A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.

BACKGROUND: This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study. Among them, 49 were in the early stage, and 124 were in the advanced stage. Patients were randomly categorized into training (n = 122) and test (n = 51) cohorts at a 7:3 ratio. Radiomics features were extracted from PEIs and 40-keV VMIs were reconstructed at both arterial and portal venous phases. Radiomics signatures were constructed based on both PEIs and 40-keV VMIs. A radiomics nomogram was developed by integrating the 40-keV VMI-based radiomics signature with selected clinical predictors. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA). RESULTS: The PEI-based radiomics signature demonstrated satisfactory diagnostic efficacy, with the areas under the ROC curves (AUCs) of 0.92 in both the training and test cohorts. The optimal radiomics signature was based on 40-keV VMIs, with AUCs of 0.96 and 0.94 in the training and test cohorts. The nomogram, which integrated a 40-keV VMI-based radiomics signature with two clinical parameters (tumour diameter and normalized iodine density at the portal venous phase), demonstrated promising calibration and discrimination in both the training and test cohorts (0.97 and 0.91, respectively). DCA indicated that the clinical-radiomics nomogram provided the most significant clinical benefit. CONCLUSIONS: The radiomics signature derived from 40-keV VMI and the clinical-radiomics nomogram based on DLCT both exhibited exceptional performance in distinguishing early from advanced stages in PDAC, aiding clinical decision-making for patients with this condition.

Association between life's essential 8 and frailty status among cancer survivors in the United States: a cross-sectional analysis.

BACKGROUND: Frailty not only affects disease survival but also impacts the long-term function and quality life of all adults diagnosed with and/or treated for cancer.The American Heart Association has introduced Life's Essential 8 (LE8) as a novel metric for assessing cardiovascular health. Currently, LE8's application in evaluating the frailty of cancer survivors remains unreported. This research seeks to explore the connection between LE8 scores and frailty levels in cancer survivors across the United States, thereby addressing a significant void in existing studies. METHODS: This study analyzed data from cancer survivors enrolled in the National Health and Nutrition Examination Surveys (NHANES) spanning the years 2005 to 2018, providing a comprehensive dataset. Multivariable logistic regression models were used to examine the linkage between LE8 rankings and frailty condition in cancer survivors. Furthermore, the study delved deeper into this correlation using restricted cubic spline (RCS) curves and subgroup analyses. RESULTS: In the fully adjusted model, an increased LE8 level was closely associated with a reduced odds ratio of frailty among cancer survivors, with an OR of 0.95 (95% CI: 0.94-0.96, p < 0.0001).This pattern persisted across different categorizations of LE8 into low, moderate, and high groups, demonstrating a consistent trend. The analysis revealed a non-linear relationship between LE8 scores and frailty status, further supporting a straightforward association (p-value for non-linearity = 0.0729). CONCLUSION: Studies have found that the higher the LE8 score, the less likely a cancer patient is to develop debilitating symptoms.This indicates that the LE8 scores may provide an opportunity for interventions aimed at improving the prognosis of cancer patients.

Magnolin inhibits intestinal epithelial cell apoptosis alleviating Crohn's disease-like colitis by suppressing the PI3K/AKT signalling pathway.

BACKGROUND AND AIMS: Previous reports have shown that preventing excessive intestinal epithelial cell (IEC) apoptosis is a crucial approach for protecting the intestinal barrier in patients with Crohn's disease (CD). Magnolin (MGL) has various biological activities, including antiapoptotic activities, but its role in CD has largely not been determined. This study investigated how MGL impacts CD-like colitis and the underlying mechanism involved. METHODS: Mice were treated with TNBS to establish a disease model, and these mice were used to assess the therapeutic effects of MGL on CD-like colitis. TNF-α-treated colon organoids were used to evaluate the impact of MGL on intestinal barrier function and IEC apoptosis. Enrichment analysis was performed to examine the potential pathways through which MGL inhibits IEC apoptosis. Finally, rescue experiments showed the mechanism by which MGL suppresses IEC apoptosis. RESULTS: The animal experiments demonstrated that MGL treatment alleviated the weight loss, colon shortening, elevated disease activity index (DAI) scores, increased colitis histological scores and upregulated inflammatory factor expression that were observed in model mice. MGL ameliorated intestinal barrier dysfunction and the loss of tight junction (TJ) proteins (ZO-1 and Claudin-1) by inhibiting IEC apoptosis in both TNBS-treated mice and TNF-α-treated colon organoids. MGL inhibited the PI3K/AKT signalling pathway, thus safeguarding the intestinal barrier and alleviating CD-like colitis in vivo and in vitro. CONCLUSIONS: MGL improves the intestinal barrier integrity and prevents CD-like colitis by inhibiting IEC apoptosis. The potential mechanism of its anti-apoptotic impact on IECs could be associated with the PI3K/AKT pathway, presenting novel approaches and avenues for the clinical management of CD.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.

