and DAMPs to initiate a protective immune response. TLRs, NLRs, CLRs, and RLRs are well-characterized PRRs of the host immune system. cGLRs have been recently identified as PRRs. In humans, the cGAS/STING signaling pathway is a part of cGLRs. cGAS recognizes cytosolic dsDNA as a PAMP or DAMP to initiate the STING-dependent immune response comprising type 1 IFN release, NF-κB activation, autophagy, and cellular senescence. The present article discusses the emergence of cGLRs as critical PRRs and how they regulate immune responses. We examined the role of cGAS/STING signaling, a well-studied cGLR system, in the activation of the immune system. The following sections discuss the role of cGAS/STING dysregulation in disease and how immune cross-talk with other PRRs maintains immune homeostasis. This understanding will lead to the design of better vaccines and immunotherapeutics for various diseases, including infections, autoimmunity, and cancers.

Hepatoblastoma is the most common primary pediatric liver tumor. Children with pulmonary metastases at diagnosis experience survival rates as low as 25%. We have shown PIM kinases play a role in hepatoblastoma tumorigenesis. In this study, we assessed the role of PIM kinases in metastatic hepatoblastoma. We employed the metastatic hepatoblastoma cell line, HLM_2. PIM kinase inhibition was attained using PIM3 siRNA and the pan-PIM inhibitor, AZD1208. Effects of PIM inhibition on proliferation were evaluated via growth curve. Flow cytometry determined changes in cell cycle. AlamarBlue assay assessed effects of PIM kinase inhibition and cisplatin treatment on viability. The lethal dose 50% (LD50) of each drug and combination indices (CI) were calculated and isobolograms constructed to determine synergy. PIM kinase inhibition resulted in decreased HLM_2 proliferation, likely through cell cycle arrest mediated by p21. Combination therapy with AZD1208 and cisplatin resulted in synergy, potentially through downregulation of the ataxia-telangiectasia mutated (ATM) kinase DNA damage response pathway. When assessing the combined effects of pharmacologic PIM kinase inhibition with cisplatin on HLM_2 cells, we found the agents to be synergistic, potentially through inhibition of the ATM pathway. These findings support further exploration of PIM kinase inhibition as a therapeutic strategy for metastatic hepatoblastoma.

Argues that deficits in basic arithmetic make it difficult for students to continue in mathematics and succeed in subjects such as chemistry and physics. Focuses on the state of the basic arithmetic skills of inner-city students. (DDR)

Cyclic voltammetry is an important component of the undergraduate chemical curriculum. Unfortunately, undergraduate students rarely have the opportunity to conduct experiments in cyclic voltammetry owing to the high cost of potentiostats, which are required to control these experiments. By using MicroLab data acquisition interfaces in conjunction with Pine Research Instrumentation screen-printed electrodes, it is possible to conduct experiments in cyclic voltammetry for a fraction of the traditional cost. Thus, by using the Pine-MicroLab interface, experiments in cyclic voltammetry can become more accessible to undergraduate chemistry students. (Contains 2 figures and 3 notes.)

Postural instability and the inability to regain balance during slip-induced events are the leading causes of falls on the same level in occupational environments. Virtual reality (VR) provides the potential to be immersed in a realistic environment, exposing themselves to fall-risk hazards without the risk of injury real-world exposure may cause. Therefore, the purpose of this study was to compare the lower extremity joint kinematics of the slipping leg during real and virtually generated slip hazards. A secondary purpose was to investigate dynamic postural stability following acute exposure to real (REAL) and virtual (VR) environmental conditions. A total of 14 healthy participants’ (7 men, 7 women; age: 23.46 ± 3.31 years; height: 173.85 ± 8.48 cm; mass: 82.19 ± 11.41 kg; shoe size (men’s): 9.03 ± 2.71) knee and ankle joint kinematics were compared during exposure to both REAL and VR environments. Participants then completed a series of Timed Up-and-Go (TUG) variations (standard, cognitive, manual) at the beginning and the end of exposure to each environment. TUG-C involved backwards counting and TUG-M involved walking with an anterior load. Environmental exposure was selected in a counterbalanced order to prevent an order effect. Knee and ankle joint kinematics were analyzed separately using a 2 × 3 repeated measure ANOVA to compare environments as well as gait types at an alpha level of 0.05. TUG variations were also analyzed separately using a 3 × 3 repeated-measures ANOVA to compare TUG variations and environment. No significant differences were observed for knee or ankle joint kinematics between environments or gait types. There were also no significant interactions between environments and gait types. However, significant differences were observed for TUG-C following VR environmental conditions (p = 0.027). Post hoc comparisons revealed significantly lower times for TUG-C following VR exposure (p = 0.029). No significance was observed for TUG-S or TUG-M. Current findings suggest the potential effectiveness of VR as a means of fall prevention training for occupational populations based on improved TUG-C and similar lower extremity joint kinematics in REAL and VR conditions.

