Clinical assessment of computed tomography for detecting ingested blister packs: A single-center retrospective study.

Objectives: Blister pack (BP) ingestion poses serious risks, such as gastrointestinal perforation, and accurate localization by computed tomography (CT) is a common practice. However, while it has been reported in vitro that CT visibility varies with the material type of BPs, there have been no reports on this variability in clinical settings. In this study, we investigated the CT detection rates of different BPs in clinical settings. Methods: This single-center retrospective study from 2010 to 2022 included patients who underwent endoscopic foreign body removal for BP ingestion. The patients were categorized into two groups for BP components, the polypropylene (PP) and the polyvinyl chloride (PVC)/polyvinylidene chloride (PVDC) groups. The primary outcome was the comparison of CT detection rates between the groups. We also evaluated whether the BPs contained tablets and analyzed their locations. Results: This study included 61 patients (15 in the PP group and 46 in the PVC/PVDC group). Detection rates were 97.8% for the PVC/PVDC group compared to 53.3% for the PP group, a significant difference (p < 0.01). No cases of BPs composed solely of PP were detected by CT. Blister packs were most commonly found in the upper thoracic esophagus. Conclusions: Even in a clinical setting, the detection rates of PVC and PVDC were higher than that of PP alone. Identifying PP without tablets has proven challenging in clinical. Considering the risk of perforation, these findings suggest that esophagogastroduodenoscopy may be necessary, even if CT detection is negative.

Synthesis and Application of Titanium Carbide (Ti3C2)-Cobalt Sulfide (Co3S4) Nanocomposites in Amino Acid Biosensing.

Background The fabrication of titanium carbide (Ti3C2)-cobalt sulfide (Co3S4)-based biosensors with high sensitivity and selectivity can change the biosensor manufacturing industry completely. Molecular and clinical diagnostics, disease progression monitoring, and drug discovery could utilize these sensors for early biomarker detection. MXene (Ti3C2) is a two-dimensional material with exceptional electrical conductivity, hydrophilicity, great thermal stability, large interlayer spacing, and a high surface area. Ti3C2's remarkable characteristics make it well-suited for biomolecule immobilization and target analyte detection. Co3S4 is a transition metal chalcogenide that has shown great potential in biosensors. Co3S4 nanoparticles (NPs) can potentially enhance Ti3C2 electrocatalytic activity, particularly in amino acid detection. L-arginine is a semi-essential amino acid, and the body frequently uses it to support healthy circulation and plays a crucial role in protein synthesis. We fabricated the Ti3C2-Co3S4 biosensor for L-arginine detection. Aim  This study aims to synthesize and apply Ti3C2-Co3S4 nanocomposites in amino acid biosensing. Materials and methods The Ti3C2 nanosheets were synthesized by the selective removal of an aluminum (Al) layer from the precursor (Ti3AlC2) using hydrofluoric acid (HF). The resulting mixture serves as an etchant, especially targeting the Al layers on Ti3AlC2 while protecting the desired MXene layers at room temperature. Cobalt nitrate hexahydrate was dissolved in deionized water. Sodium hydroxide was added to the cobalt solution and stirred. Thioacetamide was added to the above solution and stirred (Solution B). A mixture of Solution A and Solution B was stirred for 30 minutes. The mixture is transferred to a hydrothermal reactor and maintained at a temperature of 180°C for 12 hours. Once the reaction completes, we cool the resultant mixture to room temperature and then filter it using the washing technique. The sample underwent a 12-hour drying process at 80°C.  Results  This study investigated the use of a biosensor that employed Ti3C2-Co3S4 NPs to detect the concentration of L-arginine. The X-ray diffraction (XRD) shows clear and distinct peaks, which means that the synthesized Ti3C2-Co3S4 nanostructures have a crystalline structure. Scanning electron microscopy (SEM) analysis revealed that the sheetlike structure of synthesized Ti3C2-Co3S4 nanostructures revealed the crystalline morphology. The results of this study show that the Ti3C2-Co3S4 NP-based biosensor can be used to detect L-arginine in a sensitive and selective way. Conclusion  This study investigated the synthesis of Ti3C2-Co3S4 NPs and their ability to detect L-arginine levels and show a distinct correlation between the L-arginine concentration and the fluorescence intensity, demonstrating the biosensor's effectiveness in detecting L-arginine levels.