Exploring the Localization of Siderophore-Mediated Cargo Delivery in Gram-Negative Bacteria Using 3-Hydroxypyridin-4(1H)-one-Fluorescein Probes.

The design of siderophore-antibiotic conjugates is a promising strategy to overcome drug resistance in negative bacteria. However, accumulating studies have shown that only those antibiotics acting on the cell wall or cell membrane multiply their antibacterial effects when coupled with siderophores, while antibiotics acting on targets in the cytoplasm of bacteria do not show an obvious enhancement of their antibacterial effects when coupled with siderophores. To explore the causes of this phenomenon, we synthesized several conjugate probes using 3-hydroxypyridin-4(1H)-ones as siderophores and replacing the antibiotic cargo with 5-carboxyfluorescein (5-FAM) or malachite green (MG) cargo. By monitoring changes in the fluorescence intensity of FAM conjugate 20 in bacteria, the translocation of the conjugate across the outer membranes of Gram-negative pathogens was confirmed. Further, the use of the fluorogen activating protein(FAP)/MG system revealed that 3-hydroxypyridin-4(1H)-one-MG conjugate 26 was ultimately distributed mainly in the periplasm rather than being translocated into the cytosol of Escherichia coli and Pseudomonas aeruginosa PAO1. Additional mechanistic studies suggested that the uptake of the conjugate involved the siderophore-dependent iron transport pathway and the 3-hydroxypyridin-4(1H)-ones siderophore receptor-dependent mechanism. Meanwhile, we demonstrated that the conjugation of 3-hydroxypyridin-4(1H)-ones to the fluorescein 5-FAM can reduce the possibility of the conjugates crossing the membrane layers of mammalian Vero cells by passive diffusion, and the advantages of the mono-3-hydroxypyridin-4(1H)-ones as a delivery vehicle in the design of conjugates compared to the tri-3-hydroxypyridin-4(1H)-ones. Overall, this work reveals the localization rules of 3-hydroxypyridin-4(1H)-ones as siderophores to deliver the cargo into Gram-negative bacteria. It provides a theoretical basis for the subsequent design of siderophore-antibiotic conjugates, especially based on 3-hydroxypyridin-4(1H)-ones as siderophores.

Combining anodic alcohol oxidative coupling for C-C bond formation with cathodic ammonia production.

Electrocatalytic oxidation of alcohols using heterogeneous catalysts is a promising aqueous, energy-efficient and environmentally friendly approach, especially for coupling different alcohols to prolong the carbon chain via co-oxidation. Precisely regulating critical steps to tailor electrode materials and electrolyte composition is key to selectively coupling alcohols for targeted synthesis. However, selectively coupling different alcohols remains challenging due to the lack of effective catalyst and electrolyte design promoting specific pathways. Herein, we demonstrate a paired electrolysis strategy for combining anodic oxidative coupling of ethanol (EtOH) and benzyl alcohol (PhCH2OH) to synthesize cinnamaldehyde (CAL) and cathodic ammonia production. The strategies involve: (i) utilizing the salt-out effect to balance selective oxidation and coupling rates; (ii) developing platinum-loaded nickel hydroxide electrocatalysts to accelerate intermediate coupling kinetics; (iii) introducing thermodynamically favorable nitrate reduction at the cathode to improve coupling selectivity by avoiding hydrogenation of products while generating valuable ammonia instead of hydrogen. We achieved 85% coupling selectivity and 278 µmol/h NH3 productive rate at 100 mA/cm2 with a low energy input (∼1.63 V). The membrane-free, low energy, scalable approach with a wide substrate scope highlights promising applications of this methodology. This work advances heterogeneous electrocatalytic synthesis through rational design principles that integrate anodic oxidative coupling with cathodic nitrate reduction reactions, having synergistic effects on efficiency and selectivity.