In this work, a computational spectroscopy approach was used to provide a complete assignment of the inelastic neutron scattering spectra of three title alkoxysilane derivatives—3-aminopropyltrimethoxysilane (APTS), N-methyl-3-aminopropyltrimethoxysilane (MAPTS), and 3-aminopropyltriethoxysilane (APTES). The simulated spectra obtained from density functional theory (DFT) calculations exhibit a remarkable match with the experimental spectra. The description of the experimental band profiles improves as the number of molecules considered in the theoretical model increases, from monomers to trimers. This highlights the significance of incorporating non-covalent interactions, encompassing classical NH···N, N–H···O, as well as C–H···N and C–H···O hydrogen bond contacts, to achieve a comprehensive understanding of the system. A distinct scenario emerges when considering optical vibrational techniques, infrared and Raman spectroscopy. In these instances, the monomer model provides a reasonable description of the experimental spectra, and no substantial alterations are observed in the simulated spectra when employing dimer and trimer models. This observation underscores the distinctive ability of neutron spectroscopy in combination with DFT calculations in assessing the structure and dynamics of molecular materials.

For coagulation to be initiated, anticoagulant glycosaminoglycans (GAGs) such as heparins need to be neutralised to allow fibrin clot formation. Platelet activation triggers the release of several proteins that bind GAGs, including histidine-rich glycoprotein (HRG), fibrinogen, and fibronectin. Zn2+ ions are also released and have been shown to enhance the binding of HRG to heparins of a high molecular weight (HMWH) but not to those of low molecular weight (LMWH). The effect of Zn2+ on fibrinogen and fibronectin binding to GAGs is unknown. Here, chromogenic assays were used to measure the anti-factor Xa and anti-thrombin activities of heparins of different molecular weights and to assess the effects of HRG, fibrinogen, fibronectin, and Zn2+. Surface plasmon resonance was also used to examine the influence of Zn2+ on the binding of fibrinogen to heparins of different molecular weights. Zn2+ had no effect on the neutralisation of anti-factor Xa (FXa) or anti-thrombin activities of heparin by fibronectin, whereas it enhanced the neutralisation of unfractionated heparin (UFH) and HMWH by both fibrinogen and HRG. Zn2+ also increased neutralisation of the anti-FXa activity of LMWH by fibrinogen but not HRG. SPR showed that Zn2+ increased fibrinogen binding to both UFH and LMWH in a concentration-dependent manner. The presented results reveal that an increase in Zn2+ concentration has differential effects upon anticoagulant GAG neutralisation by HRG and fibrinogen, with implications for modulating anti-coagulant activity in plasma.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder and has complicated pathobiology, leading to irreversible memory loss and severe cognitive dysfunction. For patients with AD, the advent of the disease usually occurs after years of pathological changes. The early diagnosis and monitoring of AD are of great significance as the early-stage intervention and treatment may be the most effective. Biomarkers, such as beta-amyloid and tau levels in cerebrospinal fluid (CSF) and brain, offer one of the most promising paths and are combined with neuroimaging and immunological detection for AD diagnosis. However, high expense and radiation of neuroimaging and low sensitivity of immunosorbent assay limited their applications. Meanwhile, the relevance of Aβ peptides and tau proteins to the development of AD remains highly debatable, meaning that detecting one specific biomarker holds limited prospects in achieving early and accurate detection of AD. Optical sensor arrays based on pattern recognition enable the discrimination of multiple analytes in complicated environments and are thus highly advantageous for the detection of AD with multi-biomarkers. In this review, we survey the recent advances of optical sensor arrays for the diagnosis of AD, as well as the remaining challenges.

Evaluation of patients with acute kidney injury requires comprehensive assessment that includes a urinalysis, which features both semi-quantitative assessment with a urine dipstick and urine microscopy. This process is labor intensive for clinical laboratories, and availability of excellent automated instruments for urinalysis has prompted utilization and acceptance of this strategy by both by laboratories and clinicians. Recently, however, interest in provider performed microscopy has enjoyed a renaissance thanks to both improved microscopy techniques and the endorsement from social media in nephrology. Here, we present two cases of acute kidney injury in which manual microscopy added valuable information to the automated microscopy.