Web-CONEXS: an inroad to theoretical X-ray absorption spectroscopy.

Accurate analysis of the rich information contained within X-ray spectra usually calls for detailed electronic structure theory simulations. However, density functional theory (DFT), time-dependent DFT and many-body perturbation theory calculations increasingly require the use of advanced codes running on high-performance computing (HPC) facilities. Consequently, many researchers who would like to augment their experimental work with such simulations are hampered by the compounding of nontrivial knowledge requirements, specialist training and significant time investment. To this end, we present Web-CONEXS, an intuitive graphical web application for democratizing electronic structure theory simulations. Web-CONEXS generates and submits simulation workflows for theoretical X-ray absorption and X-ray emission spectroscopy to a remote computing cluster. In the present form, Web-CONEXS interfaces with three software packages: ORCA, FDMNES and Quantum ESPRESSO, and an extensive materials database courtesy of the Materials Project API. These software packages have been selected to model diverse materials and properties. Web-CONEXS has been conceived with the novice user in mind; job submission is limited to a subset of simulation parameters. This ensures that much of the simulation complexity is lifted and preliminary theoretical results are generated faster. Web-CONEXS can be leveraged to support beam time proposals and serve as a platform for preliminary analysis of experimental data.

Synthesis, structure, spectral and luminescence studies of novel guanidinium aryl(oxy)(sulfanyl)(sulfonyl)acetates.

A series of promising luminescent materials, nonlinear optical crystals, and physiologically active compounds - aryl(oxy)(sulfanyl)(sulfonyl)acetates of guanidine (A) of unknown type was synthesized. Various functional groups present in (A) were identified using FTIR spectroscopy. 1H and 13C NMR spectral studies further confirm the molecular structure (A). Crystals of guanidinium 4-chlorophenyl(sulfanyl)acetate (1) and guanidinium 4-chlorophenyl(sulfonyl)acetate (2) were successfully grown. They belong to the same lowest symmetry category, but to different crystal systems: monoclinic (1) and orthorhombic (2). It has been established that intrinsic optical absorption begins at a wavelength of âˆ¼ 290 nm for crystalline compound (1) and âˆ¼ 335 nm for crystal (2). The intrinsic luminescence spectrum of crystal (1) includes two bands with maxima at 300 and 515 nm. In the intrinsic luminescence spectrum of crystal (2), only one band is observed with a maximum at 350 nm. Such luminescence in both crystals is excited in the intrinsic absorption bands, as well as by X-ray radiation. In addition, in the near ultraviolet and throughout the visible region, where optical absorption is not detected (it is very weak), low-inertia (less than 10 ns) rather intense luminescence of uncontrolled impurity-defect centers is excited. The spectral bands of optical absorption, photo- and X-ray luminescence discovered in experiments were systematized using a diagram of energy levels and quantum transitions in crystals and defect centers of the compounds under study.

Generalizable diagnosis of chest radiographs through attention-guided decomposition of images utilizing self-consistency loss.