Association between PM2.5 constituents and cardiometabolic risk factors: exploring individual and combined effects, and mediating inflammation.

BACKGROUND: The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear. METHOD: A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively. RESULT: PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP. CONCLUSION: Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

Incorporation of Finasteride-Loaded Microspheres into Personalized Microneedle for Sustained Transdermal Delivery.

Although finasteride (FNS) tablets are considered the most effective drug for the treatment of androgenetic alopecia (AGA), their clinical applications are limited due to the associated side effects including decreased libido, breast enlargement, and liver dysfunction. In this study, we have developed a personalized microneedle (PMN) with a double-layer structure that incorporates FNS-loaded microspheres (MPs) to accommodate irregular skin surfaces. This design enables the sustained release of FNS, thereby reducing potential side effects. The needle body was synthesized with high-strength hyaluronic acid (HA) as the base material substrate. The backing layer utilized methacrylate gelatin (GelMA) with specific toughness, enabling PMN to penetrate the skin while adapting to various skin environments. The length of PMN needles (10 × 10) was approximately 600 µm, with the bottom of the needles measuring about 330 µm × 330 µm. The distance between adjacent tips was around 600 µm, allowing the drug to penetrate the stratum corneum of the skin. The results of the drug release investigation indicated the sustained and regulated release of FNS from PMN, as compared to that of pure FNS and FNS-MPs. Further, the cytotoxicity assay demonstrates that PMS displays good cytocompatibility. Altogether, this mode of administration has immense potential for the development of delivery of other drugs, as well as in the medical field.

UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation.

Owing to the success of transformer models, recent works study their applicability in 3D medical segmentation tasks. Within the transformer models, the self-attention mechanism is one of the main building blocks that strives to capture long-range dependencies, compared to the local convolutional-based design. However, the self-attention operation has quadratic complexity which proves to be a computational bottleneck, especially in volumetric medical imaging, where the inputs are 3D with numerous slices. In this paper, we propose a 3D medical image segmentation approach, named UNETR++, that offers both high-quality segmentation masks as well as efficiency in terms of parameters, compute cost, and inference speed. The core of our design is the introduction of a novel efficient paired attention (EPA) block that efficiently learns spatial and channel-wise discriminative features using a pair of inter-dependent branches based on spatial and channel attention. Our spatial attention formulation is efficient and has linear complexity with respect to the input. To enable communication between spatial and channel-focused branches, we share the weights of query and key mapping functions that provide a complimentary benefit (paired attention), while also reducing the complexity. Our extensive evaluations on five benchmarks, Synapse, BTCV, ACDC, BraTS, and Decathlon-Lung, reveal the effectiveness of our contributions in terms of both efficiency and accuracy. On Synapse, our UNETR++ sets a new state-of-the-art with a Dice Score of 87.2%, while significantly reducing parameters and FLOPs by over 71%, compared to the best method in the literature. Our code and models are available at: https://tinyurl.com/2p87x5xn.

Generation of a Human Induced Pluripotent Stem Cell Line Expressing a Magnetic Resonance Imaging Reporter Gene.

The objective of the current study is to develop a new method for tracking transplanted human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs) using magnetic resonance imaging (MRI). The CRISPR/dCas9 activation system is employed to overexpress ferritin heavy chain (FHC) in hiPSC-CMs. The mRNA and protein expression of FHC in hiPSC and hiPSC-CMs significantly increased after transfection. Iron chloride does not affect the cell viability in a concentration range from 0 to 2000 µm. hiPSCs overexpressing FHC (hiPSC- FHCOE) and hiPSC-CMs overexpressing FHC (hiPSC-CM-FHCOE) significantly enhanced cellular uptake of iron chloride but with no changes in electrophysiological properties compared to hiPSC-CM-Control. Furthermore, hiPSC-CM-FHCOE presented robust contrast and lower T2* values, signifying their potential as highly effective candidates for cardiac MRI. Next, hiPSC-CM-FHCOE is injected into mouse hearts and after 3 days of transplantation, MR images are obtained. hiPSC-CM-FHCOE cells exhibited clear signals in the hearts with lower T2* and rapid signal decay. Collectively, data from this proof-of-concept study demonstrated that endogenous labeling with FHC in hiPSC-CMs can be a potent strategy for enhancing the accuracy of cardiac MRI. This technology represents a significant step forward in tracking the transplanted hiPSC-CMs in the hearts of live animals.