BACKGROUND: Chest X-ray (CXR) is one of the most commonly performed imaging tests worldwide. Due to its wide usage, there is a growing need for automated and generalizable methods to accurately diagnose these images. Traditional methods for chest X-ray analysis often struggle with generalization across diverse datasets due to variations in imaging protocols, patient demographics, and the presence of overlapping anatomical structures. Therefore, there is a significant demand for advanced diagnostic tools that can consistently identify abnormalities across different patient populations and imaging settings. We propose a method that can provide a generalizable diagnosis of chest X-ray. METHOD: Our method utilizes an attention-guided decomposer network (ADSC) to extract disease maps from chest X-ray images. The ADSC employs one encoder and multiple decoders, incorporating a novel self-consistency loss to ensure consistent functionality across its modules. The attention-guided encoder captures salient features of abnormalities, while three distinct decoders generate a normal synthesized image, a disease map, and a reconstructed input image, respectively. A discriminator differentiates the real and the synthesized normal chest X-rays, enhancing the quality of generated images. The disease map along with the original chest X-ray image are fed to a DenseNet-121 classifier modified for multi-class classification of the input X-ray. RESULTS: Experimental results on multiple publicly available datasets demonstrate the effectiveness of our approach. For multi-class classification, we achieve up to a 3% improvement in AUROC score for certain abnormalities compared to the existing methods. For binary classification (normal versus abnormal), our method surpasses existing approaches across various datasets. In terms of generalizability, we train our model on one dataset and tested it on multiple datasets. The standard deviation of AUROC scores for different test datasets is calculated to measure the variability of performance across datasets. Our model exhibits superior generalization across datasets from diverse sources. CONCLUSIONS: Our model shows promising results for the generalizable diagnosis of chest X-rays. The impacts of using the attention mechanism and the self-consistency loss in our method are evident from the results. In the future, we plan to incorporate Explainable AI techniques to provide explanations for model decisions. Additionally, we aim to design data augmentation techniques to reduce class imbalance in our model.

Methodological evaluation of systematic reviews based on the use of artificial intelligence systems in chest radiography.

INTRODUCTION: In recent years, systems that use artificial intelligence (AI) in medical imaging have been developed, such as the interpretation of chest X-ray to rule out pathology. This has produced an increase in systematic reviews (SR) published on this topic. This article aims to evaluate the methodological quality of SRs that use AI for the diagnosis of thoracic pathology by simple chest X-ray. MATERIAL AND METHODS: SRs evaluating the use of AI systems for the automatic reading of chest X-ray were selected. Searches were conducted (from inception to May 2022): PubMed, EMBASE, and the Cochrane Database of Systematic Reviews. Two investigators selected the reviews. From each SR, general, methodological and transparency characteristics were extracted. The PRISMA statement for diagnostic tests (PRISMA-DTA) and AMSTAR-2 were used. A narrative synthesis of the evidence was performed. Protocol registry: Open Science Framework: https://osf.io/4b6u2/. RESULTS: After applying the inclusion and exclusion criteria, 7 SRs were selected (mean of 36 included studies per review). All the included SRs evaluated "deep learning" systems in which chest X-ray was used for the diagnosis of infectious diseases. Only 2 (29%) SRs indicated the existence of a review protocol. None of the SRs specified the design of the included studies or provided a list of excluded studies with their justification. Six (86%) SRs mentioned the use of PRISMA or one of its extensions. The risk of bias assessment was performed in 4 (57%) SRs. One (14%) SR included studies with some validation of AI techniques. Five (71%) SRs presented results in favour of the diagnostic capacity of the intervention. All SRs were rated "critically low" following AMSTAR-2 criteria. CONCLUSIONS: The methodological quality of SRs that use AI systems in chest radiography can be improved. The lack of compliance in some items of the tools used means that the SRs published in this field must be interpreted with caution.

Imaging findings of the postoperative chest: What the radiologist should know.

Thoracic surgical procedures are increasing in recent years, and there are different types of lung resections. Postsurgical complications vary depending on the type of resection and the time elapsed, with imaging techniques being key in the postoperative follow-up. Multidisciplinary management of these patients throughout the perioperative period is essential to ensure an optimal surgical outcome. This pictorial review will review the different thoracic surgical techniques, normal postoperative findings and postsurgical complications.

Direct Identification of O─O Bond Formation Through Three-Step Oxidation During Water Splitting by Operando Soft X-ray Absorption Spectroscopy.