Neuro-stimulating effect of Citri Reticulata Pericarpium Viride essential oil through regulating Glu/NMDAR on olfactory bulb to improve anxiety-like behavior.

ETHNOPHARMACOLOGICAL RELEVANCE: Citri Reticulata Pericarpium Viride (also known Qing-Pi or QP) is a plant in the Rutaceae family, QP is a traditional Qi-regulating medicine in Chinese medicine that is compatible with other Chinese medicine components and has extensive clinical practice in treating anxiety and depression. Reports on the pharmacological effects of QP have demonstrated its neuroprotective effects and antioxidant capacities. Numerous pharmacological benefits of QP are attributed to its antioxidant abilities. Anxiety disorders are a broadly defined category of mental illnesses. Oxidative stress and an imbalance in the antioxidant defense system are typical pathological features of these disorders. AIM OF THE STUDY: The aim of this study was to evaluate the effects of QP essential oil on anxiety using animal models and investigate the underlying neurobiological mechanisms. MATERIALS AND METHODS: This study aimed to develop an animal model of anxiety using chronic restraint stress and investigate the effects of inhalation of Citri Reticulata Pericarpium Viride essential oil on anxiety-like behavior, olfactory function, and olfactory bulb neurogenesis in mice with anxiety. RESULTS: The results showed that long-term chronic restraint stimulation caused a decrease in olfactory function, significant anxiety-like behavior, and a notable reduction in the number of neurons in the olfactory bulb. However, inhalation of Citri Reticulata Pericarpium Viride essential oil reversed these effects, improving the olfactory function, neuro-stimulating effect, alleviating anxiety-like behavior, and regulating theta (4-12Hz) oscillation in the hippocampus DG area. These effects were associated with changes in the expression levels of glutamate receptor NMDAR and NeuN in olfactory bulb. CONCLUSIONS: The study revealed that mice with anxiety induced by chronic restraint stress exhibited significant olfactory dysfunction, providing strong evidence for the causal relationship between anxiety disorders and olfactory dysfunction. Moreover, QP essential oil has the potential to be developed as a therapeutic drug for anxiety disorders, in addition to its role as a complementary anxiolytic.

Establishment of a Simple, Sensitive, and Specific Salmonella Detection Method Based on Recombinase-Aided Amplification Combined with dsDNA-Specific Nucleases.

Salmonella is a common foodborne pathogen that can cause food poisoning, posing a serious threat to human health. Therefore, quickly, sensitively, and accurately detecting Salmonella is crucial to ensuring food safety. For the Salmonella hilA gene, we designed Recombinase-aided amplification (RAA) primers and dsDNA-specific nuclease (DNase) probes. The ideal primer and probe combination was found when conditions were optimized. Under UV light, a visual Salmonella detection technique (RAA-dsDNase) was developed. Additionally, the RAA-dsDNase was modified to further reduce pollution hazards and simplify operations. One-pot RAA-dsDNase-UV or one-pot RAA-dsDNase-LFD was developed as a Salmonella detection method, using UV or a lateral flow dipstick (LFD) for result observation. Among them, one-pot RAA-dsDNase and one-pot RAA-dsDNase-LFD had detection times of 50 min and 60 min, respectively, for detecting Salmonella genomic DNA. One-pot RAA-dsDNase-UV had a detection limit of 101 copies/µL and 101 CFU/mL, while one-pot RAA-dsDNase-LFD had a sensitivity of 102 copies/µL and 102 CFU/mL. One-pot RAA-dsDNase-UV and one-pot RAA-dsDNase-LFD assays may identify 17 specific Salmonella serovars witho ut causing a cross-reaction with the remaining 8 bacteria, which include E. coli. Furthermore, Salmonella in tissue and milk samples has been reliably detected using both approaches. Overall, the detection method developed in this study can quickly, sensitively, and accurately detect Salmonella, and it is expected to become an important detection tool for the prevention and control of Salmonella in the future.

A Digermanium(III) 1,2-Dication Stabilized by Amidinate and cAAC-Phosphinidenide Ligands.

A digermanium(III) 1,2-dication comprises two cationic centers located at two interconnected Ge atoms. The strong Coulombic repulsion between two positively charged germanium cations hinders their bond formation. Balancing these two oppositions was achieved by using amidinate and cyclic (alkyl)amino carbene (cAAC)-phosphinidenide ligands, where an amidinato cAAC-phosphinidenidogermylene complex, [LGeP(cAACMe)] (2, where L = PhC(NtBu)2, cAACMe = :C{C(Me)2CH2C(Me)2NAr}, and Ar = 2,6-iPr2C6H3), underwent one-electron oxidation with a bis(phosphinidene) radical cation, [(cAACMe)P]2•+, to form a digermanium(III) 1,2-dication, [LGeP(cAACMe)]22+, in compound 4.

Optineurin-facilitated axonal mitochondria delivery promotes neuroprotection and axon regeneration.

Optineurin (OPTN) mutations are linked to amyotrophic lateral sclerosis (ALS) and normal tension glaucoma (NTG), but a relevant animal model is lacking, and the molecular mechanisms underlying neurodegeneration are unknown. We found that OPTN C-terminus truncation (OPTN∆C) causes late-onset neurodegeneration of retinal ganglion cells (RGCs), optic nerve (ON), and spinal cord motor neurons, preceded by a striking decrease of axonal mitochondria. Surprisingly, we discover that OPTN directly interacts with both microtubules and the mitochondrial transport complex TRAK1/KIF5B, stabilizing them for proper anterograde axonal mitochondrial transport, in a C-terminus dependent manner. Encouragingly, overexpressing OPTN/TRAK1/KIF5B reverses not only OPTN truncation-induced, but also ocular hypertension-induced neurodegeneration, and promotes striking ON regeneration. Therefore, in addition to generating new animal models for NTG and ALS, our results establish OPTN as a novel facilitator of the microtubule-dependent mitochondrial transport necessary for adequate axonal mitochondria delivery, and its loss as the likely molecular mechanism of neurodegeneration.

Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study.

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Multi-Modality Imaging in Vasculitis.

Systemic vasculitides are a rare and complex group of diseases that can affect multiple organ systems. Clinically, presentation may be vague and non-specific and as such, diagnosis and subsequent management are challenging. These entities are typically classified by the size of vessel involved, including large-vessel vasculitis (giant cell arteritis, Takayasu's arteritis, and clinically isolated aortitis), medium-vessel vasculitis (including polyarteritis nodosa and Kawasaki disease), and small-vessel vasculitis (granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis). There are also other systemic vasculitides that do not fit in to these categories, such as Behcet's disease, Cogan syndrome, and IgG4-related disease. Advances in medical imaging modalities have revolutionized the approach to diagnosis of these diseases. Specifically, color Doppler ultrasound, computed tomography and angiography, magnetic resonance imaging, positron emission tomography, or invasive catheterization as indicated have become fundamental in the work up of any patient with suspected systemic or localized vasculitis. This review presents the key diagnostic imaging modalities and their clinical utility in the evaluation of systemic vasculitis.

Disseminated Cryptococcus neoformans infection involving multiple bones and lung in an immunocompetent patient: a case report.

BACKGROUND: Cryptococcal osteomyelitis is a rare and potentially serious condition, typically encountered in individuals with compromised immune systems. This case underscores the unusual occurrence of disseminated Cryptococcosis in an immunocompetent person, involving multiple bones and lungs, with Cryptococcus neoformans identified as the causative agent. CASE PRESENTATION: An Indonesian man, previously in good health, presented with a chief complaint of successive multiple bone pain lasting for more one month, without any prior history of trauma. Additionally, he reported a recent onset of fever. On physical examination, tenderness was observed in the left lateral chest wall and right iliac crest. Laboratory findings indicated mildly elevated inflammatory markers. A computed tomography (CT) scan of the chest revealed an ovoid solid nodule in the right lower lung and multifocal osteolytic lesions in the sternum, ribs, and humeral head. A magnetic resonance imaging (MRI) study of the sacrum showed multiple lesions in the bilateral iliac bone and the lower L4 vertebral body. Confirmation of Cryptococcal osteomyelitis involved a fine-needle biopsy and culture, identifying Cryptococcus neoformans in the aspirate. The patient responded positively to targeted antifungal treatments, leading to a gradual improvement in his condition. CONCLUSIONS: This case emphasizes the need to consider Cryptococcus neoformans osteomyelitis in immunocompetent patients with bone pain. A definitive diagnosis involves a fine-needle biopsy for pathology and culture, and prompt initiation of appropriate antifungal treatment has proven effective in preventing mortality.