Anionic redox allows the direct formation of O─O bonds from lattice oxygens and provides higher catalytic in the oxygen evolution reaction (OER) than does the conventional metal ion mechanism. While previous theories have predicted and experiments have suggested the possible O─O bond, it has not yet been directly observed in the OER process. In this study, operando soft X-ray absorption spectroscopy (sXAS) at the O K-edge and the operando Raman spectra is performed on layered double CoFe hydroxides (LDHs) after intercalation with [Cr(C2O4)3]3-, and revealed a three-step oxidation process, staring from Co2+ to Co3+, further to Co4+ (3d6L), and ultimately leading to the formation of O─O bonds and O2 evolution above a threshold voltage (1.4 V). In contrast, a gradual oxidation of Fe is observed in CoFe LDHs. The OER activity exhibits a significant enhancement, with the overpotential decreasing from 300 to 248 mV at 10 mA cm-2, following the intercalation of [Cr(C2O4)3]3- into CoFe LDHs, underscoring a crucial role of anionic redox in facilitating water splitting.

Multi-axial Self-driven X-ray Detection by a Two-dimensional Biaxial Hybrid Organic-Inorganic Perovskite Ferroelectric.

Metal halide perovskite ferroelectrics combining spontaneous polarization and excellent semiconducting properties is an ideal platform for enabling self-driven X-ray detection, however, achievements to date have been only based on uniaxiality, which increases the complexity of device fabrication. Multi-axial ferroelectric materials have multiple equivalent polarization directions, making them potentially amenable to multi-axial self-driven X-ray detection, but the report on these types of materials is still a huge blank. Herein, a high-quality (BA)2(EA)2Pb3I10 (1) biaxial ferroelectric single crystal was successfully grown, which exhibited significant spontaneous polarization along the c-axis and b-axis. Under X-ray irradiation, bulk photovoltaic effect (BPVE) was exhibited along both the c-axis and b-axis, with open circuit voltages (Voc) of 0.23 V and 0.22 V, respectively. Then, the BPVE revealed along the inversion of polarized direction with the polarized electric fields. Intriguingly, due to the BPVE of 1, 1 achieved multi-axial self-driven X-ray detection for the first time (c-axis and b-axis) with relatively high sensitivities and ultralow detection limits (17.2 nGyair s-1 and 19.4 nGyair s-1, respectively). This work provides a reference for the subsequent use of multi-axial ferroelectricity for multi-axial self-driven optoelectronic detection.

Bridging length scales in hard materials with ultra-small angle X-ray scattering - a critical review.

Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for in situ characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.

Bactericidal human monoclonal antibody 1B1 shows specificity for meningococcal factor H binding protein variant 2 and displaces human factor H.

Thousands of disease cases and hundreds of deaths occur globally each year due to invasive meningococcal disease. Neisseria meningitidis serogroup B (MenB) is the leading cause of such disease in developed countries. Two vaccines, 4CMenB and MenB-fHbp, that protect against MenB are available and include one or two forms respectively of factor H binding protein (fHbp), a key protective antigen. Studies of circulating meningococci have identified over 1380 different fHbp amino acid sequences, which form three immunologically distinct clusters, termed variants 1, 2, and 3. Neither of the current vaccines contains a variant 2 antigen, which is less well characterized than fHbp variants 1 and 3. We characterized the interaction of fHbp variant 2 with humAb 1B1 using biochemical methods and live meningococcal assays. Further, we determined the crystal structure of the complex at 2.4 Å resolution, clearly revealing the epitope and providing the first detailed report of an antibody with distinct specificity for fHbp variant 2. Extensive mutagenesis and binding studies elucidated key hotspots in the interface. This combination of structural and functional studies provides a molecular explanation for the bactericidal potency and specificity of humAb 1B1 for fHbp variant 2. Our studies, focused on fHbp variant 2, expand the understanding of this previously under characterized group of the vast family of variants of fHbp, a virulence factor present on all meningococci. Moreover, the definition of a protective conformational epitope on fHbp variant 2 may support the design and development of novel variant 2-containing MenB vaccines affording greater breadth of protection.

Increased lung field permeability in young patients.

When the chest radiograph of a young patient shows lung hyperlucency, it is important to obtain a detailed clinical history of any previous episodes of childhood infection. Previous chest radiographs should be reviewed to determine whether the condition is congenital or acquired, and thus assist in a diagnosis of SJMS.

Correcting angular distortions in Bragg coherent X-ray diffraction imaging.

Bragg coherent X-ray diffraction imaging (BCDI) has emerged as a powerful technique for strain imaging and morphology reconstruction of nanometre-scale crystals. However, BCDI often suffers from angular distortions that appear during data acquisition, caused by radiation pressure, heating or imperfect scanning stages. This limits the applicability of BCDI, in particular for small crystals and high-flux X-ray beams. Here, we present a pre-processing algorithm that recovers the 3D datasets from the BCDI dataset measured under the impact of large angular distortions. We systematically investigate the performance of this method for different levels of distortion and find that the algorithm recovers the correct angles for distortions up to 16.4× (1640%) the angular step size dθ = 0.004°. We also show that the angles in a continuous scan can be recovered with high accuracy. As expected, the correction provides marked improvements in the subsequent phase retrieval.

A 3D and Explainable Artificial Intelligence Model for Evaluation of Chronic Otitis Media Based on Temporal Bone Computed Tomography: Model Development, Validation, and Clinical Application.

BACKGROUND: Temporal bone computed tomography (CT) helps diagnose chronic otitis media (COM). However, its interpretation requires training and expertise. Artificial intelligence (AI) can help clinicians evaluate COM through CT scans, but existing models lack transparency and may not fully leverage multidimensional diagnostic information. OBJECTIVE: We aimed to develop an explainable AI system based on 3D convolutional neural networks (CNNs) for automatic CT-based evaluation of COM. METHODS: Temporal bone CT scans were retrospectively obtained from patients operated for COM between December 2015 and July 2021 at 2 independent institutes. A region of interest encompassing the middle ear was automatically segmented, and 3D CNNs were subsequently trained to identify pathological ears and cholesteatoma. An ablation study was performed to refine model architecture. Benchmark tests were conducted against a baseline 2D model and 7 clinical experts. Model performance was measured through cross-validation and external validation. Heat maps, generated using Gradient-Weighted Class Activation Mapping, were used to highlight critical decision-making regions. Finally, the AI system was assessed with a prospective cohort to aid clinicians in preoperative COM assessment. RESULTS: Internal and external data sets contained 1661 and 108 patients (3153 and 211 eligible ears), respectively. The 3D model exhibited decent performance with mean areas under the receiver operating characteristic curves of 0.96 (SD 0.01) and 0.93 (SD 0.01), and mean accuracies of 0.878 (SD 0.017) and 0.843 (SD 0.015), respectively, for detecting pathological ears on the 2 data sets. Similar outcomes were observed for cholesteatoma identification (mean area under the receiver operating characteristic curve 0.85, SD 0.03 and 0.83, SD 0.05; mean accuracies 0.783, SD 0.04 and 0.813, SD 0.033, respectively). The proposed 3D model achieved a commendable balance between performance and network size relative to alternative models. It significantly outperformed the 2D approach in detecting COM (P≤.05) and exhibited a substantial gain in identifying cholesteatoma (P<.001). The model also demonstrated superior diagnostic capabilities over resident fellows and the attending otologist (P<.05), rivaling all senior clinicians in both tasks. The generated heat maps properly highlighted the middle ear and mastoid regions, aligning with human knowledge in interpreting temporal bone CT. The resulting AI system achieved an accuracy of 81.8% in generating preoperative diagnoses for 121 patients and contributed to clinical decision-making in 90.1% cases. CONCLUSIONS: We present a 3D CNN model trained to detect pathological changes and identify cholesteatoma via temporal bone CT scans. In both tasks, this model significantly outperforms the baseline 2D approach, achieving levels comparable with or surpassing those of human experts. The model also exhibits decent generalizability and enhanced comprehensibility. This AI system facilitates automatic COM assessment and shows promising viability in real-world clinical settings. These findings underscore AI's potential as a valuable aid for clinicians in COM evaluation. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000036300; https://www.chictr.org.cn/showprojEN.html?proj=58685.