A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm.

Asthma is a diverse disease that affects over 300 million individuals globally. The prevalence of asthma has increased by 50% every decade since the 1960s, making it a serious global health issue. In addition to its associated high mortality, asthma generates large economic losses due to the degradation of patients' quality of life and the impairment of their physical fitness. Asthma research has evolved in recent years to fully analyze why certain diseases develop based on a variety of data and observations of patients' performance. The advent of new techniques offers good opportunities and application prospects for the development of asthma diagnosis methods. Over the last few decades, techniques like data mining and machine learning have been utilized to diagnose asthma. Nevertheless, these traditional methods are unable to address all of the difficulties associated with improving a small dataset to increase its quantity, quality, and feature space complexity at the same time. In this study, we propose a sustainable approach to asthma diagnosis using advanced machine learning techniques. To be more specific, we use feature selection to find the most important features, data augmentation to improve the dataset's resilience, and the extreme gradient boosting algorithm for classification. Data augmentation in the proposed method involves generating synthetic samples to increase the size of the training dataset, which is then utilized to enhance the training data initially. This could lessen the phenomenon of imbalanced data related to asthma. Then, to improve diagnosis accuracy and prioritize significant features, the extreme gradient boosting technique is used. The outcomes indicate that the proposed approach performs better in terms of diagnostic accuracy than current techniques. Furthermore, five essential features are extracted to help physicians diagnose asthma.

The Reduced Gut Lachnospira Species Is Linked to Liver Enzyme Elevation and Insulin Resistance in Pediatric Fatty Liver Disease.

The objective of this study was to investigate gut dysbiosis and its metabolic and inflammatory implications in pediatric metabolic dysfunction-associated fatty liver disease (MAFLD). This study included 105 children and utilized anthropometric measurements, blood tests, the Ultrasound Fatty Liver Index, and fecal DNA sequencing to assess the relationship between gut microbiota and pediatric MAFLD. Notable decreases in Lachnospira spp., Faecalibacterium spp., Oscillospira spp., and Akkermansia spp. were found in the MAFLD group. Lachnospira spp. was particularly reduced in children with MAFLD and hepatitis compared to controls. Both MAFLD groups showed a reduction in flavone and flavonol biosynthesis sequences. Lachnospira spp. correlated positively with flavone and flavonol biosynthesis and negatively with insulin levels and insulin resistance. Body weight, body mass index (BMI), and total cholesterol levels were inversely correlated with flavone and flavonol biosynthesis. Reduced Lachnospira spp. in children with MAFLD may exacerbate insulin resistance and inflammation through reduced flavone and flavonol biosynthesis, offering potential therapeutic targets.

A Giant Magneto-Superelasticity of 5% Enabled by Introducing Ordered Dislocations in Ni34Co8Cu8Mn36Ga14 Single Crystal.

Elasticity, featured by a recoverable strain, refers to the ability that materials can return to their original shapes after deformation. Typically, the elastic strains of most metals are well-known 0.2%. In shape memory alloys and high entropy alloys, the elastic strains can be several percent, as called superelasticity, which are all triggered by external stresses. A superelasticity induced by magnetic field, termed as magneto-superelasticity, is extremely important for contactless work of materials and for developing brand-new large stroke actuators and high efficiency energy transducers. In magnetic shape memory alloys, the twin boundary motion driven by magnetic field can output a strain of several percent. However, this strain is unrecoverable when removing the magnetic field and hence it is not magneto-superelasticity. Here, a giant magneto-superelasticity of 5% in a Ni34Co8Cu8Mn36Ga14 single crystal is reported by introducing arrays of ordered dislocations to form preferentially oriented martensitic variants during the magnetically induced reverse martensitic transformation. This work provides an opportunity to achieve high performance in functional materials by defect engineering.