Predicting lymphovascular invasion in N0 stage non-small cell lung cancer: A nomogram based on Dual-energy CT imaging and clinical findings.

PURPOSE: To construct a nomogram for predicting lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC) using dual-energy computed tomography (DECT) findings combined with clinical findings. METHODS: We retrospectively recruited 135 patients with N0 stage NSCLC from two hospitals underwent DECT before surgery and were divided into development cohort (n = 107) and validation cohort (n = 28). The clinical findings (baseline characteristics, biochemical markers, serum tumor markers and Immunohistochemical markers), DECT-derived parameters (iodine concentration [IC], effective atomic number [Eff-Z] and normalized iodine concentration [NIC], iodine enhancement [IE] and NIC ratio [NICr]) and Fractal dimension (FD) were collected and measured. A nomogram was constructed using significant findings to predict LVI in N0 stage NSCLC and was externally validated. RESULTS: Multivariable analysis revealed that lymphocyte count (LYMPH, odds ratio [OR]: 3.71, P=0.014), IC in arterial phase (ICa, OR: 1.25, P=0.021), NIC in venous phase (NICv, OR: 587.12, P=0.009) and FD (OR: 0.01, P=0.033) were independent significant factors for predicting LVI in N0 stage NSCLC, and were used to construct a nomogram. The nomogram exhibited robust predictive capabilities in both the development and validation cohort, with AUCs of 0.819 (95 % CI: 72.6-90.4) and 0.844 (95 % CI: 68.2-95.8), respectively. The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of positive LVI, on external validation. CONCLUSIONS: Combination of clinical and DECT imaging findings could aid in predicting LVI in N0 stage NSCLC using significant findings of LYMPH, ICa, NICv and FD.

Solution Synthesis and Light-Emitting Applications of One-Dimensional Lead-Free Cerium(III) Metal Halides.

Combining rare earth elements with the halide perovskite structure offers valuable insights into designing nonlead (Pb) luminescent materials. However, most of these compositions tend to form zero-dimensional (0D) networks of metal-halide polyhedra, with higher-dimensional (1D, 2D, and 3D) structures receiving relatively less exploration. Herein, we present synthesis and optical properties of Cs3CeCl6·3H2O, characterized by its unique 1D crystal structure. The conduction band minimum of Cs3CeCl6·3H2O becomes less localized as a result of the increased structural dimension, making it possible for the materials to achieve an efficient electrical injection. For both Cs3CeCl6·3H2O single crystals and nanocrystals, we also observed remarkable luminescence with near-unity photoluminescence quantum yield and exceptional phase stability. Cs3CeCl6·3H2O single crystals demonstrate an X-ray scintillation light yield of 31900 photons/MeV, higher than that of commercial LuAG:Ce (22000 photons/MeV); electrically driven light-emitting diodes fabricated with Cs3CeCl6·3H2O nanocrystals yield the characteristic emission of Ce3+, indicating their potential use in next-generation violet-light-emitting devices.

From Photography to Radiology: How Physicians Leveraged Early Hospital X-ray Machines to Supplant Photographers.

At the end of the nineteenth century, the advent of x-ray machines fueled American medicine's reliance on technology, transforming hospitals and the medical profession. X-ray manufacturers pursued the nascent hospital market as competition and patent feuds accelerated x-ray machine modifications. Hospitals incorporated clunky new machines and employed x-ray photographers, but as the unruly apparatus stabilized, physicians joining the new specialty of radiology discounted the toils of machine troubleshooting and promoted their medically qualified x-ray interpretations. This article frames early medical radiography in terms of boundary work, highlighting how discourse among physicians, x-ray photographers, and hospital administrators vied to establish a privileged demarcation between radiological science and photographic craft. Ultimately, radiologists supplanted x-ray photographers by leveraging the automation of x-ray machines and capitalizing on the epistemic shift from photographic objectivity to qualified interpretations. By focusing on this overlooked aspect of x-ray incorporation into hospitals, this work provides a unique perspective on how harnessing mechanization and authoritative medical interpretations can shift professional boundaries.

Radiological Features of Extramedullary Hematopoiesis in a Young Male With Beta-Thalassemia: A Case Report.

The formation of the blood elements and their maturation is called hematopoiesis. In adults, this typically takes place in the bone marrow of vertebrae, ribs, and long bones. In contrast, during fetal development, the primary sites of hematopoiesis are the spleen, liver, and the yolk sac. This process of hematopoiesis, when it occurs in sites other than the bone marrow, is called the extramedullary hematopoiesis (EMH). Extramedullary hematopoiesis usually happens in patients with blood disorders like sickle cell disease and thalassemia, where there is failure of hematopoiesis in the primary sites. Here, we present a young male with beta-thalassemia who presented with shortness of breath and palpitations for one month. This manuscript discusses the imaging findings of the EMH in our patient.

How Does the Powder Mixture of Ibuprofen and Caffeine Attenuate the Solubility of Ibuprofen? Comparative Study for the Xanthine Derivatives to Recognize Their Intermolecular Interactions Using Fourier-Transform Infrared (FTIR) Spectra, Differential Scanning Calorimetry (DSC), and X-ray Powder Diffractometry (XRPD).

Molecular interactions between active pharmaceutical ingredients (APIs) and xanthine (XAT) derivatives were analyzed using singular value decomposition (SVD). XAT derivatives were mixed with equimolar amounts of ibuprofen (IBP) and diclofenac (DCF), and their dissolution behaviors were measured using high-performance liquid chromatography. The solubility of IBP decreased in mixtures with caffeine (CFN) and theophylline (TPH), whereas that of DCF increased in mixtures with CFN and TPH. No significant differences were observed between the mixtures of theobromine (TBR) or XAT with IBP and DCF. Mixtures with various molar ratios were analyzed using differential scanning calorimetry, X-ray powder diffraction, and Fourier-transform infrared spectroscopy to further explore these interactions. The results were subjected to SVD. This analysis provides valuable insights into the differences in interaction strength and predicted interaction sites between XAT derivatives and APIs based on the combinations that form mixtures. The results also showed the impact of the XAT derivatives on the dissolution behavior of IBP and DCF. Although IBP and DCF were found to form intermolecular interactions with CFN and TPH, these effects resulted in a reduction of the solubility of IBP and an increase in the solubility of DCF. The current approach has the potential to predict various interactions that may occur in different combinations, thereby contributing to a better understanding of the impact of health supplements on pharmaceuticals.

On the feasibility of time-resolved X-ray powder diffraction of macromolecules using laser-driven ultrafast X-ray sources.

With the emergence of ultrafast X-ray sources, interest in following fast processes in small molecules and macromolecules has increased. Most of the current research into ultrafast structural dynamics of macromolecules uses X-ray free-electron lasers. In parallel, small-scale laboratory-based laser-driven ultrafast X-ray sources are emerging. Continuous development of these sources is underway, and as a result many exciting applications are being reported. However, because of their low flux, such sources are not commonly used to study the structural dynamics of macromolecules. This article examines the feasibility of time-resolved powder diffraction of macromolecular microcrystals using a laboratory-scale laser-driven ultrafast X-ray source.